In this paper we study a correlation-based LIBOR market model with a square-root volatility process. This model captures downward volatility skews through taking negative correlations between forward rates and the multiplier. An approximate pricing formula is developed for swaptions, and the...

In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean (SVM) model based on Monte Carlo simulation methods. The SVM model incorporates the unobserved volatility as an explanatory variable in the mean equation. The same extension is...

In this paper we compare the predictive abilility of Stochastic Volatility (SV) models to that of volatility forecasts implied by option prices. We develop an SV model with implied volatility as an exogeneous var able in the variance equation which facilitates the use of statistical tests for...

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating...

A price process is scale-invariant if and only if the returns distribution is independent of the price level. We show that scale invariance preserves the homogeneity of a pay-off function throughout the life of the claim and hence prove that standard price hedge ratios for a wide class of...

Contrary to popular belief, the diffusion limit of a GARCH variance process is not a diffusion model unless one makes a very specific assumption that cannot be generalized. In fact, the normal GARCH(1,1) prices of European call and puts are identical to the Black-Scholes prices based on the...

We present a time series model that integrates properties from Levy-type and multifractal models. Formally, it is a stochastic volatility model with discrete time steps, t-distributed return innovations and a stochastic cascade for the volatility process. This model reproduces very well...

We propose a general class of non-constant volatility models with dependence on the past. The framework includes path-dependent volatility models such as that by Hobson&Rogers and also path dependent contracts such as options of Asian style. A key feature of the model is that market completeness...

We fit a Bayesian time-varying parameters structural VAR with stochastic volatility to the Federal Funds rate, GDP deflator inflation, real GDP growth, and the rate of growth of M2. We identify 4 shocks–monetary policy, demand non-policy, supply, and money demand–by imposing sign...

This paper compares two types of volatility models for returns, ARCH-type and stochastic volatility (SV) models, both from a theoretical and an empirical point of view. In particular a GARCH(1,1) model, an EGARCH(1,1) model and a log-normal AR(1) stochastic volatility model are considered. The...