Financial Crisis
Order Description
This is a short report after reading the BIS report on LTCM.
COMMITTEE ON THE GLOBAL FINANCIAL SYSTEM
October 1999
A REVIEW OF FINANCIAL MARKET EVENTS
IN AUTUMN 1998
BANK FOR INTERNATIONAL SETTLEMENTS
Basel, Switzerland
Table of contents
Chapter 1: Introduction and summary ………………………………………………………………………………. 1
Chapter 2: Background to the episode of market stress ………………………………………………………. 5
Chapter 3: Mechanisms producing contagion and amplifying market dynamics…………………… 11
Chapter 4: The remaining imprint and some tentative lessons……………………………………………. 18
Chapter 5: Work to be done…………………………………………………………………………………………… 20
Annex 1: Summary of interviews with market participants ……………………………………………….. 38
Annex 2: Comparative data on liquidity and credit risk…………………………………………………….. 44
Members of the Working Group on Financial Market Events in the Autumn of 1998 …………… 91
i
Chapter 1
Introduction and summary
Following its March 1999 meeting, the Committee on the Global Financial System formed a working
group, chaired by Karen Johnson of the Board of Governors of the Federal Reserve System, to
examine the events surrounding the market stresses in many international financial markets in autumn
1998. The group was charged with putting these events in perspective, with special emphasis on
understanding the suddenness of the deterioration in liquidity and elevation of risk spreads in a wide
variety of markets, the proximate causes of the withdrawal from risk-taking, and the speed with which
and extent to which markets subsequently recovered. The focus of the working group, therefore, was
on developments across many markets in a relatively narrow time frame, as opposed to the more
general investigation of market liquidity provided by an earlier report to the CGFS or the scrutiny of a
narrow set of financial entities contained in the report of the US President’s Working Group and the
recommendations on industry practices of the Counterparty Risk Management Policy Group.1
The working group assembled a large dataset on key financial prices in major international markets
and attempted to characterise the degree to which price movements in the autumn were outsized and
evidenced different correlations from those observed in relatively more tranquil times. (These data and
some of the broad regularities among them are described in Annex 2.) It also searched
contemporaneous accounts of the events to establish a time line of significant influences on markets
(included as Table 1). Group members interviewed market participants in a number of international
financial centres in June 1999 to learn about their actions regarding risk exposure and credit risk
management. The group as a whole met with a half dozen market participants in Basel in early July to
further that dialogue. Annex 1 summarises the insights gained from the interviews.
This is the report of the Working Group. Chapter 2 provides background on the episode of market
stress in autumn 1998. The first part of Chapter 2 summarises the events of the period of market
turmoil since mid-1997, noting the differences between the period July 1997–July 1998 and the period
July 1998–early 1999. The second part examines the process of recovery in markets, which occurred
rapidly as participants were encouraged by official action and emboldened by the profit opportunities
offered in wide price spreads. Chapter 3 provides an analytic interpretation of the events of
July-October 1998 and identifies important mechanisms that appeared to spread disruption across
financial centres and amplified price dynamics. Some of those factors – such as an inadequate
assessment of counterparty risks that permitted the excessive use of leverage, the failure to incorporate
in risk management potential feedback effects of market liquidity on price setting, and the lack of
information on aggregate positions – have already been identified as weaknesses in market structure in
prior analyses of the events of last autumn by both the private sector and official institutions and have
triggered a variety of responses and recommendations for additional changes. Other mechanisms –
including a shrinking number of key market participants, the widespread emulation of certain
financing, trading and risk management strategies, and compensation schemes encouraging a
short-term focus in decision-making – are more entrenched in the structure of the financial industry
and may still pose risks going forward. A diagram at the end of Chapter 3 summarises in schematic
form the cycle of deterioration in market functioning as understood by the Working Group.
Chapter 4 examines the lasting imprint of last year’s events. Risk spreads and many indicators of
market liquidity have not returned to their levels of the summer preceding the storm, and indeed some
1
See BIS, Committee on the Global Financial System (1999), Market Liquidity: Research Results and Selected Policy
Implications (the Shirakawa Report), the President’s Working Group on Financial Markets (1999) Report on Hedge
Funds and the Long-Term Capital Management Episode, and Counterpary Risk Management Policy Group (1999),
Improving Counterparty Risk Management Practices (the Corrigan-Thieke Report).
1
have returned to their crisis levels. This may suggest that, on balance, market-makers and arbitrageurs
have scaled back their activities somewhat and investors are more wary about the income prospects
associated with a broad range of securities. To the extent that such risk spreads had been bid down to
extremely low levels by historical standards in the period before the market pressures erupted, the
subsequent net increase in those spreads may have made them now more consistent with
fundamentals. Moreover, market participants appear to be taking steps to reduce their exposures to the
recurrence of a widespread flight to quality, such as by using rates on private sector rather than
government obligations as the benchmarks for pricing. But the net effect of these changes – both the
reduced amount of capital devoted to enforcing arbitrage strategies and the shifting of hedging
strategies – may have contributed to the recent widening of interest rate spreads, particularly on swaps,
in many industrial countries in recent months.
Chapter 4 also draws some tentative lessons for policymakers from this experience. Foremost is the
realisation that the first line of defence at a time of market stress is sound risk management by market
participants, which in turn requires a regulatory and monetary policy environment ensuring that
market discipline effectively governs credit decisions and risk-taking. Policymakers should also
appreciate that the fallout from last year’s financial market strains was less pronounced on real activity
in the industrial countries because a healthy commercial banking system was able to act as a substitute
means of intermediating funds. This helps to explain why in this episode the availability of credit to
non-banks proved to be relatively more resilient in financial systems, such as those in the continental
European countries, where banks play an important role, compared with those systems more oriented
towards market-based financial intermediation. Thus, keeping depository institutions safe and sound
must remain a priority. While some financial institutions were under severe stress at times, the events
of last autumn were initially more a matter of a drying-up of market liquidity than a general
withdrawal of credit availability. The subsequent dynamics, though, were complicated as the initial
deterioration in market functioning that made participants less confident about price setting also
subsequently induced credit strains as collateral values eroded and concerns about counterparties
mounted.
Chapter 5 concludes with an outline of work still to be done. The group’s efforts to describe the large
dataset it collected only scratched the surface of potential empirical work. In addition, more
sophisticated financial theory may be able to define more rigorously indicators of market stress, while
continued contacts with market participants may make it possible to understand better the management
of credit and market risks.
2
Table 1
Significant events in the second half of 1998
(All financial-market price and volume figures are for the 1998 sample period.
Price figures are based on daily closing values.)
Date
Event
6 July
14 July
20 July
21 July
23 July
7 August
13 August
14 August
17 August
31 August
1 September
Salomon Brothers bond arbitrage desk disbanded
IMF approves Russia loan package
First WSJ headline on LTCM losses
Greenspan’s Humphrey-Hawkins’ testimony
Japanese sovereign debt placed under review
World Bank approves Russia loan.
Fall in HK stock market index (down 8% from Aug 12)
First HKMA stock market intervention
Russian effective default and rouble devaluation
Largest daily fall in DJIA
Malaysia imposes capital controls
Highest volume (number of shares) on NYSE
LTCM shareholder letter issued
Greenspan speech at U.C. Berkeley
First WSJ headline on Lehman Brothers’ losses
HKMA introduced a set of seven technical measures to strengthen the mechanism
of the currency board system
Bank of Japan reduces overnight call rate
Largest daily fall in 10-year US Treasury yield
Largest daily fall in 10-year JGB yield
Largest daily increase in 10-year £ swap spread
Largest daily increase in 10-year US$ swap spread
LTCM recapitalisation
Goldman Sachs delays flotation
Federal Reserve interest rate cut
Greenspan-McDonough Congressional testimony on LTCM
Largest daily fall in 10-year UK Gilt yield
G7 statement
Bank of Spain cuts interest rates
Bank of England cuts interest rates
Yen/$ falls 9%
Central banks of Portugal and Ireland cut interest rates
Largest daily rise in 10-year US Treasury yield
Largest daily rise in 10-year UK Gilt yield
Largest daily rise in 10-year German Bund yield
Ellington Capital Management auctioned $1.5 billion of mortgage securities
Japanese Diet approves bank reform legislation
BankAmerica Corp. reports fall in earnings of 78%
Inter-meeting Federal Reserve Rate cut
First LTCM swap auction
Second LTCM swap auction
Second rate cut by Bank of England
Brazilian government formally requested the IMF program.
2 September
4 September
7 September
9 September
10 September
11 September
12 September
23 September
28 September
29 September
1October
4 October
7 October
8 October
7-8 October
9 October
10-11 October
12 October
14 October
15 October
20 October
2 November
5 November
13 November
3
Table 1 – contd.
Date
Event
17 November
Third Federal Reserve rate cut
Japan sovereign debt downgraded by Moody’s
Third LTCM swap auction
IMF Board approves the program for Brazil
Co-ordinated interest rate cut by European central banks
Third rate cut by Bank of England
Market disrupted after Chinese government refused to help foreign creditors of
GITIC
Fears of debt crisis in China sweep through Hong Kong, Hang Seng index falls
more than 4% Brazilian devaluation – wider band.
2 December
3 December
10 December
10 January
13 January
4
Chapter 2
Background to the episode of market stress
Most analysts date the onset of the recent period of turmoil in international financial markets to the
devaluation of the Thai baht in July 1997. That is not to say in retrospect that early warning signals
had not been evident sooner for some national markets or that other markets, notably in eastern
Europe, had not already been hit hard by bouts of stress. From the summer of 1997 onwards, however,
turmoil appeared quickly in other emerging markets in Asia where broadly similar vulnerabilities,
such as fragile financial sectors, possibly overvalued exchange rates and substantial short-term foreign
currency denominated liabilities relative to reserves, were seen to be present. While stresses seemed to
subside in spring 1998, they re-emerged with force in crises in Russia and Brazil and in industrial
country markets in autumn 1998. The period from July 1997 to the end of 1998 can be divided into
two distinct episodes, the first beginning in July 1997 and the second beginning in August 1998.
Establishing the important contrasts between these two episodes provides the rationale for
concentrating on the events of autumn 1998.
The turmoil that began with the Thai crisis quickly precipitated similar stresses in the financial
markets of South-East Asia, Korea, Hong Kong, Taiwan and, to some extent, Latin America. Asian
equity prices fell irregularly by about 50% from August 1997 to September 1998, and then began a
recovery (Chart 1).2 Currencies generally depreciated by 50-100% from August 1997 to the end of the
year, and then began a recovery that left an overall 50% depreciation by September 1998 (Chart 2).
The exception was Indonesia, where the rupiah depreciated sixfold and subsequently recovered
threefold.
While the turmoil in the Asian economies from June 1997 to August 1998 led to an increase in certain
risk premia in the financial markets of the industrialised economies, on balance the effects appear to
have been neutral or even supportive of a continued rally in those markets. Long-term government
bond yields in industrial countries fell, beginning around July 1997, as shown in Chart 3. The
movement was most pronounced in the US market, where rates peaked around April-May 1997, and
then trended down to early 1998. A similar movement can be seen in the German and Japanese
markets. These rate declines had some element of a “flight to quality,” as investors withdrew from
emerging market securities into industrial country government debt. But market participants also
apparently reasoned that the deterioration of economic activity in Asia, by weakening the exports of
industrial countries and causing a drag on commodity and other import prices, would lessen
worldwide inflationary pressures.
Equity markets in the United States and Europe remained strong, though that upward movement was
interrupted briefly in late October 1997, after share prices in Hong Kong shed nearly 30%. After a
sharp one-day decline, US and European markets reversed quickly and moved towards new highs in
mid-1998. Japan’s equity markets remained weak, for reasons special to Japan. Thus, despite the
turmoil in emerging markets, there appeared to be no substantial long-lasting disruption in industrial
country equity markets. Similarly, the markets for corporate debt in industrial countries were
apparently little affected. In the United States, as shown in Chart 4, for instance, spreads of corporate
yields over those on comparable government securities widened only slightly through mid-1998.
Moreover, the rise in spreads was smaller than the decline in government yields, implying that, on
balance, most corporate borrowers enjoyed more favourable terms.
2
Charts 1-12 and Tables 2-6 can be found at the end of the report.
5
To an important extent, this flight to safety benefited US assets in particular. Besides the rise in bond
and stock prices, the US dollar gained on foreign exchange markets against the currencies of both
emerging and developed economies, and the US dollar appreciated towards a local peak in August
1998, with the yen/dollar rate reaching a high of ¥147. In contrast, enthusiasm for pending monetary
union in Europe worked to offset this ongoing strength of dollar assets, holding the Deutsche
mark/dollar exchange rate essentially flat.
Thus, financial markets in industrial countries seem, for the most part, to have avoided negative effects
from the Asian crisis. To be sure, the downward movement in share prices in October 1997 showed
that a shock to one national market could spread quickly. Moreover, the mechanisms mentioned by
some analysts at the time for facilitating the spread of shocks across markets – including the extensive
use of leverage and certain financing, trading and hedging techniques – remained in place. But it was
not until August 1998 that the picture changed markedly. The effective default by Russia on some
government debt obligations on 17 August and the devaluation of the rouble shortly thereafter resulted
in sizable losses for some investors. Some of these positions were highly leveraged through
collateralised financing arrangements, such as securities lending, repurchase agreements and margin
accounts at futures exchanges, which required that positions be marked to market daily. The erosion of
the value of collateralised obligations as market prices moved produced, in effect, a global “margin
call.”
The Russian default probably increased the perception of risk in other emerging market economies,
especially in Latin America, partly by reminding investors of the inherent riskiness of investments in
these economies but also by inducing a re-examination of the ability and willingness of major
countries and international organisations to support credit-strapped sovereigns. The currencies of
many emerging economies came under substantial pressure, and the market value of the international
debt obligations of some countries declined sharply. Investors around the world shared in the resulting
losses, and economic growth and corporate profits were perceived to be vulnerable. In these
circumstances, many investors appeared to reassess the credit quality of various counterparties. More
fundamentally, investment decisions apparently reflected some combination of an upward revision to
uncertainty surrounding the expected future prices of financial instruments more broadly – either
because such risks were correctly viewed as more substantial or because an earlier misconception that
risks were low was corrected – and a reduced tolerance for bearing risk. The precise mechanisms that
spread this reaction and amplified market dynamics are discussed further in Chapter 3.
The resulting shift of demand towards safety and liquidity between mid-August and mid-September
accentuated the downward trend in yields on the government debt of major industrial countries. Yields
on higher-quality private securities fell much less, and those on issues of lower-rated firms increased
sharply. As a result, and in contrast to the earlier period, spreads of private rates over government rates
rose substantially, reaching levels not seen for many years, and issuance of corporate securities
dropped sharply. The spreads of private over comparable government rates in many major financial
centres rose to recent highs in August-October at both short (Table 2) and long (Table 3) maturities. In
industrial countries, the increases in spreads posted from lows earlier in the year ranged from 40 to
more than 300 basis points.
In equity markets, share prices in industrial countries fell markedly in August and September 1998.
General doubts about the financial sectors of industrial countries also intensified, evident in the more
pronounced drop in equity values of financial institutions relative to broader indices in the United
States and Europe (Chart 5). The largest losses were posted by European banks, which were
presumably thought by investors to have a greater direct exposure to Russia. But US financial
institutions were also hit hard, and more so over time. Reflecting the comparatively minor direct
exposures of Japanese banks to Russia and the fact that investors’ opinion of such institutions had
soured much earlier, the equity prices of Japanese banks, on average, tracked the general market there.
Similar evidence of doubts about depository institutions became evident in funding costs in the
interbank market (Chart 6). Three-month deposit rate spreads over yields on government securities
widened first and by most in the United States and Canada and ultimately rose in the United Kingdom
and France as well (though as with corporate bonds these spreads also reflected lower government
yields resulting from the flight to safety).
6
In addition, the movement of the dollar/yen exchange rate was reversed, with the dollar depreciating
against the yen in sharp declines over several days. The reasons underlying these sudden and marked
increases in the exchange value of the yen were not evidently related to macroeconomic developments
at the time. While the secular imbalances of the trade positions of the United States and Japan could
explain longer-term pressures on the yen/dollar exchange rate, no specific trigger to such concerns
emerged in these days. Rather, in retrospect and as will be discussed below, the unwinding of
leveraged positions underpinned by large yen borrowings seems to have played an important role.
The rise in spreads of the debt of emerging economies over US Treasury yields was not confined to
Russia, where prices of government paper were slashed to a fraction of their original value. Many
eastern European countries and some in Latin America saw the spread of the yields on their debt over
those on Treasuries surpass 10 percentage points (Chart 7). Losses incurred in Russia and other
emerging markets by leveraged investors – including banks, brokerage houses and hedge funds –
raised the prospects for distress sales of other risky assets by such investors, weighing on market
sentiment and depressing prices. Many of these entities reduced the scale of their operations and
trimmed their risk exposures, responding to pressures from more cautious counterparties and their own
need to preserve capital in an environment of heightened uncertainty and a lessened tolerance for
bearing risk. As a result, liquidity in many markets declined sharply, with bid-ask spreads widening
and large transactions becoming more difficult to complete.
In the market for government securities, the costs of transacting and the ability to do so in large
volume deteriorated. For example, periodic surveys of bid-ask spreads for Treasury securities
conducted among US primary dealers at the time indicated a marked increase in caution on their part
relative to what was reported to be typical in the early summer. The spreads at which dealers stood
willing to transact in on-the-run coupon securities rose from 1/64th of a price point to between 1/32nd
and 5/32nd of a point. For many older issues, no quotes were available at all. In an environment where
there was less assurance that large positions in government securities could be unwound quickly
without a sizable price concession, investors showed an increased preference for the liquidity offered
by the most recent issues at each maturity. The yields on these more actively traded “on-the-run”
securities fell noticeably relative to those available on “off-the-run” issues, those which had been
outstanding longer (Chart 8).
Demand for the most liquid benchmark securities was further increased by the need of certain market
participants to provide top-quality collateral as well as by investors stepping in to benefit from the
expected further decline in bond yields in the light of ongoing concern about global deflation. The
strong demand for German benchmark bonds as opposed to other securities, for example, led to an
appreciation of the bund futures contract and pushed bund rates further below yields on other bond
classes and other EMU sovereigns. Signs of deterioration were evident in markets for private
securities. Bid-ask spreads on corporate instruments also widened. In the United Kingdom, for
instance, spreads on Baa securities more than doubled over the course of the fall (Chart 9). In many
markets, corporate risk spreads widened as well.
Conditions in world financial markets deteriorated further following revelations in early September of
the magnitude of losses at a major hedge fund, Long-Term Capital Management (LTCM). LTCM
indicated that it sought high rates of return primarily by identifying small discrepancies in the prices of
various instruments relative to historical norms and then taking highly leveraged positions in those
instruments in the expectation that market prices would revert to such norms over time. In pursuing its
strategy, LTCM took very large positions, some of which were in relatively small and illiquid markets.
While primarily concentrated in debt instruments, the firm also put on large bets in the aggregate both
that the volatility of equity prices in the United States would decline and that a few equity prices
would revert to their more usual historical behaviour relative to one another. In aggregate, LTCM
supported assets of about $125 billion on a capital base of about $4 billion at mid-summer.
In an effort to avoid the adverse market consequences of the precipitous unwinding of LTCM’s
portfolio that might have followed the firm’s default, the Federal Reserve Bank of New York
contacted the major creditors and counterparties of LTCM to see if an alternative to default could be
found. Subsequent discussions among the creditors and counterparties led to an agreement by the
7
private sector parties to provide an additional $3½ billion of capital to LTCM in return for a 90%
equity stake in the firm.
The private sector agreement to recapitalise LTCM allowed its positions to be reduced in an orderly
manner over time. Nonetheless, the actual and anticipated unwinding of LTCM’s portfolio, as well as
actual and anticipated sales by other similarly placed leveraged investors, are likely to have
contributed materially to the tremendous volatility of financial markets in early October. Market
expectations of asset price volatility going forward, as reflected in options prices, rose sharply
(Charts 10 and 11), as bid-ask spreads and the premium for on-the-run securities widened further.
Long-term US Treasury yields briefly dipped to their lowest levels in more than 30 years, in part
because of large demand shifts resulting from concerns about the safety and liquidity of private and
emerging market securities. Spreads of rates on corporate bonds over those on comparable Treasury
securities rose considerably, and issuance of corporate bonds, especially by lower-rated firms,
remained very low. The stressed capital positions of many leveraged market participants increased
calls for collateral from creditors. However, one stress-reducing consequence of this process was that
it induced some paring-back of speculative positions in Asia, narrowing risk spreads and lessening
pressures in exchange markets there.
To some extent, commercial banks were able to cushion the constriction of market finance in
industrial countries, especially in the United States and the United Kingdom, by satisfying drawdowns
on outstanding loan commitments to business firms and by holding more securities in their portfolios.
Overall, an increased share of business lending was probably extended on floating rather than fixed
rate terms. Indicative of this substitution, swap spreads among private borrowers relative to
government rates widened in major markets, reflecting a higher premium paid for exchanging floating
rate for fixed rate obligations as well as, perhaps, a heightened assessment of credit risk (Chart 12).
In continental Europe, the impact of market stress on the availability of credit to corporate borrowers
was limited, given the relatively limited significance of market financing by corporate borrowers and
the greater focus on bank-based financial intermediation. The widening of credit and swap spreads in
continental Europe remained below levels observed in those financial systems more oriented towards
market-based intermediation and credit to corporate borrowers was less constricted.
