Synthetic Market Data Generation and Simulation

Synthetic market data generation has become popular for applications in financial research during the past decades due to increasing demand for testing and analysing the methods and trading strategies. However, in most recent studies the synthetic market data generation has been carried out using machine, or deep learning learning techniques instead of using the sound theoretical knowledge in financial mathematics, and therefore, many approaches in this respect leaves the academicians in finance out of the picture.

In this research project, our main focus is to build a financial market using the theoretical models in financial mathematics in order to generate synthetic data for financial research. Our approach will heavily make use of the stochastic processes in general and financial instruments with their theoretical simulations and pricing methodologies.