The Wishart Autoregressive (WAR) process is a dynamic model for time series of multivariate stochastic volatility. The WAR naturally accommodates the positivity and symmetry of volatility matrices and provides closed-form non-linear forecasts. The estimation of the WAR is straighforward, as it...

This article uses a bivariate stochastic volatility model to examine the leverage effects for two stock returns. The results show that the leverage effect estimates for each stock depend on the degree to which the risk premium is affected by the information about the other stock and that...

We develop a unified approach with closed-form solutions for pricing bonds, stocks, currencies and their derivatives. The specification assumes a fundamental risk factor represented by a stochastic positive definite matrix following a Wishart autoregressive (WAR) process. By assuming a...

This paper extends to the multiasset framework the closed-form solution for options with stochastic volatility derived in Heston (1993) and Ball and Roma (1994). This extension introduces a risk premium in the return equation and considers Wishart dynamics for the process of the stochastic...

This paper reveals that the class of affine term structure models introduced by Duffie and Kan (1996) is much larger than it has been usually considered in the literature. We study fundamental risk factors, which represent multivariate risk aversion of the consumer or the volatility matrix of...