Objective research and reviews to aid investing decisions
Beta measures the volatility of a stock with respect to the broad market. However, after accounting for the value premium and size effect, the generally accepted beta has no predictive power for future stock returns. Is that all there is to beta? In their May 2007 paper entitled "Long-Term and Short-Term Market Betas in Securities Prices", Gerard Hoberg and Ivo Welch decompose beta into short-term (the last 12 months) and long-term (one to ten years ago) components and investigate whether these components can separately forecast stock returns. Using daily stock prices and financial data for a large sample of companies (an average of over 3,300 firms per month) over the period 1962-2005, they find that:
The following figure, taken from the paper, depicts the intervals the authors employ to calculate short-term and long-term betas, as well as other factors used in the study. The authors update portfolios and statistics monthly using the latest available data. Red boxes mark periods for which they assume, to avoid any look-ahead bias, that data is not yet available for updates. Study results are not notably sensitive to the exact break point between the short-term and long-term beta intervals.

The following table, also from the paper, shows future annualized stock returns for different groups of stocks sorted by both short-term beta and long-term beta. For example, the group of stocks in both the 20% of stocks with the lowest (highest) short-term beta and the 20% of stocks with the highest (lowest) long-term beta has an annualized return of 12.7% (5.2%). A zero-cost portfolio that is long the former and short the latter generates an annual return of 5.5%, excluding transaction costs. Note that the long-term beta effect varies more consistently than the short-term effect.

In summary, stock betas change over time, and strategies that track these changes with high-frequency data can generate abnormal returns. Stocks with long-term high (low) but recently decreasing (increasing) betas are buys (sells).
One plausible explanation for these results is that investors respond slowly to changes in stock betas.
For related research, see Blog Synthesis: Volatility Effects.