The Heston model stands out from the class of stochastic volatility (SV) models mainly for two reasons. Firstly, the … process for the volatility is nonnegative and mean-reverting, which is what we observe in the markets. Secondly, there exists …. -- Heston model ; vanilla option ; stochastic volatility ; Monte Carlo simulation ; Feller condition ; option pricing with FFT …

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly …, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows … autoregressive conditional heteroskedasticity (GARCH), and stochastic volatility with jumps (SVJ) models. Our results are not due to …

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 …

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 …

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 …

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 …

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 …

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 …

autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term … additional determinants of future excess returns. Finally, we illustrate that the yield and volatility factors are closely con … ; yield curve risk ; stochastic volatility ; factor models ; macroeconomic fundamentals …