Dynamic Trade Execution: A Grammatical Evolution Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{CuiBO:2011:IJFMDDTEAGEA,

• author = "Wei Cui and Anthony Brabazon and Michael O'Neill",
• title = "Dynamic Trade Execution: A Grammatical Evolution Approach",
• journal = "International Journal of Financial Markets and Derivatives",
• year = "2011",
• volume = "2",
• number = "1-2",
• pages = "4--31",
• note = "Special Issue on Computational Methods For Financial Engineering Guest Editors: Dr. Nikolaos S. Thomaidis and Dr. Christos Floros",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, algorithmic trading, trade execution, artificial stock markets, evolutionary computation, financial markets, market impact, opportunity cost, agent-based systems.",
• ISSN = "1756-7130",
• URL = "http://www.inderscience.com/info/inarticle.php?artid=38526",
• DOI = "doi:10.1504/IJFMD.2011.038526",
• abstract = "Trade execution is concerned with the actual mechanics of buying or selling the desired amount of a financial instrument. Investors wishing to execute large orders face a tradeoff between market impact and opportunity cost. Trade execution strategies are designed to balance out these costs, thereby minimising total trading cost. Despite the importance of optimising the trade execution process, this is difficult to do in practice due to the dynamic nature of markets and due to our imperfect understanding of them. In this paper, we adopt a novel approach, combining an evolutionary methodology whereby we evolve high-quality trade execution strategies, with an agent-based artificial stock market, wherein the evolved strategies are tested. The evolved strategies are found to outperform a series of benchmark strategies and several avenues are suggested for future work.",
• notes = "http://www.inderscience.com/jhome.php?jcode=ijfmd",

}

Genetic Programming entries for Wei Cui Anthony Brabazon Michael O'Neill

Citations