Risk Metrics and Fine Tuning of High Frequency Trading Strategies

Cartea, ÁLvaro, and Sebastian Jaimungal. "RISK METRICS AND FINE TUNING OF HIGH‐FREQUENCY TRADING STRATEGIES." Mathematical Finance (2013).

37 Pages Posted: 26 Feb 2012 Last revised: 27 Apr 2015

Álvaro Cartea

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

Sebastian Jaimungal

University of Toronto - Department of Statistics

Multiple version iconThere are 2 versions of this paper

Date Written: February 24, 2012

Abstract

We propose risk metrics to assess the performance of High Frequency (HF) trading strategies that seek to maximize profits from making the realized spread where the holding period is extremely short (fractions of a second, seconds or at most minutes). The HF trader maximizes expected terminal wealth and is constrained by both capital and the amount of inventory that she can hold at any time. The risk metrics enable the HF trader to fine tune her strategies by trading off different metrics of inventory risk, which also proxy for capital risk, against expected profits. The dynamics of the midprice of the asset are driven by information flows which are impounded in the midprice by market participants who update their quotes in the limit order book. Furthermore, the midprice also exhibits stochastic jumps as a consequence of the arrival of market orders that have an impact on prices which can give rise to market momentum (expected prices to trend up or down). The HF trader's optimal strategy incorporates a buffer to cover adverse selection costs and manages inventories to maximize the expected gains from market momentum.

Keywords: Algorithmic Trading, High Frequency Trading, Momentum Trading, Market Impact, Adverse Selection, Risk Metrics, Inventory Risk

JEL Classification: C6, C61, D81, G1, G13

Suggested Citation

Cartea, Álvaro and Jaimungal, Sebastian, Risk Metrics and Fine Tuning of High Frequency Trading Strategies (February 24, 2012). Cartea, ÁLvaro, and Sebastian Jaimungal. "RISK METRICS AND FINE TUNING OF HIGH‐FREQUENCY TRADING STRATEGIES." Mathematical Finance (2013).. Available at SSRN: https://ssrn.com/abstract=2010417 or http://dx.doi.org/10.2139/ssrn.2010417

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

Sebastian Jaimungal

University of Toronto - Department of Statistics ( email )

100 St. George St.
Toronto, Ontario M5S 3G3
Canada

HOME PAGE: http://www.utstat.utoronto.ca/sjaimung

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