A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes
Applications
2019-03-06 v1
Abstract
The use of factor stochastic volatility models requires choosing the number of latent factors used to describe the dynamics of the financial returns process; however, empirical evidence suggests that the number and makeup of pertinent factors is time-varying and economically situational. We present a novel factor stochastic volatility model that allows for random subsets of assets to have their members experience non-market-wide panics. These participating assets will experience an increase in their variances and within-group covariances. We also give an estimation algorithm for this model that takes advantage of recent results on Particle Markov chain Monte Carlo techniques.
Cite
@article{arxiv.1903.01841,
title = {A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes},
author = {Taylor R. Brown},
journal= {arXiv preprint arXiv:1903.01841},
year = {2019}
}