On identification of high frequency traders on financial market

One of the most significant changes in the structure of the financial markets over the past few years is the development of high frequency trading (HFT). According to expert estimates, the high frequency trading is responsible for most of the transactions in financial markets (e.g., more than 77 % of transactions in the UK market, according to «Tabb Group»). High frequency trading is able to influence the occurrence of systemic instability: for example, the loss of capitalization stock indices during the so -called "flash crash" in May 6, 2010 amounted about $ 1 trillion dollars in less than 10 minutes. The term high frequency trading is relatively new and has no clear definitions. Many researchers and financial market regulators define it in different ways. Issues related with the definition and identification of high frequency trading are becoming more relevant for modern markets. This article reviews approaches to the definition of high frequency trading. We provide an overview of high frequency data and methods used to analyze these data to study high frequency agents. We also analyze methods and approaches to identification of high frequency traders. Most studies of HFT, use classification provided by organizers of trade, while the identification of high-frequency market participants devoted a relatively small number of empirical studies. Article summarizes the main approaches for identification (Kirilenko-Kyle, ASIC, IIROC). These approaches have some significant drawbacks, which requires the development of improved methods of identifying HFT.