can generate a plausible disaggregation of the conditional variance process, in which the components' volatility dynamics …

Based on criteria of mathematical simplicity and consistency with empirical market data, a stochastic volatility model … is constructed, the volatility process being driven by fractional noise. Price return statistics and asymptotic behavior …

In this article we introduce a linear quadratic volatility model with co-jumps and show how to cal- ibrate this model … simultaneous jumps in both re- turn process and volatility process and the superposition structure of a continuous linear quadratic … volatility process and a Lévy-driven Ornstein-Uhlenbeck process. We compare the quality of fit for several models, and show that …

We propose a mixed frequency stochastic volatility (MFSV) model for the dynamics of intraday asset return volatility …. In order to account for long-memory we separate stochastic daily and intraday volatility patterns by introducing a long …-run component that changes at daily frequency and a short-run component that captures the remaining intraday volatility dynamics. An …

We estimate three continuous-time stochastic volatility models following the approach by Aït-Sahalia and Kimmel (2007 … and S&P 500 Index. For the latent volatility variable, we generate and use the integrated volatility proxy using the … implied volatility of short-dated at-the-money option prices. We conduct MLE in order to estimate the parameters of the …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and …-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the …