We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a …

Cholesky multivariate stochastic volatility model. It establishes that systematically different dynamic restrictions are … divergent when volatility clusters idiosyncratically. It is illustrated that this property is important for empirical … multivariate stochastic volatility model is proposed as a robust alternative. …

-varying volatility of the data generating process can have rather adverse effects when inferring about its persistence; e.g. unit root … conditional heteroskedasticity). The paper explores the influence of time-varying volatility on fractionally integrated processes …. Concretely, we discuss how to model long memory in the presence of time-varying volatility, and analyze the effects of such …

-Leibler divergence in empirically relevant settings. We illustrate the theory with an application to time-varying volatility models. We …

A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … diffusion processes are employed, but with the filtered/estimated volatility process replacing the latent process. Our …

single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by …