Project information for FIN 803

Overview:

The project will connect the classroom material to real world data. The project should apply each of the key concepts covered in class to your chosen series. If you do not cover each concept, this must be discussed with me and approved prior to the due date. You should start on the project as soon as possible and build on it sequentially throughout the course. Please avoid seasonal data.

The term project consists of a written submission. This document provides information on the written presentation requirements, potential topics, and potential data sources.

Important dates:

Topic selection due by March 23 2021 (on second assignment)

Written portion due (not before April 13, 2021. Exact date depends on the final exam schedule).

WRITTEN PRESENTATION:

Written portion should have:

-an abstract

-an introduction that motivates your work and summarizes your main conclusions

-data section

- the frequency of your data

- the time period covered (minimum of 60 data points but the longer the better)

- data source

-analysis and evaluation (this includes descriptive statistics and appropriate tests–that is, you can start on your project now!)

-conclusions

(Be sure to tell us, based on your work, the best way to analyze your data.)

-The University Writing Center offers free analysis of your writing. Other useful online resources include:

https://owl.english.purdue.edu/owl/

and

http://faculty.chicagobooth.edu/john.cochrane/teaching/papers/phd_paper_writing.pdf

Please use proper citation methods. Plagiarism will result in a minimum penalty of zero for the project but harsher penalties will also be considered. If you are uncertain about a citation, please refer to the relevant plagiarism section in the following document “Suggestions for term papers and literature reviews.docx” on Paws/Canvas/Modules/Project and/or an online site such as libguides.usask.ca/citation or the owl site listed above.

Formatting Details:

-the paper should be double spaced, in 12 point font with a maximum of 25 pages. Pages must be numbered. Tables and graphs should be included within your text (these can be in smaller font) rather than at the end of the document. Appendices are also acceptable but be sure to refer to the appendix page number in your text.

-footnotes should be at the bottom of the page rather than at the end of the paper

-include your data on a memory key or provide electronic access to your data

-SAS, MATLAB, EVIEWS, EXCEL (or any software) commands in your text are NOT allowed

-computer output must be labelled and self-explanatory

-all pages must be numbered (yes, I said it twice but hopefully this will lead to more projects with numbered pages). This includes pages with graphs and printouts

-references within the text to graphs, tables or printouts must include a page number

-USE A SPELL CHECKER ON YOUR PAPER!!! (WORD has a spell checker)

Please see “Suggestions for term papers and literature reivews.docx” on Paws/Canvas/Modules/Project for useful information, including journal search strategies, citation requirements, example of plagiarism etc.

Potential Topics:

You may choose any empirical topic that uses and/or extends the techniques we have discussed in class. Your paper must apply every concept covered in class and you are encouraged to extend any one topic. You may replicate an existing study as long as you change it in some way (i.e. different data set or fix an econometric problem that you found). You may not use the same paper for two different courses (i.e. if you do a replication paper for ECON808, you cannot use that same paper for FIN 803). You can use this as a start on your thesis research. Please discuss your topic with me before starting on your paper. Please do not use seasonal data.

Examples:

-you are not constrained to these topics. I encourage you to study something that you find intriguing and may be part of your thesis work.

-bubbles (testing for bubbles)

-kurtosis (or skewness)– does it change over time? What role does it play in financial data–do they predict crashes or bubbles?

-asset pricing with skewness or kurtosis (i.e. extension of the CAPM)

-correlations between world markets—changing over time?

-volatility (I have a very interesting article for our section on Time Varying Variance. The URL is:

http://www.physorg.com/news11164.html)

-VIX (or similar index). What does it say about the predictability/memory of investors?

- characteristics of emerging versus developed market returns (individual or market index)

- other potential topics will be mentioned in class as the associated topic is covered

Potential Data Sources:

I. Canadian Economic and Finance Data

Statistics Canada data:

through the U of S Library

Articles & Databases\CANSIM

Finance (TSX) data:

through the U of S Library

Articles & Databases\CFMRC (1)

II. U.S. Economic and Finance Data

Economic data:

www.economagic.com

http://www.federalreserve.gov/econresdata/default.htm

Finance data:

CRSP (1), (2)

COMPUSTAT (2)

Corporate Social Responsibility data:

    WRDS and Bloomberg

WRDS:

REPRISK, (MSCI formerly KLD)

Bloomberg

Sustainalytics, RobecoSam, Arabesque, IdealRating

III. International

the best source is Datastream

IV. Other:

Academics with data on their websites:

(some academics provide variables used in their research and constructed from CRSP or COMPUSTAT. Examples are book to market, dividend payout ratios, returns in excess of the risk free rate etc)

- Amit Goyal (data from his paper “A comprehensive look at the empirical performance of equity premium prediction”, Goyal, Welch, Review of Financial Studies 2008 21(4), 1455-1508).

Includes economic fundamentals.

http://www.hec.unil.ch/agoyal/

- Kenneth R. French provides the Fama French data library at

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

- Robert Shiller (diverse series from stock market confidence indexes to housing market data)

http://www.econ.yale.edu/~shiller/data.htm

Notes:

(1) Computer Manuals for CRSP, the WRDS Platform and CFMRC are on the class page on PAWS/Canvas/Modules/Supplemental Material.

(2) CRSP and COMPUSTAT may be accessed through WRDS (Wharton Research Data Services). You need a WRDS account which you apply for at https://wrds-web.wharton.upenn.edu. Once you apply, WRDS sends it to the U of S IT for approval.

(3) Computer Manuals for SAS are on the class page at PAWS/Canvas/Modules/SAS.