# Latest Publications

## Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events

A. Fosset, J.-P. Bouchaud and M. Benzaquen

12 May 2020

We propose an actionable calibration procedure for general Quadratic Hawkes models of order book events (market orders, limit orders, cancellations). One of the main features of such models is to encode not only the influence of past events on future events but also, crucially, the influence of past price changes on such events. We show that the empirically calibrated quadratic kernel is well described by a diagonal contribution (that captures past realised volatility), plus a rank-one “Zumbach” contribution (that captures the effect of past trends). We find that the Zumbach kernel is a power-law of time, as are all other feedback kernels. As in many previous studies, the rate of truly exogenous events is found to be a small fraction of the total event rate. These two features suggest that the system is close to a critical point – in the sense that stronger feedback kernels would lead to instabilities.

## Schrödinger’s ants: A continuous description of Kirman’s recruitment model

J. Moran, A. Fosset, M. Benzaquen and J.-P. Bouchaud

14 Apr 2020

We show how the approach to equilibrium in Kirman’s ants model can be fully characterized in terms of the spectrum of a Schrödinger equation with a Pöschl-Teller (tan2 ) potential. Among other interesting properties, we have found that in the bimodal phase where ants visit mostly one food site at a time, the switch time between the two sources only depends on the “spontaneous conversion” rate and not on the recruitment rate. More complicated correlation functions can be computed exactly, and involve higher and higher eigenvalues and eigenfunctions of the Schrödinger operator, which can be expressed in terms of hypergeometric functions.

## How to build a cross-impact model from first principles: Theoretical requirements and empirical results

M. Tomas, I. Mastromatteo and M. Benzaquen

3 Apr 2020

Cross-impact, namely the fact that on average buy (sell) trades on a financial instrument induce positive (negative) price changes in other correlated assets, can be measured from abundant, although noisy, market data. In this paper we propose a principled approach that allows to perform model selection for cross-impact models, showing that symmetries and consistency requirements are particularly effective in reducing the universe of possible models to a much smaller set of viable candidates, thus mitigating the effect of noise on the properties of the inferred model. We review the empirical performance of a large number of cross-impact models, comparing their strengths and weaknesses on a number of asset classes (futures, stocks, calendar spreads). Besides showing which models perform better, we argue that in presence of comparable statistical performance, which is often the case in a noisy world, it is relevant to favor models that provide ex-ante theoretical guarantees on their behavior in limit cases. From this perspective, we advocate that the empirical validation of universal properties (symmetries, invariances) should be regarded as holding a much deeper epistemological value than any measure of statistical performance on specific model instances.

## By Force of Habit: Self-Trapping in a Dynamical Utility Landscape

J. Moran, A. Fosset, D. Luzzati, J.-P. Bouchaud and M. Benzaquen

31 Mar 2020

Historically, rational choice theory has focused on the utility maximization principle to describe how individuals make choices. In reality, there is a computational cost related to exploring the universe of available choices and it is often not clear whether we are truly maximizing an underlying utility function. In particular, memory effects and habit formation may dominate over utility maximisation. We propose a stylized model with a history-dependent utility function where the utility associated to each choice is increased when that choice has been made in the past, with a certain decaying memory kernel. We show that self-reinforcing effects can cause the agent to get stuck with a choice by sheer force of habit. We discuss the special nature of the transition between free exploration of the space of choice and self-trapping. We find in particular that the trapping time distribution is precisely a Zipf law at the transition, and that the self-trapped phase exhibits super-aging behaviour.

## Zooming In on Equity Factor Crowding

V. Volpati, M. Benzaquen, Z. Eisler, I. Mastromatteo, B. Tóth and J.-P. Bouchaud

13 Jan 2020

Crowding is most likely an important factor in the deterioration of strategy performance, the increase of trading costs and the development of systemic risk. We study the imprints of crowding on both anonymous market data and a large database of metaorders from institutional investors in the U.S. equity market. We propose direct metrics of crowding that capture the presence of investors contemporaneously trading the same stock in the same direction by looking at fluctuations of the imbalances of trades executed on the market. We identify significant signs of crowding in well known equity signals, such as Fama-French factors and especially Momentum. We show that the rebalancing of a Momentum portfolio can explain between 1–2% of order flow, and that this percentage has been significantly increasing in recent years.