However, in general, the willingness of financial institutions in industrial countries to take on risk,
especially with respect to international interbank as well as international credit and securities market
activities, diminished considerably during this phase of market stress. (See, for example, BIS,
International Banking and Financial Market Developments, March 1999 and June 1999.)
Almost as suddenly as the storm broke, market conditions in industrial countries stopped deteriorating
by mid-October. Liquidity began to improve somewhat in the days and weeks following the cut in the
Federal Reserve’s intended level for the federal funds rate on 15 October, a policy move that may have
had an especially strong market impact because it was taken between regularly scheduled monetary
policy meetings. Internationally coordinated efforts to help Brazil cope with its financial difficulties,
culminating in the announcement of an IMF-led support package in mid-November, contributed to the
easing of market strains. In the government securities markets of most industrial economies, bid-ask
spreads narrowed somewhat and the premium for on-the-run issues declined. With the earlier flight to
quality and liquidity unwinding, rates on government bonds of industrial countries backed up
considerably. Corporate bond spreads reversed a part of their earlier rise, and investment-grade bond
issuance rebounded sharply. In the high-yield bond market, investors appear to have remained more
hesitant, especially for all but the best-known issuers. Though the volume of junk bond issuance
picked up, it did so by less than in the investment-grade market.
By the beginning of 1999, some measures of market stress had eased considerably from their levels in
the fall. Equity markets had recovered most, but not all, of their autumn losses. With market yields
low in absolute terms, many corporate borrowers brought new issues to market. However, markets
remained somewhat illiquid relative to historical norms and risk spreads on corporate bonds stayed
quite elevated. Indeed, swap spreads again breached new highs in August 1999. While the widening in
swap spreads themselves probably reflected some displacement in the normal seasonal pattern of
corporate borrowing, as issuers attempted to move forward their expected sales to avoid an expected
8
increase in official rates in the United States and subdued activity around the century date change, this
may be an example of the kind of price anomaly which prior to the autumn 1998 crisis would have
been quickly eliminated by the activity of leveraged position-takers.
Just as it is difficult to point to a single event as triggering the stresses in financial markets to begin
with, no one action appears responsible for commencing the healing process. In interviews with
members of the working group, market participants offered four candidate explanations, which
apparently accumulated in October and November to encourage a return to more normal risk-taking.
(1)
Monetary policy easing, especially the inter-meeting move on 15 October by the Federal
Reserve, induced many to believe that monetary accommodation would be forthcoming as long as
market pressures posed a risk to economic expansion. Such tendencies were reinforced by the easing
of monetary policy by the Bank of England and by scheduled participants in European monetary union
converging on a single interest rate. Effectively, policymakers’ willingness to act trimmed the adverse
tail to potential economic outcomes, in a sense underwriting a renewed confidence in taking on risk.
Reflecting that change in sentiment, equity prices in most major economies rallied from mid-October
onwards.
(2)
The orderly continuation in the risk arbitrage business of the newly recapitalised LTCM
led market participants to take out any “fire sale” discount that may have been embedded in asset
prices across a wide variety of instruments used in relative value trades.
(3)
As time elapsed and no other large firm showed signs of failing, market participants came
to feel that some of their fears might have been overblown.
(4)
Wide spreads in a variety of markets induced investors with longer time horizons to return
to markets. In effect, the exit of investors and traders with a short-term focus left money on the table
for those entities willing to ride out the episode of market stress. As those spreads persisted beyond
levels that would have reflected historical norms and an appropriate assessment of risks, more of such
mobile capital entered. To be sure, the provision of some of this substitute funding did not always
come entirely at lenders’ initiative. In particular, some large internationally active commercial banks
were confronted with a heavy volume of requests to honour outstanding loan commitments. Some
businesses, rather than risk tapping markets when they were tender, drew instead upon backup lines of
credit. Because such banks were generally well capitalised, they were able to meet such contingent
obligations and, in some cases, pick up new business as well. This availability of a substitute to market
financing may have helped contain market stresses and work to limit the fallout from such stresses on
real economic activity.
9
Indications of financial market stress in the second half of 1998
•
Following Russia’s currency devaluation and default, yield spreads on corporate
bonds widened sharply worldwide, particularly for instruments with lower credit
standing. By mid-September, corporate junk bond spreads had risen 200-750 basis
points from their mid-year levels, medium-quality BBB spreads were up 25-60 basis
points, and even high-quality AA corporate spreads were 10-35 basis points higher.
Swap spreads in most major currencies rose 25-50 basis points over this period.
•
Between their mid-year peaks and early October, equities in industrial countries shed
15-35% of their market value, with financial-sector and small-capitalisation indices
falling more than the overall market. Swiss bank stock prices dropped by more than
half. Emerging market stock indices also fell hard, but had largely bottomed out by
early September.
•
Day-to-day changes in financial prices were unusually volatile. Measures of implied
volatility, inferred from options prices, rose sharply, peaking in October for most
industrial country markets, but earlier in Latin America and later in Switzerland.
•
Quoted bid-ask spreads rose in a number of markets, reflecting reduced liquidity. The
yield premium for “off-the-run” government bonds in major industrial countries also
widened somewhat, suggesting that investors were deriving particular comfort from
the more liquid “on-the-run” issues.
•
An indicator of liquidity in primary capital markets, private sector securities issuance,
fell precipitously and then rebounded dramatically near year-end, suggesting that
many firms had to delay financing for several months. However, sources of
intermediated funds apparently did not dry up, with international loan origination
volume holding steady.
10
Chapter 3
Mechanisms producing contagion and amplifying market dynamics
The general impression drawn from the working group’s analysis and discussions is that the events of
autumn 1998 cannot be understood in isolation. Rather, financial markets had weathered a series of
blows, beginning with the sharp devaluation of the Thai baht in July 1997 and continuing with crises
in Indonesia, Malaysia and Korea and a short-lived equity price correction. However, while the
immediately preceding period of turmoil was stressful in a variety of markets, there had been no
lasting imprint on the debt and equity securities of major industrial countries. The Asian crisis had not
led to wider concerns about the global banking sector to the same extent as, for example, the 1980s
Latin American debt crisis. On the contrary, to the extent that turmoil in Asia had induced a flight to
quality and provided a deflationary drag on the industrial world’s economies, yields in major countries
tended to fall, cushioning any adverse impact of a weaker profits outlook on equity prices.
Indeed, as the first half of 1998 played out, an important set of trading strategies reaped further
rewards. “Relative value arbitrage” mostly involves convergence trades, in which approximately
offsetting positions are taken in two securities that have similar, but not identical, characteristics and
trade at different prices. The securities in question might be two government notes differing only by
date of issue, equity shares of the same firm trading on different national markets, or private and
public debt instruments. By selling short the expensive security, the trader receives sufficient proceeds
to buy the cheaper one. If the assumption that the two prices will converge proves correct, capital
gains will accrue on one, or perhaps both, legs of the transaction. A particularly attractive feature of
this strategy is the property that general changes in interest rates, such as those associated with central
bank action or other macroeconomic shocks, should have offsetting effects on the purchase and short
sale. Thus, a convergence play should offer important diversification benefits to a portfolio otherwise
exposed to various macroeconomic risks.
However, unlike the conventional definition of arbitrage – i.e. the trade in identical assets that does not
put capital at risk – relative value arbitrage is risky, as it relies on an assumed relationship reasserting
itself to make prices converge in sufficient time. Often, the assumed relationship is derived from the
historical behaviour of rates of return. The increasing sophistication of finance theory in the late 1980s
and 1990s and improvements in computing power that enabled large amounts of data to be collected
and analysed rapidly have also made it possible to identify and to price the individual components of
risk in a widening class of financial instruments. Relying on those models allowed some firms to bet
on the convergence of the prices of those components of risk that were similar across financial
instruments. Yet, however sophisticated its analysis, a firm that bets on a narrowing of credit spreads
or liquidity spreads is, in effect, performing a credit or liquidity intermediation role in the economy
and suffers when the market prices of credit or liquidity risk rise for any reason.
Over the latter half of the 1990s, such convergence trades apparently won more often than they lost, as
the decline in inflation worldwide and the run-up to and eventual adoption of monetary union in
Europe produced a marked compression of nominal yields in major industrial countries – with the
notable exception of Japan. This tendency among government yields was reinforced for private
securities by a robust economic expansion in the United States that lent assurance that credit risk was
low. General gains in equity prices in the major industrial countries provided investors with sizable
increments to their wealth, some of which was directed towards more esoteric instruments in the
search for higher returns. Swap spreads declined gradually from the early 1990s to early 1997, as risk
management technologies improved and the market for these instruments became deeper and more
liquid.
The success of the relative value arbitrage trading strategies pioneered by Long-Term Capital
Management, together with the high regard for its staff, bred emulators, both at other hedge funds and
in the trading operations of investment and commercial banks. It also gave LTCM and some of its
11
brethren a market reputation that proved useful in gaining credit on advantageous terms. In retrospect,
few counterparties seem to have had a complete understanding of the risk profile of such firms, and
their credit decisions were heavily influenced by both reputation and strong past performance. In the
aggregate, counterparties did not impose sufficiently tight limits on exposures, in part because they
relied on collateral agreements requiring frequent marking to market to limit the risk of their
exposures. Although these agreements generally provided for collateral with a value sufficient to cover
current credit exposures, they did not deal adequately with the potential for future increases in
exposures should market values change dramatically.
The resources provided to the risk-arbitrage business helped enforce arbitrage relationships across a
broad variety of markets, narrowing spreads and reducing price volatility in a manner that reinforced
general macroeconomic trends. Indeed, by early 1998, risk spreads and volatility in most major
financial markets were on the low side of experience, despite the tumult in Asian emerging economies.
In this environment of thin risk spreads, low volatility and considerable resources devoted to relative
value arbitrage, the first signs of some fraying became evident in the early summer. Table 1 provides a
chronology of events that market participants deemed significant to understanding developments,
beginning in the second half of the year. In the first listed event, the proprietary trading desk of
Salomon Brothers specialising in relative value arbitrage was disbanded on 6 July, as part of the
consolidation of Citicorp and Travelers. This both sent a signal to market participants that one large
firm viewed the long-run potential of such trading to be adverse and impaired the pricing of some of
the common relative value trades as the desk’s positions were subsequently closed. In addition, and
not entirely unrelated to the price swings associated with Salomon Brothers’ action, LTCM posted two
successive monthly losses in June and July, a first for that high-flying firm.
Russia’s effective debt default triggered sharp market responses that were out of proportion to the
relatively modest losses experienced by large financial intermediaries. Apparently, there was a
reappraisal by market participants of economic fundamentals. The market participants we spoke to
viewed the default as a catalytic event that led them to rethink the certainty of the official backstop
that they had taken for granted when purchasing emerging market debt. When coupled with talk of
capital controls, and the actual imposition of such controls by Malaysia two weeks later, institutional
investors began to view the world as a more hostile and uncertain place.
Uncertainty also extended to concerns about the financial health of some US-based globally active
market participants. As worries about credit mounted, counterparties began ratcheting up standards
and terms and demanding more collateral, just as the value of many collateralised positions
deteriorated. In their own risk management, financial firms attempted to scale back their exposures in
many markets. This adjustment of exposures applied both to position-taking activities and to hedging
activities. Often, though, concerns about liquidity induced them to adjust their positions first in what
were considered to be the deepest markets, government bond cash and futures markets in particular.
This in turn led to wider risk spreads between these “core” assets and related instruments such as
corporate bonds, confounding the usual correlations among rates of return across many markets and
reducing the reliability of standard hedging strategies.
In the light of this uncertainty, there was an evident withdrawal from markets both by market-makers
and investors, reflecting capital losses on initial equity, a shift of remaining equity towards safer
instruments, and deleveraging. To an important degree, these withdrawals were mutually reinforcing.
Market-makers scaled back their participation in non-core instruments because of both the evident
lack of appetite for such securities by investors and the increase in the volatility of prices. Investors,
observing the general drying-up of liquidity for all but the largest markets and most secure
instruments, intensified their flight to safety. Together, they produced a marked escalation in the
volatilities of financial prices – both actual and expected. Table 4 provides some evidence on the
observed change in market volatility in a broad assortment of financial markets over the course of
1998. The actual change in yields on debt instruments were 40-250% more variable in the autumn than
in the first half of the year. In equity and foreign exchange markets, the step-up in the day-to-day
change in prices was even more pronounced.
12
This situation was seriously worsened by LTCM’s near collapse. Its announcement in early September
of large losses and its search for a capital injection exacerbated market strains in four dimensions.
First, the firm itself and many of the entities that copied its risk-arbitrage trading strategies were active
in narrowing the differences in returns from instruments that were essentially similar. As LTCM and
its emulators scaled back their activities – either voluntarily to preserve their capital or involuntarily as
the value of their collateral fell relative to the volatility of prices and creditors exerted more discipline
– previously narrow risk spreads on a wide variety of securities widened dramatically. Second, firms
that were direct counterparties of the hedge fund began to adjust their own risk exposures to reflect the
possibility of default. Third, market participants traded on the anticipation that LTCM – which
actively pursued a broad variety of arbitrage trading strategies and had large open positions, some in
thin markets – might be forced to close out. Fourth, many market participants, recognising that
LTCM’s trading strategies were widely copied, had serious doubts about the viability of some other
firms. In this situation of great uncertainty, rumours were rife and often fed upon themselves.
In the event, the recapitalisation of LTCM on 23 September by a consortium of 17 financial firms
from the United States and Europe that were all active counterparties did not quell these concerns.
There were ongoing fears about how quickly the firm would unwind its positions, doubts about its
continued viability, and some suspicions that other entities might be in similar circumstances. In that
regard, some market participants interpreted official efforts on LTCM’s behalf as bespeaking serious
and ongoing systemic concerns and providing justification for their own decisions to withdraw from
market activities.
The deterioration of liquidity and widening of risk spreads were abetted by various market
mechanisms that transmitted these developments to additional markets and amplified market
dynamics. (A general schematic depicting those forces at work is provided in Annex 1.) Some of those
mechanisms represent failures that have been, or are in the process of being, addressed as a result of
the general reappraisal of risk management in light of the near-failure of LTCM. These include:
(1)
Inadequate counterparty credit assessments that allowed LTCM and other entities to use
leverage excessively. Market confidence in the principals of LTCM, a consistent track record of
earnings, and that firm’s policy of spreading its business among a wide collection of counterparties to
limit information disclosure garnered it favourable credit terms from many firms. Thus, counterparty
restraint was not an effective check on the use of leverage.
While LTCM was exceptional in the extent of its leverage, it was certainly not alone in its reliance on
borrowed funds and use of derivative instruments. In a particularly common strategy employed by
many firms (although reportedly not by LTCM) leverage was undertaken in the currency of the major
market with the cheapest lending terms – Japan – and used to acquire assets denominated in other
currencies. This “yen carry” trade generally exposed the borrower not only to the risks inherent in the
position being funded, but also to the risk that the foreign exchange value of its yen obligations would
change relative to the market value of the acquired asset. When credit terms ratcheted higher in the
general flight to safety, many entities had to scale back, elevating the volatility of market prices. The
yen/dollar exchange rate was especially susceptible to large intraday changes that many observers
linked to the waxing and waning of the yen carry trade. In particular, the sharp appreciation of the yen
against the dollar in September and October was apparently related in part to the unwinding of this
trade. As credit-strapped leveraged market participants first saw the value of their collateral erode and
then began to shrink their balance sheets, they had to acquire yen in the foreign exchange market to
repay their initial borrowings.
(2)
The failure to appreciate the role of market liquidity in risk management. The large
positions that leverage allowed some firms to amass proved difficult to wind down in the general rush
to safety. Essentially, some firms’ risk management planning neglected to envision the possibility that
their own efforts to close out positions would worsen the terms they faced. This failure to appreciate
that credit problems could exacerbate market risk was most evident at LTCM, which had outstanding
positions in some instruments representing large multiples of typical daily trading volume. Such
stresses were also apparent in a variety of niche markets, such as that for Danish mortgage-backed
securities. More generally, almost all markets faced a widening of bid-ask spreads and, to some extent,
13
a partial pullback of market-makers. As liquidity dried up, hedging proved even more difficult,
intensifying pressures in the few remaining liquid instruments.
(3)
A lack of adequate information on aggregate exposures made the prior two failures more
probable. Many market participants had an understanding neither of the extent of leverage employed
nor of the concentration of risks among a few entities in some markets. Some, but by no means all, of
the market participants we spoke to admitted that they had been surprised at the overall size of LTCM
in particular and of the outstanding leveraged positions in general.
As a result, market participants in the main may have misestimated the amount of capital actually
devoted to keeping spreads tight across a variety of markets, in that they mistook leveraged positions
as representing “real money” investment decisions. As those leveraged positions were unwound when
both the collateral and the underlying capital supporting them shrank, other investors re-evaluated the
appropriateness of spreads in terms of their own risk tolerances, which were less aggressive. Indeed,
the lower amount of capital resources devoted to relative-value arbitrage –because of both losses
incurred and the withdrawal by some investors – and the general realisation of how slim that capital
base really is may imply that market prices now reflect a more appropriate balance that is weighted
more towards those who are risk averse rather than risk tolerant.
(4)
An over-reliance on quantitative tools meant that risk management was oriented towards
things that could be easily measured – namely historical rates of return and correlations among those
returns. However, during the crisis period price and return movements suddenly deviated from many
historical correlations, rendering the advice that could be derived from simple risk management rules
problematic and significantly complicating the management of portfolio risk.
Some sense of the fragility of those correlations can be obtained from Table 5, which reports the
systematic comovement among a variety of risk spreads on a daily basis over the first and second
halves of 1998. Two points are clear: first, the relationships prevailing in the earlier period were quite
loose, suggesting that they were weak reeds upon which to support complicated risk management
techniques; and, second, these correlations tended to pick up across a wide front in the second half.
In the light of this structural instability, investors who believed that they were diversified across
instruments or countries were surprised to learn that historical correlations no longer persisted. In that
environment, traders found that hedges no longer had the same properties. One lesson learned from
this, according to some market participants, was the need to rely more on scenario analysis in risk
management, in which staff are asked to estimate changes in the value of trading positions and credit
exposures resulting from a variety of market contingencies. Although they now may be recognising
the value of scenario analysis, and applying it more actively to managing market risk, most firms have
yet to merge such techniques meaningfully into their procedures for measuring and managing their
credit risk exposures.
Some market mechanisms that fostered contagion and amplified price dynamics were more
fundamental to the structure of market institutions. As a result, they may pose risks going forward.
These include:
(5)
Increasing concentration of activity among a few large global institutions that were active
in many markets made the propagation of shocks across markets more immediate and dramatic.
Because of the broad scope of their business dealings, decisions by some of these firms to reduce their
exposure to risk – either because threats to their capital diminished their appetite for risk-taking or
because doubt in the market about their viability made leverage more expensive – influenced the
prices of many financial instruments.
(6)
Many entities relied on collateralised positions that were marked to market daily. Firms
that levered their capital by borrowing in repo markets, through securities lending, or by the use of
margin accounts at futures exchanges were required to provide more collateral or close out their
positions as prices turned against them. To the extent that they elected to trim their positions rapidly
14
rather than gradually, those entities’ actions exacerbated adverse price dynamics. If, instead, other
positions were closed to free up collateral, price shocks were transmitted to other markets.3
While the pace of consolidation in the financial industry has been intense in recent years, there still
remains a large collection of different entities. However, counting the number of firms overstates the
degree of independence among those firms, because of:
(7)
Widespread emulation of certain trading strategies and risk management practices, which
has tended to reduce the effective diversity in the market. The clearest example was the emphasis on
relative-value trading strategies, pioneered by LTCM, at other hedge funds and the proprietary trading
desks of many investment banks. The highly public travails of LTCM cast doubt on those other firms
as well and created an incentive for some traders to move prices in the expectation that serious market
dislocations would follow.
By their nature, some of these market risk control tools have the potential to tighten links across
markets and to alter price dynamics. As one example, the strategy termed proxy hedging led traders to
use major national markets to offset positions in thin markets that might have been difficult to
liquidate quickly. Complaints about such practices surfaced regarding asset prices in Australia and
Hong Kong at the time that the Asia crisis broke in 1997. When considering the events of August and
September 1998, market participants reported that as financial conditions in Russia deteriorated, short
positions in both Hungarian and Brazilian debt, which offer relatively deep markets, were put in place
to hedge against long positions in Russian securities.
Even mature markets were not immune. In European markets, a broad range of assets was hedged by
the highly liquid bund futures contract, triggering market pressures when spreads between these
securities and bunds widened. In general, our contacts believed that the liquidity of instruments traded
on organised exchanges fared better than those traded over the counter, making the former more
attractive proxy hedges. They reported both that the interposition of an organised exchange in
settlement eased counterparty concerns and that the greater transparency afforded by listed trading
might have made price discovery easier. Other analysts cited the depth of the futures market for
Mexican peso instruments as important in explaining pressures on that currency during this episode.
Proxy hedging, in general, tended to spread shocks felt on the periphery of international financial
markets to the core rather quickly.
More specifically regarding risk management:
(8)
An escalation of the locus of decision-making at many firms may have spread pressures
across markets and altered price dynamics. In particular, as decisions on exposure limits shifted
toward senior managers as stresses mounted, losses in one market, because they reduced the overall
amount of capital, then prompted withdrawals from other markets. In that sense, the events of last fall
mimicked those of a traditional margin call, albeit on a worldwide scale, as positions in a variety of
markets were unloaded as a result of losses originally concentrated in a few. Consolidation across
business lines may also have complicated decision-making. According to one market participant we
spoke with, institutions with both trading operations and significant reliance on retail and wholesale
deposits may have been quick to reduce risk so as to limit losses and not arouse concerns from their
core funding base. As another example of an unintended consequence of risk management strategies,
the general tendency at the height of the crisis for risk committees to decide each evening, based on
that day’s results, the risk tolerance for the next day may have introduced autocorrelation in daily
returns.
