4m stock seasons
Investors are often tempted by rumors of calendar effects on financial markets. After all, the crashes in 1929 and 1987 both came in October. Maybe it is better to avoid the stock market in October. With so many possible ways to use a calendar to divide up the year, these investors run into issues of multiplicity. Should we divide the year by month, or perhaps by the day of the week? This exercise uses daily stock returns and divides the year by month.
Motivation
(a) Explain why it would be surprising to find stock returns statistically significantly higher year after year in a specific month or on a specific day of the week.
(b) If a stock-market trader repeatedly tests for statistically significant differences in market returns by month or by day of the week every year, what problem is likely to happen?
Method
(c) Describe how to test for a statistically significant difference in average returns on the stock market in 2010 by month?
(d) What assumption of the MRM is likely to be violated in this context?
Mechanics
(e) Perform the analysis, using May as the baseline group. Do you find a statistically significant difference among months in 2010? If so, for which months?
(f) Based on the estimated coefficients in your model, which two months have the largest difference in returns. It is important that May is the baseline category.
Message
(g) Explain how an investor would have been misled by
-statistics in 2010 to identify a statistically significant difference. Use the results for 2011 to support your answer.