The importance of large shocks to return predictability

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dc.coverageDOI: 10.1016/j.pacfin.2021.101518
dc.creatorDiaz, Juan
dc.creatorDuarte, Diogo
dc.creatorGalindo, Hamilton
dc.creatorMontecinos, Alexis
dc.creatorTruffa, Santiago
dc.date2021
dc.date.accessioned05-01-2026 18:18
dc.date.available05-01-2026 18:18
dc.description<p>Based on the rare disasters literature of Barro and Ursúa (2008), Barro and Ursúa (2009), and Barro and Jin (2011), we show that the predictability of the S&amp;P500 returns increases substantially when we control the regressions for major historical events, such as the Great Depression, World War I, World War II, the oil crisis of 1973-1974, and the subprime mortgage crisis. Controlling for these large shocks, the model with the dividend-earnings ratio as the regressor reaches an in-sample performance with an R<sup>2</sup> of 27.6%, while all the other models increase their R<sup>2</sup> after correcting for these large shocks. In addition, we show that controlling for major historical events improves the prediction performance, reducing the RSME in all of the 21 models we investigate. We check the robustness of our method by investigating the effects of controlling for the China trade shock of 2001 on the R<sup>2</sup> and RMSE of the bias-corrected regressions. Our findings suggest that correcting for these shocks is critical to improve prediction performance.</p>eng
dc.identifierhttps://investigadores.uandes.cl/en/publications/ee6bd0ec-ee28-427e-b3c5-870d56ce5862
dc.languageeng
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourcevol.68 (2021)
dc.subjectBias correction
dc.subjectChina trade shock
dc.subjectDirectional trading
dc.subjectIn- and out-of-sample forecast
dc.subjectReturn predictability
dc.titleThe importance of large shocks to return predictabilityeng
dc.typeArticleeng
dc.typeArtículospa
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