Premium
RISK METRICS AND FINE TUNING OF HIGH‐FREQUENCY
TRADING STRATEGIES
Author(s) -
Cartea Álvaro,
Jaimungal Sebastian
Publication year - 2015
Publication title -
mathematical finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.98
H-Index - 81
eISSN - 1467-9965
pISSN - 0960-1627
DOI - 10.1111/mafi.12023
Subject(s) - high frequency trading , trading strategy , proxy (statistics) , momentum (technical analysis) , expected utility hypothesis , econometrics , trend following , algorithmic trading , economics , limit (mathematics) , asset (computer security) , order (exchange) , business , financial economics , computer science , finance , mathematics , mathematical analysis , computer security , machine learning
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.