Grant: College - University Idea to Innovation Grants

Current commercial stock market simulators operate based on real time or historical stock market data. These systems cannot be applied in two important situations, namely (1) exploring scenarios of anticipated market conditions and (2) accounting for the current participant's actions in the market under simulation. Current systems are used in development of trading strategies to simulate how specific models will perform on live financial markets. However, performance based on past historical data has proven not to be an indication of future conditions and results in the financial markets. This has been seen in recent years where the unprecedented volatility of the global financial markets would not be simulated by replaying historical data. This project explores the research questions in building a simulated environment to test financial trading systems as well as the practical questions that arise in deploying such a system. A simulator will incorporate the order flow from both live market and simulated participants while accounting for anticipated future market conditions and events. Aspects of cloud technology will allow the system flexibility to integrate with financial institutions with a wide range of requirements.