Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data

dc.contributor.authorSalisu, Afees A.
dc.contributor.authorGupta, Rangan
dc.contributor.authorOgbonna, Ahamuefula E.
dc.date.accessioned2023-11-29T08:27:30Z
dc.date.issued2023
dc.description.abstractThis study examines the out-of-sample predictability of market risks measured as tail risks for stock returns of eight advanced countries using a long-range monthly data of over a century. We follow the Conditional Autoregressive Value at Risk (CAViaR) of Engle and Manganelli (2004) to measure the tail risks and consequently, we produce results for both 1% and 5% VaRs across four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the CAViaR. Thereafter, we use the “best” fit tail risks in the return predictability of the selected advanced stock markets. For the forecasting exercise, we construct three predictive models (one-predictor, two-predictor and three-predictor models) and examine their forecast performance in contrast with a driftless random walk model. Three findings are discernible from the empirical analysis. First, we find that the choice of VaR matters when determining the “best” fit CAViaR model for each return series as the outcome seems to differ between 1% and 5% VaRs. Second, the predictive model that incorporates both stock tail risk and oil tail risk produces better forecast outcomes than the one with own tail risk indicating the significance of both domestic and global risks in the return predictability of advanced countries.en_US
dc.description.departmentEconomicsen_US
dc.description.embargo2024-01-17
dc.description.librarianhj2023en_US
dc.description.sdgSDG-08:Decent work and economic growthen_US
dc.description.urihttps://www.tandfonline.com/loi/rejf20en_US
dc.identifier.citationAfees A. Salisu, Rangan Gupta & Ahamuefula E. Ogbonna (2023) Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data, The European Journal of Finance, 29:4, 466-481, DOI: 10.1080/1351847X.2022.2097883.en_US
dc.identifier.issn1351-847X (print)
dc.identifier.issn1466-4364 (online)
dc.identifier.other10.1080/1351847X.2022.2097883
dc.identifier.urihttp://hdl.handle.net/2263/93528
dc.language.isoenen_US
dc.publisherRoutledgeen_US
dc.rights© 2022 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in European Journal of Finance, vol. 29, no. 4, pp. 466–481, 2023. doi : 10.1080/1351847X.2022.2097883. European Journal of Finance is available online at : http://www.tandfonline.com/loi/rejf20.en_US
dc.subjectStock returnsen_US
dc.subjectTail risksen_US
dc.subjectForecastingen_US
dc.subjectAdvanced equity marketsen_US
dc.subjectSDG-08: Decent work and economic growthen_US
dc.subjectConditional autoregressive value at risk (CAViaR)en_US
dc.titleTail risks and forecastability of stock returns of advanced economies: evidence from centuries of dataen_US
dc.typePostprint Articleen_US

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