A rapidly growing literature has documented important improvements in volatility measurement and forecasting … provides a practical framework for non-parametrically measuring the jump component in realized volatility measurements … an easy-to-implement reduced form model for realized volatility results in highly significant jump coefficient estimates …

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of … imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of … time-varying volatility of returns, but also can accommodate the asymmetric shape of conditional distribution of the …

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous … volatility models. We analyze the distributional properties of the jump measures vis-à-vis the corresponding realized volatility … accuracy of high-frequency volatility models …

We use frequency-domain techniques, namely wavelets and cross-spectra, to examine the association between the daily …

, from asset allocation to LIBOR Surveillance and cyber security.“FILTERING NOISE FROM VOLATILITY.” White Paper 5, dated …; and a demonstration that more than 30% of SP500 securities can have percentage change in volatility of more than 10% as a …

Volatility has been one of the most active and successful areas of research in time series econometrics and economic … empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is … inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then …