Posted: December 6th, 2022

EC3114 Financial Economics I

EC3114 Financial Economics I
Autumn 2022
Coursework
Instructions
The Excel File named “Data Set for Autumn 2022 Coursework” contains the adjusted closing prices for 15 big US companies at the beginning of the month, the monthly market risk free rate and the monthly return on the market portfolio. The risk free rate and market return data come from Kenneth French’s website. The market portfolio is a huge portfolio constructed with all assets traded on the US stock exchanges.
The data runs from May 2016 to September 2019 – there are 41 closing prices for the firms, and 40 data points for the risk free rate and the market rate. When you calculate returns, you will obviously have 40 returns to match the 40 market returns. We avoid data after September 2019 to exclude the various turbulences caused by the pandemic and the war in Eastern Europe.
For the Coursework, you are required to:
i) estimate the single index model for each of the firms (i.e., 15 estimations)
ii) form an equally weighted portfolio with the 15 firms and estimate the single index model for the portfolio.
Provide all the summary statistics for all firms, market portfolio and equally weighted portfolio; and for the single index models. Report your results in a nicely drawn table (Do not copy and paste the tables from Excel).
Interpret the R-square for the single index model for individual firms, and the R-square for the single index model for the equally weighted portfolio. Compare and contrast the R-square.
Discuss what happens to idiosyncratic risk when you move from investment in an individual firm to an equally weighted portfolio.

Further, do the following:
iii) Run a second-pass regression, with the 15 betas estimated from the single index model as an independent variable. Your dependent variable should be the mean of the excess return of each firm. (That is, you will have 15 mean excess returns, and 15 corresponding betas).
Produce a scatter plot (without a line) of beta vs mean excess return. Now, report the regression result, and interpret your results. What should the intercept be? What is the coefficient of beta from this regression, and what should we value should we expect it to be? What are you estimating here?

All these analyses can be done in Excel, and I highly recommend it. (You are welcome to use any other software or programme that you are familiar with).
Make sure that the written report is your own individual work and that you do not use external help. Do not copy from anyone or anywhere. Do not solicit someone else to write your assignment. You should include a reference section at the end of the essay (Harvard style referencing), and use an appropriate style of referencing to write it out, write also in English style and not American one. Wikipedia is not an acceptable source of reference and you will be penalised for including it in the reference section. Please write clearly, and avoid long sentences that confuse the reader. Structure your essay so that it is presentable and flows nicely, with clearly labelled tables and charts (if any). Do not simply copy and paste charts and tables form Excel and other programmes. Re-structure them, and rewrite your tables in Word. Clearly explain methodologies and functions you use in Excel or other software. Explain what you are doing, and what your results say.
Write a conclusion summarising what you did, and how your calculations prove or disprove the evidence we have seen so far.
Keep the essay in the 1,200 word limit excluding charts and tables. (Do not upload the raw data in the essay).
Submit the essay in Turnitin. (There is a penalty for late submission). Start early as there are many calculations to be performed. Please avoid waiting till the last minute to submit, as this is exactly when things tend to go wrong.

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