Finance Project - Risk Management

Final Project The final project is another important component of this course. For this final project, you must pick an empirical finance topic, gather the required data, specify your methodology, perform quantitative analyses on the data and interpret the results of these analyses, and formulate a conclusion regarding the issue at hand. Marks on the final project will be based on modelling (30%), quantitative (40%), and presentation (30%) skills demonstrated. Project topics You may choose your own topic for your project, but you may also consider choosing a topic from the following list of topics:

1. Model and test weak-form information efficiency in one or more Canadian stock markets.  

2. Test to determine which model—the Capital Asset Pricing Model (CAPM) or Arbitrage Pricing Theory (APT)—is superior for determining returns on risky assets in Canadian markets.  

3. Measure, model, and forecast the volatility of bond returns in Canada.  

4. Model and test the determinants of bond credit ratings used by ratings agencies such as Moody’s.  

5. Model the long-term relationship between prices and Canada-US exchange rates.  

6. Determine the optimal hedge ratio for a spot position in cattle or oil markets.  

7. Test technical trading rules to determine which of them makes the most money.  

8. Test the hypothesis that earnings or dividend announcements have no effect on stock prices.  

9. Test spot and futures markets to determine which reacts more rapidly to news.  

10. Forecast the correlation between the TSX index and the NASDAQ index.  

11. Model and test the effect of a firm’s capital structure decisions (i.e., debt-equity weight) on share returns.

Contact the academic expert for this course as early as possible to discuss your choice of final project topic and possible data sources. Your final project topic must be approved by the academic expert before you start working on it. Project tasks

1. Pick a project topic.  

2. Contact the academic expert for topic approval.  

3. Conduct a literature review that examines at least two, and at most five, articles. For each article, write a one-paragraph summary and a one-paragraph critical review, then explain how the article relates to the topic you have chosen for your final project.  

4. Obtain data (contact the Student Support Centre if you encounter problems accessing or obtaining data).  

5. Analyze the data, according to these guidelines:  

. If your study involves structural analyses of cross-sectional, time-series, or panel data, perform the following tasks:  

1. Define the null hypotheses.

1. Run the regression(s).

1. Discuss how well the model fits by using goodness-of-fit measures.

1. Check for violations:  

4. heteroscedasticity

4. iid residuals

4. autocorrelation

4. non-normality

4. multicollinearity

4. linear functional form  

. Test the null hypotheses.  

· If your study involves building time-series (ARIMA) models, perform the following tasks:  

. Test for non-stationarity in the time series.

. Use the Box-Jenkins approach to build ARIMA models with an in-sample.

. Obtain forecasts from the ARIMA models.

. Choose the best model based on information criteria.  

· Write your project report, which should include all of these elements:  

· title page—List your name, student ID number, project title, and submission date.  

· introduction—Provide a broad overview of your project and what you hope to learn from it.  

· literature review—Summarize and critically review chosen articles.  

· data descriptions—Describe what, where, and how you have obtained data or transformed them, and the time periods involved.  

· methodology—Outline whether you are using structural or time-series models, and specify models (equations) used.  

· results—Discuss the regression results obtained in EViews, and whether or not they are favourable to your original hypotheses.  

· conclusion—Briefly describe (one to two paragraphs) what you have learned from your analyses.  

· references—Provide full bibliographical information in APA format, including the articles in your literature review.  

· appendices—Include discussions, tables, or graphs that do not contribute directly to the “meat” of your project write-up, but might nevertheless be of interest to your audience (i.e., your marker).

Use Microsoft Word or other compatible word-processing software to prepare your finished assignment. You will be using EViews extensively for your project, so your project write-upmust include descriptions of analyses performed using this software package, and your conclusions must refer to these results. Submit any EViews file(s) used for your analyses with your MSWord file.

Assignment Submission - Final Project

Submit all assignments in a format that is compatible with Microsoft Office. If you are unsure about whether your files are compatible, check with your instructor or contact the Student Support Centre.

When naming your assignment file for submission, be sure to include your last name, the course abbreviation and number, and the assignment number in the file name. Use an underscore, not spaces, between characters. Follow this example as a guide: 

Assignment Instructions:

As stated above, use Microsoft Word or other MS Office-compatible word-processing software to prepare your finished assignment. Your project write-up must include descriptions of analyses performed using the EViews software package, and your conclusions must refer to these results. Submit any EViews file(s) used for your analyses with your MSWord file.

Marks on the final project are based on modelling (30%), quantitative (40%), and presentation (30%) skills demonstrated.