Choose some historical data for some particular companies or organisations or asset classes in any markets and/or economic regions or countries, e.g., your home countries or UK/US etc.
Assignment Brief
Research Methods for Risk Management
Coursework for the quantitative part
The deadline for submission of the project report is 3pm on 16th June 2020. The report (3000 words with a ±10% tolerance) should be word-processed, double spaced, fully referenced in 12 points fonts. Your coursework needs to be submitted electronically to Moodle. See your Student Handbook (on Moodle) for further details of this process.
Quantitative Project Question:
Choose some historical data for some particular companies or organisations or asset classes in any markets and/or economic regions or countries, e.g., your home countries or UK/US etc. Conduct some empirical analyses on the dataset to investigate a core question of your choice along with several supporting sub topics. Discuss the implications of your results from the point of view of risk management.
Submission requirements:
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A 3000 words report in Word or PDF format.
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A zip file including your Stata do file(s) that record your codes and operations, data, and 3 core references.
Marking scheme: see document ‘Marking Classification Guide’.
Guidance:
About do files and code, you can write your Stata codes directly in the Editor of Stata. Or you can operate your data with Stata menus and then in the end you can save your history of commands (left panel of Stata) to a do file. The data can be in any usual format like .dta/.csv/excel files etc. You must use Stata to do the coursework since using Stata to do analyses is one of the main learning contents in the module. Other software is not allowed. Besides, including screenshots in the zip package is optional, but you still need to include the do files and data
There will be two tabs in the submission window, one tab for the report and another tab for the zip file. Please submit your work to the correct places.
The coursework report should begin with an introduction and brief literature review. You may introduce and employ any methods you think of as appropriate. In any case, you should clearly define any notations and variables you use and methodologies you make use of, and need to provide suitable references wherever necessary. You never have to cover all topics in the module. You are free to choose methods in one topic or several topics, but your report should be consistent on one core question. The number of methods will not matter. Your critical analyses, interpretations and discussions of your results, which are beyond what are covered in lectures (as well as any clear evidence of your further readings of the relevant literature) could be extra rewarded, provided they are done in a correct and appropriate manner. Data can be collected from Yahoo Finance, the Federal Reserve Economic Data (FRED) of Federal Reserve Bank of St. Louis, databases subscribed by the university, data about your home countries, or other resources available, see, e.g., https://finance.yahoo.com/, https://fred.stlouisfed.org/, and https://www.nottingham.ac.uk/business/research/available-databases.aspx.
In addition to the topics and materials covered in class, you may like to refer to the following literature in particular as your reference. The list provides some examples and ideas, but you do not have to follow them.
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Andersen, T., Bollerslev, T., Diebold, F. X. and Ebens, H. (2001). The Distribution of Realized Stock Return Volatility. Journal of Financial Economics, 61, 43-76.
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Bansal, R. and Lundblad, C. (2002). Market efficiency, asset returns, and the size of the risk premium in global equity markets. Journal of Econometrics, 109, 195-237.
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Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance, 1, 223-236
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Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987-1007.
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Lo, A. W. and MacKinlay, A. C. (1988). Stock market prices do not follow random walks: evidence from a simple Specification test. Review of Financial Studies, 1, 41-66.
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McNeil, A., Frey, R. and Embrechts, P. (2005). Quantitative Risk Management: Concepts, Techniques, and Tools. Princeton University Press, Princeton and Oxford.
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Poterba, J. M. and Summers, L. H. (1988). Mean reversion in stock prices: evidence and implications. Journal of Financial Economics, 22, 27-59.
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Solnik, B. (1990). The distribution of daily stock returns and settlement procedures: the Paris Bourse. Journal of Finance, 45, 1601-1609.
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Taylor, S. J. (2005). Asset Price Dynamics, Volatility, and Prediction. Princeton University Press, Princeton and Oxford.
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Tsay, R. S. (2002). Analysis of Financial Time Series. Wiley, New York.
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You should also show evidence of independent research and reading such as other journal articles on this topic. When reading various journal articles, you are strongly advised to pay careful attention to how data, graphs and tables are presented, and aim to achieve the same presentation style for your coursework.