(9)
Some compensation and accounting practices may have intensified the responses to the
original shocks and delayed other market participants who were well capitalised from stepping in to
replace arbitrageurs who faced credit constraints. Some market participants reported that the fact that
most financial institutions had been extremely profitable through the first half of 1998 may have made
3
These systemic risks were noted in BIS (1998), OTC Derivatives: Settlement Procedures and Counterparty Risk
Management (the “Parkinson IV Report”), p. 6.
15
managers quicker to close out losing positions for fear of jeopardising shareholders’ earnings and their
own bonuses. Other discussions with market participants suggested that internal limits triggered by
marking to market implied that the preservation of risk capital required closing out some positions
even though there may have been the strong suspicion that prices had overshot only temporarily. In
that regard, competitive pressures may have induced some firms to close out positions so as not to be
seen by the public as lagging behind peers that had already disclosed losses and announced remedial
action.
Finally, the tendency for portfolio managers to be compensated according to their performance relative
to various market benchmarks made many unwilling to attempt to ride out the storm. Instead, they
traded actively to track their peers because their compensation would be relatively secure if they were
safely in the middle of the pack of fund managers.
It must be remembered, though, that while such practices are deeply ingrained in the industry, the
events of last fall did trigger realignments in the upper echelons of management at many firms. To the
extent that this episode induced a general reassessment of the importance of oversight of risk-taking
activity by senior management and boards of directors, some longer-term benefits may well accrue.
The general lesson about market practices that emerges is an old one that could be put in either of two
ways: in fall 1998, a number of large, active financial intermediaries either had too little capital
relative to the risk they were undertaking, or exposed themselves to excessive risk in the pursuit of
return. In some sense, the returns that relative value arbitrageurs earned in normal times could be
thought of as compensation for performing liquidity intermediation – that is, taking on an illiquidity
risk that the average investor was, properly, unwilling to bear. In normal times, this kind of
intermediation is rewarded by positive returns, as compensation for the risk that on rare occasions
market functioning might deteriorate, making relatively illiquid instruments especially unattractive to
most potential holders. The events of last fall highlighted the fact that the seemingly abnormal returns
earned by relative value arbitrage in normal times are not risk-free when viewed over a longer time
span.
For all the financial sophistication of prominent market participants, the economic framework that
may have applied was one of the oldest – the overshooting or “cobweb” model of economic dynamics.
Relative value trading was profitable at first because the risk and human capital devoted to take
advantage of the available opportunities was in scarce supply. Profits to that sector, naturally, attracted
more risk and human capital over time, tending to erode those profits. Rather than reaching a stable
equilibrium, however, the response to lower profits was to take on still larger positions and an
excessive amount of risk. A benign macroeconomic background and the loosening of credit terms by
counterparties cushioned the inevitable fall in returns in the industry at first, leading to yet more
risk-taking, but at the cost of what was ultimately a more wrenching adjustment.
16
The circle of deterioration in market functioning
Initial
shock
Strains on firms:
• Heightened concerns about counterparties
• Reduction in available collateral
• Reduction in risk tolerance/ increased perception of risks
17
Proxy
hedging
Deleveraging
Change in assessment
of credit risk
•
Drying-up of
liquidity
•
Changes in
market price
17
Other
markets
Chapter 4
The remaining imprint and some tentative lessons
One year after the market strains emerged, most spreads have narrowed, but not back to the thin levels
prevailing before the summer of 1998. Some spreads, such as those on interest rate swaps, are at or
above autumn 1998 levels. While bid-ask spreads for on-the-run issues have mostly returned to their
levels of before the crisis, off-the-run bid-ask spreads have not yet recovered.
By way of perspective, it is important to remember that there have been other episodes of major
stresses in fixed income markets in the past decade. In 1989 and 1990, the criminal prosecution and
subsequent bankruptcy of Drexel Burnham Lambert removed the dominant market-maker in a major
market segment: high-yield securities. In 1994, the realisation that a substantial realignment of Federal
Reserve policy was under way induced substantial strains in the debt markets of major industrial
economies. The former produced a large deterioration in the prices of the high-yield securities that
Drexel marketed and some systemic concerns related to clearance and settlement. The latter was
associated with the failure of at least one large leveraged hedge fund that relied on sophisticated
financial modelling, David Askin’s Granite Capital, which adversely affected the niche market for
collateralised mortgage obligations. In addition, the general contagion at the time evident in elevated
interest rate volatility raised correlations among returns above historical norms, lessening the benefits
from diversification and making investors skittish. As in the 1998 episode, some of the movements in
interest rates across markets in 1994 were blamed on market mechanisms such as proxy hedging.
Autumn 1998 provided drama with elements drawn from both prior episodes. Macroeconomic events
seemed closer to the root, and there was a much publicised example of the failure of sophisticated
modelling, as in 1994. But the scale and scope of LTCM’s activities in the business of relative value
arbitrage was closer to – but by no means as dominant as – Drexel’s presence in the high-yield
market.4
At the time of writing, the events of 1998 appear to have lifted more quickly than did those of 1989–
90 in the junk bond market but perhaps not so completely as those in 1994 one year later. To an
important degree, that is good news: the risk spreads prevailing in the summer of 1998 were, by and
large, unusually thin and counterparty assessments too generous. Nor is it obvious from the elevated
level of equity prices in many industrial countries, especially the United States, that credit conditions
are now restrictive.
Policymakers can draw five main lessons from the events of last autumn. Some of these lessons relate
to failures of risk management and regulatory procedures that are the focus of remedial efforts by
industry and the official sector, while others are more fundamental to the structure of financial
institutions in an era of globalisation and rapid change.
(1)
Some of the mechanisms that tightened linkages across markets and amplified price
dynamics can be addressed by carefully considered industry and government initiatives. In some
areas, this work is already under way. In particular, regulators and supervisors have provided
additional guidance on lending to highly leveraged institutions. Industry efforts, spurred by the large
losses that were experienced, are being devoted to managing market and credit risks more effectively.
Meanwhile, national governments and international organisations are examining adapting existing
reporting systems or mandating additional ones to foster greater transparency in markets.
4
It must be emphasised that at no point has the issue of criminal wrongdoing been associated with the activities of LTCM.
18
(2)
Some of the mechanisms that are more basic to institutional structure are not easily
changed by official statements or actions. Regulatory action or moral suasion is unlikely to be able to
lengthen investors’ time horizons, make traders less mindful of year-end bonuses, or render people in
general less apt to copy success. The adverse consequences of consolidation on trading dynamics have
to be weighed against economies of scale and scope in all the other businesses that financial
institutions take part in. While the turnover in senior management at several global intermediaries over
the past year may indicate that the industry is actually wrestling with these difficult issues in corporate
governance, policymakers must appreciate that similar episodes of elevated volatility of financial
prices may well take place again in the future. A goal of policymakers should be to create a regulatory
and monetary policy environment that makes it less likely that this volatility creates systemic
concerns.
(3)
Monitoring markets and understanding trading and credit risk practices is important.
Many of the most visible manifestations of market stresses occurred in markets not always directly
followed by central banks. As long as financial institutions spread their activities into new markets and
more risks become priced, central banks will have to continue to build up expertise to follow those
developments.
(4)
There is a tension between transparency of official action and reassuring market
participants. To an important extent, market participants commit to trade in financial markets because
they expect others to do so. If they think others will not, they will not, creating a self-fulfilling
prophecy. Thus, even a modest reappraisal of risk-taking appetites, imposition of a small cost, or even
public statements warning about certain behaviours could have large consequences for market activity.
The public expression of concerns about market liquidity associated with the events surrounding the
recapitalisation of LTCM could well have been interpreted by some as official concerns about other
potential counterparties. When everyone fears this, everyone withdraws, justifying their fears. At the
same time, expressing those concerns is important so that the public has an understanding of policy
setting. This is a tension in policymaking that is likely to recur going forward.
19
Chapter 5
Work to be done
This report is intended to be read alongside the other efforts within the financial industry and by
international groups to understand the events of last year. Unlike those other reports, we have tried to
emphasise the consequences across a variety of financial markets of a confluence of factors. In that
regard, this report can be taken to suggest that aspects of industry structure and market mechanisms,
which are usually studied individually, interact in a way that can have broad consequences for pricing
financial instruments. Much work remains to be done, which can be separated into two categories.
(1)
Initiatives related to improving the transparency of financial markets. There is already
some pressure to change aspects of industry structure that seem to have facilitated the spread of shocks
and amplified their effects. As noted above, national governments and international organisations are
examining either adapting existing reporting systems or mandating additional ones to foster greater
transparency in markets. Without question, it is important to follow through on that programme,
including some of the government initiatives included in the US President’s Working Group Report
(1999), the private sector recommendations in the Credit Risk Management Policy Group Report
(1999), and the multilateral efforts coordinated by, among others, the Bank for International
Settlements, the International Monetary Fund and the Basel Committee.
(2)
Initiatives related to monitoring and analysing financial markets. If the explanation for
what happened in last autumn relates to the interaction among many markets, then central banks may
well have to increase the scope of their surveillance and analysis of market pricing and functioning. In
terms of longer-term projects, it is clear that the in-depth empirical analysis of liquidity indicators will
offer a deeper understanding of market functioning. The group’s efforts to describe the large dataset it
collected only scratched the surface of potential empirical work. The differing performance of
organised and OTC markets during the crisis calls for a greater effort to understand the use of different
trading platforms. But theory also may have a role to play. It is possible that more sophisticated
financial modelling may be able to define more rigorously indicators of market stress. Some of the key
tasks here include distinguishing between liquidity and credit risk premia, backing out default
probabilities under different distributional assumptions, and studying how different margining
practices affect leverage under different scenarios. Lastly, some of the most productive time spent by
this working group was talking with market participants about their actions and reactions when
markets were stressed. Continued contacts with market participants are necessary to understand better
the continually evolving practices in the management of credit and market risks.
20
Table 2
Extremes in short-term interest rate spreads during 1998
(basis points)
Low
Date of
Low
High
Date of
High
High
Less
Low
– 22
6 Oct.
16
30 Oct.
38
1
Japan 3-month interbank
2
Hong Kong 3-month interbank
19
23 Apr.
1294
28 Aug.
1275
3
Hong Kong 6-month interbank
100
23 Apr.
1198
28 Aug.
1098
4
Hong Kong 12-month interbank
169
23 Apr.
854
28 Aug.
685
5
Mexico 1-month interbank
86
27 Apr.
628
14 Sep.
542
6
US 3-month interbank
33
26 Feb.
144
16 Oct.
111
7
US 12-month interbank
40
24 Feb.
86
16 Oct.
46
8
US 1-month prime commercial paper
– 2
9 Sep.
54
16 Dec.
56
9
US 1-month second-tier commercial paper
14
26 Feb.
135
2 Dec.
121
10
Canada 3-month interbank
– 58
27 Aug.
67
7 Oct.
125
11
UK 3-month interbank versus repo rate
15
1 Jan.
58
23 Dec.
43
12
France 3-month interbank
– 12
15 Apr.
43
28 Dec.
55
13
France 12-month interbank
– 9
1 Apr.
34
29 Dec.
43
14
France 1-month commercial paper
– 19
30 Nov.
22
30 Dec.
41
Note: Inter-bank rate spreads are measured by using Euro-rates, except for Mexico and Hong Kong.
21
Table 3
Extremes in yield spreads during 1998
(basis points)
Low
Date of
Low
High
Date of
High
High
Less
Low
1
Japan 5-year AA corporate bond
58
5 Jan.
92
20 Nov.
34
2
Japan 5-year BBB corporate bond
177
8 Jan.
227
22 Dec.
50
3
Japan 5-year bank bond
14
29 Jan.
77
10 Sep.
63
4
Japan 10-year yen Swap
58
5 Jan.
84
28 Aug.
26
5
Hong Kong 10-year government bond
222
23 Mar.
506
26 June
284
6
Hong Kong 3-year agency bond
1
6 Jan.
105
12 Oct.
104
7
Hong Kong 10-year HK$ Swap
134
5 Jan.
199
9 Jan.
65
8
Latin America Brady bond
292
23 Mar.
985
10 Sep.
693
9
Mexico corporate Eurobond
313
26 Feb.
1253
11 Sep.
940
10
US 10-year AA corporate bond
70
23 Jan.
138
5 Oct.
68
11
US 10-year BBB corporate bond
114
23 Jan.
225
4 Nov.
111
12
US speculative-grade bond
307
30 Mar.
687
19 Oct.
380
13
US 10-year US$ swap
44
11 Feb.
97
14 Oct.
53
14
Canada 10-year $ swap
17
5 Feb.
48
14 Oct.
31
15
UK 5-year Aa corporate bond
48
13 Mar.
147
5 Oct.
99
16
UK 5-year Baa corporate bond
82
17 June
191
13 Oct.
109
17
UK four 5-year bank bonds
53
2 Jan.
154
5 Oct.
101
18
UK 10-year sterling swap
26
5 Jan.
116
5 Oct.
90
19
Netherlands two industrial bonds
25
19 Mar.
68
3 Dec.
43
20
Netherlands four 10-year bank bonds
24
21 Jan.
49
14 Oct.
25
21
Germany industrial bond
19
6 Mar.
114
11 Dec.
95
22
Germany 9-10 year mortgage bond
20
29 Apr.
57
21 Sep.
37
23
Germany 9-10 year bank bond
21
6 May
59
21 Sep.
38
24
Germany 10-year DM swap
18
1 May
69
25 Aug.
51
25
France A3 corporate bond
35
5 Mar.
66
30 Nov.
31
26
France average swap rate
19
18 May
36
4 Sep.
17
27
Swiss corporate bond
22
21 July
61
1 Oct.
39
28
Swiss 5-7 year SFr swap
39
1 June
89
31 Dec.
46
Note: Spreads are measured by using domestic rates.
22
Table 4
Ex post volatility during 1998
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
Japan 10-year
100
84
188
59
140
Hong Kong 3-year
100
47
117
98
37
Hong Kong 5-year
100
58
144
135
53
Hong Kong 10-year
100
55
145
143
47
US 2-year
100
50
161
185
181
US 5-year
100
53
149
210
143
US 10-year
100
51
132
224
122
US 30-year
100
52
154
265
151
US 10-year inflation-indexed
100
69
94
193
106
UK 10-year
100
99
149
283
122
Netherlands 10-year
100
57
177
264
104
Germany 10-year
100
63
184
283
103
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Japan
100
76
133
206
110
Japan bank
100
78
105
173
93
Hong Kong
100
91
113
113
75
Korea
100
87
70
108
90
Russia
100
156
172
140
79
Brazil
100
103
302
230
164
Mexico
100
99
258
215
109
US
100
138
274
235
122
US financial
100
139
270
289
143
Canada
100
157
247
257
117
UK
100
129
219
253
145
UK financial
100
131
189
268
138
Germany
100
104
217
250
144
France
100
112
205
254
124
France financial
100
142
237
311
153
Switzerland
100
132
254
341
139
Switzerland bank
100
160
332
449
188
Government Bond Yields
Stock Market
23
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Table 4 – cont.
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
Hong Kong dollar/US dollar (12-month
forward)
100
100
154
71
34
Yen/US dollar
100
72
157
219
112
Yen/Swiss franc
100
105
166
289
118
US dollar/Canadian dollar
100
95
214
262
142
US dollar/German mark
100
91
131
136
102
US dollar/Swiss franc
100
106
163
234
158
Exchange Rate
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Notes: Volatility is measured as the square root of the mean daily squared change in the yield (essentially the standard deviation assuming
a zero mean). Shading denotes the highest volatility and boldface denotes the largest increase.
24
Table 5
Correlations Among Yield Spreads (tenths)
1/1/98 to 7/3/98
UK
Aa
30
Japan 5-year AA corporate bond
Japan 5-year BBB corp. bond
Japan 5-year bank bond
Japan 10-year yen swap
HK 10-year government bond
HK 3-year agency bond
HK 10-year HK$ swap
Latin America Brady bond
Mexico corporate Eurobond
US 10-year AA corporate bond
US 10-year BBB corporate bond
US speculative-grade bond
US 2-year US$ swap
US 10-year US$ swap
Canada 10-year C$ swap
UK 5-year AA corporate bond
UK 5-year Baa corporate bond
UK four 5-year bank bonds
UK 10-year sterling swap
Netherlands two industrial bonds
Netherlands four 10-year bank bonds
Germany industrial bond
Germany 9–10 year mortgage bond
Germany 9–10 year bank bond
Germany 10 year DM swap
Switzerland corporate bond
Switzerland 5–7 year SFr swap
+2
+1
+1
+4
–1
+1
+3
+1
–1
+1
+1
UK
Baa
+2
+3
+2
+3
+3
+2
–1
–1
–1
+1
–2
–1
+8
UK
bnk
+1
+1
+2
+1
+3
+1
+2
+3
+2
+1
+1
+3
+3
+2
+1
+7
+7
UK
swa
+1
+2
–2
+3
+1
–2
+2
+2
+1
–1
+1
+2
–1
–1
Nth
ind
+2
+3
+2
+2
+1
+3
+2
+1
+1
+1
+1
–1
+1
+2
+2
Nth
bnk
+1
+1
+1
+1
–1
–1
+1
–1
+1
–1
–1
+3
+2
+1
–1
+2
Ger
ind
+1
–1
–1
+1
+2
–1
+1
+1
+3
+2
+4
+1
+2
+2
–1
–2
+1
–4
–1
7/6/98 to 12/31/98
Ger
mrt
Ger
bnk
–1
+3
+1
+2
–2
+3
+3
+4
+4
+4
+5
+1
+3
+2
+1
+3
+2
+1
+2
–1
+1
+3
+3
+4
+3
+3
+1
+3
+2
+1
+1
+2
+1
–1
+3
+8
Ger
swa
–1
+2
+2
–1
+2
+2
–1
–1
+1
+1
+1
–1
–1
+4
+1
–1
Swi
crp
+1
+2
–1
–2
+1
–1
–2
–2
+1
+1
–2
–1
+1
–2
–1
–1
–1
+1
+1
Swi
swa
+1
+1
–1
–1
+2
–1
+1
+1
–1
+2
+1
–2
–2
–1
+2
+1
+1
+1
+1
+8
UK
Aa
+1
+1
+1
–2
–1
+2
–1
+4
+4
+4
+4
+6
+5
+6
+5
UK
Baa
+1
+1
–3
–2
+2
–1
+3
+4
+4
+4
+6
+5
+6
+5
+10
UK
bnk
+2
–3
–1
+2
–1
+3
+4
+5
+4
+6
+3
+5
+4
+9
+9
UK
swa
+2
+3
+2
Nth
ind
Nth
bnk
+2
+2
+3
–3
+1
+2
–2
–1
+5
+5
+2
+1
+4
+2
+6
+4
+7
+5
+7
+1
+3
+2
+1
+3
+3
+2
+2
+2
+2
+2
+1
+4
+5
+2
+2
+4
+2
+3
+2
+5
+4
+5
+5
+2
Ger
ind
–2
–1
–2
–1
+1
–1
+2
+2
+1
+1
+1
+1
+2
+1
+1
+1
+2
+2
+1
+2
Ger
mrt
+2
+2
+4
+1
+3
Ger
bnk
+3
+2
+3
+2
+3
Ger
swa
+1
+1
+3
+1
+3
+5
+4
+1
+1
+2
+3
+6
+3
+4
+3
+3
+6
+5
+5
+1
+1
+3
+3
+6
+3
+4
+3
+4
+6
+5
+4
–1
–1
+2
+2
+6
+3
+3
+2
+3
+6
+4
+3
+4
+4
+10
+3
+2
+9
+8
Swi
crp
+1
+2
Swi
swa
–1
–2
–1
–2
+2
–1
+1
+2
+3
+3
+5
+2
+3
+2
+5
+5
+5
+3
+2
+2
–1
–1
+1
+1
+1
+3
+1
+2
+1
+2
+1
+1
+1
+1
+1
–2
+1
Notes: Statistics are based on 5-day changes in spreads, to allow for time-of-day differences. Correlation coefficients are rounded to nearest 10% and expressed in tenths, so that “+3” denotes 30%, for example. Shading ranges
from white for zero or negative correlation to black for 100% (rounded) correlation. Each data label references both a row of the matrix and the column above its right-most extent.
25
Chart 1
Equity Prices
North America and Japan
Asia
Index, January 2, 1997 = 100
LTCM
Thailand Equity Russia U.S. Rate Cut
Pressures
180
Index, January 2, 1997
LTCM
180
Thailand Equity Russia
U.S. Rate Cut
Pressures
140
U.S.
Korea*
Hong Kong
150
100
Canada
60
120
Thailand
Indonesia
20
J M M J S N J M M J S N J M M J
1997
1998
1999
Japan*
90
Eastern Europe
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
350
300
250
60
Russia
J M M J S N J M M J S N J M M J
1997
1998
1999
Europe
200
150
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
Italy
270
100
Poland
50
240
0
J M M J S N J M M J S N J M M J
1997
1998
1999
210
Latin America
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
Germany
180
200
Brazil
160
France
150
Mexico
120
U.K.
