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

被引:3
|
作者
Abanto-Valle, Carlos A. [1 ]
Rodriguez, Gabriel [2 ]
Garrafa-Aragon, Hernan B. [3 ]
机构
[1] Univ Fed Rio de Janeiro, Dept Stat, Caixa Postal 68530, BR-21945970 Rio De Janeiro, Brazil
[2] Pontificia Univ Catolica Peru, Dept Econ, 1801 Univ Ave, Lima 32, Peru
[3] Univ Nacl Ingn, Escuela Ingn Estadist, Lima, Peru
关键词
Feed-back effect; Hamiltonian Monte Carlo; Markov Chain Monte Carlo; Non linear state space models; Stochastic Volatility in Mean; Stock Latin American markets; Riemannian Manifold Hamiltonian Monte Carlo; LEVEL SHIFTS; LONG-MEMORY; MODEL; DISTRIBUTIONS;
D O I
10.1016/j.qref.2021.02.005
中图分类号
F [经济];
学科分类号
02 ;
摘要
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). (c) 2021 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.
引用
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页码:272 / 286
页数:15
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