Stochastic Volatility Models with Integrated GARCH(t) Structure
نویسنده
چکیده
A stochastic volatility model consists of a pair of stochastic processes {Xt, Yt}, of which only Yt is observed, but where the conditional distribution of Yt|Xt = xt has a scale that depends on xt. The unobserved Xt is interpreted as a state variable that affects the processes that result in the observed Yt. The conditional heteroscedasticity (CH) approach to modeling volatility is based on the conditional variance function
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