Low-latency trading $
By Joel Hasbrouck, Gideon Saar. 2013
844 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/54272142d45fa3b3387ab7ef1887da05cd5afc90
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Albert J. Menkveld
- Ryan Riordan
- Markus Baldauf
- Joshua Mollner
- Jonathan Brogaard
- Terrence Hendershott
- Carole Comerton-Forde
- Tālis J. Putniņš
In Finance
- Albert J. Menkveld
- Ryan Riordan
- Joshua Mollner
- Markus Baldauf
- Jonathan Brogaard
- Tālis J. Putniņš
- Carole Comerton-Forde
- Terrence Hendershott
Citations in the corpus
- News Trading and Speed (2012, neutral): “β t = 1 1− t σu Σ 1/2 0 ( 1 + σ2 vσ 2 e Σ0(σ(2) v + σ 2 e) )1/2 , (13) γ = 0, (14) λ = Σ 1/2 0 σu ( 1 + σ2 vσ 2 e Σ0(σ(2) v + σ 2 e) )1/2 , (15)”
- High‐Frequency Trading and Market Performance (2020, positive): “…that enhanced HFT reduces the spread (or generally improves liquidity) is provided by Brogaard (2010), Hendershott, Jones, and Menkveld (2011), Hasbrouck and Saar (2013), Menkveld (2013), Frino, Mollica, and Webb (2014), Brogaard et al. (2015), Conrad, Wahal, and Xiang (2015), Boehmer, Fong,…”
- The Economics of High-Frequency Trading: Taking Stock (2016, background): “Hasbrouck & Saar (2013) provide the most detailed account of active limit-order managements.”
- A visual analytics approach to understanding cycling behaviour (2012, neutral): “The test liquids used in the majority of the existing experimental studies are water and ethanol and only a few experimental works have examined actual fuels such as Diesel oil, which is a widely used liquid in internal combustion engines and is also a focus of the current study.”
- A Dynamic Limit Order Market with Fast and Slow Traders (2014, neutral): “Several empirical papers (see e.g. Hendershott et al. (2011), Boehmer et al. (2012), and Hasbrouck and Saar (2011)) have documented a negative relationship between algorithmic trading and traditional measures of market liquidity (e.g. quoted and effective spreads).”
- Micro-price trading in an order-driven market (2014, background): “Although there is no steadfast consensus, the adoption of automated and algorithmic trading appears to have increased the quality of markets [20]–[22].”
- Zero-Commission Individual Investors, High Frequency Traders, and Stock Market Quality (2021, neutral): “Strategic runs, as defined in Hasbrouck and Saar (2013), are chains of consecutive order submission, cancellations, and executions with identical order sizes on the same side of the order book, where follow-up submissions occur within 100 milliseconds of each order cancellation.”
- Every Cloud Has a Silver Lining: Fast Trading, Microwave Connectivity, and Trading Costs (2020, background): “While some studies report that the relation is negative (Hasbrouck and Saar, 2013; Brogaard, Hendershott and Riordan, 2014), others find it to be positive (Boehmer, Fong and Wu, 2015).”
- The Flash Crash: High-Frequency Trading in an Electronic Market (2017, neutral): “Our approach also differs from studies that attempt to infer the behavior of high frequency traders from aggregate market data (see Hendershott, Jones, and Menkveld (2011), Hasbrouck and Saar (2013), and Conrad, Wahal, and Xiang (2015), inter alia).”
- High-Frequency Trading and Extreme Price Movements (2018, neutral): “In modern markets high frequency traders (HFTs) play an important, if not the dominant, role in providing liquidity (Hasbrouck and Saar, 2013; Menkveld, 2013; Malinova, Park and Riordan, 2014, Conrad, Wahal and Xiang, 2015).”
- A Dysfunctional Role of High Frequency Trading in Electronic Markets (2012, neutral): “[3]; Hasbrouck and Saar [11]; Hendershott et al.”