Gibbs

Bayesian Analysis of Stochastic Volatility Model And Estimating Volatility with Gibbs Sampler

Stochastic volatility models are those in which the volatility of a stochastic process is itself randomly distributed. There are two random processes, one for observation, and one for the latent variables which controls specifically the volatility which is the degree of variation of a time series over time. Volatility is highly important for stocks in finance. Low volatility implies the stock will behave nearly deterministic. Large volatility means the stock price experience large spikes in pricing.