estimate the dependence structures and bivariate copulas between the estimated volatility of different markets. Thereafter, the …

volatility and time-varying parameters. The proposed model also allows for endogeneity of the trade durations as well as for …

This paper proposes a stochastic volatility model (PAR-SV) in which the log-volatility follows a first-order periodic … autoregression. This model aims at representing time series with volatility displaying a stochastic periodic dynamic structure, and …-SV model such as periodic stationarity and autocovariance structure are first studied. Then, parameter estimation is examined …

simulated and real data. In particular, applications to Bayesian volatility forecasting and Value-at-Risk estimation for daily …

We propose a novel class of count time series models, the mixed Poisson integer-valued stochastic volatility models … volatility model, encompasses a wide range of conditional distributions of counts. We study its probabilistic structure and …