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Investors’ uncertainty and forecasting stock market volatility
This article examines whether incorporating investors’ uncertainty, as captured by the conditional volatility of sentiment, can help forecasting volatility of stock markets. In this regard, using the Markov-switching multifractal (MSM) model, we find that investors’ uncertainty can substantially increase the accuracy of the forecasts of stock market volatility according to the forecast encompassing test. We further provide evidence that the MSM outperforms the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model.
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Journal
Journal of Behavioral FinanceIssue
Latest ArticlesPublisher
RoutledgeLocation
Philadelphia, Pa.Publisher DOI
ISSN
1542-7560eISSN
1542-7579Language
engPublication classification
C1 Refereed article in a scholarly journal; C Journal articleCopyright notice
2020, Institute of Behavioral FinanceUsage metrics
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