More Statistical Properties of Order Books and Price Impact

By Marc Potters, Jean-Philippe Bouchaud. 2002

314 citations recorded by the source corpus.

We investigate present some new statistical properties of order books. We analyse data from the Nasdaq and investigate (a) the statistics of incoming limit order prices, (b) the shape of the average order book, and (c) the typical life time of a limit order as a function of the distance from the best price. We also determine the ‘price impact’ function using French and British stocks, and find a logarithmic, rather than a power-law, dependence of the price response on the volume. The weak time dependence of the response function shows that the impact is, surprisingly, quasi-permanent, and suggests that trading itself is interpreted by the market as new information.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/c28061927061331c7c813ba4a8fae7a7c7217e0f

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Citations in the corpus

An empirical behavioral model of liquidity and volatility (2007, unknown): “[57] Potters, M.”
Fluctuations and response in financial markets: the subtle nature of ‘random’ price changes (2003, unknown): “7 However, other effects are probably important to understand this concavity, such as the conditioning of large market orders to the size of the order book— see [7, 33].”
What really causes large price changes? (2003, background): “tical system, which can be treated using mathematical methods from statistical mechanics [5, 6, 13, 18, 56, 58], markets are far from the thermodynamic limit, and display strong finite size effects.”
High-frequency trading in a limit order book (2008, background): “One of the important achievements of this literature has been to explain the statistical properties of the limit order book (see Bouchaud et al. 2002, Luckock 2003, Potters and Bouchaud 2003, Smith et al. 2003).”
Econophysics: Empirical facts and agent-based models (2009, unknown): “Many subsequent papers offer complementary empirical findings and modeling, e.g. Gopikrishnan et al. (2000a), Challet and Stinchcombe (2001), Maslov and Mills (2001), Bouchaud et al. (2002), Potters and Bouchaud (2003).”
No‐arbitrage implies power‐law market impact and rough volatility (2018, background): “s exists a macroscopic permanent market impact function and the convergence of the sequence (MIT(f;)) T0 is equivalent to that of (TMI T(f;)) T0. Motivated by the empirical results on market impact [2, 6, 16, 23, 26] discussed in the introduction, we make the following natural assumption. Assumption”
Market Impacts and the Life Cycle of Investors Orders (2014, methodology): “in (Potters and Bouchaud, 2003) and used by other authors before us (Gatheral, 2010; Bouchaud et al.”
The Long Memory of the Efficient Market (2003, unknown): “[8] Bouchaud, J.-P., Y. Gefen, M. Potters, and M. Wyart , 2004, Fluctuations and response in financial markets: the subtle nature of ’random’ price changes, Quantitative Finance 4 176-190.”
Limit order books (2010, methodology): “On both the Paris Bourse and NASDAQ (Potters and Bouchaud, 2003), a logarithmic functional form was found to provide a better fit to φm than was a power-law relationship.”
The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows (2007, methodology): “The estimation of the Hill exponent gives values comparable with those estimated empirically by Zovko and Farmer (2002) and Potters and Bouchaud (2003).”
A Hamilton-Jacobi-Bellman approach to optimal trade execution (2011, unknown): “AMS Classification 65N06, 93C20”
Optimal execution strategies in limit order books with general shape functions (2007, background): “It is a well established empirical fact that order books exhibit a certain resilience as to the price impact of a large buy market orders, i.e., after the initial impact the best ask price reverts back to its previous position; cf. Biais et al. [9], Potters and Bouchaud [17], Bouchaud et al. [10], a”
On the origin of power-law tails in price fluctuations (2003, background): “In the PSE, Bouchaud et al [4] have suggested that the average market impact function4 is of the form log Vi , yielding β → 0 in the limit as Vi → ∞.”
Anomalous price impact and the critical nature of liquidity in financial markets (2011, background): “One knows, for example, that the deposition and cancellation rates of limit orders strongly depend on the distance from the current price [33], that the assumption of a Poisson process is an oversimplification [34] (these observations apply to the real order book, but probably will also hold for the”