# Pricing foreign exchange options under stochastic volatility and interest rates using an RBF--FD method

## TL;DR

This paper introduces a localized RBF-FD numerical method for efficiently pricing FX options under a complex model with stochastic interest rates and volatility, overcoming computational challenges of traditional methods.

## Contribution

The paper develops a novel RBF-FD approach tailored for a complex FX option pricing PDE with non-affine terms, improving efficiency and accuracy.

## Key findings

- The RBF-FD method achieves high accuracy in FX option pricing.
- The approach reduces computational cost compared to traditional methods.
- Numerical results demonstrate the method's effectiveness in computing Greeks.

## Abstract

This paper proposes a numerical method for pricing foreign exchange (FX) options in a model which deals with stochastic interest rates and stochastic volatility of the FX rate. The model considers four stochastic drivers, each represented by an It\^{o}'s diffusion with time--dependent drift, and with a full matrix of correlations. It is known that prices of FX options in this model can be found by solving an associated backward partial differential equation (PDE). However, it contains non--affine terms, which makes its difficult to solve it analytically. Also, a standard approach of solving it numerically by using traditional finite--difference (FD) or finite elements (FE) methods suffers from the high computational burden. Therefore, in this paper a flavor of a localized radial basis functions (RBFs) method, RBF--FD, is developed which allows for a good accuracy at a relatively low computational cost. Results of numerical simulations are presented which demonstrate efficiency of such an approach in terms of both performance and accuracy for pricing FX options and computation of the associated Greeks.