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The Design and Regulation of High Frequency Traders

Daniel Ladley ()

No 19/02, Discussion Papers in Economics from Division of Economics, School of Business, University of Leicester

Abstract: Central to the ability of a high frequency trader to make money is speed. In order to be first to trading opportunities fi rms invest in the fastest hardware and the shortest connections between their machines and the markets. This, however, is not enough, algorithms must be short, no more than a few lines of code. As a result there is a trade-off in the design of optimal HFT strategies: being the fastest necessitates being less sophisticated. To understand the effect of this tension a computational model is presented that captures latency, both of code execution and information transmission. Trading algorithms are modelled through genetic programmes with longer programmes allowing more sophisticated decisions at the cost of slower execution times. It is shown that depending on the market composition short fast strategies and slower more sophisticated strategies may both be viable and exploit different trading opportunities. The relative pro fits of these different approaches vary, however, slow traders bene t from their presence. A suite of regulations are tested to manage the risks associated with high frequency trading, the majority are found to be ineffective, however, constraining the ratio of orders to trades may be promising.

Keywords: Finance; Genetic Programming; High Frequency Trading; Strategy Design; Regulation (search for similar items in EconPapers)
Date: 2019-03
New Economics Papers: this item is included in nep-cmp and nep-mst
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