Trading strategies during circuit breakers and extreme market movements
By Michael A. Goldstein, Kenneth A. Kavajecz. 2004
148 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/d1d20125a6f66604557fccc5186cc62f61b5aba0
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
- Charles M. Jones
- Terrence Hendershott
- Shao‐Chi Chang
- Sheng-Syan Chen
- Yueh-hsiang Lin
- Robin K. Chou
- Peter Hoffmann
In Finance
- Albert J. Menkveld
- Charles M. Jones
- Terrence Hendershott
- Shao‐Chi Chang
- Sheng-Syan Chen
- Yueh-hsiang Lin
- Robin K. Chou
- Peter Hoffmann
Citations in the corpus
- Order Book Characteristics and the Volume-Volatility Relation: Empirical Evidence from a Limit Order Market (2006, unknown): “In any case, theoretical models by Shalen (1993) (asymmetric information) and Harris and Raviv (1993) (symmetric information) show that dispersion of beliefs will intensify the volume-volatility relation, by increasing both trading volume and volatility.”
- Weather and intraday patterns in stock returns and trading activity (2008, background): “Moreover, market depth is found to be negatively related to volatility in the literature (Bessembinder and Seguin, 1993; Ahn et al., 2001; Goldstein and Kavajecz, 2004).”
- Does Algorithmic Trading Improve Liquidity (2011, background): “For example, the evidence in Goldstein and Kavajecz (2004) indicates that humans are used more often when markets are illiquid and volatile.”