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

Chordia, Tarun; Green, T Clifton; Kottimukkalur, Badrinath

doi:10.1093/rfs/hhy025

Cited by 49 publications

(28 citation statements)

References 27 publications

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“…The effect could be caused by HFTs reacting faster to a signal non-HFTs also observe (Von Beschwitz, Keim, andMassa 2015, Chordia, Green, andKottimukkalur 2018). But the most probable signals they would both utilize in close succession do not fully explain the results (e.g., past returns, news articles, analyst forecasts and recommendations, management guidance, and form 8-K filings).…”

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confidence: 91%

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Hirschey

2021

Management Science

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This study provides evidence that high-frequency traders (HFTs) identify patterns in past trades and orders that allow them to anticipate and trade ahead of other investors’ order flow. Specifically, HFTs’ aggressive purchases and sales lead those of other investors, and this effect is stronger at times when it is more difficult for non-HFTs to disguise their order flow. Consistent with some HFTs being more skilled or more focused on anticipatory strategies, I show that trades from a subset of HFTs consistently predict non-HFT order flow the best. The results are not explained by HFTs reacting faster to news or past returns, by contrarian or trend-chasing behavior by non-HFTs, or by trader misclassification. These findings support the existence of an anticipatory trading channel through which HFTs increase non-HFT trading costs. This paper was accepted by Karl Diether, finance.

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confidence: 91%

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Hirschey

2021

Management Science

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“…Chaboud et al (2014) find that HFTs improve price efficiency through lower return autocorrelations and fewer arbitrage opportunities. Chordia, Green, and Kottimukkalur (2018) show that high-frequency market orders impound information quickly following macroeconomic announcements. 4 A message refers to any instruction received by an exchange; a message includes marketable orders, limit order placements, limit order cancellations, and limit order replacements.…”

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confidence: 99%

“…() find that HFTs improve price efficiency through lower return autocorrelations and fewer arbitrage opportunities. Chordia, Green, and Kottimukkalur () show that high‐frequency market orders impound information quickly following macroeconomic announcements.…”

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confidence: 99%

Price Discovery without Trading: Evidence from Limit Orders

Brogaard¹,

Hendershott²,

Riordan

2019

The Journal of Finance

179

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We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to changes in HFTs’ behavior. Consistent with adverse selection arising from faster reactions to public information, HFTs’ informational advantage is partially explained by public information.

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“…Patell and Wolfson (1984) observe the first reaction to corporate announcements of U.S. listed firms in 1976-1977 in the first few minutes following the announcements, while significant trading profits occur overnight or at the opening of the next trading day. Chordia et al (2018), on the other hand, show that S&P 500 exchange-traded fund and E-mini S&P 500 futures contract prices react to macroeconomic surprise news in 2008-2014 within the first five milliseconds where trading intensity rises by more than 100-fold. Reaching beyond the scope of this study, HFT related topics include but not limited to its impacts on market quality, i.e., on liquidity (Hasbrouck and Saar, 2013;Brogaard et al, 2014;Brogaard et al, 2017) and on volatility (Brogaard, 2010;Zhang, 2010;Chaboud et al, 2014), HFT effects on price discovery (Carrion, 2013;Menkveld, 2013;Conrad et al, 2015), HFT through market downturns and crashes (Kirilenko et al, 2017;Brogaard et al, 2017; "high frequency trading" "algorithmic trading" "stock exchange" "stock market" Madhavan, 2012;McInish et al, 2014), HFT impacts on other participants: crowding out effect (Malinova et al, 2013;Jones, 2013;Hoffmann, 2014), adverse selection effect (Cartea and Penalva, 2012;Biais et al, 2015;Egginton et al, 2016), welfare effects (Boehmer et al, 2015;Stiglitz, 2014;Budish et al, 2015), vast HFT investments (Menkveld, 2013;Biais et al, 2015;Budish et al, 2015), HFT competition (Baron et al, 2019;Brogaard and Garriott, 2019), HFT profits (Malinova et al, 2013;Scholtus et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

Ersan

Dalgic

Ekinci

et al. 2021

Alanya Akademik Bakış

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High-frequency trading (HFT) has been dominating the activity in developed financial markets in the last two decades. Despite its recent formation, the literature on the impacts of HFT on financial markets and participants is broad. However, there are ongoing debates and unanswered questions within many subtopics. We survey through the research towards HFT effects on liquidity in an attempt to explain the coexistence of evidence regarding both the positive and the negative impacts of HFT. We name two main factors leading to mixed results. Former concerns the negative market conditions such as intraday shocks, through which HFT trading patterns may sharply change. Latter regards the certain characteristics of HFT liquidity provision with the potential to present externalities for the market.2 BYX exchange utilized by CBOE reduced order processing times by around sevenfold from 445 microseconds in 2009 to 64 microseconds in 2018 (Baldauf and Mollner, 2020). HFT firms are in an arms race that leads them to send data from exchanges to electronic traders in latencies as small as 4 nanoseconds (Sprothen, 2016). 3 Throughout the text, we use 'high-frequency trading (trader)' and 'low-latency trading (trader)' interchangeably. We use 'HFT' as the acronym for high-frequency trading; 'HFTs' as the acronym for high-frequency traders; and non-HFTs as the acronym for low-frequency traders (traders other than high-frequency traders).

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

Cited by 49 publications

References 27 publications

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Price Discovery without Trading: Evidence from Limit Orders

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

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