Detailed Brief for Individual Assessment
Assignment Title: Individual report —
regression analysis in practice Description of the assignment: Choose a company listed in a major stock exchange (e.g. London, Frankfurt or New York). Take a sample of ten years of its stock returns, using monthly data. This can be downloaded from Yahoo Finance or Investing.com. Build a multiple regression model to explore the relationship between the stock returns and different factors.
Your independent variables should include any factor that you deem relevant for your stock. There are several factor-based models in the literature, which you should refer to. Factors should be chosen amongst those for which there are factor returns available online, such as:
• The Fama-French factors
• The q-factors model Run your regression model and interpret the results obtained based on the taught material. Additional consideration
You will be marked based on the written work submitted. The coursework is designed to apply regression analysis in practice, so you should pay attention to both applying the correct techniques and to ensure that you carefully interpret the results, and critically evaluate their relation to your expectations and the prediction of financial and economic theory. You should EViews to run your regressions. Reports should not exceed 1,500 words (+/- 10%) excluding tables/figures and references.
1) A Word document or PDF file
2) The excel file containing your dataset Sample structure of your report:
1. Introduction
Introduce your company and discuss the question you are trying to answer with your empirical project.
2. Theory and Hypotheses
Discuss the asset pricing theory underlying your model and state the hypotheses you are going to test.
3. Empirical Model and Data Present the empirical model you are using to test your hypotheses.
Specify the econometric model you will estimate. Which factors did you chose to include in the model? What sign do you expect each coefficient to have, and what is the interpretation of the coefficients? This is where you can also present some data about your company, in order to justify the factors, you have chosen.
4. Potential issues with your regression
In this section you discuss the potential issues with your regression. You should focus on those issues discussed in class:
– Model specification issues should be addressed: Are there any important omitted variables? Could there be issues with the functional form of your variables (e.g. logs, squares)?
Do you plan to show different model specification in the next section?
– You should also discuss the potential issues of autocorrelation, heteroskedasticity and multicollinearity. This should be tested and corrected for if the problems exists, or describe how you would have corrected the model had you found a problem.
5. Results
This is where you present your key estimation results. The interpretation of the results should be careful and comprehensive. Focus on both the statistical aspects (e.g. are coefficients significant) and their financial interpretation (e.g. are the coefficient the size and sign you expected?)
6. Conclusion
Elaborate some conclusions about your results taking in consideration the research goals established in the outset.
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