Structural instability and predictability

Neluka Devpura, Paresh Kumar Narayan and Susan Sunila Sharma

Journal of International Financial Markets, Institutions and Money, 2019, vol. 63, issue C

Abstract: We propose a structural break predictive regression model that accounts for predictor persistency, endogeneity, heteroscedasticity, and a structural break. Monte Carlo (MC) simulations indicate that this test performs satisfactorily compared to competitor estimators. We employ a popular U.S. data set (the period January 1927 to December 2016) that includes stock market returns and multiple predictors. We show, consistent with the MC results, evidence of a structural break. Our analysis reveals that a structural break–based predictive regression model fits the data reasonably well in predicting stock price returns.

Keywords: Structural break; Predictability; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfin:v:63:y:2019:i:c:s1042443119300150

DOI: 10.1016/j.intfin.2019.101145

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