DOIONLINE

DOIONLINE NO - IJMAS-IRAJ-DOIONLINE-17554

Publish In
International Journal of Management and Applied Science (IJMAS)-IJMAS
Journal Home
Volume Issue
Issue
Volume-6,Issue-11  ( Nov, 2020 )
Paper Title
Minimizing Low-Latency Arbitrage Trading Opportunity for HFT Traders: (A Mathematical Model with HFT Simulation)
Author Name
Solomon Harsha, Khaldoun Khashanah
Affilition
Stevens Institute of Technology, Hoboken, New Jersey
Pages
1-15
Abstract
All financial markets experts agree HFT creates liquidity in the markets and it is good for the trading community, trading venues and for overall economy of the country [1]. A market maker facilitates trade and supplies liquidity by simultaneously maintaining offers to buy and sell. Because of the market fragmentation securities can be traded across multiple trading venues. As the markets are continuous the price of the traded securities in all the trading venues will not settle instantaneously to NBBO because of the computational and transmission latencies between these trading venues. Basically, this latency between the trading venues involve following components: 1. The intrinsic latency due to geographic distances between information sources; 2. The throughput latency due to local network architecture; and 3. The computational latency in calculating the NBBO. Because of this a new type of HFT strategy in which traders exercise superior speed in order to exploit price disparities between the exchanges. This type of trading is called Low Latency Arbitrage Trading wherein the HFT traders quickly identify such anomalies in the prices between the two trading venues and whichever trading venue the price is less, they buy stock at high speeds and sell in the other market where the price is slightly more and make profits. One more type of arbitrage trading is HFT traders gather all the information in other trading venues market volumes and quickly estimate precisely what will be the next NBBO before the NBBO can be announced and place their orders in queue first and make profits continuously before every announcement of the NBBO. And the HFT traders keep repeating for every announcement of the NBBO. Because of this activity HFT traders are not only liquidity suppliers but also significant liquidity consumers adversely affecting the low-speed algorithmic traders. At the same time low speed algorithmic traders are depending on the HFT for the liquidity and prices. Because of this co-existence of HFT and low speed traders there exists a predator-prey relationship causing dissatisfaction among the low-speed traders. In this project we study and mathematically model a Low latency arbitrage trading eco-system and propose a solution to optimally minimize the low latency arbitrage trading without discouraging the HFT traders as they provide liquidity to the financial markets.
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