Affine processes provide a versatile framework for modelling complex financial phenomena, ranging from interest rate dynamics to credit risk and beyond. Their defining characteristic is the affine, or ...

The traditional approach to stochastic volatility (SV) modelling begins with the specification of an SV process, typically on the grounds of its analytical tractability (see, for example, Heston, 1993 ...

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 Energy Exchange ...

Stochastic volatility represents an essential framework for understanding the dynamic uncertainty inherent in financial markets. This approach extends traditional models by recognising that volatility ...

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating ...

We extend the existing small-time asymptotics for implied volatilities under the Heston stochastic volatility model to the multifactor volatility Heston model, which is also known as the Wishart ...

• Ahsan, M. N. and Dufour, J-M. (2019). “A simple efficient moment-based estimator for the stochastic volatility model,” Advances in Econometrics. Vol. 40A, pp ...

The ability of the usual factors from empirical arbitrage-free representations of the term structure — that is, spanned factors — to account for interest rate volatility dynamics has been much debated ...

Volatility modeling is no longer just about pricing derivatives—it's the foundation for modern trading strategies, hedging precision, and portfolio optimization. Whether you're trading gold futures, ...