High Frequency Trading and Price Discovery

By Jonathan Brogaard, Terrence Hendershott, Ryan Riordan. Social Science Research Network, 2014

1,100 citations recorded by the source corpus.

We examine the role of high-frequency traders (HFTs) in price discovery and price efficiency. Overall HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the highest volatility days. This is done through their liquidity demanding orders. In contrast, HFTs' liquidity supplying orders are adversely selected. The direction of HFTs' trading predicts price changes over short horizons measured in seconds. The direction of HFTs' trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/90ac67bdffd4278ee0efe6fc54918c0dd50fe978

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Citations in the corpus

What Is the Optimal Trading Frequency in Financial Markets (2017, background): “In contrast, Brogaard, Hendershott, and Riordan (2014) report that the relative bid-ask spreads of large, medium, and small U.S. stocks are 4.7, 14.6 and 38.1 basis points, respectively.”
Quantifying the High-Frequency Trading "Arms Race" (2021, neutral): “Brogaard, Hendershott, and Riordan (2014) and Baron et al. (2019) compute a large set of HFT firms’ overall profits on specific exchanges (in NASDAQ data and Swedish data, respectively), and Baron et al. (2019) show that relatively faster HFTs earn significantly greater profits, but neither paper…”
News Trading and Speed (2012, neutral): “β t = 1 1− t σu (Σ0 + σ2 v) 1 ( 1 + σ 2 e σ2 v f )1/2 1 + (1− f)σ2 v Σ0 1 + σ 2 e σ2 v + σ 2 e σ2 v f 2 + σ 2 e σ2 v + σ 2 e σ2 v f  , (19)”
International Evidence on Algorithmic Trading (2015, neutral): “(see Hendershott and Riordan, 2009, or Menkveld, 2010), they are based on relatively small samples. Even the most comprehensive study so far, Hendershott, Jones, and Menkveld (2010), does not use data beyond 2006 and its main analysis is based on a change in trading protocol that happened in 2003.”
News-Driven Return Reversals: Liquidity Provision Ahead of Earnings Announcements (2014, background): “…composition of liquidity providers such as increased involvement from high-frequency traders that attempt to avoid holding inventories overnight (Brogaard, Hendershott, and Riordan, 2013).11 While disentangling these potential explanations is beyond the scope of this paper, the figure…”
The Empirical Analysis of Liquidity (2014, result): “This is consistent with Brunnermeier and Pedersen [2009] who show that funding liquidity dries up when volatility is high.”
The Diversity of High-Frequency Traders (2013, background): “Given that Hendershott et al. (2011) and Boehmer et al.”
The Flash Crash: High-Frequency Trading in an Electronic Market (2017, neutral): “The closest studies to ours are Brogaard, Hendershott, and Riordan (2016), who study high-frequency traders as classified by NASDAQ during the 2008 short-sale ban and Brogaard et al. (2016), who study the activity of high-frequency traders as classified by NASDAQ around extreme price movements.”