## Conditional Correlations and Principal Regression Analysis for Futures

A. Karami, R. Benichou,

M. Benzaquen and

J.-P. Bouchaud

1 Jan 2020

We explore the effect of past market movements on the instantaneous correlations between assets within the futures market. Quantifying this effect is of interest to estimate and manage the risk associated to portfolios of futures in a non-stationary context. We apply and extend a previously reported method called the Principal Regression Analysis (PRA) to a universe of 84 futures contracts between 2009 and 2019. We show that the past up (resp. down) 10 day trends of a novel predictor -- the eigen-factor -- tend to reduce (resp. increase) instantaneous correlations. We then carry out a multifactor PRA on sectorial predictors corresponding to the four futures sectors (indexes, commodities, bonds and currencies), and show that the effect of past market movements on the future variations of the instantaneous correlations can be decomposed into two significant components. The first component is due to the market movements within the index sector, while the second component is due to the market movements within the bonds sector.

## Endogenous Liquidity Crises

A. Fosset, J.-P. Bouchaud and M. Benzaquen

3 Dec 2019

Empirical data reveals that the liquidity flow into the order book (depositions, cancellations and market orders) is influenced by past price changes. In particular, we show that liquidity tends to decrease with the amplitude of past volatility and price trends. Such a feedback mechanism in turn increases the volatility, possibly leading to a liquidity crisis. Accounting for such effects within a stylized order book model, we demonstrate numerically that there exists a second order phase transition between a stable regime for weak feedback to an unstable regime for strong feedback, in which liquidity crises arise with probability one. We characterize the critical exponents, which appear to belong to a new universality class. We then propose a simpler model for spread dynamics that maps onto a linear Hawkes process which also exhibits liquidity crises. If relevant for the real markets, such a phase transition scenario requires the system to sit below, but very close to the instability threshold (self-organised criticality), or else that the feedback intensity is itself time dependent and occasionally visits the unstable region. An alternative scenario is provided by a class of non-linear Hawkes process that show occasional “activated” liquidity crises, without having to be poised at the edge of instability.

## Beauty and structural complexity

S. Lakhal, A. Darmon, JP. Bouchaud, M. Benzaquen

15 Oct 2019

We revisit the long-standing question of the relation between image appreciation and its staistical properties. We generate two different sets of random images well distributed along three measures of entropic complexity. We run a large-scale survey un wich people are asked to sort the images by preference, wich reveals maximum appreciation at intermediate entropic complexity. We show tht the algorithmic complexity of the coarse-grained images, expected to capture structural complexity while abstracting from high frequency noise, is a good predictor of preferences. Our analysis suggets that there might exist some universal quantitative criteria for aesthetic judgement.

## Confidence Collapse in a Multi-Household, Self-Reflexive DSGE Model

F. Morelli, M. Benzaquen, M. Tarzia and J.-P. Bouchaud

17 Jul 2019

We investigate a multi-household DSGE model in which past aggregate consumption impacts the confidence, and therefore consumption propensity, of individual households. We find that such a minimal setup is extremely rich, and leads to a variety of realistic output dynamics: high output with no crises; high output with increased volatility and deep, short lived recessions; alternation of high and low output states where relatively mild drop in economic conditions can lead to a temporary confidence collapse and steep decline in economic activity. The crisis probability depends exponentially on the parameters of the model, which means that markets cannot efficiently price the associated risk premium. We conclude by stressing that within our framework, narratives become an important monetary policy tool, that can help steering the economy back on track.

## Impact is not just volatility

F. Bucci, I. Mastromatteo, M. Benzaquen and J.-P. Bouchaud

5 Jul 2019

The notion of market impact is subtle and sometimes misinterpreted. Here we argue that impact should not be misconstrued as volatility. In particular, the so-called “square-root impact law”, which states that impact grows as the square-root of traded volume, has nothing to do with price diffusion, i.e. that typical price changes grow as the square-root of time. We rationalise empirical findings on impact and volatility by introducing a simple scaling argument and confronting it to data.

