the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account … representation as a time-varying heavy-tailed copula which is particularly useful if the interest focuses on dependence structures …

the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the … microstructure noise has an adverse effect on both spot variance estimation and jump detection. In our approach we can analyze high …

-varying correlation parameter in the covariance matrix of the transition equation’s error terms. We treat the latter parameter as a state … variable, which makes the state space model become nonlinear and therefore its estimation by Kalman filtering and maximum … employs cubic splines for the auxiliary model, and a bootstrap filter method to estimate the time-varying correlation together …

impact of past values of realized correlation on future values is at least 10% higher when stock returns are negative rather … than positive. This finding supports the conjecture that correlation between stock returns tends to be higher when stock …