Stock market oscillations during the corona crash: The role of fear and uncertainty

Štefan Lyócsa and Peter Molnár

Finance Research Letters, 2020, vol. 36, issue C

Abstract: Stock market returns are difficult to predict, but crisis periods tend to be an exception to this rule. We document that, during the event period from November 2019 to May 2020 with the S&P 500 market index, the corona crash was not an exception. We use a nonlinear autoregressive model, where the autoregressive coefficient is governed by i) abnormal Google searches related to COVID-19 and ii) realized volatility. We find that the autoregressive coefficient was negative over the whole event period, but as market uncertainty and attention to virus increased, the magnitude of the autoregressive coefficient increased as well.

Keywords: Coronavirus; Return persistence; LSTAR; Google searches; Volatility; COVID-19 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:36:y:2020:i:c:s1544612320309818

DOI: 10.1016/j.frl.2020.101707

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