Anomalous price impact and the critical nature of liquidity in financial markets

By B. Tóth, Y. Lempérière, C. Deremble, J. D. Lataillade, J. Kockelkoren, Jean-Philippe Bouchaud. 2011

259 citations recorded by the source corpus.

We propose a dynamical theory of market liquidity that predicts that the average supply/demand profile is V-shaped and {\it vanishes} around the current price. This result is generic, and only relies on mild assumptions about the order flow and on the fact that prices are (to a first approximation) diffusive. This naturally accounts for two striking stylized facts: first, large metaorders have to be fragmented in order to be digested by the liquidity funnel, leading to long-memory in the sign of the order flow. Second, the anomalously small local liquidity induces a breakdown of linear response and a diverging impact of small orders, explaining the "square-root" impact law, for which we provide additional empirical support. Finally, we test our arguments quantitatively using a numerical model of order flow based on the same minimal ingredients.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/f7c9df73d88a91cb79eed72495448ef6d9d743bd

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Citations in the corpus

The adaptive nature of liquidity taking in limit order books (2014, methodology): “In [22] authors proposed that the random scalar f ∈ [0, 1] is drawn from a beta distribution Pζ(f) = ζ (1 − f)ζ−1.”
No‐arbitrage implies power‐law market impact and rough volatility (2018, background): “As for the transient part of the market impact, empirical measurements show that provided the execution rate of the metaorder is relatively constant, the function MI is close to a power-law with respect to time, that is MI(t) ∼ t1−α with α ∈ (0, 1), see [2, 6, 23, 29].”
Optimal execution with non-linear transient market impact (2014, background): “And various studies of market impact costs have found the square root formula to fit transaction costs’ data remarkably well (see Tóth et al. 2011 in particular).”
Market Impacts and the Life Cycle of Investors Orders (2014, background): “T R ] 6 D ec 2 01 4 [Gatheral, 2010], [Moro et al., 2009], [Toth et al., 2011a], [Bouchaud et al., 2009], [Farmer et al., 2006], [Brokmann et al., 2014] and [Zarinelli et al., 2015].”
Limit order books (2010, background): “However, the distribution of mid-price returns generated by the model does not exhibit heavy tails, and Tóth et al. (2011) reported that time series of logarithmic mid-price returns generated by the model have a Hurst exponent of H < 12 when the model’s parameters are chosen to mimic realistic…”
Crises and Collective Socio-Economic Phenomena: Simple Models and Challenges (2012, background): “Now, as argued in [141] and more recently in [66], supply and demand in financial markets cannot be instantaneously matched.”
TRADING WITH SMALL PRICE IMPACT (2014, unknown): “, [4, 56]).”
Beyond the Square Root: Evidence for Logarithmic Dependence of Market Impact on Size and Participation Rate (2014, unknown): “As suggested in [3], the square-root law of market impact seems to be a very robust statistical regularity.”