Random walks, liquidity molasses and critical response in financial markets

By Jean-Philippe Bouchaud, J. Kockelkoren, Marc Potters. 2004

154 citations recorded by the source corpus.

Stock prices are observed to be random walks in time despite a strong, long-term memory in the signs of trades (buys or sells). Lillo and Farmer have recently suggested that these correlations are compensated by opposite long-ranged fluctuations in liquidity, with an otherwise permanent market impact, challenging the scenario proposed in Quantitative Finance, 2004, 4, 176, where the impact is instead transient, with a power-law decay in time. The exponent of this decay is precisely tuned to a critical value, ensuring simultaneously that prices are diffusive on long time scales and that the impact function is nearly lag independent. We provide new analysis of empirical data that confirm and make more precise our previous claims. We show that the power-law decay of the bare impact function comes both from an excess flow of limit order opposite to the market order flow, and to a systematic anti-correlation of the bid–ask motion between trades, two effects that create a ‘liquidity molasses’ which dampens market volatility.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/e1c39ec4dfc8d9341d41853b72d7f8bf222e78ed

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Citations in the corpus

Optimal execution with non-linear transient market impact (2014, background): “The second generation of market impact models focuses on the transient nature of market impact (Bouchaud et al. 2004, Bouchaud et al. 2006, Gatheral and Schied 2013, Obizhaeva and Wang 2013).”
Relation between bid–ask spread, impact and volatility in order-driven markets (2006, background): “The first one is the lagged impact function introduced in Bouchaud et al. (2004, 2006) R‘ ¼ "i ðm‘þi miÞ , ð6Þ which is found, within the MRR model, to increase from R1 ¼ ð1 Þ to R1 ¼ (see appendix A and figure 1).”
The price impact of order book events: market orders, limit orders and cancellations (2009, background): “…calculations, the response function (15) can be expressed through equations (16) and (12) as R 1 ð‘ Þ ¼ X 2 Pð 2Þ X 05n ‘ G 2 ðnÞC 1, 2 ð‘ nÞ þ X n4‘ G 2 ðnÞC 2, 1ðn ‘ Þ " X n40 G 2ðnÞC 2, 1ðnÞ # : ð17Þ This is a direct extension of equation (3), which was obtained by Bouchaud et al. (2006).”
The short-term price impact of trades is universal (2017, background): “It is also clearly related to the previously documented passive limit order counter-flow (“liquidity refill”), which manifests itself as the decay of the propagator G (Bouchaud et al., 2006; Eisler et al., 2013; Tóth et al., 2012).”
An empirical behavioral model of liquidity and volatility (2007, background): “Journal of economic dynamics and control, 21(8-9), 1471–1491.”
No-dynamic-arbitrage and market impact (2010, unknown): “In the language of Gerig (2007) and Bouchaud et al.”