Financial Econometrics (Part 2)
Aim:
To introduce students to stationary and non-stationary time series models (ARMA and ARIMA, respectively). To examine stochastic volatility via ARCH and GARCH modelling. To examine time series features and stochastic volatility properties simultaneously in a single equation model. To demonstrate the application of the above type(s) of modelling to financial data. To use these models for estimation, inference and forecasting.
Syllabus Outline:
Univariate linear stochastic models: ARMA and ARIMA modelling, estimation and forecasting using ARMA and ARIMA models, application to macroeconomic and/or financial data. Modelling stochastic volatility: ARCH and GARCH processes. ARCH in mean model, Asymmetric ARCH models, TARCH and EGARCH model. AR(I)MA models with (G)ARCH errors. Applications to financial data.
You are expected to read the relevant material in advance.
The computer software for this course is Eviews（9.0), which is available on the student network. For most of the exercises you will be required to collect data from the BANKSCOPE, DATASTREAM databases.
Indicative Reading:
Brookes, C., Introductory Econometrics for Finance Cambridge University Press 2008
HARRIS, R and Sollis, R., Applied Time Series Modelling and Forecasting Wiley 2003
PINDYCK, R & RUBENFELD D Econometric Models & Economic Forecasts McGraw & Hill 3rd Edition
Harvey, A. C. Time Series Models, Harvester Wheatsheaf 1993
Mills, T. C. Time Series Techniques for Economists, Cambridge 1990
Mills, T. C. The Econometric Modelling of Financial Time Series, 1993 Cambridge.
Hamilton, J. D. Time Series Analysis, 1994 Princeton
Cuthbertson K, Nitzsche D., Quantitative Financial Ecnomics, 2004 Wiley
Assignment
This will involve answering a set of short questions based on your analysis of a data-set. The assignment is worth 25% of the total assessment. In addition to the above assignment there will be a final unseen examination (worth 50% of the final marks).
Professor Shabbar Jaffry (R4.01)
Financial Econometrics (part 2)
Assessed Coursework
This coursework (individual not a group work) counts for 25% of your overall assessment for this unit. Please submit your completed answers (a maximum of 7 A4 pages) to the Assessment Office, Richmond Building. Essential workings/results/tables can be included in the appendix. Please also submit all your Eviews workings, data and the assignment on to a CD/disk with your coursework.
This coursework requires you to collect 4 sectors of the economy (e.g. real estate, banking, general retail etc.) daily (daily observations excluding weekends and holidays) indices (for London exchange market or for other market if the data is available) from the DataStream software. The length of each series should not be less than 10 years. In answering the questions below, you may wish to consult the help option in Eviews.
You are expected to have collected data for the assignment by 15th February and complete estimations by the end of March.
Choose one of the four series on which to conduct your analysis. For your chosen series, in Eviews use the Genr option to calculate (i) the log of the series, e.g. e=log(your chosen series), and (ii) the daily log returns (e.g. r=e-e(-1)).
Examine the descriptive statistics for both e and r. What do you conclude about the distributions of e and r? Is e normally distributed? Is r normally distributed? Explain why/why not?
Obtain the correlograms, and examine the autocorrelations and partial autocorrelations for both e and r. What do you conclude about the behaviour of e and r? Are they stationary/non-stationary?
Are your conclusions about stationary/non-stationary of e and r confirmed by appropriate unit root tests?
Estimate and select an appropriate ARMA (p,q) model for e. In selecting your preferred model, explain how you use the information provided by:
The estimated coefficients (and their t-statistics);
Ljung-Box Q-statistics for autocorrelation in the residuals; and
AIC and SBC information criteria for choosing between alternative models.
Carry out forecast of e for 100 observations based on your chosen model and comment on your results.
In the following section (v), use 100 less observations from the full sample (e.g. if the full sample was 2000 then only use 1900) available to you.
Carry out forecast (out of sample) of e for 100 observations based on your chosen model and comment on your results.
Now estimate an AR (1) model for the log return r.
Test for the presence of ARCH effects in the residuals of this regression.
Select and estimate an appropriate GARCH (p,q) model for the conditional variance of the residuals of this regression. Justify your choice of selected model.
Now extend your selected model in (ii) to include EGARCH and TGARCH effects. Interpret the estimated EGARCH and TGARCH coefficients.
OR
Discuss and explain any two from the following list:
Long-run and short-run and ECM models
Spurious regressions, cointegration, Engle-Granger and dynamic modelling approaches
The limitations of using a single equation approach to testing for cointegration when there are more than two variables in the model. Short-run dynamic models
Please provide a word count for this question AND ensure that your answer does not exceed 1000 words. Marks will be deducted for overlong essays.
Estimate a VAR (p) model for the log of four selected series.
Test for Granger causality between pair of these series (take log of these series first).
Test for cointegration between four series (chosen in part 4) using Johansen method.
Professor Shabbar Jaffry
Our Service Charter
-
Excellent Quality / 100% Plagiarism-Free
We employ a number of measures to ensure top quality essays. The papers go through a system of quality control prior to delivery. We run plagiarism checks on each paper to ensure that they will be 100% plagiarism-free. So, only clean copies hit customers’ emails. We also never resell the papers completed by our writers. So, once it is checked using a plagiarism checker, the paper will be unique. Speaking of the academic writing standards, we will stick to the assignment brief given by the customer and assign the perfect writer. By saying “the perfect writer” we mean the one having an academic degree in the customer’s study field and positive feedback from other customers. -
Free Revisions
We keep the quality bar of all papers high. But in case you need some extra brilliance to the paper, here’s what to do. First of all, you can choose a top writer. It means that we will assign an expert with a degree in your subject. And secondly, you can rely on our editing services. Our editors will revise your papers, checking whether or not they comply with high standards of academic writing. In addition, editing entails adjusting content if it’s off the topic, adding more sources, refining the language style, and making sure the referencing style is followed. -
Confidentiality / 100% No Disclosure
We make sure that clients’ personal data remains confidential and is not exploited for any purposes beyond those related to our services. We only ask you to provide us with the information that is required to produce the paper according to your writing needs. Please note that the payment info is protected as well. Feel free to refer to the support team for more information about our payment methods. The fact that you used our service is kept secret due to the advanced security standards. So, you can be sure that no one will find out that you got a paper from our writing service. -
Money Back Guarantee
If the writer doesn’t address all the questions on your assignment brief or the delivered paper appears to be off the topic, you can ask for a refund. Or, if it is applicable, you can opt in for free revision within 14-30 days, depending on your paper’s length. The revision or refund request should be sent within 14 days after delivery. The customer gets 100% money-back in case they haven't downloaded the paper. All approved refunds will be returned to the customer’s credit card or Bonus Balance in a form of store credit. Take a note that we will send an extra compensation if the customers goes with a store credit. -
24/7 Customer Support
We have a support team working 24/7 ready to give your issue concerning the order their immediate attention. If you have any questions about the ordering process, communication with the writer, payment options, feel free to join live chat. Be sure to get a fast response. They can also give you the exact price quote, taking into account the timing, desired academic level of the paper, and the number of pages.