Stochastic volatility models have revolutionised the field of option pricing by allowing the volatility of an asset to vary randomly over time rather than remain constant. These models have ...

This paper generalizes the standard homoscedastic macro-finance model by allowing for stochastic volatility, using the "square root" specification of the mainstream finance literature. Empirically, ...

Pricing Partners, the world leader in OTC derivatives pricing analytics, mathematical models and independent valuations, announced today that its award winning Price-it Library now contains a model ...

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 ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three ...

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 ...

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness ...

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, ...

Whether the financial markets are turbulent or calm, the subject of volatility has been of great interest to quants for decades. Some of the pioneering research was published in the mid-1990s, ...