Most of the empirical applications of the stochastic volatility (SV) model are based on the assumption that the conditional distribution of returns, given the latent volatility process, is normal. In ...

Abstract ABSTRACT This paper builds and implements a multifactor stochastic volatility model for the latent (and unobservable) volatility of the baseload and peakload forward contracts at the European ...

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 ...

In parallel, stochastic volatility models capture the time‐varying uncertainty inherent in financial markets, where volatility itself follows a random process.

Dominique Bang, head of interest rate vanilla analytics at Bank of America Merrill Lynch in London, joined us in our studio to talk about his work on a local stochastic volatility model. In his ...