120
Argentina
80
90
40
J M M J S N J M M J S N J M M J
J M M J S N J M M J S N J M M J
1997
1998
1999
1997
1998
1999
*Japan: Index,January 6, 1997; Korea: Index, January 3, 1997
Chart 2
Nominal Currency Exchange Values
(Foreign currency prices of U.S. dollar)
Asia
Index, January 2, 1997 = 100
130
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
Index, January 2, 1997
675
Thailand Equity
Russia LTCM
U.S. Rate Cut
Pressures
600
525
450
120
Indonesia
375
Thailand
300
225
Korea
Malaysia
110
150
75
J M M J S N J M M J S N J M M J
Canada
100
Eastern Europe
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
700
600
Japan
Russia
500
90
J M M J S N J M M J S N J M M J
1997
1998
1999
400
Bulgaria
300
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
130
Poland
Czech
Republic
200
100
0
J M M J S N J M M J S N J M M J
1997
1998
1999
120
Latin America
LTCM
Thailand Equity Russia
U.S. Rate Cut
Pressures
Brazil
240
210
180
110
150
Mexico
120
Germany/
restated Euro
Argentina
100
J M M J S N J M M J S N J M M J
1997
1998
1999
90
60
J M M J S N J M M J S N J M M J
1997
1998
1999
Chart 3
Long-term Government Bond Yields
United States
Percent
Thailand
Equity Pressures
Russia LTCM U.S. Rate Cut
7
6
5
4
3
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Germany
Percent
Thailand
Equity Pressures
Russia LTCM U.S. Rate Cut
6
5
4
3
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Japan
Percent
Thailand
Equity Pressures
Russia LTCM U.S. Rate Cut
4
3
2
1
0
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Chart 4
Corporate Yield Spreads
AA-Rated Bonds
BBB-Rated Bonds
Basis Points
Thailand
LTCM
Equity Russia U.S. Rate Cut
Pressures
180
Thailand
Basis Points
LTCM
280
Equity Russia
U.S. Rate Cut
Pressures
240
150
Japan
120
200
160
90
U.S.
U.S.
120
60
U.K.
Japan
30
80
U.K.
0
40
D F A J A O D F A J A O D F A J
1997
1998
1999
D F A J A O D F A J A O D F A J
1997
1998
1999
Europe
Speculative-Grade Bonds
Basis Points
Thailand
LTCM
Equity Russia
U.S.
Pressures
Rate Cut
150
Thailand
Basis Points
1400
LTCM
Russia
U.S. Rate Cut
Equity
Pressures
1200
120
1000
90
Germany*
Mexico
Netherlands
800
60
600
Switzerland
30
United States
+
0
–
200
30
D F A J A O D F A J A O D F A J
1997
1998
1999
*Break in German series
400
0
D F A J A O D F A J A O D F A J
1997
1998
1999
Chart 5
Broad and Bank Stock Indexes
United States
Thailand
1100
Equity Pressures
Russia LTCM U.S. Rate Cut
1500
900
1300
700
S&P 500(right scale)
1100
500
300
Money Center
Banks
(left scale)
Regional Banks
(left scale)
100
900
700
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Europe
240
Thailand
Equity Pressures
220
240
Russia LTCM U.S. Rate Cut
Bloomberg Europe
500
220
200
200
180
180
Bloomberg Europe
500 Banks
160
160
140
140
120
120
100
100
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Japan
900
Thailand
Equity Pressures
1650
Russia LTCM U.S. Rate Cut
800
1550
Topix
(right scale)
700
1450
600
1350
500
1250
400
Topix Banks
(left scale)
300
200
1150
1050
950
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Chart 6
3-Month Interbank Rate Spreads
North America and Japan
Basis points
200
Thailand
Equity Pressures
LTCM
Russia
U.S. Rate Cut
150
100
United States
50
Canada
+
0
–
Japan
50
100
J
F M A M J J A S O N D
1997
J
F M A M J J A S O N D
1998
J
F M A M J J
1999
Europe
Basis points
75
Thailand
Equity Pressures
LTCM
Russia
U.S. Rate Cut
50
United Kingdom
25
France
+
0
–
25
J
F M A M J J A S O N D
1997
J
F M A M J J A S O N D
1998
Note: Eurocurrency rate over treasury spreads plotted, except UK and France.
For the UK, we calculated the eurosterling rate over the repo rate.
For France, we calculated the domestic inter-bank(bid) rate over the treasury rate.
J
F M A M J J
1999
Chart 7
Government Bond Yield Spreads
Offshore Bond Yield over U.S. Treasury
Daily
Thailand
Russia
Equity Pressures
LTCM
20
U.S. Rate Cut
15
Indonesia
Malaysia
Korea
10
5
Thailand
0
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Stripped Brady Bond Yield Spreads over U.S. Treasuries
Thailand
Equity Pressures
LTCM U.S. Rate Cut
Russia
80
Russia
70
60
50
40
30
20
Bulgaria
10
Poland
0
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Stripped Brady Bond Yield Spreads over U.S. Treasuries
Thailand
Equity Pressures
LTCM U.S.
Rate Cut
Russia
25
20
Brazil
15
10
Argentina
5
Mexico
Equity Pressures
J F M A M J J A S O N D J
1997
0
F M A M J J A S O N D J
1998
F M A M J J
1999
Chart 8
Liquidity Spreads for 10-Year Government Bonds
Basis Points
30
Thailand
Equity Pressures
Russia
LTCM
U.S. Rate Cut
24
18
United Kingdom
Yield spread difference between
8.5% 2007 and 7.25% 2007 gilt
12
6
+
0
–
Japan
Spread between off-the-run and
on-the-run 10-year JGB
6
12
D
J
F M A M J J
1997
A S O N D
J
F M A M J J
1998
A S O N D
J
F M A M J
1999
Off-the-Run U.S. Treasury Spreads over On-the-Run
Daily
LTCM U.S. Rate Cut
Thailand
Equity Pressures
Russia
28
Thirty Year
Five Year
Ten Year
21
14
7
+
0
–
7
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J
1999
Chart 9
Bid-Ask Spreads
United Kingdom
Russia
LTCM
Basis Points
350
U.S. Rate Cut
300
250
200
150
AA Corporate Bond
100
BAA Corporate Bond
50
Dec
Jan
Feb
Mar
Apr
May
June
1998
July
Aug
Sep
Oct
Nov
Dec
Chart 10
Implied Volatility for Interest Rates
Government Bond Yields
Thailand
Equity Pressures
Percent
Russia LTCM
U.S. Rate Cut
120
100
80
60
Brazil 30-day C-Bond
40
France 10-Year
20
United States 30-Year
0
D
J
F M A M J J
1997
A S O N D
J
F M A M J J
1998
A S O N D
J
F M A M J
1999
3-Month Interest Rates
Percent
70
Thailand
Equity Pressures
Russia LTCM
U.S. Rate Cut
60
50
40
United States
30
France
20
10
United Kingdom
0
D
J
F M A M J J
1997
A S O N D
J
F M A M J J
1998
A S O N D
J
F M A M J
1999
Chart 11
Implied Volatility
Stock Market Indices
Percent
Thailand
Equity Pressures
Russia
60
LTCM
U.S. Rate Cut
Switzerland
50
40
30
United Kingdom
United States
20
10
0
D
J
F M A M J J
1997
A S O N D
J
F M A M J J
1998
A S O N D
J
F M A M J
1999
Dollar Exchange Rates
Percent
Thailand
Equity Pressures
Russia
60
LTCM
U.S. Rate Cut
50
Swiss Franc
40
30
30-day Mexican Peso
20
10
0
D
J
F M A M J J
1997
A S O N D
J
F M A M J J
1998
A S O N D
J
F M A M J
1999
Chart 12
Swap Spreads over Ten-Year Government Securities
Thailand
Russia LTCM U.S. Rate Cut
Equity Pressures
100
Daily
80
60
United States
Japan
40
20
Canada
U.S. Rate Cut
J F M A M J J A S O N D J
1997
Thailand
0
F M A M J J A S O N D J
1998
Equity Pressures
F M A M J J A
1999
Russia LTCM U.S. Rate Cut
120
100
80
60
United Kingdom
40
20
Germany
0
J
F M A M J J A S O N D J
1997
F M A M J J A S O N D J
1998
F M A M J J A
1999
Annex 1
Summary of interviews with market participants
This annex summarises the interviews with market participants on the market events of autumn 1998.
The interviews were conducted by the central banks in each country represented in the Working
Group, and by the Group itself during its 2 July meeting.
The questions focused on four main topics. Firstly, interviewees were asked to identify the major
market events during autumn 1998. Secondly, they characterised the market conditions during the
crisis. Thirdly, they reviewed their firm’s activities from the specific standpoint of risk management
activities during the crisis. Finally, they were invited to draw long-run lessons from the crisis.
This annex, based on national write-ups, reflects the consensus view that tended to emerge among
market participants, citing divergent points of view when necessary.
The presentation follows the lines of the questions addressed to market participants. In the first
section, the major market events during autumn 1998 are described as they were perceived by market
participants: the triggering factors, the unfolding of the crisis and the beginning of relief in the
financial markets. Secondly, market functioning during the crisis period is discussed, with a focus on
the interaction of market, credit and liquidity risks. Finally, the legacy of the crisis is analysed in
several respects: risk aversion behaviour, risk management techniques and the internal organisation of
financial firms.
1.
Major market events during autumn 1998 as perceived by market participants
This section focuses on the perception of events by market participants but does not describe the
events themselves, which are summarised in Table 1 on page 3-4.
1.1
The triggering factors
Both the Russian crisis (rouble devaluation and default) and near-collapse of LTCM were mentioned
as the major events triggering the crisis. One interviewee noted that a major shock was caused to the
market when the IMF signalled that its support of Russia was not unconditional. Another reason
Russia’s default may have caused so much turmoil was because it was a default on traded securities
whereas the Asian problems in 1997 had been primarily in bank loans, which caused problems for
banks affected but did not necessarily disrupt markets more broadly.
1.2
The unfolding of the crisis and the beginning of the recovery
The unfolding of the crisis in developed markets, which was characterised by numerous risks (see
section 2), was punctuated by both events and rumours. In Japan, however, the effects of the crisis
were relatively limited, given the low exposure of Japanese banks to Russia, the focus on domestic
developments, such as the government’s banking reform policies, and the presence of a negative riskaverse mood since the collapse of financial firms.
The Hong Kong Monetary Authority stock market intervention in August, capital controls in Malaysia
in September, rumours of difficulties at Lehman Brothers and other financial institutions, the dramatic
fall in the yen/dollar exchange rate at the beginning of October, and reports of losses or lower earnings
by large banks (such as BankAmerica Corp.) were mentioned by respondents as the most significant
events.
38
According to several market participants, the first rate cut decided by the FOMC (23 September)
fuelled concern among traders. That decision was perceived as a sign that markets were experiencing
even more severe troubles than initially thought.
The second monetary easing by the Federal Reserve (15 October) signalled the beginning of the
abatement of financial strains. At that time, traders clearly understood the commitment of the Federal
Reserve to fix the problems. Even with the beginning of the recovery, market participants continued to
avoid large exposures for the rest of 1998, because they did not want to further jeopardise the gains
that they had booked in the first half of the year.
2.
Market functioning during the crisis
Perhaps the most striking characteristic of the autumn 1998 crisis is the unfolding of multiple
combined risks. For the sake of clarity, section 2.1 describes how market participants assessed these
risks in isolation and section 2.2 is devoted to the dynamics of the crisis.
2.1
The different strains on financial markets during autumn 1998
Market participants identified several severe strains in financial markets during the crisis.
First of all, financial markets registered severe bouts of high volatility: there were increases both in
historical volatility, reflecting the turbulence that markets had already experienced, and in implied
volatility, measuring market risk expected in the future as discounted by market participants. The
drying-up of liquidity hit financial markets, even the most active ones. Finally, the crisis led to a
reappraisal of credit risk especially among financial intermediaries. This last feature was particularly
stressed by the respondents.
2.1.1
The peaks in realised/expected market risks
Market risk, as measured by the volatility of asset prices, was the best documented of the phenomena
that occurred during the autumn 1998 crisis. Therefore, the interviewees did not analyse this feature in
detail.
2.1.2
The drying-up of liquidity
The drying-up of liquidity took several forms.
Market participants mentioned the widening in bid-ask spreads, to an unprecedented extent in several
markets. This was particularly true of the foreign exchange market and more precisely the dollar/yen
rate at the beginning of October. In extreme conditions, markets became one-sided. Simultaneously,
investors looked for the most liquid government bond issues, e.g. on-the-run issues, in order to ensure
the possibility of easily unwinding long positions. That reallocation raised the price of on-the-run
issues relative to off-the-run issues, the spread between these two issues reflecting the liquidity
premium.
Market participants diverged in their analysis of the functioning of government bond markets. Some
respondents noted that even compulsory market-making was not sufficient to ensure the liquidity of a
market: a number of market-makers withdrew from trading and did not ensure quotations. But
according to others, the ability to transact for the desired amounts was maintained through the crisis.
Even these respondents admitted, however, that this continued functioning was limited to on-the-run
issues.
2.1.3
The reappraisal of credit risk
In market participants’ view, credit risk reappraisal was the most important phenomenon of the crisis.
The consequences of this reappraisal for financial markets were manifold.
39
The events described above triggered a search for the safest financial assets. This search manifested
itself in a flight to quality, benefiting US and European government bonds, and for a brutal but
short-lived period a flight to cash episode benefiting the short end of these yield curves.
This reassessment also led to a sharp widening in credit spreads. The credit risk of financial
intermediaries, which is reflected by the spread between swap rates and government bond rates, was
revised upwards by investors. Likewise, spreads between corporate bonds and government bonds
surged.
Several interviewees reported that the widening in credit spreads was further amplified by the
drying-up of liquidity and by hedging activities. The search for the most liquid assets underpinned
government bonds, thanks to the depth of these markets, to the detriment of financial assets issued by
the private sector. Moreover, during the crisis, market-makers changed the way they hedged their
corporate bond portfolios by switching to interest rate swaps instead of government bonds. This switch
was motivated by the fact that swap spreads followed the same pattern as credit spreads. This new
behaviour (which had already been adopted by some market-makers) in turn fuelled the widening in
credit spreads. It is noteworthy that, according to some respondents, these two types of spreads reacted
differently in the immediate aftermath of the crisis and therefore generated counterproductive hedges.
Simultaneously, credit risk reappraisal, especially with regard to financial intermediaries, took the
form of reductions in credit lines to other financial institutions. Only a minority of market
participants noted cuts in credit lines, however. Though sharply reduced, lending activity was not
discontinued altogether.
2.2
The interaction of risk
Only a very small number of market participants declined to characterise the 1998 crisis as
“exceptional”. Most interviewees mentioned that the events described, including the emergence and
interaction of the three kinds of risk mentioned above, led to the worst crisis ever. In this respect, they
stressed deficiencies in risk management techniques and the role they played in the contagion process.
2.2.1
An explosive combination of risks
The diagram below summarises the market participants’ view regarding the interaction of the three
risks in the most comprehensive way. The sequencing of these six points is for the convenience of this
report: the actual process was very swift.
Portfolio reallocations
1
Initial market
shock
VAR, mark-to-market,
stop-loss, margin calls,
proxy hedging.
2.a
2.b
Spillover into
other markets
Deleveraging
3
4.a
6
Higher credit risk :
. flight to quality,
widening in spreads,
. higher financing costs,
reduced credit lines
5.a
Liquidity drying-up
4.c
4.b
Higher market risk
volatility
5.b
40
:
1: The initial market shock, e.g. the Russian crisis and LTCM episode, triggered portfolio reallocations
due to value-at-risk (VaR) models, mark-to-market techniques and stop-loss orders (see below for
further details).
2.a: Portfolio reallocations led to a deleveraging process (see below for further details).
2.b: Portfolio reallocations, in reaction to the initial shock to one asset, needed to involve other classes
of assets in order to reach a new equilibrium for the rebalanced portfolio. Moreover, in order to honour
margin calls, investors had to sell other assets.
An important example of the spillover process had already been seen in the interactions among the
different Asian and Pacific markets. Institutional investors who had long positions in less liquid Asian
markets, such as Thailand, Indonesia and Malaysia, created short positions in more liquid Asian
financial markets, such as Hong Kong, Singapore and Australia, as a proxy hedge to their long
positions. That process engineered a sharp fall in these markets despite the fact that the economic
conditions of these places were still relatively sound.
3: The deleveraging process that induced, for instance, a reduction in activity in repo markets and in
arbitrage activities more broadly, caused liquidity to dry up in the markets where this process took
place.
4.a: Traders were prevented from withdrawing from illiquid markets. Therefore, they unwound
positions in related asset classes.
4.b: The evaporation of liquidity exacerbated market price volatility.
4.c: It also reduced the sources of financing for financial institutions that relied on the market for
funding. Therefore, the credit risk assigned to these entities rose. Financial institutions that had already
represented a relatively high credit risk faced financial difficulties: higher financing costs and reduced
credit lines. Moreover, higher perceived credit risk led to a flight to quality and a widening in credit
spreads.
5.a: The contagion process spread volatility to other markets.
5.b: In a high volatility environment, compliance with mark-to-market limits led to “distress sales”.
High paper losses seemed briefly to endanger financial institutions.
6: Higher credit risk (higher financing costs and difficulties obtaining financing) compelled financial
institutions to unwind their positions. This withdrawal magnified the drying-up of liquidity.
2.2.2
The role played by risk management techniques in the contagion process
Value-at-risk models measure market risk over a determined horizon and within a defined confidence
level. In extreme market conditions, these models show some weaknesses.
There was a range of responses among the interviewees as to whether the magnitude of mature market
turbulence was within or above their VaR limits. A large majority of interviewees admitted that last
autumn’s events were in the “tails” of distribution and that therefore their VaR models were useless
for measuring and monitoring market risk. On the other hand, other respondents (though a very small
number) judged that their VaR models remained adequate.
Most of the interviewees also stressed that during autumn 1998 their estimated correlation matrices
(which relied on historical data) and their assumption that liquidity would be available within a
short-term horizon became unrealistic.
All in all, they shared the view that VaR models are not designed to measure/monitor market risk
under extreme conditions: they are only supposed to provide reliable information on potential losses in
a statistically defined percentage of occurrences. Instead, stress events have to be analysed by other
tools, such as stress tests.
The deficiencies of the VaR methodology in conditions of contagion were unanimously emphasised
by market participants. The surge in VaR levels above predefined limits during the crisis compelled
market participants to unwind positions in the assets for which VaR limits were exceeded. Because of
41
the widespread use of similar models, similar behaviour was adopted by numerous investors. The
resulting simultaneous pressure to unwind positions dried up the liquidity of markets and therefore
exacerbated price volatility.
Moreover, illiquidity prevented investors from liquidating certain assets (i.e. those for which the VaR
limits was exceeded) by as much as the VaR model would have suggested. Investors were forced to
liquidate other, related assets. In this way, the contagion process was amplified.
In the view of market participants, the mark-to-market approach also played a major role in the
contagion process. When stop-loss limits as measured by the mark-to-market technique were reached,
sales were activated automatically and put additional pressure on markets. Furthermore, for leveraged
instruments such as futures contracts or repo transactions margin calls, again relying on
mark-to-market calculations, drove investors to sell assets.
2.2.3
Weaknesses of credit risk assessment
Some market participants admitted that time series data, on emerging economy issuers especially,
were neither consistent nor long enough to appraise credit risk in a reliable manner.
Moreover, interviewees mentioned that competition among financial institutions contributed to lower
haircut levels and margin calls.
2.2.4
The weaknesses of a non-integrated risk management process
Risk management techniques did not take into account the interplay between market risk and credit
risk. These risks were measured in isolation. Most market participants mentioned that, in their own
financial institutions, credit risk management and market risk management were conducted by
separate teams with their own language. Finally, because of the assumption of a continuous liquid
market, liquidity risk was not adequately appreciated.
3.
The long-term impact of the crisis
According to interviewees, the exceptional intensity of the autumn 1998 crisis probably led to a
structural shift in risk aversion profiles in the financial industry. This structural evolution manifested
itself in improvements in risk management techniques and improvements in the internal organisation
of financial firms.
3.1
A likely structural change in risk appetite
Most market participants reported that the emerging market crisis in 1997–98 and the mature market
turbulence in autumn 1998 provoked a structural decrease in their level of risk appetite. On the other
hand, a very small number of interviewees contended that persistently higher yield premia and higher
expected market risk (measured by implied volatility) than before the crisis were the consequence of
persistently greater risks.
The majority’s point of view was supported by several lessons from the crisis. One legacy of the crisis
is that financial institutions can suddenly lose their equity, especially when they have highly leveraged
exposures. In other respects, traders know that liquidity on financial markets cannot be taken for
granted any more.
This more cautious behaviour has led to a resilience in indicators of financial strains (implied
volatilities, credit spreads), many of which have not yet returned to their pre-crisis levels. More
prudence has also triggered a decline in the level of activity on financial markets – proprietary trading
as well as activities on behalf of customers. After the sharp and forced deleveraging process during the
crisis, market participants deliberately maintain lower leveraged positions than previously. A negative
consequence of the reduction in proprietary trading activity may be that price anomalies are now more
persistent than they used to be.
42
3.2
The legacy for risk management techniques
3.2.1
Refinements in market risk management
As mentioned above, in the view of market participants the VaR model is not designed to measure or
monitor market risk under extreme conditions. Therefore, they do not reject the technique but are
endeavouring to refine it. One example of these refinements concerns the horizon over which VaR is
calculated. Specifically, it has been lengthened in order to take into account the difficulty in
unwinding positions due to the drying-up of liquidity.
