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Can High‐frequency Trading Strategies Constantly Beat the Market?
Author(s) -
Manahov Viktor
Publication year - 2016
Publication title -
international journal of finance and economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 39
eISSN - 1099-1158
pISSN - 1076-9307
DOI - 10.1002/ijfe.1541
Subject(s) - high frequency trading , genetic programming , financial market , order (exchange) , economics , trading strategy , stock market , financial economics , stock (firearms) , algorithmic trading , computer science , finance , artificial intelligence , engineering , mechanical engineering , paleontology , horse , biology
Policymakers are still debating whether or not high‐frequency trading (HFT) is beneficial or harmful to financial markets. We develop four artificial stock markets populated with HFT scalpers and aggressive high‐frequency traders using Strongly Typed Genetic Programming trading algorithm. We simulate real‐life HFT by applying Strongly Typed Genetic Programming to real‐time millisecond data of Apple, Bank of America, Russell 1000 and Russell 2000 and observe that HFT scalpers front‐run the order flow generating persistent profits. We also use combinations of forecasting techniques as benchmarks to demonstrate that HFT scalping strategies anticipate the trading order flow and constantly beat the market. Copyright © 2015 John Wiley & Sons, Ltd.