Limit order book as a market for liquidity

By Thierry Foucault, Ohad Kadan, Eugene Kandel. 2001

627 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/3e2327f8f543dd1718c85a064f5692ae0adccb40

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Citations in the corpus

Informed Traders and Limit Order Markets (2008, background): “Foucault, Kadan, and Kandel (2005) characterize equilibrium in a dynamic limit order book with private values and differences in time preferences.”
Limited Attention and the Allocation of Effort in Securities Trading (2008, background): “…and ask quotes conditional on their level of inventory risk and the probability of informed trade.7 In addition, models of limit order markets suggest that limit book dynamics will depend on order arrival rates and the patience of traders (see Foucault, Kadan, and Kandel (2005) and Rosu (2006)).”
Statistical Modeling of High-Frequency Financial Data (2011, background): “…interplay between order ﬂow, liquidity and price dynamics [15, 55, 29] and might help bridge the gap between market microstructure theory [12, 51, 30, 33, 45, 54]–which has provided useful insights by focusing on models of price formation mechanism in stylized equilibrium settings– and ‘black…”
Limit Order Markets: A Survey 1 (2008, background): “This sequential undercutting endogenizes one of the assumptions in Foucault, Kadan, and Kandel (2005).”
Estimating the Gains from Trade in Limit Order Markets (2006, neutral): “…prices, unlike the traders in Parlour (1998); the traders’ limit orders in our model may last for multiple periods, unlike the limit orders in Foucault (1999); and limit Estimating the Gains from Trade 2755 orders in our model may be canceled, unlike the limit orders in Foucault et al. (2005).”
The 'Make or Take' Decision in an Electronic Market: Evidence on the Evolution of Liquidity (2005, neutral): “Theoretical analyses of limit orders include Cohen, Maier, Schwartz, and Whitcomb [1981]; Rock [1990]; Angel [1994]; Glosten [1994]; Kumar and Seppi [1994]; Chakravarty and Holden [1995]; Parlour [1998]; Harris [1998]; Foucault [1999]; Parlour and Seppi [2001]; and Foucault, Kadan, and Kandel [2001]”
Do Dark Pools Harm Price Discovery (2013, neutral): “Models that rely on nonanonymity (explicitly or implicitly) to filter informed traders include those of Seppi (1990), Benveniste, Marcus, and Wilhelm (1992), Easley, Keifer, and O’Hara (1996), Madhavan and Cheng (1997), Grammig, Schiereck, and Theissen (2001), and Garfinkel and Nimalendran (2003), a”
Modelling high-frequency limit order book dynamics with support vector machines (2015, background): “…and typically unvalidated mathematical assumptions on models, parameters may be unobservable, and the intensive computation required by statistical methods makes them difﬁcult to be deployed in real world environments (Parlour 1998, Biais et al. 2000, Bouchaud et al. 2002, Foucault et al. 2005).”
Testing Stylized Facts of Bitcoin Limit Order Books (2019, background): “Focusing on levels deeper in the LOB, Gomber et al. (2015) study liquidity costs for large volumes and their reaction after liquidity shocks in the form of large trades. Gopikrishnan et al. (2000) focus on statistics of trades from LOBs for many major US stocks, and report power laws in the distribu”
How Markets Slowly Digest Changes in Supply and Demand (2008, positive): “A sell immediately following a buy, on the other hand, has an enhanced impact equal to R1 = θ(1 + ρ), in such a way that the conditional average impact of the next trade is zero: p+R1 + (1− p+)R1 ≡ 0 Gerig [2007]. This is the “asymmetric liquidity” effect explained above (Lillo and Farmer [2004], Fa”
Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models (2011, neutral): “Based on game-theoretical dynamic models, Foucault (1999) and Foucault et al. (2005) argue that the bid-ask spread is the dominant parameter for the decision between different order types on stock markets.”
New low-frequency spread measures (2009, neutral): “, 1993), (2) changes in the mix of patient versus impatient traders causing variation in the aggressiveness of undercutting the existing spread (Foucault et al., 2005), (3) stochastic volatility, which causes time-variation in the inventory cost component and time-variation in the noise/”
Limit-Order Submission Strategies under Asymmetric Information (2010, methodology): “A higher arrival rate should lower expected time-toexecution (Foucault et al., 2005) and thus lead to less aggressive order submissions.”