arXiv subjects

Jean-Philippe Bouchaud

Publications and source records attributed to Jean-Philippe Bouchaud.

At least 37 records · Page 2Linked to original sources

arXiv2025

Post-COVID Inflation & the Monetary Policy Dilemma: An Agent-Based Scenario Analysis

The economic shocks that followed the COVID-19 pandemic have brought to light the difficulty, both for academics and policy makers, of describing and predicting the dynamics of inflation. This paper offers an alternative modelling approach. We study the 2020-2023 period within the well-studied Mark-0 Agent-Based Model, in which economic agents act and react according to plausible behavioural rules. We include a mechanism through which trust of economic agents in the Central Bank can de-anchor. We investigate the influence of regulatory policies on inflationary dynamics resulting from three exogenous shocks, calibrated on those that followed the COVID-19 pandemic: a production/consumption shock due to COVID-related lockdowns, a supply-chain shock, and an energy price shock exacerbated by the Russian invasion of Ukraine. By exploring the impact of these shocks under different assumptions about monetary policy efficacy and transmission channels, we review various explanations for the resurgence of inflation in the United States, including demand-pull, cost-push, and profit-driven factors. Our main results are four-fold: (i) without appropriate fiscal policy, the shocked economy can take years to recover, or even tip over into a deep recession; {(ii) the success of monetary policy in curbing inflation is primarily due to expectation anchoring, rather than to the direct economic impact of interest rate hikes; (iii) however, strong inflation anchoring is detrimental to consumption and unemployment, leading to a narrow window of ``optimal'' policy responses due to the trade-off between inflation and unemployment;} (iv) the two most sensitive model parameters are those describing wage and price indexation. The results of our study have implications for Central Bank decision-making, and offers an easy-to-use tool that may help anticipate the consequences of different monetary and fiscal policies.

econ.GN↗

arXiv2025

Free Convolution and Generalized Dyson Brownian Motion

The eigenvalue spectrum of the sum of large random matrices that are mutually "free", i.e., randomly rotated, can be obtained using the formalism of R-transforms, with many applications in different fields. We provide a direct interpretation of the otherwise abstract additivity property of R-transforms for the sum in terms of a dynamical evolution of "particles" (the eigenvalues), interacting through two-body and higher-body forces and subject to a Gaussian noise, generalizing the usual Dyson Brownian motion with Coulomb interaction. Interestingly, the appearance of an outlier outside of the bulk of the spectrum is signalled by a divergence of the "velocity" of the generalized Dyson motion. We extend our result to products of free matrices.

cond-mat.dis-nn↗

arXiv2025

Generating realistic metaorders from public data

This paper introduces a novel algorithm for generating realistic metaorders from public trade data, addressing a longstanding challenge in price impact research that has traditionally relied on proprietary datasets. Our method effectively recovers all established stylized facts of metaorders impact, such as the Square Root Law, the concave profile during metaorder execution, and the post-execution decay. This algorithm not only overcomes the dependence on proprietary data, a major barrier to research reproducibility, but also enables the creation of larger and more robust datasets that may increase the quality of empirical studies. Our findings strongly suggest that average realized short-term price impact is not due to information revelation (as in the Kyle framework) but has a mechanical origin which could explain the universality of the Square Root Law.

q-fin.TR↗

arXiv2025

The Diffusive Nature of Housing Prices

We analyze the French housing market prices in the period 1970-2022, with high-resolution data from 2018 to 2022. The spatial correlation of the observed price field exhibits logarithmic decay characteristic of the two-dimensional random diffusion equation -- local interactions may create long-range correlations. We introduce a stylized model, used in the past to model spatial regularities in voting patterns, that accounts for both spatial and temporal correlations with reasonable values of parameters. Our analysis reveals that price shocks are persistent in time and their amplitude is strongly heterogeneous in space. Our study confirms and quantifies the diffusive nature of housing prices that was anticipated long ago (Clapp et al. 1994, Pollakowski et al. 1997), albeit on much restricted, local data sets.

cond-mat.stat-mech↗

arXiv2025

Critical fragility in socio-technical systems

Socio-technical systems, where technological and human elements interact in a goal-oriented manner, provide important functional support to our societies. Here we draw attention to the underappreciated concept of timeliness -- i.e., system elements being available at the right place at the right time -- that has been ubiquitously and integrally adopted as a quality standard in the \textit{modus operandi\/} of socio-technical systems. We point out that a variety of incentives, often reinforced by competitive pressures, prompt system operators to myopically optimize for efficiencies, running the risk of inadvertently taking timeliness to the limit of its operational performance, correspondingly making the system critically fragile to perturbations by pushing the entire system towards the proverbial `edge of a cliff'. Invoking a stylized model for operational delays, we identify the limiting operational performance of timeliness, as a true critical point, where the smallest of perturbations can lead to a systemic collapse. Specifically for firm-to-firm production networks, we suggest that the proximity to \textit{critical fragility\/} is an important ingredient for understanding the fundamental ``excess volatility puzzle'' in economics. Further, in generality for optimizing socio-technical systems, we propose that critical fragility is a crucial aspect in managing the trade-off between efficiency and robustness.

