HFT-Races
Unverified Arbitrage strategy on Indices by ericbudish. BotFinder score 18 out of 100.
Code package to analyze high-frequency trading (HFT) races using financial-exchange message data, following Aquilina, Budish and O'Neill (2021).
Source: github
BotFinder analysis pending.
HFT-Races
HFT-Races This repository contains code for researchers, regulators or practitioners who wish to use financial-exchange message data to quantify latency arbitrage and study other aspects of speed-sensitive trading, following Matteo Aquilina, Eric Budish and Peter O’Neill, “Quantifying the High-Frequency Trading ‘Arms Race’”, Quarterly Journal of Economics, 2021 (hereafter, “ABO”). The Python code processes the user's message data, detects trading races, and outputs a race-level statistical dataset along with complementary trading data. The R code produces race summary statistics, tables and figures analogous to all reported results in ABO. We also provide a small artificial data set that can be used to understand the data structure and to test one's configuration. This code should be used in conjunction with the detailed documentation linked below. About Version 1.1 (November 2021). Please visit https://github.com/ericbudish/HFT-Races to check for updates. Documentation Please refer to ABO Code and Data Appendix for detailed documentation and instructions. Quick Start 1. Download and
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