Adverse Selection and Competitive Market Making: Empirical Evidence from a Limit Order Market
By Patrik Sandås. 2001
200 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/f35c99499ab4589c865811e76d9db67bce03b249
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
- Christine A. Parlour
- Duane J. Seppi
- J. D. Farmer
- Stacy Williams
- Mark McDonald
- Daniel J. Fenn
- Sam D. Howison
- M. Gould
In Finance
- Duane J. Seppi
- J. D. Farmer
- Szabolcs Mike
- Sam D. Howison
- Stacy Williams
- Mark McDonald
- Daniel J. Fenn
- M. A. Porter
In Management Science and Operations Research
- Christine A. Parlour
- Chester Spatt
- Lawrence R. Glosten
- Szabolcs Mike
- Stacy Williams
- J. D. Farmer
- Mark McDonald
- Bruno Biais
Citations in the corpus
- Estimating the Gains from Trade in Limit Order Markets (2006, unknown): “Hollifield, Miller, and Sand̊as (2003) show that the optimal order submission strategy has a monotonicity property.”
- Economic News and the Impact of Trading on Bond Prices (2004, background): “For example, Sandas (2001) finds negative order processing costs in the Stockholm Stock Exchange’s limit-order market, and argues that these costs could reflect rational behavior in a setting where traders make heterogeneous valuations of the asset.”
- Equilibrium in a Dynamic Limit Order Market (2005, unknown): “Sandås (2001) uses data from the Stockholm exchange to develop and test static restrictions implied by Glosten (1994).”
- Liquidity-Based Competition for Order Flow (2003, background): “…Hillion, and Spatt (1995), Greene (1996), Handa and Schwartz (1996), Harris and Hasbrouck (1996), and Kavajecz (1999) describe the basic empirical properties of limit orders and Hollifield, Miller, and Sandas (2002) and Sandas (2001) carry out structural estimations. and submits market orders.”
- Order Book Characteristics and the Volume-Volatility Relation: Empirical Evidence from a Limit Order Market (2006, unknown): “On the other hand, Sand̊as (2001) tests the predictions in Glosten (1994) in the Swedish market, which is a pure limit order market similar to the Norwegian market examined in this study.”
- An empirical behavioral model of liquidity and volatility (2007, background): “A small sample is (Demsetz 1968, Stoll 1978, Glosten 1988, Glosten 1992, Easley and O’Hara 1992, Foucault, Kadan and Kandel 2005, Sandas 2001).”
- Technology and Liquidity Provision: The Blurring of Traditional Definitions (2009, unknown): “The shape of the book under these circumstances is considered theoretically in Glosten (1994) and empirically in Sandas (2001).”
- Limit order books (2010, background): “In a study of the Stockholm Stock Exchange, Sandås (2001) reported that order flows at time t were conditional on both L(t) and on previous order flows.”
- Traders’ choice between limit and market orders: evidence from NYSE stocks (2003, background): “... have documented how limit-order trading reacts to market conditions include Hollifield et al. (1999), who show that changes in the relative profitability of limit and market orders are important for explaining the empirical variation in order submission rates in the Stockholm Stock Exchange; Gol”
- Hidden and Displayed Liquidity in Securities Markets with Informed Liquidity Providers (2013, background): “See Sandas (2001) for evidence that liquidity supply is not perfectly competitive in equities trading.”
- Order book approach to price impact (2003, methodology): “An analysis of the limit order book of the Stockholm Stock Exchange (Sandas 2001) suggests that the virtual price impact calculated from the order book is significantly larger than what is expected from a regression model.”
- A Dynamic Model of the Limit Order Book (2009, unknown): “This is consistent with the empirical literature, which shows that limit order traders make positive profits: see Sandås (2001) for the case of Stockholm Stock Exchange and Harris and Hasbrouck (1996) for NYSE’s SuperDOT system.”
- Liquidity Cycles and Make/Take Fees in Electronic Markets (2013, background): “In a more complex model, the upper bound could derive from an upward marginal cost of liquidity provision due, for instance, to exposure to informed trading as in Glosten (1994) or Sandås (2001).”