The well-known Heath-Jarrow-Morton (HJM) framework provides a universal and efficacious instrument for modeling the stochastic evolution of an entire yield curve by explaining the interest rate dynamics in continuous time under no-arbitrage conditions. Existing implementations involve...

In this paper we propose methods, from a classical and Bayesian approach, to estimate the constant volatility of an asset when it is not appropriate to fit heteroscedastic or stochastic volatility models relative to the sample series of the asset where no large increase in volatility is...

This study investigates an option pricing method called g-pricing based on backward stochastic differential equations combined with deep learning. We adopted a data-driven approach to find a market-appropriate generator of the backward stochastic differential equation, which is achieved by...