In this paper, we propose an approximation method based on the Wiener-Ito chaos expansion for the pricing of European contingent claims. Our method is applicable to widely used option pricing models such as local volatility models, stochastic volatility models, and their combinations. This...

This paper proposes a mixed approach of asymptotic expansion (AE) and artificial neural network (ANN) methods for option pricing in order to improve computational speed, stability, and approximation accuracy. In practice, there is wide use of complex stochastic volatility models (SVMs) which can...

This study proposes an artificial neural network (ANN) based option pricing framework under the SABR (stochastic alpha beta rho) and free boundary SABR volatility models. Unlike previous research, we do not directly apply the ANN technique to train and predict option implied volatilities....

Recent empirical studies have demonstrated the informative nature of the equity returns in explaining the variation of the underlying firm's credit default swap (CDS) spreads. Motivated by these findings, we propose a unified credit-equity model by extending the latent structural model in Kijima...

We advance a model of the tradable permit market and derive a pricing formula for contingent claims traded in the market in a general equilibrium framework. It is shown that prices of such contingent claims exhibit significantly different properties from those in the ordinary financial markets....