Stochastic volatility is the unpredictable nature of asset price volatility over time. It's a flexible alternative to the Black Scholes' constant volatility assumption.

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 ...

As artificial intelligence models are increasingly applied to macroeconomic data, on-chain behavior, and market cycle ...

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, ...

Local volatility models introduced by Dupire (1994) and Derman & Kani (1994) are now widely used to price and manage the risks of structured products. The dimensionality of risks to be simultaneously ...

We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range.

This article uses a Bayesian unit-root test in stochastic volatility models. The time series of interest is the volatility that is unobservable. The unit-root testing is based on the posterior odds ...

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, ...