Joint tails impact in stochastic volatility portfolio selection models

Marco Bonomelli (), Rosella Giacometti () and Sergio Ortobelli Lozza ()
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Marco Bonomelli: University of Bergamo
Rosella Giacometti: University of Bergamo
Sergio Ortobelli Lozza: University of Bergamo

Annals of Operations Research, 2020, vol. 292, issue 2, No 12, 833-848

Abstract: Abstract This paper examines the impact of the joints tails of the portfolio return and its empirical volatility on the optimal portfolio choices. We assume that the portfolio return and its volatility dynamic is approximated by a bivariate Markov chain constructed on its historical distribution. This allows the introduction of a non parametric stochastic volatility portfolio model without the explicit use of a GARCH type or other parametric stochastic volatility models. We describe the bi-dimensional tree structure of the Markov chain and discuss alternative portfolio strategies based on the maximization of the Sharpe ratio and of a modified Sharpe ratio that takes into account the behaviour of a market benchmark. Finally, we empirically evaluate the impact of the portfolio and its stochastic volatility joint tails on optimal portfolio choices. In particular, we examine and compare the out of sample wealth obtained optimizing the portfolio performances conditioned on the joint tails of the proposed stochastic volatility model.

Keywords: Markov chain; Sharpe ratio; Stochastic dominance; Stochastic volatility (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10479-020-03531-w

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