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Predicting Systematic Risk With Macroeconomic And Financial Variables

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  • Tolga Cenesizoglu
  • Denada Ibrushi

Abstract

We analyze the predictive power of several macroeconomic and financial indicators in forecasting quarterly realized betas of 30 industry and 25 size and book‐to‐market portfolios. We model realized betas as autoregressive processes of order 1 and include lagged values of macroeconomic and financial indicators as exogenous predictor variables. In out‐of‐sample forecasting exercises, forecasts using bond market variables as exogenous predictors statistically outperform forecasts from a benchmark model without any exogenous predictors. These forecasts based on bond market variables also economically outperform benchmark forecasts by providing better performance in hedging the market risk of portfolios.

Suggested Citation

  • Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    • Handle: RePEc:bla:jfnres:v:43:y:2020:i:3:p:649-673
    DOI: 10.1111/jfir.12221
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