High Frequency Trading

Paper Session

Friday, Jan. 6, 2017 2:30 PM – 4:30 PM

Sheraton Grand Chicago, Chicago Ballroom VI
Hosted By: American Finance Association
  • Chair: Mao Ye, University of Illinois-Urbana-Champaign

Rent Seeking by Low Latency Traders: Evidence from Trading on Macroeconomic Announcements

Tarun Chordia
,
Emory University
Clifton Green
,
Emory University
Badrinath Kottimukkalur
,
Emory University

Abstract

Prices of stock index exchange traded funds and index futures respond to macroeconomic announcement surprises within a tenth of a second, with trading intensity increasing ten-fold in the quarter second following the news release. Profits from trading quickly on announcement surprises are relatively small and decline in recent years. Trading profits also decrease with quote intensity. The speed of information incorporation increases in recent years and order flow becomes less informative, consistent with prices responding to news directly rather than indirectly through trading. Our evidence is consistent with increasing competition among low latency traders, which mitigates concerns about their speed advantage.

Data Abundance and Asset Price Informativeness

Jerome Dugast
,
University of Luxembourg
Thierry Foucault
,
HEC Paris

Abstract

Information processing filters out the noise in raw data but it takes time. Hence, filtered signals are available only with a lag relative to unfiltered signals. As the cost of raw data declines, unfiltered signals become cheaper to produce and more investors trade on them. As a result, asset prices reflect unfiltered signals more quickly. This effect decreases the value of processing information unless unfiltered signals are very noisy. Thus, a decline in the cost of raw data can trigger a decline in the number of investors trading on filtered signals and, for this reason, the informativeness of asset prices in the long run.

Correlated High-Frequency Trading

Ekkehart Boehmer
,
Singapore Management University
Dan Li
,
Hong Kong University of Science and Technology
Gideon Saar
,
Cornell University

Abstract

In this paper, we examine product differentiation in the high-frequency trading (HFT) industry by looking at the correlated behavior of HFT firms. Since the “product” of an HFT firm is a proprietary trading strategy, we use a principal component analysis to detect three underlying strategies that are common to multiple HFT firms. We show that the short-horizon volatility of most stocks loads negatively on the extent of market-wide competition between HFT firms, and document a negative relation between HFT competition and market concentration, presenting evidence that smaller trading venues are more viable when HFT competition is higher.

Fast Traders Make a Quick Buck: The Role of Speed in Liquidity Provision

Markus Baldauf
,
University of British Columbia
Joshua Mollner
,
Northwestern University

Abstract

We study the consequences of information arrival for market outcomes when both high-frequency and slower traders provide liquidity. We present a model that predicts faster traders achieve a relative increase in profits obtained from liquidity provision following a news event through (i) avoiding adverse selection by canceling mispriced quotes, and (ii) winning the race to post updated quotes. We find strong support for these model predictions using data from the Toronto Stock Exchange. The identification strategy is based on an unanticipated news event in which the Twitter feed of the Associated Press falsely reported a terrorist attack.
Discussant(s)
Jonathan Brogaard
,
University of Washington
Laura Veldkamp
,
New York University
Dacheng Xiu
,
University of Chicago
Ioanid Rosu
,
HEC Paris
JEL Classifications
  • G1 - General Financial Markets