Algorithmic Trading and the Market for Liquidity

By Terrence Hendershott, Ryan Riordan. Journal of Financial and Quantitative Analysis, 2013

383 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/1e91aea127ea50d8f944a045d22932aef26436fe

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

In Finance

Citations in the corpus

International Evidence on Algorithmic Trading (2015, neutral): “For example, Hendershott and Riordan (2013) examine 30 Deutscher Aktien Index stocks on the Deutsche Boerse in January of 2008.”
Low-latency trading $ (2013, neutral): “Early papers on algorithmic trading sought to establish stylized facts related to algorithmic activity (Prix, Loistl, and Huetl, 2007; Gsell, 2009; Gsell and Gomber, 2009; Groth, 2009), while later research evaluated its impact on the market (Chaboud, Hjalmarsson, Vega and Chiquoine, 2013; Hendersho”
High Frequency Trading and Price Discovery (2014, background): “Hendershott and Riordan (2013) focus on the monitoring capabilities of AT and study the relationship between AT and liquidity supply and demand dynamics.”
Risk and Return in High-Frequency Trading (2018, neutral): “We estimate the following probit regression, which in essence follows the setup of Hendershott and Riordan (2013) and Brogaard et al. (2015): Pr[𝐻𝐻𝑃𝑃𝐻𝐻𝐿𝐿 𝐻𝐻𝐻𝐻𝑇𝑇 𝑇𝑇𝑟𝑟𝑃𝑃𝑇𝑇𝑃𝑃𝐻𝐻] = Φ[𝑃𝑃 + 𝛽𝛽 𝑁𝑁𝑃𝑃𝑁𝑁𝐻𝐻 + 𝛾𝛾′𝑃𝑃𝑇𝑇𝑃𝑃𝐿𝐿𝑟𝑟𝑇𝑇𝐴𝐴𝐻𝐻 + 𝑆𝑆𝐿𝐿𝑇𝑇𝑃𝑃𝑅𝑅…”
The Economics of High-Frequency Trading: Taking Stock (2016, background): “Hendershott & Riordan (2013) show that ATs are quick to post limit orders when spreads are wide, but take limit orders when spreads are narrow.”
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, positive): “…summary, this stream of the literature concludes that automated trading strategies improve liquidity (Hendershott et al. (2011), ouck and Saar (2011)), are highly profitable (e.g. 6 Menkveld (2012)), and contribute to price discovery (e.g. Hendershott and Riordan (2012), Hendershott et al. (2012)).”