Econometric Methods

SUMMATIVE ASSIGNMENT

For this assignment you must complete either Project A or Project B.


Project A:

Use the Dataset_#mutual.xls corresponding to your Z#####.

To complete this assignment, you will need the returns of the mutual fund # and the factors in the
Dataset_#mutual.xls.
The variable names and the descriptions of the variables are as follows:

Variable Names Descriptions

MutualFund1_#_ret Returns of the mutual fund 1

MutualFund2_#_ret Returns of the mutual fund 2

CRSP index Market Index

1-month T-Bill Risk free rate

ExRm CRSP index minus 1-month T-Bill

SMB Small (market capitalization) minus big factor

HML High (book-to-market ratio) minus low factor

MoM Momentum factor (long prior-month winners and short prior-month
losers)

TradedLIQ Traded liquidity factor

Question
: (a). Estimate an appropriate CAPM model describing the return of the mutual funds as a function of some or all factors above: CRSP index, 1-month T-Bill , ExRm , SMB , HML , MoM and TradedLIQ. Carry out and report the necessary statistical tests to justify the choice of your specification. Discuss any found issues with respect to omitted variable bias.

(b). Compare the performances of the two funds and the exposure of the portfolios to different risk factors by comparing relevant coefficients (such as the intercept and slopes) of the models through appropriate tests.

The following references will be useful when you interpret and compare the coefficients.

Fama, Eugene F.; French, Kenneth R. (1993). “Common Risk Factors in the Returns on Stocks and Bonds”. Journal of Financial Economics 33 (1): 3–56

Fama, Eugene F.; French, Kenneth R. (1992). “The Cross-Section of Expected Stock Returns”. Journal of Finance 47 (2)

Pastor, Lubos & Stambaugh, Robert F., 2003. “Liquidity Risk and Expected Stock Returns,” Journal of Political Economy, University of Chicago Press, vol. 111(3)

End of Project A

Project B:

Use the Dataset_#fish.xls corresponding to your Z#####.

In this project you will estimate the demand for Cod (a saltwater fish). To complete this assignment, you will use the 300 weekly observations on the quantity of Cod purchased, the price of Cod, the price of Chicken, the price of Beef, Weekly Income, the average body mass index (BMI), and the average water temperature in the North Atlantic Ocean (where Cod are cultivated). You will find these 300 observations in the
Dataset_#fish.xls
file
.

Question:

Produce a scatterplot of price and quantity demanded of Cod. Set aside the variable “average water temperature.” Estimate the household demand function for Cod as a function of the price of Cod, Weekly Income, the price of Beef, and some or all of the other provided variables. Carry out and report the necessary statistical tests to choose your specification. Report the estimated own price elasticity, estimated income elasticity of demand, and the cross-price elasticity of demand with Beef. Discuss any found issues with respect to omitted variable bias.
Suppose the price of Cod is determined by simultaneous solution of the market supply and demand of Cod. Discuss how this is problematic for your estimate of the own price of elasticity for Cod. Use the variable “average water temperature” to obtain a new estimate of the own price elasticity of Cod. Evaluate whether “average water temperature” is an appropriate instrument.
End of Project B

Overall word limit, 1000 words maximum.

The word count should:

Include all the text, including title, preface, introduction, in-text citations, quotations, footnotes and any other item not specifically excluded below.
Exclude diagrams, tables (including tables/lists of contents and figures), equations, references and appendices. However, it is not appropriate to use diagrams or tables merely as a way of circumventing the word limit. If a student uses a table or figure as a means of presenting his/her own words, then this is included in the word count.
Examiners will stop reading once the word limit has been reached, and work beyond this point will not be assessed. Checks of word counts will be carried out on submitted work, including any assignments or dissertations/business projects that appear to be clearly over-length. Checks may take place manually and/or with the aid of the word count provided via an electronic submission. Where a student has intentionally misrepresented their word count, the School may treat this as an offence under Section IV of the General Regulations of the University. Extreme cases may be viewed as dishonest practice under Section IV, 5 (a) (x) of the General Regulations.

Very occasionally it may be appropriate to present, in an appendix, material which does not properly belong in the main body of the assessment but which some students wish to provide for the sake of completeness. Any appendices will not have a role in the assessment– examiners are under no obligation to read appendices and they do not form part of the word count. Material that students wish to be assessed should always be included in the main body of the text.

YOUR COMPLETED ASSIGNMENT MUST BE SUBMITTED TO DUO NO LATER THAN 11.59AM ON 13 DECEMBER 2019.

MARKING GUIDELINES

Performance in the summative assessment for this module is judged against the following criteria:

Relevance to question
Organisation, structure and presentation
Depth of understanding
Analysis and discussion
Use of sources and referencing
Overall conclusions
Students should use the template on DUO for their assignments.

The word count should include all the text (plus endnotes and footnotes), but exclude diagrams, tables, bibliography, references and appendices. Guidance on referencing can be found in your Assessment handbook under ‘Things you Need to Know’ on DUO.

The assignment which you submit on-line should INCLUDE all appendices

PLAGIARISM and COLLUSION

Students suspected of plagiarism, either of published work or work from unpublished sources, including the work of other students, or of collusion will be dealt with according to Business School and University guidelines.

Your assignment will be put through the plagiarism detection service.

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