Interviewees emphasised the need for improvement in stress testing in order to estimate potential
losses in extreme conditions (the “fat tails” of the distribution). Progress was acknowledged to be
needed in defining these scenarios through a better analysis of disruptive price movements.
3.2.2
Improvements in credit risk management
With regard to the LTCM episode and the opacity of the firm’s positions and level of leverage, market
participants underlined the need to know their customers better. They did not elaborate on the
appropriate disclosure improvements, but they seemed to be less willing to lend to financial
institutions that conduct business without transparency (e.g. financial institutions that do not want to
disclose information that would help their counterparties to measure their positions and degree of
leverage). They referred to more cautious policies regarding the quality of assets taken as collateral,
the level of haircuts and margin calls. Market participants also suggested that netting agreements could
be another way to improve credit risk management.
3.2.3
Appraisal of liquidity risk and the interactions among risks
Regarding liquidity risk, respondents say that they now calculate VaR with a longer horizon, i.e. a
“liquidity-adjusted” VaR (see above). Some interviewees indicated that they are increasingly sensitive
to the size of the market in which they want to take positions. Regarding the interactions among risks,
market participants are studying ways to take account of correlations between credit risk and market
risk. Some of them are studying a common measure for these two risks in order to calculate a single
global VaR.
3.3
The internal organisation of financial firms
3.3.1
The lessons for the organisation of trading activities
Some market participants mentioned reorganisations in their front office activities. For instance,
separate emerging market trading units were dissolved and integrated into regular global market
trading units. Arbitrage activity, which in some financial firms formed a separate business line, has
been integrated into other business lines.
3.3.2
The lessons for the organisation of risk management
Interviewees shared the view that the assessment of the interactions among risks calls for closer links
between teams managing credit risk and market risk, and perhaps the merger of these separate staffs.
They also foresee that the definition of stress scenarios (the identification of potential financial strains
and estimation of their magnitude) could be developed by joint economic teams.
3.3.3
The need to define and communicate strategic objectives for the firm
The need to define strategic objectives for the firm is essential during crises. In the face of exceptional
events, managers must make clear choices: whether to cut positions after experiencing substantial
losses; whether to sue the issuer when there is a forced debt restructuring or to accept the restructuring
in order to maintain good business relationships. Moreover, these strategic objectives have to be
communicated and explained to traders, especially when these overall objectives may be in conflict
with the goals of trading units.
43
Annex 2
Comparative data on liquidity and credit risk
The purpose of this annex is to empirically characterise the events in financial markets in the second
half of 1998 with the help of an extensive customised dataset that has been compiled from the
contributions of working group members. The analysis is particularly focused on the degree of
comovement in asset prices, in addition to the extremity of price movements and market liquidity. In
particular, we will be trying to address questions such as:
•
How extreme were price movements, credit spreads, measures of implied and realised price
volatility, and indicators of liquidity in comparison to normal periods? Although many of our
data series are available for a relatively short period, we will also try to place 1998 in a
somewhat longer-term context.
•
Which markets were particularly impacted? Were there some markets that escaped
unscathed?
•
Were short-term comovements of asset prices markedly different from those seen in other
periods?
•
Were all markets affected most at about the same time or at different points during the
period?
•
What was the timing of the market turmoil with respect to major news events, such as the
Russian default and the re-capitalisation of the Long-Term Capital Management (LTCM)
hedge fund? How did subsamples (e.g. pre- and post- Russia and LTCM) differ?
•
What evidence is there of reduced liquidity during the period and which markets were
affected? We look at bid-ask spreads, trading volume, primary market activity, and liquidity
premiums in asset prices.
•
Particularly from a central bank perspective, a key implication of financial market turmoil is
the risks and challenges it poses for financial institutions that must operate under those
conditions. Thus we try to cast some of the analysis in terms of the consequences for risk
exposures of trading firms and for the effectiveness of common hedging strategies.
Our principal findings are:
•
During the second half of 1998 credit spreads widened, stock prices fell and volatility
increased markedly in the majority of financial markets worldwide.
•
Although the 17 August news of the Russian default seemed to serve as a trigger point for
volatility and significant asset price declines, conditions worsened after the 23 September
announcement of the LTCM recapitalisation agreement, and many market indicators hit
bottom in the first half of October.
•
However, the timing and severity differed somewhat across broad market categories. Hong
Kong’s experience was mild in comparison to what it saw in the first half of the year.
Emerging markets more generally were hit particularly hard in August, but did not worsen
significantly, and in many cases improved, from early September. Most short-maturity
spreads and Japanese bond spreads only began to widen significantly towards the end of the
year, as most other markets were recovering.
•
Financial sector stock indices fell more than national market indices, but swap spreads and
bank bond spreads widened by about the same amount as corporate bond yield spreads.
44
•
Correlations between weekly changes in yield spreads were heightened somewhat in the
second half of the year but, with the exception of closely related assets, typically reached
levels of only around 20-50%. Thus “correlation risk” ought to have increased by large
amounts only for relatively undiversified portfolios of credits. However, there was somewhat
greater comovement in options prices, as reflected in measures of implied volatility. To the
extent that they can be measured over a period so short, correlations appeared to be highest
during the five-week period between the Russian default and the LTCM recapitalisation
agreement. Individual correlation coefficients did not seem to be exceptionally unstable in
the second half of 1998.
•
Market participants hedging positions with futures or options would not have been insulated
from the market turbulence.
•
Quoted bid-ask spreads rose in some markets but not in some of the others for which data
were available, such as European interbank markets. Overall turnover in exchange-traded
instruments did not decline significantly, but OTC trading of emerging market bonds fell
sharply in the fourth quarter, despite the recovery in prices.
•
For some market indicators, particularly for stock market volatility, this was the most
turbulent episode of the 1990s, but numerous other financial indicators – including most of
our credit spread series – have reached more extreme levels within the past few years.
Overall, the confluence of market movements since in late summer and autumn 1998 seems
to fall into the category of a somewhat unusual but not extremely rare event.
The remainder of the discussion examines the evidence one piece at a time. A significant portion of
the analysis is structured by separating 1998 into shorter intervals, the boundaries of which are marked
by news events we considered to have potentially significant market implications, such as the Russian
default and the LTCM news. Because there was some anecdotal evidence of significant deterioration
prior to mid-August, we further divided the pre-Russia sample into two pieces, choosing the 6 July
disbanding of Salomon Brothers’ storied bond arbitrage desk as the transition point. Finally, we
selected the mid-October US rate cut as a possible trigger point for recovery. Accordingly, we found
ourselves with five sub-periods:
1 January – 3 July
6 July – 14 August
17 August – 22 September
23 September – 15 October
16 October – 31 December
Credit spreads in 1998
Table A1 shows average (yield and swap) spreads, relative to a government bond of the same
maturity, for each of the sub-periods, listed geographically from Japan to Switzerland. A majority of
these spreads, particularly in European and North American markets, reached their peak levels (the
shaded cells) in the post-LTCM period, but most showed their largest increases (displayed in boldface)
between the pre and post-Russia periods. Spreads that were initially wider tended to experience larger
proportional increases, although the Japanese BBB bond spread barely budged. Yield spreads mostly
declined after the US inter-meeting rate cut in mid-October, in a number of cases, as shown in
Table A2, reaching their 1998 peaks just before the Federal Reserve’s surprise announcement.
Short-term markets (Table A3) show a more mixed pattern. Asian and emerging market spreads
widened between mid-year and late September but then narrowed, particularly in Hong Kong, by
year-end. The UK, US and Canadian spreads shown here rose mostly after 22 September. The US and
Canadian interbank spreads came back down later in the year, but US commercial paper spreads
widened further. The French short-term spreads shown here changed little over the whole period.
45
Short-term spreads often reached their peak levels (Table A4) at about the same time as longer-term
spreads in the same country, but the UK interbank and US commercial paper spreads did not peak
until December.
Bank spreads in 1998
Figures A1 to A4 show bank bond yield spreads with corporate bond spreads and swap spreads for
Japan, the Netherlands, the United Kingdom and Germany respectively. The patterns vary somewhat
across the four countries, but in general bank bonds were not punished much more than other
corporate bonds, and swap rates did not diverge sharply from bond yields. The comovement between
swap spreads and bank bond spreads, which was particularly close in the United Kingdom and
Germany, suggests that swap spreads were widening more on credit concerns than from any reluctance
on the part of market participants to bear interest rate risk.
In Japan, however, swap spreads declined significantly in September and early October, while bank
bond spreads lagged somewhat. Nevertheless, by year-end, Japanese bank bonds were trading once
again at yield spreads distinctly narrower than AA-rated corporate bonds. Corporate bonds also
underperformed in the Netherlands, with spreads widening relative to bank bonds.
Market indicators of liquidity
Table A5 shows bid-ask spreads for a variety of markets. The table reflects sharply higher transaction
costs for the Mexican peso exchange rate by late summer, and later increases for UK corporate bonds
decreasing in credit quality. However, at least based on the data shown here, liquidity in Swiss and
French swap and interbank markets appears to have been unimpaired, with quoted bid-ask spreads
holding steady through the year. A caveat is that to the extent that these data represent indicative
prices, rather than firm offers to trade in significant quantities, they may not reflect variation over time
in the ability of these markets to absorb transaction flow.
Table A6 shows spreads between non-benchmark and benchmark 10-year government bonds for
Japan, the United States and the United Kingdom, which are thought to reflect the greater liquidity of
the more traded benchmark security. Also shown is the spread between Dutch and German sovereigns,
which probably reflects greater liquidity for the German bunds, which serve as underlying instruments
for exchange-traded derivatives, rather than considerations of relative default risk or devaluation risk.
The two European spreads widened distinctly following the Russia and LTCM events.
Stock prices
Table A7 shows the lowest levels reached in the five sub-periods for national stock market indices
around the world. Most of the industrial country indices hit lows in early October that were 20-30%
below their mid-year levels, with east Asian and Latin American markets bottoming somewhat earlier.
Financial sector stocks fared somewhat worse than broader indices, with the Swiss bank index losing
more than half of its value in just three months. Small-capitalisation stocks in the United States, which
are less liquid and likely to be more affected by informational asymmetries, underperformed the
broader market.
Implied and actual volatility
Table A8 shows sub-period averages of implied volatility measures derived from options prices for a
variety of underlying assets: stock indices, bonds, short rates and foreign exchange. Most of these rose
sharply following the Russian default and increased further after the LTCM re-capitalisation, reaching
levels 1½ to 2½ times their first-half averages. To the extent that the financial sector has an aggregate
short position in options, which it sells in various forms to non-financial entities in return for implicit
46
or explicit fee income, the consequent increase in options prices would have led to losses, at least on a
marked-to-market basis.
Actual volatility, at least within the brief sub-periods shown (Tables A9 and A10), often rose even
more. For bond yields, exchange rates and stock market indices, volatility was usually highest for
emerging markets (including Hong Kong) after the Russian default, and it was highest for G10
financial markets after the LTCM recapitalisation.
In addition, Table A11 shows realised volatility for the same list of yield spreads treated in Tables A1
and A2, which in many cases tripled or more from levels recorded in the first half of the year. For
more than half of these spreads, volatility peaked in the post-Russia sub-period, but volatility
increased subsequently for bond yield spreads in Hong Kong, Japan, the United Kingdom, and
Switzerland.
Financial trading firms that use value-at-risk (VaR) measures for risk management typically use a
backward-looking measure of historical volatility over a much longer sample period. In fact, the Basel
Committee guidelines for the “internal models” approach to capital charges for market risk stipulate a
minimum computation period of at least a year. Table A12 demonstrates that, when implied volatility
measures were reaching their peak levels last year, such a historical measure of volatility over
250 trading days fell far short of the market expectations of future volatility that were implicit in
options prices for most of these instruments. (In addition, Figure A5 depicts the substantial extent to
which 250-day historical volatility lagged implied volatility for the UK stock index.) For this reason,
conventional VaR measures, in addition to taking no account of illiquidity or counterparty credit risk,
probably understated the amount of market risk in financial firms’ trading portfolios.
Flow measures of liquidity
Table A13 shows average daily secondary market trading volume in a number of instruments for the
five sub-periods. For most of these instruments, volume stayed close to normal levels through the
Russia and LTCM news events, but then fell to its lowest level (the shaded cells) late in the year.
Interestingly, Hong Kong trading volume in futures and bonds was actually higher after the Russian
default than earlier in the summer.
Table A14 provides much more comprehensive volume information on exchange-traded derivatives,
but only at a quarterly frequency. Volume was strong in the second half of 1998, although there was a
decrease from the third to the fourth quarter. In contrast, trading in emerging market debt (which is
dominated by Latin American issues) fell sharply in the third quarter and precipitously in the fourth,
with almost no recovery in the first quarter of 1999.
The figures in Table A15 suggest that primary market volumes suffered more distinctly. Global net
private issuance of bonds fell sharply in the fourth quarter, and money market issuance fell short of the
quantity maturing. Monthly data for UK corporate bonds suggests that August and September activity
was particularly weak. Syndicated loan origination (Table A16) declined less.
Correlations
Table A17 (which stretches across three pages) compares correlations between five-day changes in
yield spreads in the first and second halves of 1998, with the coefficients expressed in tenths to save
space. Although some pairs of spreads are highly correlated, coefficients that are near zero or even
negative are commonplace. On balance, correlations were somewhat higher in the second half, with
the average coefficient (Table A18) increasing from 11% to 21%. Even in the most extreme
sub-period – the five weeks after the Russian default – the average coefficient is only 37%. Also note
that the average absolute change in correlations – compared to the previous six months – was only
slightly higher for the second half of 1998 than for the first half. In other words, individual correlation
coefficients did not seem to be exceptionally unstable in the second half of 1998.
47
The story is a little different for closely related yield spreads that were already significantly correlated
in the first half of 1998. In particular (Tables A19 and A20), UK five-year bond spreads moved nearly
in lockstep in the second half of the year, with average correlation reaching as high as 80%. (However,
it is a fairly general statistical regularity that significantly correlated variables become more highly
correlated in volatile periods – see Boyer, Gibson and Loretan (1997) for a discussion in the context of
normally distributed variables.)
Correlations in implied volatility measures (Tables A21 and A22) essentially reflect comovements in
options prices, net of the effect of changes in the value of the assets on which the options are based.
These correlations increased in the second half of the year, particularly in the sub-period immediately
following the Russian default. To the extent that financial firms tend, on net, to hold short positions in
options, increased correlation may be problematic.
Hedging risk
Another potential pitfall of changes in correlations is that hedging strategies will be undermined.
Table A23 examines the effectiveness of a short futures position as a hedge for a long position in a
government bond. In the upper panel, which shows the percentage reduction in risk exposure as a
result of the hedge, a figure of 100 would denote a perfect hedge, with zero residual volatility in the
hedged position. This type of hedge was least effective (comparing over the five sub-periods) for the
Japanese bond and the Brazilian Brady bond following LTCM, but futures hedging for the US, UK
and German government bonds during this period was about as effective as at any other time during
1998. However, residual volatility was still high, because volatility in the prices of the underlying
bonds was higher. Thus, despite a reasonably effective hedge, hedgers would not have been insulated
from the increase in volatility.
The last four lines in each panel show so-called cross-hedges, in which short German bund futures
positions are offset against long positions in bonds issued by other national governments within the
euro area. Interestingly, in each case, this hedge was unusually effective in the post-LTCM period. For
the Dutch and French bonds, the residual volatility of the hedged position after 22 September was not
only the lowest of the five sub-periods, but also less than for the hedge of the German bond.
One of the more striking features of these results is how ineffective most of these hedges were much
of the time. The last panel shows how effective futures hedges were when held over the entire subperiod. Numbers closer to 100 % represent more effective hedges, with numbers greater than 100 %
reflecting excess movement in the futures market. In addition to suggesting that futures hedging is
more effective over longer periods, the figures imply that the futures and cash markets diverged most
for most of these bonds after the LTCM recapitalisation announcement.
Table A24 shows analogous figures for hedges using interest rate swaps against 10-year government
bond positions for Japan, the United States, the United Kingdom and Germany. For Japan and
Germany, this was a uniformly ineffective hedge for a one-day holding period, with residual volatility
exceeding that of the unhedged position in every sub-period. Over longer periods (the lower panel),
however, swap hedging appears to be the most effective in Germany of the four countries examined.
The US and UK hedges were relatively effective in the post-LTCM period, but residual volatility was
still much higher than in the first half of the year.
Longer-term perspective
A remaining question is how the turbulence in the second half of 1998 compares to other periods.
Figure A6 shows several implied volatility measures since the early 1990s. All of these series reached
comparable or higher levels in recent years. For example, French and US government bond yield
volatility was higher for much of 1994.
Furthermore, most of the yield spreads in Table A25 and the short rate spreads in Table A26 reached
higher levels in the 1990s than in 1998, in some cases by a substantial margin. For example, Mexican
Brady bond spreads were about 400 basis points higher in early 1995, in the wake of the peso
48
devaluation, as were US speculative-grade bonds at the beginning of 1991, not long after the scandal
involving Drexel Burnham Lambert. Hong Kong interbank spreads peaked in late 1997 during the
so-called Asian financial crisis.
The 1998 stock market declines in Table A27 are 1990s records for most of the industrialised country
indices, but at least in some cases, such as the United Kingdom’s FT-SE 100 index, fall short of the
declines generated by the crash of October 1987. The 1998 peak stock price volatility figures shown in
Table A28 are also frequently the most extreme values for the 1990s for North American and
European markets.
1998 peak volatility levels for bond yields (Table A29) and long-term and short-term spreads
(Tables A30 and A31), however, tend to fall well short of the 1990s extremes, with Japan’s
three-month interbank rate spread the only exception. In many cases, the highest volatility occurred in
1994.
Surprisingly, 1998 (specifically October) contains the 1990s extreme for three of the five exchange
rates shown in Table A32, although this is largely attributable to the sharp rise in the exchange value
of the yen on 7 and 8 October. There was also a temporary blip in the Canadian dollar at the same
time.
49
Table A1
Average yield spreads during 1998
(basis points)
Level
Change from previous period average
1 Jan.
to 3 July
Japan 5-year AA corporate bond
70
Japan 5-year BBB corporate bond
189
Japan 5-year bank bond
Japan 10-year yen Swap
Hong Kong 10-year government bond
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
0
+
6
+
4
+
5
–
1
+
11
+
2
+
14
39
+
12
+
19
–
3
–
21
64
+
3
+
3
–
23
–
1
+ 115
–
15
–
79
– 137
346
Hong Kong 3-year agency bond
43
+
22
+
10
+
10
–
10
Hong Kong 10-year HK$ Swap
109
–
40
+
6
–
13
–
4
Latin America Brady bond
345
+
79
+ 377
–
41
–
97
Mexico corporate eurobond
355
+
93
+ 502
+
94
– 240
US 10-year AA corporate bond
77
+
5
+
23
+
22
–
9
US 10-year BBB corporate bond
123
+
11
+
42
+
36
+
2
US speculative-grade bond
332
+
42
+ 146
+ 104
–
24
US 2-year US$ swap
37
+
4
+
11
+
9
–
5
US 10-year US$ swap
51
+
6
+
20
+
11
–
8
Canada 10-year $ swap
21
+
6
+
12
+
5
–
11
UK 5-year Aa corporate bond
54
+
3
+
26
+
46
–
16
UK 5-year Baa corporate bond
88
+
2
+
24
+
53
–
17
UK four 5-year bank bonds
59
+
4
+
28
+
46
–
16
UK 10-year sterling swap
33
+
4
+
30
+
33
–
11
Netherlands two industrial bonds
33
+
3
+
5
+
6
+
11
Netherlands four 10-year bank bonds
28
+
2
+
8
+
7
–
2
Germany industrial bond (from May)
71
+
1
+
6
–
3
+
8
Germany 9-10 year mortgage bond
27
+
0
+
21
+
1
–
3
Germany 9-10 year bank bond
25
+
2
+
20
+
1
–
6
Germany 10-year DM swap
25
+
9
+
19
+
0
–
12
France A3 corporate bond
41
–
2
+
10
+
13
+
2
France average swap rate
20
+
0
+
12
–
2
–
3
Swiss corporate bond
41
–
14
+
6
+
18
–
6
Swiss 5-7 year SFr swap
52
+
1
+
1
+
6
–
5
Notes: Shading denotes highest average spread and boldface denotes the largest increase. Spreads generally are measured relative to a
government bond of the same maturity and currency (US dollars for the Latin American and Mexican bonds). The Hong Kong
government spread is measured relative to a US Treasury bond.
