This paper provides tractable expressions for broad classes of standard transforms for the case of affine jump diffusions. Extending and unifying existing results, these include expressions for exponential, polynomial-log-linear, and polynomial transforms of a state vector in both conditional...

This paper introduces a unified machine learning framework for solving general asset pricing problems. Building on representations of asset prices in discrete-time and continuous-time models, we develop a solution strategy using neural networks and further machine learning techniques to...

Derivatives, especially equity and volatility options, contain valuable and oftentimes essential information for estimating stochastic volatility models. Absent strong assumptions, their typically highly nonlinear pricing dependence on the state vector prevents or at least severely impedes their...