realized volatility. The jump component has very different time series properties than the continuous component, and accounting … for this allows improved forecasting of future realized volatility. We investigate the potential forecasting role of … implied volatility backed out from option prices in the presence of these new separate realized volatility components. We show …

In this paper, I study the drop of real GDP volatility which has been observed in the United States during the postwar …

capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in … evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing … also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness …

The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diffusion process which …

volatility models. We propose a continuous timefractionally integrated Wishart stochastic volatility (FIWSV) process. We derive …

. This makes the result markedly different from the volatility case. Observationally equivalent decompositions of the …

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this … stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value …

The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We … suggest use of the principal component methodology of Stock and Watson (2002) for the stochastic volatility factor model …

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as …. Liquidity is causal for future volatility but not vice versa. Furthermore, trade sizes are negatively driven by past trading …