High-frequency Finance Research Platform,
Contributor's Guide |
A Wiki-style Global Project
The current economic crisis is a testament of the deficiency of modern economic theory and its tools of analysis.
We plan to build a research platform for a global information system of the economy and the financial markets. The platform utilizes the discoveries of high frequency finance to develop an innovative approach of economic modelling and analysis of trader behaviour by combing a broad range of disciplines.
We propose to embark on a project to develop a High-frequency Finance Research Platform. This platform will be used to improve the understanding of market dynamics. The long-term goal is to build a platform that serves both researchers and the general public. For researchers, it will be a research and simulation platform. For the general public, it will generate online forecasts of the general economy and the financial markets, very much like a weather forecast . To achieve this objective, the platform has to collect fundamental data and market price information. This data is used to feed fundamental models of the economy and to construct maps of how market participants build positions that may ultimately give rise to cascading price moves causing economic crisis. The platform is both a research tool for innovative model building and serves as an operational infrastructure to operate the models on an ongoing basis allowing for 24/7 validation of the forecasts of the models that have been developed.
The system that we propose to build will be a web-based, open-source system . Users may upload their modules, and construct interactions between modules. Modules may vary from simple data-retrieval modules to sophisticated financial models. They may also be analysis tools or graphic interfaces. Crucial to the platform is a set of databases, which we intend to collect . By building and connecting modules, the user may use the data to verify or experiment with different financial models. Human interaction is inevitably laborious. Interface will be designed to allow the platform to interact with computer programs. This will allow us to make use of optimization tools to find models. The diagram below shows the overall architecture of the system.
The platform is intended to be open-source. This will encourage
researchers all over the world to participate.
The project involves expertise from different disciplines,
including finance, economics, computational intelligence (for model building), mathematics, computer and behavioural sciences.
Following are some of the ways that this platform can be used:
- Regulators will pick and choose the modules in the system (which could be developed by top experts in their fields) to generate market reports, like what we are accustomed to in weather reports. These reports may indicate risk of financial turmoil. Through evolutionary computation, one may attempt to automate the process of finding conditions under which crashes will occur . This will allow us to build a
financial early warning system.
- An economist may be interest in developing a new model on volatility. She has no expertise, nor interest, in building computer interfaces. Neither does she have data to test her new model. She can pick up one of the existing volatility modules deposited in the platform and replace it by her own. Then she can test her model with data deposited in the platform, which is something that she was unable to do without the platform.
- A computational intelligence expert may pick up a module on volatility that contains many parameters, and use evolutionary computation to search for parameters under which the volatility model fits the data. Model-fitting is very laborious if done manually. This computational intelligence expert may not have sufficient knowledge to develop new models on volatility, but, with the platform, he can make substantial contribution to perfecting volatility models.
- A researcher may want to develop quantitative trading strategies to stabilize financial markets. What he could do is to develop a module based on his algorithm and test it in the platform. There he will be able to test the algorithm without having to possess data himself.
- A visualization expert may want to use the platform to demonstrate her tools for visualizing complex simulation results. Her contribution will benefit other users of the system.
- Richard Olsen and Clive Cookson, "How Science can prevent the next bubble", FT.COM 2009.02.12
- Richard Olsen, "How to Trade", THINK ABOUT Press, Olsen Ltd (ISBN: 978-3-9523708-0-3), 2010
- "A Model Approach - more development work is needed to help computer simulations inform economic policy", Nature, Vol.460, Issue 7256, 6 August 2009
Edward Tsang; Created: 2009.06.16;
Last Updated: 2010.09.21