This paper specifies a multivariate stochastic volatility (SV) model for the Samp;P500 index and spot interest rate processes. We first estimate the multivariate SV model via the efficient method of moments (EMM) technique based on observations of underlying state variables, and then investigate...

This paper specifies a multivariate stochastic volatility (SV) model for the Samp;P500 index and spot interest rate processes. We first estimate the multivariate SV model via the efficient method of moments (EMM) technique based on observations of underlying state variables, and then investigate...

While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the Black-Scholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to first estimate a multivariate SV model...

While the stochastic volatility (SV) generalization has been shown to improvethe explanatory power compared to the Black-Scholes model, the empiricalimplications of the SV models on option pricing have not been adequately tested.The purpose of this paper is to first estimate a multivariate SV...

This paper evaluates the performance of volatility forecasting based on stochastic volatility (SV) models. We show that the choice of squared asset-return residuals as a proxy for ex-post volatility directly leads to extremely low explanatory power in the common regression analysis of volatility...

While the conditional volatility of time series is always dependent of the model specification, the {\\em ex post} or realized volatility series is often constructed on a model-free basis. The common proxies of daily volatility in the literature are the squared daily asset returns and the sum of...

While the stochastic volatility (SV) generalization has been shown to improve the explanatory power compared to the Black-Scholes model, the empirical implications of the SV models on option pricing have not been adequately tested. The purpose of this paper is to first estimate a multivariate SV...

In this article we examine the backfill bias or instant history bias for hedge funds using additional information from the Tass database. This is information about the exact date a hedge fund starts reporting to Tass. Using this information we are able to reveal the length of the instant...

We decompose the conditional expected mutual fund return in five parts. Two parts, selectivityand expert market timing, can be attributed to manager skill, and three to variation in marketexposure that can be achieved by private investors as well. The dynamic model that we use toestimate the...

This paper focuses on the estimation of mutual fund styles by return-based style analysis. Often the investment style is assumed to be constant through time. Alternatively, time variation is sometimes implicitly accounted for by using rolling regressions when estimating the style exposures. The...