Learning, slowly unfolding disasters, and asset prices

Mohammad Ghaderi, Mete Kilic and Sang Byung Seo

Journal of Financial Economics, 2022, vol. 143, issue 1, 527-549

Abstract: We develop a model that generates slowly unfolding disasters not only in the macroeconomy but also in financial markets. In our model, investors cannot exactly distinguish whether the economy is experiencing a mild/temporary downturn or is on the verge of a severe/prolonged disaster. Due to imperfect information, disaster periods are not fully identified by investors ex ante. Bayesian learning induces equity prices to gradually react to persistent consumption declines, which plays a critical role in explaining the VIX, variance risk premium, and put-protected portfolio returns. We show that our model can rationalize the market patterns of recent major crises, such as the dot-com bubble burst, Great Recession, and COVID-19 crisis, through investors' belief channel.

Keywords: Bayesian learning; Economic disasters; Market crises; VIX; Put-protected portfolios (search for similar items in EconPapers)
JEL-codes: E20 G12 G13 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:143:y:2022:i:1:p:527-549

DOI: 10.1016/j.jfineco.2021.05.030

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