1. Violating which of the classical linear regression model assumption will lead to a biased OLS estimator? [1] 2. In a system of equations given below, Y’s are endogenous while X’s are exogenous. Which of the equation is just identified? Explain. [2] 3. State one advantage of using a Vector Autoregression (VAR) model. [1] 4. In the following VAR model, write down the null hypothesis for the Granger causality test of ݕଶdoes not Granger cause ݕଵ? [1] 5. In a VAR model, name the method of analysing the proportion of the movements in the dependent variables that are due to their “own” shocks, versus shocks to the other variables. [1] Section B. Answer ALL questions (35 marks) Question B1 (20 marks) In the paper on the “Overreaction Hypothesis and the UK Stock Market” by Clare and Thomas (1995), the authors employed monthly UK stock returns from January 1955 to December 1990 on all firms traded on the London Stock exchange to run a regression ttDeR, (B1-1) where WtpLtptDRRR,,,, Rdenotes the monthly average excess return over the stock market and tdenotes the 18 independent tracking periods. LtpR, and WtpR, are the loser’s and winner’s portfolio returns respectively. (a)State the overreaction hypothesis and how can one use regression (B1-1) to test for the overreaction hypothesis? [2] (b) Suppose the loser stocks are generally more risky, explain the drawback of using regression (B1-1) when testing the overreaction hypothesis. How would you correct for it? [2] Using the data employed by Clare and Thomas (1995), suppose you are interested in analyzing whether there are quarterly return differences between the loser and winner portfolios. You estimated the following regression by OLS: tttttDeQQQR,33,22,11, (B1-2) YYYXXuYYXuYYu10123341521201321230123 ttttttttttttttttuyyyyyyyuyyyyyyy23222312122222121122211212021321231112212211112121111101
2020 Nov ECON339 Spring Session/T3 Wollongong/PSB Academy Page 3 of 3 where WtpLtptDRRR,,,, R denotes monthly excess return over the stock market, iQ is a dummy variable for i=1, 2 and 3 such that 1iQif return is in the i-th quarter and 0 otherwise. The result is 680.0RSS,03.0ˆ,005.0ˆ,01.0ˆ,02.0ˆ321
(c)What is the difference in the mean return between the first and second quarter? [1]
(d)Now define a fourth quarter dummy as tQ,41 if return is in the fourth quarter and 0 otherwise. Suppose you drop the first quarter dummy from regression (B1-2) and include the fourth quarter dummy instead such that tttttDeQQQR,33,22,44,. (B1-3) What will the estimated value of 324,,,now be?
[4] (e)Can one run the following regression titiitDuQR41,, (B1-5) to analyse whether there are quarterly return differences between the loser and winner portfolio? Explain.