## Are trading invariants really invariant? Trading costs matter

F. Bucci, F. Lillo, J.-P. Bouchaud and M. Benzaquen

12 Feb 2019

We revisit the trading invariance hypothesis recently proposed by Kyle and Obizhaeva by empirically investigating a large dataset of bets, or metaorders, provided by ANcerno. The hypothesis predicts that the quantity I := R/N^3/2, where R is the exchanged risk (volatility × volume × price) and N is the number of bets, is invariant. We find that the 3/2 scaling between R and N works well and is robust against changes of year, market capitalisation and economic sector. However our analysis clearly shows that I is not invariant. We find a very high correlation (> 0.8) between I and the total trading cost (spread and market impact) of the bet. We propose new invariants defined as a ratio of I and costs and find a large decrease in variance. We show that the small dispersion of the new invariants is mainly driven by (i) the scaling of the spread with the volatility per transaction, (ii) the near invariance of the distribution of metaorder size and of the volume and number fractions of bets across stocks.

## Slow decay of impact in equity markets: insights from the ANcerno database

F. Bucci, M. Benzaquen, F. Lillo, and J.-P. Bouchaud

17 Jan 2019

We present an empirical study of price reversion after the executed metaorders. We use a data set with more than 8 million metaorders executed by institutionalinvestors in the US equity market. We show that relaxation takes place as soonas the metaorder ends:while at the end of the same day it is on average ≈2/3 of the peak impact, the decay continues the next days, following a power-law functionat short time scales, and converges to a non-zero asymptotic value at long timescales (∼50 days) equal to ≈1/2 of the impact at the end of the first day. Dueto a significant, multiday correlation of the sign of executed metaorders, a carefuldeconvolution of theobservedimpact must be performed to extract the estimate ofthe impact decay of isolated metaorders.

## How does latent liquidity get revealed in the limit order book?

L. Dall'Amico*, A. Fosset*, J.-P. Bouchaud and M. Benzaquen

14 Nov 2018

Latent order book models have allowed for significant progress in our understanding of price formation in financial markets. In particular they are able to reproduce a number of stylized facts, such as the square-root impact law. An important question that is raised – if one is to bring such models closer to real market data – is that of the connection between the latent (unobservable) order book and the real (observable) order book. Here we suggest a simple, consistent mechanism for the revelation of latent liquidity that allows for quantitative estimation of the latent order book from real market data. We successfully confront our results to real order book data for over a hundred assets and discuss market stability. One of our key theoretical results is the existence of a market instability threshold, where the conversion of latent order becomes too slow, inducing liquidity crises.

## Crossover from Linear to Square-Root Market Impact

F. Bucci, M. Benzaquen, F. Lillo, and J.-P. Bouchaud

13 Nov 2018

Using a large database of 8 million institutional trades executed in the U.S. equity market, we establish a clear crossover between a linear market impact regime and a square-root regime as a function of the volume of the order. Our empirical results are remarkably well explained by a recently proposed dynamical theory of liquidity that makes specific predictions about the scaling function describing this crossover. Allowing at least two characteristic time scales for the liquidity (“fast” and “slow”) enables one to reach quantitative agreement with the data.

## Market impact with multi-timescale liquidity

M. Benzaquen and J.-P. Bouchaud

10 Oct 2017

We present an extended version of the recently proposed "LLOB" model for the dynamics of latent liquidity in financial markets. By allowing for finite cancellation and deposition rates within a continuous reaction-diffusion setup, we account for finite memory effects on the dynamics of the latent order book. We compute in particular the finite memory corrections to the square root impact law, as well as the impact decay and the permanent impact of a meta-order. The latter is found to be linear in the traded volume and independent of the trading rate, as dictated by no-arbitrage arguments. In addition, we consider the case of a spectrum of cancellation and deposition rates, which allows us to obtain a square root impact law for moderate participation rates, as observed empirically. Our multi-scale framework also provides an alternative solution to the so-called price diffusivity puzzle in the presence of a long-range correlated order flow.