Empirical Finance Spring II 2023 Assignment 2
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Empirical Finance Spring II 2023
Assignment 2
Q1. (50pts) Event study
We observed the Carey stock price movements over the last five days. Events occurred on day 2 and 4.
Day 1 2 3 4 5 |
Event 0 1 0 1 0 Price 1.00 1.30 1.25 1.02 1.01 |
We go through steps for computing the impact of “Event” on the Carey stocks.
1. (10pts) Compute daily log returns (4 samples) and their sample average
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
2. (10pts) What is the average daily return only on event days?
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
3. (10pts) Is the following statement true or false?
“Stock returns are positive on event days.”
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
4. (10pts) Is the following statement true or false?
“Stock returns fluctuate more during event days.”
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
5. (10pts) We now know that earnings announcements were released in day 2 and 4. Only on day 2, earnings were positive. Is the following statement true or false?
“Stock return is higher on a positive earning announcement day.”
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
Q2. (100pts) Event study - coding exercise
You will find 2 stock returns (labeled “A” and “B” ) and 3 factors (labeled “MKT, FMT, RF”) in “Q2assignment2.xlsx.” Note that MKT is the market factor (excess market return), FMT is the farming-minus-technology factor, and RF is the risk-free rate, respectively.
1. (10pts) Construct excess return for stock A and B, respectively. Estimate the CAPM regression and report the estimated coefficient and adjusted R2 .
2. (10pts) Augment the CAPM regression by including the FMT factor. Call this FAC- TOR regression. Report the estimated coefficients (on MKT and FMT) and adjusted R2 . Based on the coefficient estimates, discuss the characteristics of A and B stock.
3. (20pts) Conduct sentiment analysis on “Articles1” and “Articles2” in “Q2assignment2.xlsx.” For this, you should rely on python codes that I uploaded in canvas. You will create a vector (length 28) with sentiment scores (sentiment score is set to zero if there is no article released on that day). Report the mean of two sentiment-score vectors .
4. (30pts) Propose regression models that predict excess returns and report the estimation results. Your goal is to generate R2 values at least greater than 0.9 for both A and B stocks.
(Grading instruction) Full 30 pts for the most parsimonious model. 10 pts off if complicated. 0 pts if R2 is less than 0.9.
5. (30pts) We are forecasting returns for A and B stocks on day 31. On day 31, the following information is provided: MKT31 = 1; FMT31 = 0.5; ; Article 1 is “Farmers are adapting to the impacts of climate change by implementing new technologies and sustainable practices”; Article 2 is “Technology has the power to connect us, but is it also driving us apart?” Our predictions for stock returns are around 1 .4 for A and 0.6 for B. Your goal is to explain how we obtained these predictions.
(Grading instruction) Points are only given to answers with explanation. No partial credit allowed.
Q3. (50pts) Investment
You can spend up to $10,000 in investing. Your choice would be AngloGold Ashanti, Kala Pharmaceuticals, Merck, Tesla, Walmart. The minimum requirement is that you have to spend at least $1,000 on each stock. For concreteness, let’s take the adjusted-close price on April 19 for example. You have to spend at least these amounts to meet the minimum requirement for each stock. You subsequently invest the remaining amount into a stock that you anticipate to be profitable. Denote the share by wAU , wKALA , wMRK , wTSLA , wWMT .
Symbol |
Stock |
Price |
Share |
Total |
AU |
AngloGold Ashanti |
PAU = 26.14 |
39 |
1019.5 |
KALA |
Kala Pharmaceuticals |
PKALA = 15.68 |
64 |
1003.5 |
MRK |
Merck |
PMRK = 114.13 |
9 |
1027.2 |
TSLA |
Tesla |
PTSLA = 180.59 |
6 |
1083.5 |
WMT |
Walmart |
PWMT = 150.01 |
7 |
1050.1 |
The objective is to choose wAU , wKALA , wMRK , wTSLA , wWMT such that
Pp = wAU PAU + wKALA PKALA + wMRK PMRK + wTSLA PTSLA + wWMT PWMT ,
P = wAU PU + wKALA PALA + wMRK PRK + wTSLA PSLA + wWMT PMT the monthly holding period return
HPR = − 1
is maximized (note that Pp cannot exceed $10,000).
Explain how much you would buy each stock, that is, how you would choose wAU , wKALA , wMRK , wTSLA , wWMT . Your answer should be based on your analysis of HPR from the historical data. Thus, what only matters is HPR, that is, what’s your monthly return on investment, not about Pp or P . Make sure to provide convincing argument. I want to see how you reached that conclusion.
(Grading instruction) I am asking you to use your imagination + data analysis skill you’ve learned so far in class because this is a forecasting exercise. Only 1/3 of students will get full points for this question. The rest will not get higher than 20 pts. I will pick a few groups for class presentation.
Q4. (0pts) Reading
Read Can ChatGPT Decipher Fespeak? and summarize in four paragraphs. I will take off 20 pts if the summary is bad.
2023-05-18