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

Autor:	Gabriel Rodríguez, Hernán B. Garrafa-Aragón, Carlos A. Abanto-Valle
Rok vydání:	2021
Předmět:	Hamiltonian mechanics Economics and Econometrics Stochastic volatility Markov chain Monte Carlo Hybrid Monte Carlo symbols.namesake Empirical research Order (exchange) Econometrics symbols Volatility (finance) Finance Stock (geology) Mathematics
Zdroj:	The Quarterly Review of Economics and Finance. 80:272-286
ISSN:	1062-9769
Popis:	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) .
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b1031187494c0959cd2d778b2b4fb1f5 https://doi.org/10.1016/j.qref.2021.02.005 Zobrazit plný text záznamu Full Text from ScienceDirect