BAFI/FNCE 429: Investment Management
Group Assignment III
Spring 2024
Instructions
>The general instructions in the course syllabus are applied for this group assignment and you are required to follow them.
>The due date for this group assignment is 11:59pm on Friday, March 29th, 2024. Please upload 1) a PDF file of your group report with answers to the list of questions below and 2) an Excel workbook that shows your work to the Canvas. For both, make sure that all of your group members’ names and CWRU IDs and your group number are shown on the cover page of the report and first spreadsheet of the workbook. For each, also make sure that only one copy is submitted since duplicates make confusion and delay in grading.
Introduction
In this group assignment, first, you will test asset pricing models with the Fama-MacBeth (FM) two-stage regression methodology, which we study in Lecture 6. The four asset pricing models to be tested are the CAPM, Fama-French three-factor model (FF3M) and five-factor model (FF5M), and an extension of the FF3M with a Pastor-Stambaugh (PS) liquidity factor. Second, as an application of the tested asset pricing models, you will evaluate the performances of a momentum-based trading strategy and an illiquidity-based trading strategy. Finally, you will answer questions related to your group’s managed portfolio in the Stock|Trak trading game, which serves as the first report. The total points of this group assignment are 46 points.
Data
For empirical analyses, the entire sample period starts at January, 1970 and ends at December, 2021, i.e., 52 years. The Excel spreadsheet “GA3_Data.xlsx” contains variables with monthly frequency and they are the rate of returns in percentages. The detailed information about these variables is provided below.
1. Risk factors and risk-free rate:
> FF’s five factors and short-term (i.e., one-month to maturity) U.S. T-bill rate are MKTRF, SMB, HML, RMW, CMA, and RF, respectively.
> Pastor-Stambaugh (PS) liquidity factor is PS_VWF.
2. Test assets:
> 5x5 value-weighted FF’s Size- and BM-sorted portfolios, where Size is defined as price times the number of shares outstanding and BM is the book-to-market ratio.
3. Returns of two trading strategies:
> MOM_RET is the value-weighted monthly return of a momentum-based trading strategy.
> ILLIQ_RET is the value-weighted monthly return of an illiquidity-based trading strategy.
List of Questions:
1. (6pts) Using 5x5 FF Size- and BM-sorted portfolios as test assets, run FM regressions to test the CAPM and FF3M, separately, where betas are assumed to be constant over time. Tabulate monthly and annualized prices of the factor risks and their t-statistics for both asset pricing models. Under the CAPM, is the market risk priced in the cross-section of test portfolios? Under the FF3M, which risks are priced in the cross-section?
2. (6tps) Now add the PS liquidity factor to the FF3M and call this extended asset pricing model FF3M+PS. Using 5x5 FF Size- and BM-sorted portfolios as test assets, run FM regressions to test the FF3M+PS and FF5M, separately, where betas are assumed to be constant over time. Tabulate monthly and annualized prices of the factor risks and their t-statistics for both asset pricing models. In each of the two tests, which risks are priced in the cross-section of test portfolios?
In Questions 3 and 4, as an application of the tested asset pricing models, you analyze the performances of a momentum-based trading strategy (whose return is MOMRET below) and an illiquidity-based trading strategy (whose return is ILLIQRET below), respectively.
3. (6pts) Suppose that you constructed a momentum-based trading strategy by going long
(=buy) for winner stocks and by going short (=sell) for loser stocks. (We will study the details on the momentum-based trading strategy in the second half of the semester. For now, let’s take it for granted.) Run the following time-series regression: In month t,
MOMRETt = a + βMKTRFMKTRFt + βSMBSMBt + βHMLHMLt
+βRMWRMwt + βCMA CMAt + βpSpSt + et,
where MOMRET t is the return of the constructed momentum-based trading strategy. Tabulate the alpha, slope coefficients of MKTRF, SMB, HML, RMW, CMA, and PS, and their t-statistics. At the 5% level, is the alpha statistically significant? Which betas are statistically significant? As in Q8 of Group Assignment 1, draw conclusions based on these alpha and betas.
4. (6pts) Suppose that you constructed an illiquidity-based trading strategy by going long (=buy) for illiquid stocks and by going short (=sell) for liquid stocks. (We will study the details on the illiquidity-based trading strategy in Lecture 7. For now, let’s take it for granted.) Run the following time-series regression: In month t,
ILLIQRETt = a + βMKTRFMKTRFt + βSMBSMBt + βHMLHMLt
+βRMWRMwt + βCMACMAt + βpSpSt + et,
where ILLIQRETt is the return of the constructed illiquidity-based trading strategy. Tabulate the alpha, slope coefficients of MKTRF, SMB, HML, RMW, CMA, and PS, and their t-statistics. At the 5% level, is the alpha statistically significant? Which betas are statistically significant? As in Q8 of Group Assignment 1, draw conclusions based on these alpha and betas.
The Questions 5 to 7 are related to your managed portfolio in the Stock|Trak trading game.
5. (8pts) In the inception of the Stock|Trak trading game, the two initial requirements were
imposed: 1) your portfolio must contain at least 10 stocks by the close of stock markets on Feb., 14th, 2024 and 2) your portfolio must contain at least 20 stocks and at least 80% of the initial cash (=$5,000,000) must be invested in those stocks by Feb., 23th, 2024, and these two conditions must be met at any time point afterward. Present the proof showing that your team satisfies the imposed requirements 1) and 2).
6. (9pts) Using the information available until March 22th, Friday, 2024 (about seven weeks
after the inception of the Stock|Trak trading game), tabulate separately the three Stock|Trak- related Excel spreadsheets: Tradelog, Positions, and Weekly value and returns in Tradelog.xlsx, which have been maintained by your team.
7. (5pts) Based on your answers in Questions 5 and 6, explain the investment philosophy and/or rationale behind your team’s trading strategies and/or your team’s stock selection (with a maximum of 300 words). Feel free to include one chart and one graph at max if they are necessary.
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