50
Table A2
High/low yield spreads during 1998
(basis points)
1998
low
Date of
low
1998
high
Date of
high
Increase
from low
Japan 5-year AA corporate bond
58
5 Jan.
92
20 Nov.
34
Japan 5-year BBB corporate bond
177
8 Jan.
227
22 Dec.
50
Japan 5-year bank bond
14
29 Jan.
77
10 Sep.
63
Japan 10-year yen Swap
58
5 Jan.
84
28 Aug.
26
222
23 March
506
26 June
284
Hong Kong 3-year agency bond
1
6 Jan.
105
12 Oct.
104
Hong Kong 10-year HK$ Swap
134
5 Jan.
199
9 Jan.
65
Latin America Brady bond
292
23 March
985
10 Sep.
693
Mexico corporate eurobond
313
26 Feb.
1253
11 Sep.
940
US 10-year AA corporate bond
70
23 Jan.
138
5 Oct.
68
US 10-year BBB corporate bond
114
23 Jan.
225
4 Nov.
111
US speculative-grade bond
307
30 March
687
19 Oct.
380
US 2-year US$ swap
30
24 Feb.
73
14 Oct.
43
US 10-year US$ swap
44
11 Feb.
97
14 Oct.
53
Canada 10-year $ swap
17
5 Feb.
48
14 Oct.
31
UK 5-year Aa corporate bond
48
13 March
147
5 Oct.
99
UK 5-year Baa corporate bond
82
17 June
191
13 Oct.
109
UK four 5-year bank bonds
53
2 Jan.
154
5 Oct.
101
UK 10-year sterling swap
26
5 Jan.
116
5 Oct.
90
Netherlands two industrial bonds
25
19 March
68
3 Dec.
43
Netherlands four 10-year bank bonds
24
21 Jan.
49
14 Oct.
25
Germany industrial bond (from May)
57
12 Aug.
114
11 Dec.
57
Germany 9-10 year mortgage bond
20
29 April
57
21 Sep.
37
Germany 9-10 year bank bond
21
6 May
59
21 Sep.
38
Germany 10-year DM swap
18
1 May
69
25 Aug.
51
France A3 corporate bond
35
5 March
66
30 Nov.
31
France average swap rate
19
18 May
36
4 Sep.
17
Swiss corporate bond
22
21 July
61
1 Oct.
39
Swiss 5-7 year SFr swap
39
1 June
89
31 Dec.
50
Hong Kong 10-year government bond
Notes: Spreads generally are measured relative to a government bond of the same maturity and currency (US dollars for the Latin
American and Mexican bonds). The Hong Kong government spread is measured relative to a US Treasury bond.
51
Table A3
Average short-term interest rate spreads during 1998
(basis points)
Level
Change from previous period average
1 Jan.
to 3 July
Japan 3-month interbank euro-rate
–
2
6 July
to 14 Aug.
–
4
17 Aug.
to 22 Sep.
+
4
23 Sep.
to 15 Oct.
–
3
16 Oct.
to 31 Dec.
–
2
Hong Kong 3-month domestic interbank
262
+ 100
+ 164
– 310
– 157
Hong Kong 6-month domestic interbank
333
+ 100
+ 147
– 291
– 157
Hong Kong 12-month domestic interbank
390
+ 75
+ 122
– 228
– 142
Mexico 1-month domestic interbank
165
+
8
+ 146
+ 23
– 45
US 3-month interbank euro-rate
53
+
8
+
9
+ 37
– 25
US 12-month interbank euro-rate
59
+
2
+
6
+
4
–
US 1-month prime commercial paper
7
+
1
–
1
+
5
+ 13
US 1-month second-tier commercial
paper
27
0
+
1
+ 17
+ 38
Canada 3-month interbank euro-rate
20
– 13
+
6
+ 31
– 23
UK 3-month interbank (euro-rate) versus
repo
22
+
1
+
2
+
2
+ 13
+
1
+
2
+
6
0
–
2
+
1
0
–
2
France 3-month domestic interbank
–
6
–
1
France 12-month domestic interbank
–
1
–
1
France 1-month commercial paper
3
0
+
1
8
Notes: Shading denotes highest average spread and boldface denotes the largest increase. Spreads are measured relative to government
treasury bills unless it is stated otherwise. Hong Kong interbank rates are midway between bid and ask. Other interbank rates are bid
quotes.
52
Table A4
Peak short-term interest rate spreads during 1998
(basis points)
1998
low
Date of
low
1998
high
Date of
high
– 22
6 Oct.
16
30 Oct.
38
Hong Kong 3-month domestic interbank
19
23 Apr.
1294
28 Aug.
1275
Hong Kong 6-month domestic interbank
100
23 Apr.
1198
28 Aug.
1098
Hong Kong 12-month domestic interbank
169
23 Apr.
854
28 Aug.
685
Mexico 1-month domestic interbank
86
27 Apr.
628
14 Sep.
542
US 3-month interbank euro-rate
33
26 Feb.
144
16 Oct.
111
US 12-month interbank euro-rate
40
24 Feb.
86
16 Oct.
46
2
9 Sep.
54
16 Dec.
56
14
26 Feb.
135
2 Dec.
121
– 58
27 Aug.
67
7 Oct.
125
15
13 Jan.
58
23 Dec.
43
France 3-month domestic interbank
– 11
27 Apr.
15
21 Dec.
26
France 12-month domestic interbank
–
1
2 Jan.
5
9 Jan.
6
France 1-month commercial paper
– 19
30 Nov.
22
30 Dec.
41
Japan 3-month interbank euro-rate
US 1-month prime commercial paper
–
US 1-month second-tier commercial paper
Canada 3-month interbank euro-rate
UK 3-month interbank (euro-rate) versus repo
Increase
from low
Note: Spreads are measured relative to government treasury bills unless it is stated otherwise. Hong Kong interbank rates are midway
between bid and ask. Other interbank rates are bid quotes.
53
Table A5
Bid-Ask Spreads
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Hong Kong 3-year agency bond
100
82
82
82
82
Mexico Peso/US Dollar exchange rate
100
82
317
222
105
Canada 3-month treasury bill
100
99
103
177
116
Canada 1-year treasury bill
100
93
86
184
117
UK Aa corporate bond
100
114
104
154
174
UK A corporate bond
100
115
137
200
217
UK Baa corporate bond
100
110
126
245
246
France 3-month interbank rate
100
100
100
100
100
France 3-month repo rate
100
94
94
99
93
France 1-year swap rate
100
100
100
100
100
France 10-year swap rate
100
58
83
85
85
Swiss 5-year swap rate
100
101
101
101
101
Note: Shading denotes highest average spread and boldface denotes the largest increase.
Table A6
Average liquidity spreads for 10-year government bonds during 1998
(basis points)
Level
Change from previous period average
1 Jan.
to 3 July
Japan
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
– 0
– 0
+ 1
+ 0
+ 1
US
9
– 0
– 2
– 1
– 2
UK
4
+ 0
+ 5
+ 5
– 2
Netherlands (versus German yield curve)
3
+ 6
+ 6
+ 2
– 7
Notes: Shading denotes highest average spread and boldface denotes the largest increase. Spreads are measured relative to a benchmark
or “on-the-run” bond yield unless it is stated otherwise.
54
Table A7
Lowest stock market index levels during 1998
(1 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
value
date
value
date
value
date
value
date
value
date
Japan
88
12 Jan.
92
14 Aug.
82
21 Sep.
77
15 Oct.
79
16 Oct.
Japan bank
85
17 June
78
12Aug.
70
28 Aug.
62
1 Oct.
68
16 Oct.
Hong Kong
87
15 June
78
13 Aug.
83
1 Sep.
88
23 Sep.
112
19 Oct.
Korea
89
16 June
96
13 July
92
18 Aug.
93
23 Sep.
114
27 Oct.
Russia
99
2 July
69
13 Aug.
33
21 Sep.
26
5 Oct.
37
28 Oct.
Brazil
92
15 June
85
12 Aug.
48
10 Sep.
60
1 Oct.
66
29 Oct.
Mexico
92
15 June
81
12 Aug.
65
10 Sep.
76
7 Oct.
84
3 Dec.
US
81
9 Jan.
93
14 Aug.
83
31 Aug.
84
8 Oct.
92
16 Oct.
US financial
79
9 Jan.
88
14 Aug.
73
10 Sep.
69
8 Oct.
81
27 Oct.
US small-cap
89
12 Jan.
87
5 Aug.
73
31 Aug.
67
8 Oct.
75
16 Oct.
Canada
85
12 Jan.
85
14 Aug.
75
31 Aug.
72
5 Oct.
79
19 Oct.
UK
86
12 Jan.
91
13 Aug.
84
21 Sep.
79
5 Oct.
86
19 Oct.
UK financial
89
12 Jan.
89
13 Aug.
80
21 Sep.
71
5 Oct.
84
19 Oct.
Germany
69
12 Jan.
89
11 Aug.
75
21 Sep.
66
8 Oct.
75
23 Oct.
France
67
12 Jan.
90
11 Aug.
78
21 Sep.
69
8 Oct.
80
16 Oct.
France financial
69
12 Jan.
96
11 Aug.
72
21 Sep.
58
5 Oct.
73
23 Oct.
Switzerland
75
12 Jan.
93
11 Aug.
75
21 Sep.
64
5 Oct.
75
19 Oct.
Switzerland bank
65
12 Jan.
94
11 Aug.
61
21 Sep.
48
1 Oct.
58
19 Oct.
Note: Shading denotes lowest level and boldface denotes the largest drop from the previous-period low.
55
Table A8
Implied volatility measures during 1998
Index: [1 Jan. to 3 July] = 100
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec
Mexico stock index
100
141
261
235
138
US 30-year government bond
100
85
134
180
199
US 3-month eurodollar
100
108
168
188
125
US stock market index (S&P 500)
100
90
104
129
128
UK stock market index (FTSE 100)
100
101
156
178
137
UK long government bond
100
86
107
165
139
UK 3-month interest rate
100
101
152
193
231
France 10-year government bond
100
75
130
146
132
France 3-month interest rate
100
76
130
171
159
Switzerland stock market index
100
109
174
211
182
Switzerland SFr/US$ exchange rate
100
93
116
158
176
Note: Shading denotes peak implied volatility and bold-face denotes the largest increase.
56
Table A9
Government bond yield volatility during 1998
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Japan 10-year
100
84
188
59
140
Hong Kong 3-year
100
47
117
98
37
Hong Kong 5-year
100
58
144
135
53
Hong Kong 10-year
100
55
145
143
47
US 2-year
100
50
161
185
181
US 5-year
100
53
149
210
143
US 10-year
100
51
132
224
122
US 30-year
100
52
154
265
151
US 10-year inflation-indexed
100
69
94
193
106
UK 10-year
100
99
149
283
122
Netherlands 10-year
100
57
177
264
104
Germany 10-year
100
63
184
283
103
Exchange rate volatility during 1998
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Hong Kong dollar/US dollar (12-month
forward)
100
100
154
71
34
Yen/US dollar
100
72
157
219
112
Yen/Swiss franc
100
105
166
289
118
US dollar/Canadian dollar
100
95
214
262
142
US dollar/German mark
100
91
131
136
102
US dollar/Swiss franc
100
106
163
234
158
Notes: Volatility is measured as the square root of the mean daily squared change in the yield (essentially the standard deviation assuming
a zero mean). Shading denotes the highest volatility and bold-face denotes the largest increase.
57
Table A10
Stock market volatility during 1998
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Japan
100
76
133
206
110
Japan bank
100
78
105
173
93
Hong Kong
100
91
113
113
75
Korea
100
87
70
108
90
Russia
100
156
172
140
79
Brazil
100
103
302
230
164
Mexico
100
99
258
215
109
US
100
138
274
235
122
US financial
100
139
270
289
143
US small-cap
100
163
274
278
127
Canada
100
157
247
257
117
UK
100
129
219
253
145
UK financial
100
131
189
268
138
Germany
100
104
217
250
144
France
100
112
205
254
124
France financial
100
142
237
311
153
Switzerland
100
127
248
313
133
Switzerland bank
100
133
300
367
159
Notes: Volatility is measured as the square root of the mean daily squared change in the natural log of the price (essentially the standard
deviation assuming a zero mean). Shading denotes the highest volatility and bold-face denotes the largest increase.
58
Table A11
Yield spread volatility during 1998
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Japan 5-year AA corporate bond
100
85
243
235
273
Japan 5-year BBB corporate bond
100
86
115
160
125
Japan 5-year bank bond
100
70
82
75
100
Japan 10-year yen Swap
100
91
416
408
371
Hong Kong 10-year government bond
100
51
132
167
67
Hong Kong 3-year agency bond
100
59
62
120
22
Hong Kong 10-year HK$ Swap
100
77
259
58
59
Latin America Brady bond
100
212
807
415
243
Mexico corporate eurobond
100
283
832
365
285
US 10-year AA corporate bond
100
73
305
309
173
US 10-year BBB corporate bond
100
84
464
220
165
US speculative-grade bond
100
91
278
228
158
US 2-year US$ swap
100
117
355
354
308
US 10-year US$ swap
100
106
346
291
249
Canada 10-year $ swap
100
91
186
106
178
UK 5-year Aa corporate bond
100
84
193
409
219
UK 5-year Baa corporate bond
100
69
157
387
158
UK four 5-year bank bonds
100
90
172
278
128
UK 10-year sterling swap
100
139
277
267
199
Netherlands two industrial bonds
100
114
168
150
147
Netherlands four 10-year bank bonds
100
50
118
109
110
Germany industrial bond (from May)
100
417
289
292
238
Germany 9-10 year mortgage bond
100
65
246
215
109
Germany 9-10 year bank bond
100
95
267
249
132
Germany 10-year DM swap
100
97
387
293
159
Swiss corporate bond
100
115
172
297
129
Swiss 5-7 year SFr swap
100
111
197
413
249
Notes: Volatility is measured as the square root of the mean daily squared change in the spread (essentially the standard deviation
assuming a zero mean). Shading denotes the highest volatility and bold-face denotes the largest increase.
59
Table A12
Peaks in implied volatility measures during 1998
(Percent Annual)
Peak in
implied
volatility
Date of
peak
250-day
historical
volatility
Ratio:
implied/
historical
Mexico stock index
84
15 Sep.
38
221%
US stock market index (S&P 500)
43
27 Oct.
20
215%
US 3-month eurodollar
33
19 Oct.
7
471%
US 30-year government bond
14
9 Oct.
13
108%
UK stock market index (FTSE 100)
48
5 Oct.
20
240%
UK long government bond
13
12 Oct.
15
87%
UK 3-month interest rate
19
14 Dec.
7
271%
France 10-year government bond
13
26 Aug.
4
325%
France 3-month interest rate
18
2 Dec.
12
150%
Switzerland stock market index
56
5 Nov.
27
207%
Switzerland SFr/US$ exchange rate
20
30 Oct.
9
222%
Note: Historical volatility is the standard deviation of one-day changes in the natural log of the underlying, measured over the previous 250
weekdays and scaled to annual percent units.
60
Table A13
Average daily trading volume
(1 January 1998 to 3 July 1998 = 100)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Hong Kong government securities
100
61
102
97
84
Hong Kong private sector debt instruments
100
70
236
89
101
Hong Kong stock index futures
100
102
122
102
79
Hong Kong 3-month HIBOR futures
100
108
144
90
61
Mexico foreign exchange
100
114
79
69
61
Germany bonds
100
92
111
102
88
France 10-year bond futures
100
81
136
108
55
France 3-month bond futures
100
50
79
52
41
France 5-year PIBOR futures
100
39
70
36
24
Note: Shading denotes the period of lowest volume and bold-face denotes the largest decrease.
Table A14
Global trading volume
(Quarterly, 1998:1 = 100)
Futures
Options
1997:1
85
103
1997:2
95
109
1997:3
93
100
108
1997:4
95
113
127
1998:1
100
100
100
1998:2
95
98
113
1998:3
108
144
84
1998:4
94
128
42
1999:1
Emerging market debt
43
61
Table A15
Private sector securities issuance
(First Quarter of 1998 = 100)
Money Market
(net global)
Bonds
(net global)
UK corporate bonds
(gross)
110
1997:1Q
50
85
75
26
64
1997:2Q
42
88
62
71
100
1997:3Q
59
104
47
65
122
1997:4Q
– 25
75
22
21
87
1998:1Q
100
100
78
135
35
1998:2Q
10
132
38
52
124
1998:3Q
53
83
43
1
25
1998:4Q
– 46
47
62
63
1999:1Q
282
130
Note: UK corporate bond issuance is stated monthly; net global issuance series are quarterly figures compiled by the Bank for
International Settlements.
62
Table A16
Total international syndicated loan origination
(billions of US dollars)
Year
Month
Announced loans
1997
1
44
1997
2
60
1997
3
99
1997
4
96
1997
5
133
1997
6
111
1997
7
99
1997
8
67
1997
9
97
1997
10
111
1997
11
81
1997
12
138
1998
1
37
1998
2
91
1998
3
102
1998
4
92
1998
5
77
1998
6
100
1998
7
80
1998
8
84
1998
9
70
1998
10
74
1998
11
65
1998
12
86
1999
1
30
1999
2
44
1999
3
82
63
Table A17
Non-european yield spread correlations
1 January 1998 to 3 July 1998 (tenths)
Japan 5-year AA corporate bond
+5
+5
Japan 5-year BBB corporate bond
+2
+1
+1
+1
Japan 5-year bank bond
–1
–2
Japan 10-year yen Swap
+1
Hong Kong 10-year government bond
–1
Hong Kong 3-year agency bond
–1
+1
+2
–1
+3
–1
-3
+1
–3
–1
+1
+1
+2
+1
+3
+2
+2
+2
+2
+3
+1
+1
+1
+1
+7
+7
+1
+2
+5
–1
+1
–2
+2
+3
+2
+8
Hong Kong 10-year HK$ Swap
Latin America Brady bond
Mexico corporate eurobond
–1
–1
+1
–1
+3
+3
+3
–2
–2
–2
–2
+2
+4
+3
+1
+1
+1
+4
+2
+4
+3
+3
+3
+7
+4
+6
+4
+9
+5
+2
+5
+1
+6
+2
+5
+2
+5
+6
+3
+5
+3
US 10-year AA corporate bond
US 10-year BBB corporate bond
US speculative-grade bond
US 2-year US$ swap
US 10-year US$ swap
+5
Canada 10-year $ swap
6 July 1998 to 31 December 1998 (tenths)
Japan 5-year AA corporate bond
+6
Japan 5-year BBB corporate bond
Japan 5-year bank bond
Japan 10-year yen Swap
+4
+6
+2
+1
+1
+4
–1
+1
+3
+3
+1
+3
Hong Kong 10-year government bond
+1
Hong Kong 3-year agency bond
Hong Kong 10-year HK$ Swap
Latin America Brady bond
Mexico corporate eurobond
US 10-year AA corporate bond
US 10-year BBB corporate bond
US speculative-grade bond
US 2-year US$ swap
US 10-year US$ swap
+1
+2
+2
+3
+1
+3
+3
+3
+3
+2
+4
+4
+2
+2
+2
+2
+1
–1
–1
–1
+2
+2
+1
–1
+1
+2
+2
+2
+2
+3
+2
–1
–1
–1
+8
+2
+2
+5
+4
+4
+9
+2
+1
–1
+2
+2
+1
+2
–1
+2
+1
+1
+2
–1
–2
+4
+6
+3
+7
+4
+5
+5
+6
+1
+7
+2
+1
+2
+4
+5
+5
+7
+7
+1
+6
Canada 10-year $ swap
64
Table A17 (continued)
Correlations of non-european and european yield spreads
1 January 1998 to 3 July 1998 (tenths)
UK
Aa
Japan 5-year AA corporate bond
UK
Baa
UK
bnk
+2
+1
UK
swa
Nth
ind
Nth
bnk
+2
+1
Ger
mrt
Ger
bnk
Ger
swa
Swi
crp
–1
–1
+1
Japan 5-year BBB corp. bond
+2
+3
+1
+1
+1
Japan 5-year bank bond
+1
+2
+2
+2
+1
+3
Japan 10-year yen swap
+1
+3
+1
–2
+3
+1
+1
HK 10-year government bond
+4
+3
+3
+3
+2
–1
+2
+2
HK 3-year agency bond
–1
+1
+1
+2
–1
-2
HK 10-year HK$ swap
+1
+2
-2
+1
+1
Latin America Brady bond
+3
+3
+2
+3
Mexico corporate eurobond
+1
+2
+2
+2
US 10-year AA corporate bond
+2
+2
+3
Swi
swa
+1
+1
–1
–1
+2
–2
–1
–1
+2
+1
+2
+3
+1
-1
–1
–1
+3
+3
+2
–2
–1
+4
+3
+2
–2
+1
+4
+4
–1
+1
+1
–1
+1
+1
–2
–1
–1
+1
+1
+1
+4
+3
+5
+3
+1
+1
+1
+3
+3
+1
+2
+2
+1
+1
+1
Ger
mrt
Ger
bnk
Ger
swa
Swi
crp
Swi
swa
+2
+3
+1
+1
–1
+1
+2
+2
+1
+2
–2
+2
+4
+3
+3
–2
+1
+2
+1
–1
–1
–1
+3
+3
+3
–2
–1
+2
+1
US 10-year BBB corporate bond
–1
–1
+1
US speculative-grade bond
+1
–1
+3
+1
+1
US 2-year US$ swap
+1
+1
+3
–1
+1
US 10-year US$ swap
–2
+2
+1
Canada 10-year C$ swap
–1
+1
+2
-1
–1
–1
–1
+2
6 July 1998 to 31 December 1998 (tenths)
UK
Aa
UK
Baa
UK
bnk
UK
swa
Nth
ind
Nth
bnk
Japan 5-year AA corporate bond
+1
+2
Japan 5-year BBB corp. bond
+1
+1
Japan 5-year bank bond
+1
+1
+2
Japan 10-year yen swap
–2
–3
–3
HK 10-year government bond
–1
–2
–1
+2
HK 3-year agency bond
+2
+2
+2
+3
HK 10-year HK$ swap
–1
–1
–1
Latin America Brady bond
+4
+3
+3
+5
+3
+4
+5
+5
+5
+1
Mexico corporate eurobond
+4
+4
+4
+5
+2
+5
+4
+5
+4
+2
US 10-year AA corporate bond
+4
+4
+5
+2
+2
+1
+1
–1
+3
US 10-year BBB corporate bond
+4
+4
+4
+1
+1
+2
+1
+1
–1
+3
US speculative-grade bond
+6
+6
+6
+4
+3
+4
+2
+3
+2
+5
+1
US 2-year US$ swap
+5
+5
+3
+2
+3
+2
+3
+3
+2
+2
+2
US 10-year US$ swap
+6
+6
+5
+6
+2
+3
+6
+6
+6
+3
+1
Canada 10-year C$ swap
+5
+5
+4
+4
+2
+2
+3
+3
+3
+2
+2
+3
+2
+2
–3
+1
65
–1
Table A17 (continued)
European yield spread correlations
1 January 1998 to 3 July 1998 (tenths)
UK 5-year AA corporate bond
+8
+1
+3
–1
+2
+2
–1
+2
+1
UK 10-year sterling swap
–1
Netherlands two industrial bonds
+2
UK 5-year Baa corporate bond
+7
+7
UK four 5-year bank bonds
Netherlands four 10-year bank bonds
+1
+1
–2
–2
+1
–1
–1
–2
+2
+2
–1
–1
–1
+1
+1
+4
+2
+1
–1
Germany 9-10 year mortgage bond
–1
+8
Germany 9-10 year bank bond
–1
+1
+1
+1
Germany 10-year DM swap
+1
Switzerland corporate bond
+1
+8
Switzerland 5-7 year SFr swap
6 July 1998 to 31 December 1998 (tenths)
UK 5-year AA corporate bond
+10
UK 5-year Baa corporate bond
UK four 5-year bank bonds
UK 10-year sterling swap
Netherlands two industrial bonds
+9
+7
+2
+5
+4
+4
+3
+5
+1
+9
+5
+2
+4
+3
+3
+2
+5
+1
+7
+2
+5
+3
+4
+3
+5
+1
+1
+5
+6
+6
+6
+3
+2
Netherlands four 10-year bank bonds
+4
Germany 9-10 year mortgage bond
Germany 9-10 year bank bond
+4
+3
+10
+9
+2
+1
+2
+1
+1
+8
Germany 10-year DM swap
+1
Switzerland corporate bond
+1
+3
Switzerland 5-7 year SFr swap
Notes: Statistics are based on 5-day changes in spreads, to allow for time-of-day differences. Correlation coefficients are rounded to
nearest 10% and expressed in tenths, so that “+3” denotes 30%, for example. Shading ranges from white for zero or negative correlation
to black for 100% (rounded) correlation. Each data label references both a row of the matrix and the column above its right-most extent.
