M31507 Financial Econometrics Assignment 2, 2026 | University of Portsmouth

You can see the related solution of this brief: Economics Assignment Example

M31507 Financial Econometrics Assignment 2, 2026

Assessed Coursework 2

This coursework (individual, not group work) counts for 50% of your overall assessment for this module. Please submit your completed answers (a maximum of 7 A4 pages, excluding the appendix) to the module Moodle page. Please also submit all your EViews workings copied in the appendix with your coursework.

This coursework exercise should be completed individually. This coursework requires a significant time commitment.

Learning Outcomes

This coursework assignment assesses the following learning outcomes (LO) of the module:

• Assess the properties and limitations of econometric methods as applied to the analysis of financial data.
• Formulate and test econometric models to examine different forms of financial data.
• Evaluate the results of econometric analysis.

Data:

Please use the same data file that you have used for the first assignment for this module. You were provided data about one stock downloaded from Yahoo Finance. If, for some reason, you have misplaced your data file, don’t worry, a data file containing your data is still available on the module Moodle page. The spreadsheet has details about your allocated data file.

Your Price series is Adj Close.

In answering the questions below, you may wish to consult the help option in EViews.

1. For your series, in EViews, use the Genr option to calculate (i) the log of the price series, e.g.
e=log (Adj Close), and (ii) the daily log returns (e.g. r=log(Adj Close)-log(Adj Close(-1))).
 
Now, try to find the most appropriate ARMA(p,q) model for r by choosing the ARMA model (i.e. the choice of orders p and q) that minimises the Schwarz criterion. Do this over the range of ARMA(p,q) models defined by p = 0,1,2, … and q = 0,1,2,….

Now estimate your chosen ARMA model for the log return r series.

i. Test for the presence of ARCH effects in the residuals of this regression.
ii. Select and estimate an appropriate GARCH (p,q) model for the conditional variance of the residuals of this regression.

Justify your choice of the selected GARCH model using the information provided by:

i. The estimated coefficients (and their t-statistics or p values)
ii. Information criteria.

Now extend your selected GARCH model to include EGARCH and TGARCH effects separately.
Justify your choice of selected EGARCH and TGARCH models using the information provided by:

iii. The estimated coefficients (and their t-statistics or p values)
iv. Information criteria.

Interpret the chosen estimated EGARCH and TGARCH coefficients.

University Grade criteria (Levels 4–8) – General (generic) criteria applicable to essays, reports and aspects of projects and dissertations. However, your report is technical in nature, and the criteria are quite general.