2018
DOI: 10.1017/s0022109018001096
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Risk and Return in High-Frequency Trading

Abstract: We study performance and competition among firms engaging in high-frequency trading (HFT). We construct measures of latency and find that differences in relative latency account for large differences in HFT firms’ trading performance. HFT firms that improve their latency rank due to colocation upgrades see improved trading performance. The stronger performance associated with speed comes through both the short-lived information channel and the risk management channel, and speed is useful for various strategies… Show more

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Cited by 198 publications
(108 citation statements)
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“…Fourth, by analyzing Bund Futures trading, we complement research on HFT and fast trading in other assets, such as Kirilenko et al (2017) who use data from the U.S. E-mini futures market, Baron et al (2015) who use data from the Scandinavian equity market, and Biais et al (2016) who use data from the French equity market. Our results show that conclusions on the effects of HFT cannot necessarily be transferred from one market to another, but tends to be specific to the asset and the underlying market structures.…”
Section: Introductionmentioning
confidence: 99%
“…Fourth, by analyzing Bund Futures trading, we complement research on HFT and fast trading in other assets, such as Kirilenko et al (2017) who use data from the U.S. E-mini futures market, Baron et al (2015) who use data from the Scandinavian equity market, and Biais et al (2016) who use data from the French equity market. Our results show that conclusions on the effects of HFT cannot necessarily be transferred from one market to another, but tends to be specific to the asset and the underlying market structures.…”
Section: Introductionmentioning
confidence: 99%
“…4 First, HFTs' aggressive orders anticipate short-term price movements and contribute significantly to trading volume. For instance, Brogaard, Hendershott, and Riordan (2014) find that HFTs' aggressive orders predict price changes over very short horizons and account for 25% to 42% of trading volume depending on market capitalization (see also Baron, Brogaard, and Kirilenko (2014), Benos andSagade (2013), andKirilenko et al (2014) for similar evidence). Second, HFTs' aggressive orders are correlated with news such as market-wide returns, quote updates, macroeconomic announcements, E-mini price changes, and newswires items (see Brogaard, Hendershott, and Riordan (2014) and Zhang (2012)).…”
mentioning
confidence: 99%
“…For example, Clark‐Joseph (), Baron et al . (), and Kirilenko et al . () classify a trading account as a high‐frequency trader if its trading volume is relatively high but end‐of‐day inventory position is low compared to its trading volume.…”
Section: High‐frequency Trading: Definition Data and Typesmentioning
confidence: 86%