physics.soc-ph↗

arXiv2024

Navigating through Economic Complexity: Phase Diagrams & Parameter Sloppiness

We argue that establishing the phase diagram of Agent Based Models (ABM) is a crucial first step, together with a qualitative understanding of how collective phenomena come about, before any calibration or more quantitative predictions are attempted. Computer-aided *gedanken* experiments are by themselves of genuine value: if we are not able to make sense of emergent phenomena in a world in which we set all the rules, how can we expect to be successful in the real world? ABMs indeed often reveal the existence of Black Swans/Dark Corners i.e. discontinuity lines beyond which runaway instabilities appear, whereas most classical economic/finance models are blind to such scenarii. Testing for the overall robustness of the phase diagram against changes in heuristic rules is a way to ascertain the plausibility of such scenarii. Furthermore, exploring the phase diagrams of ABM in high dimensions should benefit enormously from the identification of ``stiff'' and ``sloppy'' directions in parameter space.

econ.TH↗

arXiv2024

Distribution of the Diagonal Entries of the Resolvent of a Complex Ginibre Matrix

The study of eigenvalue distributions in random matrix theory is often conducted by analyzing the resolvent matrix $ \mathbf{G}_{\mathbf{M}}^N(z) = (z \mathbf{1} - \mathbf{M})^{-1} $. The normalized trace of the resolvent, known as the Stieltjes transform $ \mathfrak{g}_{\mathbf{M}}^N(z) $, converges to a limit $ \mathfrak{g}_{\mathbf{M}}(z) $ as the matrix dimension $ N $ grows, which provides the eigenvalue density $ ρ_{\mathbf{M}} $ in the large-$ N $ limit. In the Hermitian case, the distribution of $ \mathfrak{g}_{\mathbf{M}}^N(z) $, now regarded as a random variable, is explicitly known when $ z $ lies within the limiting spectrum, and it coincides with the distribution of any diagonal entry of $ \mathbf{G}_{\mathbf{M}}^N(z) $. In this paper, we investigate what becomes of these results when $ \mathbf{M} $ is non-Hermitian. Our main result is the exact computation of the diagonal elements of $ \mathbf{G}_{\mathbf{M}}^N(z) $ when $ \mathbf{M} $ is a Ginibre matrix of size $ N $, as well as the high-dimensional limit for different regimes of $ z $, revealing a tail behavior connected to the statistics of the left and right eigenvectors. Interestingly, the limit distribution is stable under inversion, a property previously observed in the symmetric case. We then propose two general conjectures regarding the distribution of the diagonal elements of the resolvent and its normalized trace in the non-Hermitian case, both of which reveal a symmetry under inversion.

math-ph↗

arXiv2024

The Self-Organized Criticality Paradigm in Economics & Finance

``Self-Organised Criticality'' (SOC) is the mechanism by which complex systems spontaneously settle close to a *critical point*, at the edge between stability and chaos, and characterized by fat-tailed fluctuations and long-memory correlations. Such a scenario may explain why insignificant perturbations can generate large disruptions, through the propagation of ``avalanches'' across the system. In this short review, we discuss how SOC could offer a plausible solution to the excess volatility puzzle in financial markets and the analogue ``small shocks, large business cycle puzzle'' for the economy at large, as initially surmised by Per Bak et al. in 1993. We argue that in general the quest for efficiency and the necessity of *resilience* may be mutually incompatible and require specific policy considerations.

q-fin.GN↗

arXiv2024

Revisiting Elastic String Models of Forward Interest Rates

Twenty five years ago, several authors proposed to describe the forward interest rate curve (FRC) as an elastic string along which idiosyncratic shocks propagate, accounting for the peculiar structure of the return correlation across different maturities. In this paper, we revisit the specific "stiff'' elastic string field theory of Baaquie and Bouchaud (2004) in a way that makes its micro-foundation more transparent. Our model can be interpreted as capturing the effect of market forces that set the rates of nearby tenors in a self-referential fashion. The model is parsimonious and accurately reproduces the whole correlation structure of the FRC over the time period 1994-2023, with an error around 1% and with only one adjustable parameter, the value of which being very stable across the last three decades. The dependence of correlation on time resolution (also called the Epps effect) is also faithfully reproduced within the model and leads to a cross-tenor information propagation time on the order of 30 minutes. Finally, we confirm that the perceived time in interest rate markets is a strongly sub-linear function of real time, as surmised by Baaquie and Bouchaud (2004). In fact, our results are fully compatible with hyperbolic discounting, in line with the recent behavioral Finance literature (Farmer and Geanakoplos, 2009).

