implemented and do not contain any numerical integration.These formulas are important in volatility surface construction and CMS …

method consists of specifying the joint distribution of the volatility and underlying at a given expiry and requires the … obtained as one-dimensional integrals. The specification of the volatility function is flexible and allows additional control …

Stochastic volatility models are widely used in interest rate modeling to match the option smiles -- the two most …, Heston-LMM and SABR-LMM respectively.In this paper we consider the CEV model with a general stochastic volatility. Assuming … that rate-volatility correlation is zero we are able to obtain an exact integral representation of the option price …

We study measures of foreign exchange rate volatility based on high-frequency (5-minute) $/DM exchange rate returns … using recent nonparametric statistical techniques to compute realized return volatility and its separate continuous sample … implied volatility. We find that implied volatility is an informationally efficient but biased forecast of future realized …

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly … significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and … yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods …

This paper proposes the new concept of stochastic leverage in stochastic volatility models.Stochastic leverage refers … stochastic volatility process. We provide a systematic treatment of stochastic leverage and propose to model the stochastic … tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility models which …

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 …

Using positive semidefinite supOU (superposition of Ornstein-Uhlenbeck type) processes to describe the volatility, we … introduce a multivariate stochastic volatility model for financial data which is capable of modelling long range dependence … effects. The finiteness of moments and the second order structure of the volatility, the log returns, as well as their …

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends … standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability … in the data. We discuss how stochastic volatility of volatility can be defined both non–parametrically, where we link it …