SINGAPORE MANAGEMENT UNIVERSITY
School of Economics
Econ107 Introduction to Econometrics
Group Project
Due: 4pm, Thursday, 30 March 2016
General Guidelines
You can choose one of the two projects which are described below. For each topic, data are provided. Analyze the data, provide motivation for your econometric model, discuss the diagnostics and your empirical conclusions. Compare alternative formulations of the models and assess their pros and cons.
Your report should not be more than 10 pages, inclusive of any tabulated results. (You need to save this word document and then open it in a separate window before you can access the datasets).
There will be no presentation.
Topic A: Predicting stock returns
What are the variables that can predict stock returns? Dataset Predict_Data (data) provides quarterly NYSE/AMEX value-weighted index log-return (1926–2002) from the Center for Research in Security Prices (CRSP), the risk free rate, the dividend–price ratio, the earnings–price ratio, the three-month T-bill rate and the long-short yield spread. Construct an econometric model to predict the excess return (which is the log return minus the risk free rate) using the lagged predictors. Provide economic justification, econometric diagnostics, and model selection justifications. Discuss practical implications of your findings.
Regarding the data, following Campbell and Shiller (1988), the dividend–price ratio is computed as dividends over the past year divided by the current price, and the earnings–price ratio is computed as a moving average of earnings over the past ten years divided by the current price. Following the tradition, the predictor variables are all in logs. To compute excess return s of stocks over a risk-free return, we use the three- month T-bill rate. Following Fama and French (1989), the long yield used in computing the yield spread is Moody’s seasoned Aaa corporate bond yield. The short rate is the one-month T-bill rate.
Topic B: Month-of-the-year effect
Capital market efficiency has been a popular research topic. Studies in time efficiency have found month-of-the-year effect, that is, stock returns in certain month of the year are different from the other months. Using data set DJIA1928-2003 (data) analyze, via regression models, the month-of-the-year effect in the Dow-Jones Industrial Average Index. The data were obtained from yahoo.finance. Examine the robustness of your results with respect to different sample periods. Discuss practical implications of your findings.