q-fin.ST↗

arXiv2024

Timeliness criticality in complex systems

In complex systems, external parameters often determine the phase in which the system operates, i.e., its macroscopic behavior. For nearly a century, statistical physics has extensively studied systems' transitions across phases, (universal) critical exponents, and related dynamical properties. Here we consider the functionality of systems, notably operations in socio-technical ones, production in economic ones and, more generally, any schedule-based system, where timing is of crucial importance. We introduce a stylized model of delay propagation on temporal networks, where the magnitude of delay-mitigating buffer acts as a control parameter. The model exhibits {\it timeliness criticality}, a novel form of critical behavior. We characterize fluctuations near criticality, commonly referred to as ``avalanches'', and identify the corresponding critical exponents. The model exhibits timeliness criticality also when run on real-world temporal systems such as production networks. Additionally, we explore potential connections with the Mode-Coupling Theory of glasses, the depinning transition and the directed polymer problem.

physics.soc-ph↗

arXiv2024

The Spectral Boundary of Block Structured Random Matrices

Economic and ecological models can be extremely complex, with a large number of agents/species each featuring multiple interacting dynamical quantities. In an attempt to understand the generic stability properties of such systems, we define and study an interesting new matrix ensemble with extensive correlations, generalising the elliptic ensemble. We determine analytically the boundary of its eigenvalue spectrum in the complex plane, as a function of the correlations determined by the model at hand. We solve numerically our equations in several cases of interest, and show that the resulting spectra can take a surprisingly wide variety of shapes.

cond-mat.dis-nn↗

arXiv2024

Revisiting Granular Models of Firm Growth

We revisit granular models that represent the size of a firm as the sum of the sizes of multiple constituents or sub-units. Originally developed to address the unexpectedly slow reduction in volatility as firm size increases, these models also explain the shape of the distribution of firm growth rates. We introduce new theoretical insights regarding the relationship between firm size and growth rate statistics within this framework, directly linking the growth statistics of a firm to how diversified it is. The non-intuitive nature of our results arises from the fat-tailed distributions of the size and the number of sub-units, which suggest the categorization of firms into three distinct diversification types: well-diversified firms with sizes evenly distributed across many sub-units, firms with many sub-units but concentrated size in just a few, and poorly diversified firms consisting of only a small number of sub-units. Inspired by our theoretical findings, we identify new empirical patterns in firm growth. Our findings show that growth volatility, when adjusted by average size-conditioned volatility, has a size-independent distribution, but with a tail that is much too thin to be in agreement with the predictions of granular models. Furthermore, the predicted Gaussian distribution of growth rates, even when rescaled for firm-specific volatility, remains fat-tailed across all sizes. Such discrepancies not only challenge the granularity hypothesis but also underscore the need for deeper exploration into the mechanisms driving firm growth.

econ.GN↗

arXiv2024

Emergent Inequalities in a Primitive Agent-Based Good-Exchange Model

Rising inequalities around the globe bring into question our economic systems and the origin of such inequalities. Here we propose a toy agent-based model where each entity is simultaneously producing and consuming indivisible goods. We find that the system exhibits a non-trivial phase transition beyond which a market clearing equilibrium exists but becomes dynamically unreachable. When production capacity exceeds a threshold and adapts too slowly, some agents cannot sell all their goods. This leads to global price deflation and induces strong wealth inequalities, with the spontaneous separation of the population into a rich class and a poor class. We explore ways to alleviate poverty in this model and whether they have real life significance.

cond-mat.dis-nn↗

arXiv2024

Ponzi Funds

Many active funds hold concentrated portfolios. Flow-driven trading in these securities causes price pressure, which pushes up the funds' existing positions resulting in realized returns. We decompose fund returns into a price pressure (self-inflated) and a fundamental component and show that when allocating capital across funds, investors are unable to identify whether realized returns are self-inflated or fundamental. Because investors chase self-inflated fund returns at a high frequency, even short-lived impact meaningfully affects fund flows at longer time scales. The combination of price impact and return chasing causes an endogenous feedback loop and a reallocation of wealth to early fund investors, which unravels once the price pressure reverts. We find that flows chasing self-inflated returns predict bubbles in ETFs and their subsequent crashes, and lead to a daily wealth reallocation of 500 Million from ETFs alone. We provide a simple regulatory reporting measure -- fund illiquidity -- which captures a fund's potential for self-inflated returns.

q-fin.GN↗

arXiv2024

"Microstructure Modes" -- Disentangling the Joint Dynamics of Prices & Order Flow

