Moments Structure of l1-Stochastic Volatility Models

We consider Taylor's stochastic volatility model when the innovations of the hidden log-volatility process have a Laplace distribution (l1 exponential density), rather than the standard Gaussian distribution (l2) usually employed. Using a distribution with heavier tails allows better modeling of the abrupt changes of regime observed in financial time series. We derive here the moments and autocovariance function of such l1-based stochastic volatility models.