66
Table A18
Average yield spread correlations (percent)
Period
Average correlation
(for period)
Average correlation
(previous 6 months)
Average | absolute |
change
1 Jan. 1998 –
3 July 1998
11
14
17
6 July 1998 –
31 Dec. 1998
21
11
21
6 July 1998 –
14 Aug.1998
17
11
27
17 Aug.1998 –
22 Sep. 1998
37
13
31
23 Sep. 1998 –
15 Oct. 1998
17
27
37
16 Oct. 1998 –
31 Dec. 1998
12
23
26
Notes: Statistics are based on correlations of 5-day changes in spreads, as reported in Table A17.
Table A19
UK Bond yield spread correlations
1 January 1998 to 3 July 1998 (tenths)
UK 5-year Aa corporate bond
+6
UK 5-year A corporate bond
+8
+5
+7
+3
+6
+6
+7
+3
+3
+3
+5
+6
+2
+5
UK 5-year Baa corporate bond
UK 5-year Barclays bank bond
+2
UK 5-year Lloyds bank bond
+2
+3
UK 5-year NatWest bank bond
+7
+2
UK 5-year Royal Scotland bank bond
6 July 1998 to 31 December 1998 (tenths)
UK 5-year Aa corporate bond
+9
UK 5-year A corporate bond
UK 5-year Baa corporate bond
UK 5-year Barclays bank bond
UK 5-year Lloyds bank bond
UK 5-year NatWest bank bond
+10
+7
+8
+8
+8
+9
+9
+6
+7
+7
+6
+8
+8
+8
+4
+5
+6
+7
+8
+7
UK 5-year Royal Scotland bank bond
67
Table A20
Average UK Bond yield spread correlations (percent)
Period
Average correlation
(for period)
Average correlation
(previous 6 months)
Average | absolute |
change
1 Jan. 1998 –
3 July 1998
44
56
23
6 July 1998 –
31 Dec. 1998
73
44
29
6 July 1998 –
14 Aug.1998
45
44
10
17 Aug.1998 –
22 Sep. 1998
82
45
37
23 Sep. 1998 –
15 Oct. 1998
79
68
16
16 Oct. 1998 –
31 Dec. 1998
63
75
12
Notes: Statistics are based on correlations of 5-day changes in spreads, as reported in Table A19.
68
Table A21
Correlations of implied volatility measures
1 January 1998 to 3 July 1998 (tenths)
Mexico stock index
+1
US stock market index (S&P 500)
+4
US 30-year government bond
+3
+4
+2
+2
+1
+1
+4
+2
+1
–1
+1
–1
+3
+4
–1
+1
+2
+1
+1
+1
+5
+2
+1
+1
+2
+4
+3
+1
+1
+2
+5
+1
US 3-month eurodollar
UK stock market index (FTSE 100)
+2
UK long government bond
UK 3-month interest rate
+1
France 10-year government bond
+1
–1
+3
+1
+1
+2
France 3-month interest rate
–2
–3
–1
–2
–1
Switzerland stock market index
+4
Switzerland SFr/US$ exchange rate
6 July 1998 to 31 December 1998 (tenths)
Mexico stock index
–1
US stock market index (S&P 500)
+2
US 30-year government bond
US 3-month eurodollar
+1
+3
–1
+1
+4
+3
+8
+3
+1
+2
+6
+2
+2
+3
+2
+1
+4
+1
+2
+3
+2
+4
+4
–1
+3
+1
+1
+3
+3
+1
+3
+2
+2
+1
+3
+2
+1
+4
–1
+4
+1
+2
France 10-year government bond
+2
–1
France 3-month interest rate
+3
UK stock market index (FTSE 100)
UK long government bond
UK 3-month interest rate
Switzerland stock market index
+1
Switzerland SFr/US$ exchange rate
Notes: Statistics are based on 5-day changes in implied volatility, to allow for time-of-day differences. Correlation coefficients are
rounded to nearest 10% and expressed in tenths, so that “+3” denotes 30%, for example. Shading ranges from white for zero or negative
correlation to black for 100% (rounded) correlation. Each data label references both the row of the matrix it occupies and the column
above its right-most extent.
69
Table A21 (continued)
Correlations of implied volatility measures
17 August 1998 to 22 September 1998 (tenths)
Mexico stock index
+7
+8
+4
+6
+6
+7
+1
+5
+6
+4
+9
+6
+9
+8
+8
+4
+3
+6
+5
+4
+7
+5
+7
+3
+2
+5
+3
+7
+6
+8
-2
+4
-1
+6
+9
+9
+1
+4
+5
+6
+7
+2
+5
+6
+6
UK 3-month interest rate
+6
+4
+7
France 10-year government bond
-1
+4
-4
+1
+3
US stock market index (S&P 500)
US 30-year government bond
US 3-month eurodollar
UK stock market index (FTSE 100)
UK long government bond
France 3-month interest rate
Switzerland stock market index
+3
Switzerland SFr/US$ exchange rate
Notes: Statistics are based on 5-day changes in implied volatility, to allow for time-of-day differences. Correlation coefficients are
rounded to nearest 10% and expressed in tenths, so that “+3” denotes 30%, for example. Shading ranges from white for zero or negative
correlation to black for 100% (rounded) correlation. Each data label references both the row of the matrix it occupies and the column
above its right-most extent.
Table A22
Average correlations of implied volatility measures (percent)
Period
Average correlation
(for period)
Average correlation
(previous 6 months)
Average | absolute |
change
1 Jan. 1998 –
3 July 1998
12
21
15
6 July 1998 –
31 Dec. 1998
19
13
18
6 July 1998 –
14 Aug.1998
10
13
25
17 Aug.1998 –
22 Sep. 1998
47
13
38
23 Sep. 1998 –
15 Oct. 1998
19
31
44
16 Oct. 1998 –
31 Dec. 1998
20
24
25
Note: Statistics are based on correlations of 5-day changes in spreads, as reported in Table A21.
70
Table A23
Effectiveness of hedging a bond yield with a short futures position
Reduction in volatility compared to unhedged position (percent)
1 Jan.
to
3 July
6 July
to
14 Aug.
17 Aug.
to
22 Sep.
23 Sep.
to
15 Oct.
16 Oct.
to
31 Dec.
Japan 10-year bond
16
27
56
– 2
54
Brazil 16-year Brady bond
50
56
71
27
35
US 30-year government bond
70
62
64
79
68
UK 10-year bond (using “long gilt” futures)
42
63
72
69
70
Germany 10-year bond
– 6
21
61
60
52
Netherlands 10-year bond (using German futures)
– 37
3
18
79
34
13
17
39
77
26
Italy 10-year bond (using German futures)
– 2
13
3
54
13
Spain 10-year bond (using German futures)
– 34
8
– 11
75
38
France 10-year bond (using German futures)
Residual volatility of hedged position (basis points, annualised)
1 Jan.
to
3 July
6 July
to
14 Aug.
17 Aug.
to
22 Sep.
23 Sep.
to
15 Oct.
16 Oct.
to
31 Dec.
54
32
35
57
47
8
14
27
29
16
US 30-year government bond
24
16
36
39
32
UK 10-year bond (using “long gilt” futures)
39
24
26
61
23
Germany 10-year bond
54
20
35
53
26
Netherlands 10-year bond (using German futures)
69
28
64
26
31
France 10-year bond (using German futures)
50
42
63
35
41
Italy 10-year bond (using German futures)
61
26
66
69
43
Spain 10-year bond (using German futures)
72
27
72
40
32
Japan 10-year bond
Brazil 16-year Brady bond
Note: These figures are based on notional hedges of changes in the yield. (except for the Brazil Brady bond future, where only one
specific bond is eligible for delivery). Thus, when the futures price is based on the price of a notional bond, the price is converted to an
implicit yield. A unit hedge ratio is used. (the true optimal hedge ratio may be affected by the identity of the cheapest-to-deliver
underlying bond, which likely varies over time.) The numbers in parentheses are the change in the bond yield over the period, in basis
points (except for the Brazil Brady Bond future, where they are percent changes in the bond price).
71
Table A23 (continued)
Effectiveness of hedging a bond yield with a short futures position
Cumulative Effectiveness: Ratio of Change in Futures Yield to Change in Bond Yield (Percent)
Japan 10-year bond
US 30-year government bond
UK long gilt bond
Germany 10-year bond
Netherlands 10-year bond (using German futures)
France 10-year bond (using German futures)
Italy 10-year bond (using German futures)
Spain 10-year bond (using German futures)
1-Jan
6-Jul
17-Aug
23-Sep
16-Oct
to 3-Jul
to 14-Aug
to 22-Sep
to 15-Oct
to 31-Dec
78
138
65
-110
48
(-32)
(-11)
(-51)
(-5)
(118)
90
-580
83
86
87
(-25)
(1)
(-69)
(-11)
(21)
83
63
80
121
55
(-46)
(-21)
(-63)
(6)
(-70)
103
87
108
185
193
(-63)
(-24)
(-60)
(19)
(-27)
131
116
123
231
150
(-48)
(-21)
(-49)
(8)
(-18)
126
118
121
134
83
(-50)
(-21)
(-50)
(14)
(-18)
117
124
156
153
49
(-54)
(-20)
(-39)
(12)
(-56)
90
116
182
132
50
(-70)
(-21)
(-33)
(14)
(-54)
Notes: These figures are based on notional hedges of changes in the yield over the entirety of the sub-periods. Thus, when the futures price
is based on the price of a notional bond, the price is converted to an implicit yield. The UK, France, and Italy bond yields are for benchmark
bonds, and for other countries, the bond yield is from a yield curve estimation (generally taken from Bloomberg). The upper number in each
cell is the ratio (in percent) of the change in the futures yield over the period to the change in the bond yield over the period. The number in
parentheses below is the change in the bond yield over the period, expressed in basis points. For example, during the first period, the
Japanese bond yield dropped 32 basis points, but the futures yield fell only 25 basis points – 78 percent as much. Period with effectiveness
furthest from 100 percent is shaded.
72
Table A24
Effectiveness of hedging a 10-year government bond yield with a swap
Reduction in volatility compared to unhedged position (percent)
1 Jan.
to 3 July
Japan 10-year bond
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
– 32
– 40
– 47
– 72
– 27
US 10-year bond
80
62
49
75
62
UK 10-year bond
44
– 3
1
49
27
– 5
– 35
– 36
– 29
– 15
Germany 10-year bond
Residual volatility of hedged position (percent, annualised)
1 Jan.
to 3 July
6 July
to 14 Aug.
17 Aug.
to 22 Sep.
23 Sep.
to 15 Oct.
16 Oct.
to 31 Dec.
Japan 10-year bond
84
62
117
96
130
US 10-year bond
16
16
51
48
38
UK 10-year bond
38
68
93
99
58
Germany 10-year bond
54
33
122
172
62
Notes: These figures are based on notional hedges of changes in the yield. A unit hedge ratio is used. ). Shading denotes the periods with
the least effective hedges or most residual volatility.
Cumulative Effectiveness: Ratio of Change in Swap Rate to Change in Bond Yield (Percent)
Japan 10-year bond
US 10-year bond
UK 10-year bond
Germany 10-year bond
1-Jan
6-Jul
17-Aug
23-Sep
16-Oct
to 3-Jul
to 14-Aug
to 22-Sep
to 15-Oct
to 31-Dec
41
19
-9
310
-30
(-32)
(-11)
(-51)
(-5)
(118)
72
650
50
45
-5
(-25)
(1)
(-69)
(-11)
(21)
34
198
-1
338
125
(-46)
(-21)
(-63)
(6)
(-70)
88
41
69
47
186
(-61)
(-28)
(-56)
(1)
(-14)
Notes: These figures are based on notional hedges of changes in the yield over the entirety of the sub-periods. The UK bond yield is for a
benchmark bond and for other countries, the bond yield is from a yield curve estimation (generally taken from Bloomberg). The upper
number in each cell is the ratio (in percent) of the change in the swap rate over the period to the change in the bond yield over the period.
The number in parentheses below is the change in the bond yield over the period, expressed in basis points. For example, during the first
period, the Japanese bond yield dropped 32 basis points, but the swap rate fell only 13 basis points – 41 percent as much. Period with
effectiveness furthest from 100 percent is shaded.
73
Table A25
Peak yield spreads: 1998 versus the rest of the 1990s
(basis points)
Data go
back to:
1998
peak
Non1998
peak
Date of
peak
Ratio of
peaks
Mexico Brady bond
1992
468
847
16 Mar. 95
55%
US speculative-grade bond
1990
687
1059
3 Jan. 91
65%
Canada 10-year C$ swap
1990
48
100
4 Jan. 90
48%
Netherlands government bond (vs. Germany)
1990
27
75
16 Jan. 90
36%
Netherlands two industrial bonds
1992
68
84
31 Dec. 93
81%
Netherlands two bank bonds
1992
47
67
29 Dec. 93
70%
Germany mortgage bond index
1990
110
122
14 Sep. 92
90%
Germany bank bond index
1990
22
53
14 Sep. 92
42%
Germany 10-year DM swap
1990
69
52
25 Feb. 94
133%
Swiss corporate bond
1992
61
70
24 Jan. 96
87%
Swiss 5-7 year SFr swap
1992
89
78
28 Feb. 96
114%
Table A26
Peak short rate spreads: 1998 versus the rest of the 1990s
(basis points)
Data go
back to:
1998
peak
Non-1998
peak
Date of
peak
Ratio of
peaks
Japan 3-month interbank
1992
22
21
22 Dec. 95
105%
Hong Kong 3-month interbank
1989
1294
1928
23 Oct. 97
67%
Hong Kong 6-month interbank
1989
1198
1417
23 Oct. 97
85%
Hong Kong 12-month interbank
1989
854
1404
23 Oct. 97
61%
US 3-month interbank
1989
144
166
27 Dec. 90
87%
US 12-month interbank
1989
86
220
22 Mar. 89
39%
Canada 3-month interbank
1989
67
69
13 Nov. 97
97%
France 3-month interbank
1989
43
362
30 Sep. 92
12%
France 12-month interbank
1989
34
93
13 Nov. 92
37%
74
Table A27
Largest within-year stock price declines: 1998 versus the rest of the 1990s
(percent)
Data go
back to:
1998
decline
Non-1998
decline
Japan
1989
– 25%
– 47%
1 Oct. 90
53%
Hong Kong
1989
– 44%
– 46%
28 Oct. 97
95%
Korea
1989
– 51%
– 56%
12 Dec. 97
92%
Brazil
1989
– 61%
– 69%
29 March 90
89%
Mexico
1992
– 45%
– 39%
27 Feb. 95
117%
US
1989
– 19%
– 20%
11 Oct. 90
97%
US financial
1989
– 35%
– 41%
29 Oct. 90
86%
US small-cap
1989
– 37%
– 30%
30 Oct. 90
121%
Canada
1989
– 32%
– 25%
16 Oct. 90
127%
UK
1989
– 25%
– 19%
28 Sep. 90
129%
UK financial
1989
– 39%
– 28%
24 Sep. 90
136%
Germany
1989
– 37%
– 32%
28 Sep. 90
115%
France
1992
– 33%
– 23%
25 Oct. 94
144%
France financial
1992
– 48%
– 34%
5 Oct. 94
143%
Switzerland (based on weekly data)
1992
– 39%
– 22%
6 July 94
179%
Switzerland bank (based on weekly data)
1992
– 55%
– 25%
7 Dec. 94
217%
Note: Measured as the largest percent decline between any two dates within a given year.
75
End-date of
decline
Ratio of
declines
Table A28
Peak of within-month volatility of stock prices:
1998 versus the rest of the 1990s
(June 1998 = 100)
Data go
back to:
1998
peak
Non-1998
peak
Month of
peak
Ratio of
peaks
Japan
1989
180
221
Nov. 97
81%
Hong Kong
1989
143
207
Oct. 97
69%
Korea
1989
132
146
Dec. 97
90%
Brazil
1989
235
422
Aug. 92
56%
Mexico
1992
211
176
Oct. 97
120%
US
1989
221
209
Oct. 97
106%
US financial
1989
278
190
Sep. 90
146%
US small-cap
1989
246
287
Dec. 90
86%
Canada
1989
242
165
Oct. 97
147%
UK
1989
213
164
Sep. 92
130%
UK financial
1989
230
183
Sep. 92
126%
Germany
1989
266
293
Oct. 89
91%
France
1992
226
177
Oct. 97
128%
France financial
1992
298
180
Sep. 92
166%
Switzerland
1992
271
199
Feb. 94
136%
Switzerland bank
1992
279
142
Feb. 94
196%
Note: Volatility is measured as the square root of the mean daily squared change in the yield or log stock price within the month.
Table A29
Peak of within-month volatility of government bond yields:
1998 versus the rest of the 1990s
(June 1998 = 100)
Data go
back to:
1998
peak
Non-1998
peak
Japan 10-year
1989
237
348
Feb. 90
68%
Hong Kong 3-year
1993
120
167
Oct. 97
72%
US 2-year
1989
283
363
June 95
78%
US 5-year
1989
269
347
April 94
77%
US 10-year
1989
270
323
April 94
84%
US 30-year
1989
205
277
April 94
74%
UK 10-year
1990
205
289
June 94
71%
Netherlands 10-year
1990
305
389
Feb. 90
78%
Germany 10-year
1990
290
414
Feb. 90
70%
76
Month of
peak
Ratio of
peaks
Table A30
Peak of within-month volatility of yield spreads:
1998 versus the rest of the 1990s
(June 1998 = 100)
Data go
back to:
1998
peak
Non1998
peak
Mexico Brady bond
1992
390
1245
Jan. 95
31%
US speculative-grade bond
1990
260
371
April 90
70%
Canada 10-year C$ swap
1990
339
638
Oct. 92
53%
Netherlands government bond (vs. Germany)
1990
173
348
June 94
50%
Netherlands two industrial bonds
1992
262
474
June 94
55%
Netherlands two bank bonds
1992
243
340
June 94
71%
Germany mortgage bond index
1990
589
785
Aug. 91
75%
Germany bank bond index
1990
181
600
March 94
30%
Germany 10-year DM swap
1990
576
695
June 94
83%
Month of
peak
Ratio of
peaks
Note: Volatility is measured as the square root of the mean daily squared change in the spread within the month.
Table A31
Peak of within-month volatility of short rate spreads:
1998 versus the rest of the 1990s
(June 1998 = 100)
Data go
back to:
1998 peak
Non-1998
peak
Month of
peak
Ratio of
peaks
Japan 3-month interbank
1992
853
787
Dec. 93
108%
Hong Kong 3-month interbank
1989
167
418
Oct. 97
40%
Hong Kong 6-month interbank
1989
194
400
Oct. 97
49%
Hong Kong 12-month interbank
1989
137
454
Oct. 97
30%
US 3-month interbank
1989
306
550
Dec. 90
56%
US 12-month interbank
1989
330
1037
March 89
32%
Canada 3-month interbank
1989
231
441
Sep. 92
52%
France 3-month interbank
1989
1134
8862
Sep. 92
13%
France 12-month interbank
1989
470
1897
July 93
25%
Note: Interbank rate spreads are measured by using euro-rates, except for Mexico and Hong Kong.
