High-Frequency Traders and Price Informativeness during Earnings Announcements

Review of Accounting Studies, Forthcoming

63 Pages Posted: 9 Jul 2016 Last revised: 26 May 2020

See all articles by Neil Bhattacharya

Neil Bhattacharya

Singapore Management University - School of Accountancy; Southern Methodist University (SMU) - Accounting Department

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business

Xu (Frank) Wang

Saint Louis University - Chaifetz School of Business

Date Written: May 22, 2020

Abstract

Prompted by concerns that high frequency traders (HFTs) reap unfair advantages over other traders by using faster trading technologies, regulators are contemplating measures to slow down equity markets. Currently, HFTs account for a significant fraction of the total market volume. Although regulatory proposals are aimed at curbing HFTs’ ultra-low-latency activities, research suggests that HFTs play various other roles in markets, including liquidity provision as voluntary market makers. However, little is known about their role in incorporating firm-specific fundamental information into prices. Employing a novel dataset that identifies trades by HFTs and non-HFTs, we investigate whether HFTs facilitate incorporation of longer-term fundamental information revealed via earnings announcements. We find that earnings response coefficients are larger and abnormal price impact of trades is lower when HFTs trade more following earnings announcements, suggesting that HFTs facilitate efficient assimilation of earnings news. HFTs also enhance the forecasting capabilities of financial analysts; specifically forecast dispersion is lower and forecast revision speed is faster for announcements with greater HFT presence. Furthermore, HFT participation increases return synchronicity around earnings announcements when multiple firms in the same industry announce earnings on the same day, suggesting that HFTs help incorporate relevant industry information. This effect arises from HFTs’ liquidity supplying function. We address the endogenous preference of HFTs for large and liquid stocks by including multiple controls for size and liquidity, implementing abnormal or change specification for the price impact tests, and performing pre-treatment placebo tests for all of our analyses.

Keywords: High Frequency Trading; earnings announcements; earnings response coefficient; price impact of trades; analyst forecast

JEL Classification: D53; G12; G14; M41

Suggested Citation

Bhattacharya, Neil and Chakrabarty, Bidisha and Wang, Xu (Frank), High-Frequency Traders and Price Informativeness during Earnings Announcements (May 22, 2020). Review of Accounting Studies, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2806559 or http://dx.doi.org/10.2139/ssrn.2806559

Neil Bhattacharya (Contact Author)

Singapore Management University - School of Accountancy ( email )

60 Stamford Road
Singapore 178900
Singapore

Southern Methodist University (SMU) - Accounting Department ( email )

United States
214-768-3082 (Phone)
214-768-4099 (Fax)

HOME PAGE: http://www.cox.smu.edu

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business ( email )

3674 Lindell Blvd
St. Louis, MO MO 63108-3397
United States
3149773607 (Phone)
3149771479 (Fax)

HOME PAGE: http://business.slu.edu/departments/finance/faculty-staff/bidisha-chakrabarty

Xu (Frank) Wang

Saint Louis University - Chaifetz School of Business ( email )

3674 Lindell Blvd
St. Louis, MO 63108-3397
United States

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