Information uncertainty and the momentum effect

I identify simple proxies for uncertainty and attempt to determine if the returns to a momentum strategy vary with these proxies. The proxies identified include the stock’s daily 6-month historical return volatility, the magnitude of alpha in a 6-month historical regression of the stock’s daily returns on the Fama-French factors and the (1-R2) value of the regression. The exposures to each of the risk factors were also tested as possible proxies for uncertainty related to the factors. Using daily stock return data from CRSP from 1926 to 2006, stocks are first sorted into quintiles based on these proxies. A momentum strategy is pursued in each uncertainty quintile by taking long and short positions in the deciles with the highest and lowest past returns respectively over a 6 month ranking period, and holding these positions for a further 6 months. It was found that with greater volatility, momentum returns are higher. Similarly, as the magnitude of alphas rises, momentum returns increase. These results support the hypothesis that greater uncertainty contributes to momentum. Finally, momentum returns are higher with larger exposures to the market factor, but show no statistically significant trends with the size and book-to-market factors. When (1-R2) values increase however, momentum returns decline, in contradiction with the hypothesis that greater uncertainty contributes to momentum. Stocks were also sorted into industry groups according to Kenneth French’s twelve industry portfolio classification. The industries were ranked according to the volatility of their daily returns and the returns to a momentum strategy within the industry. There was no clear relationship between the volatility of daily returns and momentum returns of the twelve industry portfolios