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.

摘要

本研究比较评估了一个常数 beta 和两个随时间变化的 beta 过程规范的预测性能。在 2019-2020 年的几个阶段预测了 23 只股票的回报。自回归和随机游走 beta 分别在 COVID-19 大流行之前和期间显示出优异的预测性能。在 Diebold-Mariano 检验中，常数 beta 规范从未支配过两个时变 beta 模型。在基于资本资产定价或市场模型进行预测时，尤其是在危机期间，应考虑 Beta 规范类型。考虑其他风险因素的基于套利定价理论的滚动回归结果表明，时变系统风险因素超出了市场风险。