 The importance of large shocks to return predictabilityJuan Diaz, Diogo Duarte, Hamilton Galindo, Alexis Montecinos and Santiago Truffa Pacific-Basin Finance Journal, 2021, vol. 68, issue C Abstract: 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&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 R2 of 27.6%, while all the other models increase their R2 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 R2 and RMSE of the bias-corrected regressions. Our findings suggest that correcting for these shocks is critical to improve prediction performance. Keywords: Return predictability; Bias correction; Directional trading; In- and out-of-sample forecast; China trade shock (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:68:y:2021:i:c:s0927538x21000251 DOI: 10.1016/j.pacfin.2021.101518 Access Statistics for this article Pacific-Basin Finance Journal is currently edited by K. Chan and S. Ghon Rhee More articles in Pacific-Basin Finance Journal from Elsevier |
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