Stochastic Volatility in Mean: Empirical evidence from Latin-American stock markets using Hamiltonian Monte Carlo and Riemann Manifold HMC methods

Carlos A. Abanto-Valle, Gabriel Rodríguez and Hernán B. Garrafa-Aragón

The Quarterly Review of Economics and Finance, 2021, vol. 80, issue C, 272-286

Abstract: The Stochastic Volatility in Mean (SVM) model of Koopman and Uspensky (2002) is revisited. An empirical study of five Latin American indexes in order to see the impact of the volatility in the mean of the returns is performed. Markov Chain Monte Carlo (MCMC) Hamiltonian dynamics is used to estimate latent volatilities and parameters. Our findings show that volatility has a negative impact on returns, indicating that volatility feedback effect is stronger than the effect related to the expected volatility. This result is clear and opposite to the finding of Koopman and Uspensky (2002).

Keywords: Feed-back effect; Hamiltonian Monte Carlo; Markov Chain Monte Carlo; Non linear state space models; Riemannian Manifold Hamiltonian Monte Carlo; Stochastic Volatility in Mean; Stock Latin American markets (search for similar items in EconPapers)
JEL-codes: C11 C15 C22 C51 C52 C58 G12 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:quaeco:v:80:y:2021:i:c:p:272-286

DOI: 10.1016/j.qref.2021.02.005

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