Abstract
ABSTRACT This study comparatively evaluated the forecasting performance of a constant beta and two time-varying beta process specifications. Returns for 23 stocks were forecasted for several horizons in 2019–2020. The autoregressive and random walk betas showed superior forecasting performance before and during the COVID-19 pandemic, respectively. In a Diebold–Mariano test, the constant beta specification never dominated both time-varying beta models. Beta specification type should be considered when forecasting based on capital asset pricing or market models, particularly during crises. Results of rolling regressions based on arbitrage pricing theory considering other risk factors suggest time-varying systematic risk factors beyond market risks.
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