The Shadow Price of Latency: Improving Intraday Fill Ratios in Foreign Exchange Markets

42 Pages Posted: 18 Jun 2018 Last revised: 25 Nov 2018

See all articles by Álvaro Cartea

Álvaro Cartea

University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance

Leandro Sánchez-Betancourt

University of Oxford

Date Written: August 1, 2018

Abstract

Latency is the time delay between an exchange streaming market data to a trader, the trader processing information and deciding to trade, and the exchange receiving the order from the trader. Liquidity takers face a moving target problem as a consequence of their latency in the marketplace. They send market orders with a limit price that aim at a price and quantity they observed in the limit order book (LOB), and by the time their order is processed by the exchange, prices could have worsened, so the order may not be filled, or prices could have improved, so the order is filled at a better price. In this paper we provide a model to compute the price that liquidity takers would be willing to pay to reduce their latency in the marketplace. To this end, we derive a latency-optimal strategy that specifies the limit price of liquidity taking orders to increase the chances of filling orders if, due to latency, prices or quantities in the LOB have worsened. The latency-optimal strategy balances the tradeoff between the costs of walking the LOB and targeting a desired percentage of filled orders over a period of time. We employ the cost of improving fills with the latency-optimal strategy to compute the shadow price of latency. Finally, we use a proprietary data set of foreign exchange (FX) to compute the maximum price that a FX trader would be willing to pay for co-location and hardware to reduce their latency in the marketplace.

Keywords: latency, fill ratio, high-frequency trading, algorithmic trading

Suggested Citation

Cartea, Álvaro and Sánchez-Betancourt, Leandro, The Shadow Price of Latency: Improving Intraday Fill Ratios in Foreign Exchange Markets (August 1, 2018). Available at SSRN: https://ssrn.com/abstract=3190961 or http://dx.doi.org/10.2139/ssrn.3190961

Álvaro Cartea (Contact Author)

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Leandro Sánchez-Betancourt

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

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