Monthly Beta Forecasting with Low‐, Medium‐ and High‐Frequency Stock Returns

Abstract

Generating one-month-ahead systematic (beta) risk forecasts is common place in financial management. This paper evaluates the accuracy of these beta forecasts in three return measurement settings; monthly, daily and 30 minutes. It is found that the popular Fama-MacBeth beta from 5 years of monthly returns generates the most accurate beta forecast among estimators based on monthly returns. A realized beta estimator from daily returns over the prior year, generates the most accurate beta forecast among estimators based on daily returns. A realized beta estimator from 30 minute returns over the prior 2 months, generates the most accurate beta forecast among estimators based on 30 minute returns. In environments where low, medium and high frequency returns are accurately available, beta forecasting with low frequency returns are the least accurate and beta forecasting with high frequency returns are the most accurate. The improvements in precision of the beta forecasts are demonstrated in portfolio optimization for a targeted beta exposure.

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