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 ...

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 ...

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 ...

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 ...

• 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 ...

The ability to compute exotic greeks is important in explaining profit and loss statements, but what is the best way to calculate them effectively? In a virtual talk for the Bloomberg Quant (BBQ) ...

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, ...