An effort to understand the ‘boom and bust’ cycles of financial markets and to predict their volatility has seen the launch of a virtual stock market experiment at NUI Galway.
The virtual stock market will provide a platform to conduct a series of experiments with both automated computer agents and humans. The aim is to understand the factors that underpin ‘boom and bust’ cycles, as well as human and software agents’ interactions.
The virtual stock market is the result of a multi-disciplinary research collaboration between the JE Cairnes School of Business and Economics, the Digital Enterprise Research Institute (DERI ), and the Computer Integrated Manufacturing Research Unit (CIMRU ) at NUI Galway. The virtual stock market lists ten companies and has four types of computer agents trading in the market.
UI Galway students are invited to trade on the stock market and each participant will be given an initial endowment of 10,000 airgead (virtual currency ) and an equivalent anumber of shares.
Dr Srinivas Raghavendra, an economics lecturer at NUI Galway, Dr Laurentiu Vasiliu, a group leader in DERI/CIMRU; and PhD student Daniel Paraschiv in CIMRU/DERI are behind the experiment.
Dr Raghavendra comments: “The main objective of our research is to understand the generating processes that underlie the empirical facts of the real world financial markets.
“We approach this problem from an experimental economics point of view as we believe that experiments with human agents could provide us with insights or testable hypotheses to further our understanding of the dynamics of financial markets”.
Human traders on the virtual stock market are welcome to try out their own investment strategies, technical trading strategies or other hybrid strategies. The high-frequency data (real time data ) of the virtual market can be directly downloaded to a spreadsheet, which will allow participants to try out various technical trading rules.
Dr Vasiliu said that it is envisioned by the DERI commercialisation team to move the concept forward towards a potential future professional stock exchange testing environment, where novel strategies and financial products can be tested by interested financial houses.
“This would ensure a basis for evaluating new financial approaches as well as IT technologies that are currently developed by NUI Galway and other Irish universities. At the same time it can be shown how a very close cooperation between IT and Economics researchers provides a safe and needed financial testing ground, particularly in the current economic climate,” he said.
There is also a teaching benefit to be had from NUI Galway’s new stock exchange.
According to Dr Raghavendra: “As a teaching tool, the virtual stock market provides an excellent opportunity for students, at all levels, to understand the basic functioning of a stock market.
For advanced students, it provides a platform to test their own investment strategies. For students of computer science and IT, this platform provides a unique opportunity to understand the interface between human agents and computer agents (algorithms ), and its implications for the dynamics of financial markets”.
The scope of the Virtual Stock Market can be extended to futures trading and monetary policy experiments.
Dr Raghavendra adds: “Even the anticipation of a monetary policy swings the markets, let alone the post announcement effect. The experiments in this area would be useful to study the dynamic between monetary policy rules and instruments, and human agents’ expectation formation, which is one of the fundamental issues in understanding the stability of markets.”
The results of the experiment with the virtual stock market will be presented in July to the Society for Computational Economics at the 15th International Conference on Computing in Economics and Finance in Sydney, Australia.
The trading data is available to traders at two frequencies. Traders would have daily data on open, high, low and close prices, and volume traded for all the stocks. They would also have intra-day data at a frequency of five minutes on open, high, low, close and volume for the stocks. Traders can use the daily data for long-term strategies and short-term strategies with the intra-day data. The indicators embedded in the software are logarithmic return and the distribution of logarithmic return.