International Evidence on Algorithmic Trading
By Ekkehart Boehmer, Kingsley Y. Fong, Julie Wu. 2015
269 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/2dde378b30aa5acadbfed3ee3483a512f547a6d9
Citations in the corpus
- The Diversity of High-Frequency Traders (2013, unknown): “Given that Hendershott et al. (2011) and Boehmer et al. (2011) base their AT proxies on quoting activity, our evidence may indicate that the market quality effects that they associate with AT is more likely to be effects of market making than with other AT strategies.”
- A Dynamic Limit Order Market with Fast and Slow Traders (2014, unknown): “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).”
- Need for Speed? Exchange Latency and Liquidity (2016, unknown): “Boehmer, Fong, and Wu (2015) study an international sample of colocation introductions and document that they are followed by spread declines.”
- High‐Frequency Trading and Market Performance (2020, unknown): “(16)Other empirical work similarly argues that HFT improves price informativeness (Brogaard, 2010; Carrion, 2013; Brogaard et al., 2014; Chaboud et al., 2014; Conrad et al., 2015; Boehmer et al., 2018).”
- High frequency trading and the new market makers (2013, unknown): “Boehmer, Fong, and Wu (2012) study a 2001-2009 international sample and find that greater AT intensity improves liquidity and informational efficiency, and increases volatility The remainder of the paper is structured as follows.”