A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes

03/05/2019

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by   Taylor R. Brown, et al.

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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.