Understanding the micro-dynamics of asset prices in modern electronic order books is crucial for investors and regulators. In this paper, we use an order by order Eurostoxx database spanning over 3 years to analyze the joint dynamics of prices and order flow. In order to alleviate various problems caused by high-frequency noise, we propose a double coarse-graining procedure that allows us to extract meaningful information at the minute time scale. We use Principal Component Analysis to construct "microstructure modes" that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric. We define and calibrate a Vector Auto-Regressive (VAR) model that encodes the dynamical evolution of these modes. The parameters of the VAR model are found to be extremely stable in time, and lead to relatively high $R^2$ prediction scores, especially for symmetric liquidity modes. The VAR model becomes marginally unstable as more lags are included, reflecting the long-memory nature of flows and giving some further credence to the possibility of "endogenous liquidity crises". Although very satisfactory on several counts, we show that our VAR framework does not account for the well known square-root law of price impact.

q-fin.ST↗

arXiv2024

Riding Wavelets: A Method to Discover New Classes of Price Jumps

Cascades of events and extreme occurrences have garnered significant attention across diverse domains such as financial markets, seismology, and social physics. Such events can stem either from the internal dynamics inherent to the system (endogenous), or from external shocks (exogenous). The possibility of separating these two classes of events has critical implications for professionals in those fields. We introduce an unsupervised framework leveraging a representation of jump time-series based on wavelet coefficients and apply it to stock price jumps. In line with previous work, we recover the fact that the time-asymmetry of volatility is a major feature. Mean-reversion and trend are found to be two additional key features, allowing us to identify new classes of jumps. Furthermore, thanks to our wavelet-based representation, we investigate the reflexive properties of co-jumps, which occur when multiple stocks experience price jumps within the same minute. We argue that a significant fraction of co-jumps results from an endogenous contagion mechanism.

q-fin.GN↗

arXiv2024

Why is the Dynamics of Glasses Super-Arrhenius?

The steep increase of the relaxation time of glass forming liquids upon cooling is traditionally ascribed to an impending entropy crisis: since the system has "nowhere to go", dynamics must come to a halt. This classic argument, due to Adam \& Gibbs, has been bolstered and refined by the development of the Random First Order Transition (RFOT) theory, which fares remarkably well at reproducing most salient experimental facts of super-cooled liquids. All static predictions of RFOT, including the existence of a point-to-set length and the role of pinning sites, have been vindicated by detailed numerical simulations. Yet, there is no consensus that the basic mechanism explaining the glass transition is the one captured by RFOT. Strong doubts have emerged following the observation that adding or removing kinetic constraints can change the relaxation time by orders of magnitude, while leaving thermodynamics unchanged. This is at odds with the idea of a one-to-one mapping between excess entropy and relaxation time. In the following discussion paper presented at the Solvay conference in October 2023, we review areas of consensus and dissent of RFOT with other competing theoretical proposals, and propose possible paths for (partial) reconciliation. We further argue that extensive numerical simulations of the non-linear susceptibility of glasses, in particular in the aging regime, should shed important light on the mechanism at the origin of the super-Arrhenius behaviour of the relaxation time. In any case, more imagination is still needed to come up with experimental, theoretical or numerical ideas that would allow to finally settle the question of why glasses do not flow.

cond-mat.dis-nn↗

arXiv2024

Unlearnable Games and "Satisficing'' Decisions: A Simple Model for a Complex World

As a schematic model of the complexity economic agents are confronted with, we introduce the ``SK-game'', a discrete time binary choice model inspired from mean-field spin-glasses. We show that even in a completely static environment, agents are unable to learn collectively-optimal strategies. This is either because the learning process gets trapped in a sub-optimal fixed point, or because learning never converges and leads to a never ending evolution of agents intentions. Contrarily to the hope that learning might save the standard ``rational expectation'' framework in economics, we argue that complex situations are generically unlearnable and agents must do with satisficing solutions, as argued long ago by Herbert Simon (Simon 1955). Only a centralized, omniscient agent endowed with enormous computing power could qualify to determine the optimal strategy of all agents. Using a mix of analytical arguments and numerical simulations, we find that (i) long memory of past rewards is beneficial to learning whereas over-reaction to recent past is detrimental and leads to cycles or chaos; (ii) increased competition destabilizes fixed points and leads first to chaos and, in the high competition limit, to quasi-cycles; (iii) some amount of randomness in the learning process, perhaps paradoxically, allows the system to reach better collective decisions; (iv) non-stationary, ``aging'' behaviour spontaneously emerge in a large swath of parameter space of our complex but static world. On the positive side, we find that the learning process allows cooperative systems to coordinate around satisficing solutions with rather high (but markedly sub-optimal) average reward. However, hyper-sensitivity to the game parameters makes it impossible to predict ex ante who will be better or worse off in our stylized economy.

cond-mat.stat-mech↗