Modeling the time-varying skewness via decomposition for out-of-sample forecast

Xiaochun Liu ()

MPRA Paper from University Library of Munich, Germany

Abstract: This paper models time-varying skewness for financial return dynamics. We decompose nancial returns into the product of the absolute returns and signs, so-called the intriguing decomposition. The joint distribution between the decomposed components is modeled through a copula function with marginals. Allowing the copula dependence parameter time-varying, we estimate the dynamic nonlinear dependence between absolute returns and signs, which governs time- varying skewness for out-of-sample forecast of financial returns. The empirical results in this paper show that the proposed models with dynamic dependence obtain better gains of out-of-sample fore- cast, and suggest the robust strategy for a risk-averse investor in response to the market timing. This paper also explores the sources of the forecasting performance via a recently developed econometric pin-down approach. Beyond the pure statistical sense, we find that the forecasts of time-varying skewness trace closely to NBER-dated business-cycle phases.

Keywords: Time-varying skewness; Dynamic nonlinear dependence; Copulas; Out-of-sample forecast; Sources of forecasting performance (search for similar items in EconPapers)
JEL-codes: C53 G00 (search for similar items in EconPapers)
Date: 2011-08-30
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Journal Article: Modeling time-varying skewness via decomposition for out-of-sample forecast (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:41248

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