Forecasting aggregate market volatility: The role of good and bad uncertainties

Li Liu and Yudong Wang

Journal of Forecasting, 2021, vol. 40, issue 1, 40-61

Abstract: We decompose economic uncertainty into "good" and "bad" components according to the sign of innovations. Our results indicate that bad uncertainty provides stronger predictive content regarding future market volatility than good uncertainty. The asymmetric models with good and bad uncertainties forecast market volatility in a better way than the symmetric models with overall uncertainty. The combination for asymmetric uncertainty models significantly outperforms the benchmark of autoregression, as well as the combination for symmetric models. The revealed volatility predictability is further demonstrated to be economically significant in the framework of portfolio allocation.

Date: 2021
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Citations: View citations in EconPapers (8)

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https://doi.org/10.1002/for.2694

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:40:y:2021:i:1:p:40-61

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