77
Table A32
Peak of within-month volatility of exchange rates:
1998 versus the rest of the 1990s
(June 1998 = 100)
Data go
back to:
1998 peak
Yen/US dollar
1989
126
Yen/Swiss franc
1992
US dollar/Canadian dollar
Non-1998
peak
Month of
peak
Ratio of
peaks
75
March 95
167%
204
160
Sep. 92
128%
1989
326
262
Oct. 95
125%
US dollar/German mark
1989
137
296
Sep. 92
46%
US dollar/Swiss franc
1992
262
488
March 95
54%
Note: Volatility is measured as the square root of the mean daily squared change in the log exchange rate within the month.
78
Figure A1
Bank Bond Yield Spreads
Japan
Versus Corporate Yield Spread
Basis Points
Russia
LTCM
250
Rate Cut
BBB Bond
200
150
100
AA Bond
50
Bank Bond
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Versus Swap Spread
Basis Points
Russia
LTCM
100
Rate Cut
80
Swap
60
40
Bank Bond
20
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Figure A2
Bank Bond Yield Spreads
Netherlands
Versus Corporate Yield Spread
Basis Points
Russia
LTCM
80
Rate Cut
70
60
50
Corporate
40
30
Bank Bond
20
10
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Versus Swap Spread
Basis Points
Russia
LTCM
60
Rate Cut
50
40
Bank Bond
30
20
Swap
10
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Figure A3
Bank Bond Yield Spreads
United Kingdom
Versus Corporate Yield Spread
Basis Points
Russia
LTCM
210
Rate Cut
180
150
120
BBB Bond
90
Bank Bond
60
AA Bond
30
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Versus Swap Spread
Basis Points
Russia
LTCM
180
Rate Cut
150
120
90
Bank Bond
60
30
Swap
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Figure A4
Bank Bond Yield Spreads
Germany
Versus Corporate Yield Spread
Basis Points
Russia
LTCM
125
U.S. Rate Cut
100
Corporate
75
50
Bank Bond
25
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Versus Swap Spread
Basis Points
Russia
LTCM
80
U.S. Rate Cut
70
60
50
40
Swap
Bank Bond
30
20
10
0
Jan
Feb
Mar
Apr
May
June
July
1998
Note: Spreads are measured by using domestic rates.
Aug
Sep
Oct
Nov
Dec
Figure A5
Implied and Historical Volatility
FTSE 100
Percent
Russia
LTCM
60
Rate Cut
54
48
42
36
30
Implied Volatility
24
18
250-day Historical Volatility
12
6
0
Jan
Feb
Mar
Apr
May
June
July
1998
Aug
Sep
Oct
Nov
Dec
Figure A6
Implied Volatility over the 1990s
3-Month Interest Rates
Percent
80
60
France
40
United States
20
1990
1991
1992
1993
1994
1995
1996
1997
1998
0
1999
Government Bonds
Percent
20
15
United States
10
France
5
1990
1991
1992
1993
1994
1995
1996
1997
1998
0
1999
Stock Market Indices
Percent
100
80
Mexico
60
40
20
Switzerland
1990
1991
1992
1993
1994
1995
1996
1997
1998
0
1999
Sources and further details for data series used
Brazil 16-year Brady bond futures hedge: based on daily percent change in price of Brazil 2014
“C-Bond” and percent change in price of nearest-to-expiration Brazil C-Bond future trading on
Chicago Mercantile Exchange (source: Bloomberg).
Brazil stock market index: Brazilian Bovespa Stock Index (source: Bloomberg).
Canada 3-month interbank: spread between 3-month euro currency bid rate for the Canadian dollar
and treasury bill rate for Canada (source: BIS, Bank of Canada).
Canada 10-year $ swap: swap spreads quoted relative to the on-the-run Canadian government bond
(source: Bloomberg).
Canada stock market index: Toronto Stock Exchange 300 Composite Index (source: Bloomberg).
France 1-month commercial paper: spread between weighted weekly average rate at issue for 1-month
maturity commercial paper Act/360 and daily 1-month euro currency bid rate for the French Franc
(source: Banque de France, BIS).
France 1-year, 10-year swap rate: spread between bid and ask swap market rate quoted on simple
interest basis, 360 days per year, with the same maturity (source: Banque de France).
France 3-month bond futures: 3-Month Pibor futures contract volume, in number of contracts (source:
Banque de France).
France 3-month interbank: spread between 3-month interbank bid market rate quoted on simple
interest basis and 3-month treasury bill rate for France (source: Banque de France).
France 3-month interbank rate: spread between 3-month bid and ask interbank market rate quoted on
simple interest basis, 360 days per year (source: Banque de France).
France 3-month interest rate implied volatility: settlement volatility for the option on most traded
3-month future contract “Pibor” (source: MATIF SA).
France 3-month repo rate: spread between 3-month bid and ask repo market rate quoted on simple
interest basis, 360 days per year (source: Banque de France).
France 5-year PIBOR futures: 5-Year PIBOR euro futures contract volume, in number of contracts
(source: Banque de France).
France 10-year bond (using German futures) futures hedge: based on daily change in benchmark
10-year France government bond (source: Reuters) and daily change in price of nearest-to-expiration
German 10-year bond futures traded on London International Financial Futures and Options Exchange
(LIFFE) converted to a yield based on the characteristics of the underlying notional asset (6% yield
and 10-year maturity) (source: Bloomberg).
France 10-year bond futures: 10-year Notionnel futures contract volume, in number of contracts
(source: Banque de France).
France 10-year government bond implied volatility: settlement volatility for the option on most traded
10-year future contract “Notionnel” (source: MATIF SA).
France A3 corporate bond: the sum of the average weighted spread between swap and credit curve for
A3 issuers and the average weighted spread between swap and OAT curve. The spreads are weighted
with the outstanding amount and the remaining maturity of each issue (source: CCF Charterhouse).
France average swap rate: the average spread between swap and OAT curve. The spread is weighted
with the outstanding amount and the remaining maturity of each issue (source: CCF Charterhouse).
France financial stock market index: Financial services subindex of SBF120 French stock index
(source: Bloomberg).
85
France stock market index: CAC 40 index of French stock prices (source: Bloomberg).
Germany 9-10 year mortgage bond, Germany 9-10 year bank bond: difference between yield on
German mortgage (bank) bond over 9 to 10 years and yield on German listed Federal debt securities
with residual maturities of over 9 to 10 years (source: Deutsche Bundesbank).
Germany 10-year bond futures hedge: based on daily change in estimated German Government Bund
yield curve at 10 years (Source: Bloomberg) and daily change in price of nearest-to-expiration German
10-year bond futures traded on London International Financial Futures and Options Exchange (LIFFE)
converted to a yield based on the characteristics of the underlying notional asset (6% yield and 10-year
maturity) (Source: Bloomberg).
Germany 10-year bond swap hedge: based on daily change in estimated Germany Bund yield curve at
10 years (source: Bloomberg) and daily change in yield of nearest-to-expiration Germany 10-year
swap rate (source: Bloomberg, Datastream).
Germany 10-year DM swap: the difference between the German BGN benchmark bonds and the
composite IRS rate (source: Bloomberg).
Germany 10-year government bond yield: bond yield generic 10-year German Bund (source:
Datastream)
Germany bank bond index: spread between the German public bond yield and the German bank bond
yield. Both series are weighted average yields for bearer bonds with remaining maturities over 3 years
(source: Deutsche Bundesbank).
Germany bonds: stock market turnover (spot and OTC trading): All debt securities (source:
Bundesbank).
Germany industrial bond (from May): difference between yield of German industrial bonds and yield
on German listed Federal debt securities. Both series are weighted average yields for bearer bonds
with remaining maturities over 3 years (source: Deutsche Bundesbank).
Germany mortgage bond index: the spread between the German public bond yield and the German
mortgage bond yield. Both series are weighted average yields for bearer bonds with remaining
maturities over 3 years (source: Deutsche Bundesbank).
Germany stock market index: Deutsche Aktien – DAX index (source: Reuters)
Hong Kong 3-month, 6-month, 12-month interbank: spread between the HIBOR and LIBOR of the
respective maturity (source: Standard Chartered Bank, Reuters).
Hong Kong 3-month HIBOR futures: daily volume of 3-month HIBOR futures contract (source: Hong
Kong Futures Exchange Limited).
Hong Kong 3-year agency bond: Spread between MTRC Note (or remaining maturity of 3 years) and
its corresponding Exchange Fund Note (source: HKMA).
Hong Kong 3-year, 5-year, 10-year government bond yield: yield of Exchange Fund Note with the
relative maturity (source: HKMA).
Hong Kong 10-year government bond: spread between 10-year Exchange Fund Notes and 10-year US
Treasuries (source: HKMA and Reuters).
Hong Kong 10-year HK$ Swap: spread between 10-year HK$ interest rate swap and Exchange Fund
Note (source: HKMA and various financial information service providers).
Hong Kong dollar/US dollar (12-month forward): sum of Hong Kong dollar/US dollar exchange rate
and 1/10,000 of the 12-month Hong Kong dollar forward exchange rate (source: Census and Statistics
Department, Hang Send Bank Limited).
Hong Kong government securities: daily turnover of Exchange Fund Bills and Notes (source:
HKMA).
86
Hong private sector debt instruments: daily turnover of HK$ private sector debt instruments lodged
with the Central Money Markets Unit, operated by the HKMA (source: HKMA).
Hong Kong stock market index: daily closing of the Hang Seng Index (source: CEIC).
Hong Kong stock market index futures: total daily volume of Hang Seng Index futures contracts
(source: Hong Kong Futures Exchange Limited).
Italy 10-year bond (using German futures) futures hedge: based on daily change in benchmark Italian
bond (source: Reuters) and daily change in price of nearest-to-expiration German 10-year bond futures
traded on London International Financial Futures and Options Exchange (LIFFE) converted to a yield
based on the characteristics of the underlying notional asset (6% yield and 10-year maturity) (source:
Bloomberg).
Japan 3-month interbank: difference between 3-month euro-rate for the yen and the 3-month Treasury
bill rate in the Tokyo market (source: BIS, Japan Securities Dealers Association).
Japan 5-year AA corporate bond, Japan 5-year BBB corporate bond: spread between corporate bond
quote rate and JGB with the same maturity (source: Japan Securities Dealers Association, via
Tokyo-Mitsubishi Securities).
Japan 5-year bank bond: spread between 5-year bank debentures yield rate and JGB with same
maturity (source: Japan Securities Dealers Association, via Tokyo-Mitsubishi Securities).
Japan 10-year bond futures hedge: based on daily change in estimated Japanese Government Bond
yield curve at 10 years (source: Bloomberg) and daily change in price of nearest-to-expiration
Japanese 10-year bond futures traded on Tokyo Stock Exchange (TSE) (source: Bloomberg).
Japan 10-year bond swap hedge: based on daily change in estimated Japanese Government Bond yield
curve at 10 years (source: Bloomberg) and daily change in yield of nearest-to-expiration Japanese
10-year swap rate (source: Reuters, Tokyo Stock Exchange, Bank of Tokyo-Mitsubishi, Reuters).
Japan 10-year government bond yield: 10 year Benchmark yield of Japanese Government Bond
(source: Tokyo Stock Exchange, Bank of Tokyo-Mitsubishi).
Japan 10-year liquidity spread: spread between off-the-run and on-the-run 10-year Japanese
Government Bond (source: Tokyo Stock Exchange, Bank of Tokyo-Mitsubishi).
Japan 10-year yen Swap: spread between 10-year Japanese interest rate swaps and JGB benchmark
(source: Telerate (or Reuters)).
Japan bank stock market index: TOPIX Banking Sector Subindex (source: Tokyo Stock Exchange).
Japan stock market index: Tokyo Stock Exchange TOPIX Index (source: Tokyo Stock Index).
Korea stock market index: Korean composite index (source: Bloomberg).
Latin America Brady bond: JP Morgan Emerging Markets Bond Index Latin America spread over
Treasury bonds (source: JP Morgan).
Mexico 1-month inter-bank: difference in the equilibrium interbank interest rate and the Prebon Index.
The Prebon Index was calculated using several Cetes 28d contracts in the secondary market (source:
Banco de México, Prebon).
Mexico Brady bond: JP Morgan Emerging Market Bond Index Mexico spread (source: JP Morgan).
Mexico corporate Eurobond: JP Morgan Latin Eurobond Index Mexico Corporate spread over
Treasury bonds (source: JP Morgan).
Mexico foreign exchange: Mexican foreign exchange market volume (source: Banco de México).
Mexico Peso/US Dollar exchange rate: spread between the closing bid and ask price of the Peso-US
Dollar (source: Banco de México).
Mexico stock market index: Mexican Bolsa Index (source: Bloomberg).
87
Mexico stock index implied volatility: 30 day implied volatility of ATM peso options (source: Prebon
Yamane).
Netherlands 10-year bond (using German futures) futures hedge: based on daily change in benchmark
10-year Netherlands bond (source: Bloomberg) and daily change in price of nearest-to-expiration
German 10-year bond futures traded on London International Financial Futures and Options Exchange
(LIFFE) converted to a yield based on the characteristics of the underlying notional asset (6% yield
and 10-year maturity) (Source: Bloomberg).
Netherlands 10-year government bond yield: yield for generic 10-year Netherlands government bond
(source: ask Central Bank of Netherlands???).
Netherlands 10-year liquidity spread (versus German yield curve): yield spread between 10-year
Netherlands and German government bond yield curves (source: Datastream).
Netherlands four 10-year bank bonds: average of yield spreads of ABN Amro 8.25% 4/07 bond, Bank
Nederlandse Gemeenten 5.5% 1/08 bond, ING 5.5% 1/08 bond, and Nederlandse Waterschapsbank
5.5% 1/08 bond over Netherlands government bonds of similar maturities (source: Datastream).
Netherlands two bank bonds: average of yield spreads of Bank Nederlandse Gemeenten 7.625% 12/02
bond and ING 10% 3/01 bond over Netherlands government bonds of similar maturities (source:
Datastream).
Netherlands two industrial bonds: average of yield spreads between Akzo Nobel NV 8% 12/02 bond
and Unilever NV 9% 7/00 bond over Netherlands government bonds of similar maturities (source:
Datastream).
Russia stock market index: Russian Trading System Index (source: Reuters).
Spain 10-year bond (using German futures) futures hedge: based on daily change in benchmark
10-year Spain government bond (source: Reuters) and daily change in price of nearest-to-expiration
German 10-year bond futures traded on London International Financial Futures and Options Exchange
(LIFFE) converted to a yield based on the characteristics of the underlying notional asset (6% yield
and 10-year maturity) (source: Bloomberg).
Switzerland 5–7 year SFr swap: spreads for the Swiss Franc swap rate are calculated by applying the
DBI convex combination on the spreads of 5 and 7 year swap rates over Government Bond yields
(source: Bloomberg).
Switzerland 5-year swap rate: spread between 5-year bid and ask swap market rate (source:
Bloomberg).
Switzerland bank stock index: Swiss Market Index (source: Datastream).
Switzerland corporate bond: with an average duration of approximately six years, the Swiss Domestic
Bond Index (DBI) is comprised of first class domestic bonds and federal bonds. The spread is
calculated over a linear combination of the 5 and 7 year benchmark Government Bonds matching the
DBI duration. Weekly data was used from 1 January through 30 June. Afterwards, business daily data
was used (source: Swiss Stock Exchange, Primark).
Switzerland SFr/US$ exchange rate implied volatility: (source: Datastream).
Switzerland stock index: Swiss Banking Index (source: Datastream).
Switzerland stock market index implied volatility: implied volatility of the Swiss Market Index
(source: Datastream).
UK 3-month interbank versus repo rate: sterling interbank rate over 3-month repo spread (source:
Bank of England).
UK 3-month interest rate implied volatility: short sterling implied volatility (source: LIFFE).
UK 5-year Aa, A, Baa corporate bond: calculated from 5-year duration corporate bonds, spread over
duration matched Gilts (source: Bank of England).
88
UK 5-year Barclays, Lloyds, NatWest, Royal Scotland bank bond: spread for 5-year bank bond over
5-year Gilts (source: Bank of England).
UK four 5-year bank bonds: average of 5-year Barclays Bank, Lloyds Bank, Natwest Bank, and Royal
Bank of Scotland bank spread over duration-matched Gilts (source: Bank of England).
UK 10-year government bond yield: 10-year UK gilt benchmark bond yield (source: Reuters).
UK 10-year bond swap hedge: based on daily change in estimated UK long gilt bond yield curve at
10 years (source: Reuters) and daily change in yield of nearest-to-expiration 10-year sterling (zero)
swap rate (source: Reuters, Bank of England).
UK 10-year liquidity spread: spread between yield spread of 8.50% 2007 gilt and the yield spread of
7.25% 2007 gilt (source: Bank of England).
UK 10-year sterling swap: using Svensson model for zero Gilt yields (source: Bank of England).
UK Aa, A, Baa corporate bond: average bid-ask spread of relative UK corporate bonds (source:
Reuters).
UK financial stock market index: FTSE financial stock index (source: Datastream).
UK long gilt futures hedge: based on daily change in estimated UK gilt benchmark bond yield curve at
10 years (source: Reuters) and daily change in price of nearest-to-expiration UK 10-year long gilt
bond futures traded on London International Financial Futures and Options Exchange (LIFFE)
converted to a yield based on the characteristics of the underlying notional asset (7% yield and 15-year
maturity) (source: Bloomberg).
UK long government bond implied volatility: long Gilt implied volatility (source: LIFFE).
UK stock market index: FTSE 100 stock index (source: Datastream).
UK stock market index implied volatility: FTSE 100 implied volatility (source: LIFFE).
US 1-month prime commercial paper: commercial paper AA rate over 1-month repo rate (source:
Federal Reserve).
US 1-month second-tier commercial paper: 1-month commercial paper A2 rate over P2 rate (source:
Federal Reserve).
US 2-year, 5-year, 10-year, 30-year government bond yield: US Treasury bond yield with the relative
maturity (source: Federal Reserve).
US 2-year US$ swap, US 10-year US$ swap: swap spreads quoted relative to the on-the-run Treasury
yield curve (source: Bloomberg).
US 3-month Eurodollar implied volatility: implied volatility for 3-month Eurodollar (source: Federal
Reserve).
US 3-month, 12-month interbank: difference between the euro currency bid rate for the US dollar and
US Treasury bill rate of the same maturity (source: BIS, Federal Reserve).
US 10-year AA corporate bond, US 10-year BBB corporate bond: spread between Merrill Lynch
corporate bond quoted yields and 10-year Treasury bond with the same maturity (source: Merrill
Lynch, Federal Reserve).
US 10-year bond swap hedge: based on daily change in estimated Treasury bond yield curve at
10 years (source: Bloomberg) and daily change in yield of nearest-to-expiration Treasury 10-year
swap rate (source: Federal Reserve).
US 10-year inflation-indexed government bond yield: 10-year indexed note yield (source: Federal
Reserve).
US 10-year liquidity spread: spread between 10-year off-the-run and on-the-run Treasury bill rate
(source: Federal Reserve).
89
US 30-year government bond futures hedge: based on daily change in estimated Treasury bond yield
curve at 30 years (source: Bloomberg) and daily change in price of nearest-to-expiration Treasury
30-year bond futures traded on Chicago Board of Trade (CBT) converted to a yield based on the
characteristics of the underlying notional asset (8% yield and 20-year maturity) (source: Bloomberg).
US 30-year government bond implied volatility: implied volatility of 30-year government bonds
(source: Federal Reserve).
US dollar/Canadian dollar: US$/Canadian dollar spot exchange rate (source: Federal Reserve).
US dollar/German mark: US$/Euro spot exchange rate, restated German mark before 1999 (source:
Federal Reserve).
US dollar/Swiss franc: US$/Swiss franc exchange rate (source: Datastream).
US financial stock market index: S&P Financial Stock Index (source: Bloomberg).
US small-cap stock market index: Russell 2000 Stock Index (source: Federal Reserve).
US speculative-grade bond: spread between Merrill Lynch High Yield bond yield and 7-year Treasury
bond (source: Merrill Lynch, Federal Reserve).
US stock market index: S&P 500 Stock Index (source: Federal Reserve).
US stock market index (S&P 500) implied volatility: (source: Federal Reserve).
Yen/Swiss franc: Swiss franc – 100 Yen exchange rate (source: Datastream).
Yen/US dollar: Yen/$US dollar spot exchange rate (source: Federal Reserve).
90
Members of the Working Group on
Financial Market Events in the Autumn of 1998
Chairperson
Ms Karen Johnson
Board of Governors of the Federal Reserve
System
Banque de France
Mr François Haas
Ms Sophie Blanchet
Ms Imêne Rahmouni
Deutsche Bundesbank
Mr Edgar Brandt
Hong Kong Monetary Authority
Mr Francis Lau
Bank of Japan
Mr Masaaki Shirakawa
Mr Tatsuya Yonetani
Banco de México
Mr Javier Duclaud
Mr Alonso Garcia Tames
De Nederlandsche Bank
Mr Eloy Lindeijer
Sveriges Riksbank
Mr Kjell Nordin
Mr Anders Eklöf
Swiss National Bank
Mr Dominik Egli
Bank of England
Mr Alex Bowen
Federal Reserve Bank of New York
Mr Dino Kos
Board of Governors of the Federal Reserve
System
Mr Vincent Reinhart
European Central Bank
Mr Javier Santillán
Bank for International Settlements
Mr Benjamin Cohen
91
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