A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Neural network models colloidal particle dynamics in non-equilibrium systems.
Investigates spontaneous symmetry breaking in non-equilibrium systems.
Framework preserves emergent physics in non-equilibrium systems from particle trajectories.
Mathematical model predicts international trade and global economy dynamics.
Alternative finance models from physics for non-equilibrium systems.
New method reconstructs non-equilibrium stochastic systems from data.
A new method uses deep learning to predict rare events in complex systems.
New CGMD model predicts non-equilibrium processes better than existing methods.
We analyze the statistics of daily price change of stock market in the framework of a statistical physics model for the collective fluctuation of stock portfolio. In this model the time series of price changes are coded into the sequences of up and down spins, and the Hamiltonian of the system is expressed by spin-spin…
The origin of the long-range memory in the non-equilibrium systems is still an open problem as the phenomenon can be reproduced using models based on Markov processes. In these cases a notion of spurious memory is introduced. A good example of Markov processes with spurious memory is stochastic process driven by a non-…
A new method relaxes molecules without needing non-equilibrium data.
We seek to infer the parameters of an ergodic Markov process from samples taken independently from the steady state. Our focus is on non-equilibrium processes, where the steady state is not described by the Boltzmann measure, but is generally unknown and hard to compute, which prevents the application of established eq…
The paper provides a geometric framework for understanding non-equilibrium thermodynamics.
Rate GENERIC extends thermodynamics principles to non-equilibrium systems.
In this chapter the complex systems are discussed in the context of economic and business policy and decision making. It will be showed and motivated that social systems are typically chaotic, non-linear and/or non-equilibrium and therefore complex systems. It is discussed that the rapid change in global consumer behav…
Employing data on the assessed value of land in 1983 -- 2005 Japan, we investigate the dynamical behavior in the high scale region of non-equilibrium systems. From the detailed quasi-balance and Gibrat's law, we derive a relation between the change of Pareto index and a symmetry in the detailed quasi-balance. The relat…
NEO combines orbits to sample and estimate complex distributions.
Paper connects RL and non-equilibrium statistical mechanics for entropy-regularized RL.
This paper outlines a critical gap in the assessment methodology used to estimate the macroeconomic costs and benefits of climate policy. It shows that the vast majority of models used for assessing climate policy use assumptions about the financial system that sit at odds with the observed reality. In particular, the …
We investigate the dynamical behavior in the large scale region of non-equilibrium systems, by employing data on the assessed value of land in 1983 -- 2006 Japan. In the system we find the detailed quasi-balance, which has the symmetry: x_1 -> a {x_2}^θ (x_1 and x_2 are two successive land prices). By using the detaile…
In this paper I give a brief introduction to a family of simple but non-trivial models designed to increase our understanding of collective processes in markets, the so-called Minority Games, and their non-equilibrium statistical mathematical analysis. Since the most commonly studied members of this family define disor…
Investigates fluid flow perturbations using geometric theory.
Develops a method for non-equilibrium importance sampling to estimate expectations and constants.
General equilibrium equations in economics play the same role with many-body Newtonian equations in physics. Accordingly, each solution of the general equilibrium equations can be regarded as a possible microstate of the economic system. Since Arrow's Impossibility Theorem and Rawls' principle of social fairness will p…
Improved sampling for gauge theory with SNFs.
By treating the financial market as a thermodynamic system, we establish a one-to-one correspondence between thermodynamic variables and economic quantities. Measured by the expected loss under the worst-case scenario, financial risk caused by model uncertainty is regarded as a result of the interaction between financi…
Tractable model explains market dynamics using Langevin and SUSY QM.
This thesis explores emergent intelligence in disordered systems like spin glasses and neural networks.
This paper tackles traffic volume estimation challenges with a deep learning method.
Framework infers Langevin dynamics from stochastic observations of latent systems.
Researchers use Gaussian processes to approximate Lagrange multipliers for Maximum-Entropy distributions.
Develops neural networks that follow thermodynamics principles.
We develop a formalism to study linearized perturbations around the equilibria of a pure exchange economy. With the use of mean field theory techniques, we derive equations for the flow of products in an economy driven by heterogeneous preferences and probabilistic interaction between agents. We are able to show that i…
PA reinterpreted as SB problem, unifying thermodynamics and optimal transport.
Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder inherent to these systems and in part to non-equilibrium effects which are difficu…
Superstatistics is a widely employed tool of non-equilibrium statistical physics which plays an important role in analysis of hierarchical complex dynamical systems. Yet, its "canonical" formulation in terms of a single nuisance parameter is often too restrictive when applied to complex empirical data. Here we show tha…
The paper uses geometry to understand how neural networks learn.
We propose a novel method to directly learn a stochastic transition operator whose repeated application provides generated samples. Traditional undirected graphical models approach this problem indirectly by learning a Markov chain model whose stationary distribution obeys detailed balance with respect to a parameteriz…
Thermodynamic integration (TI) for computing marginal likelihoods is based on an inverse annealing path from the prior to the posterior distribution. In many cases, the resulting estimator suffers from high variability, which particularly stems from the prior regime. When comparing complex models with differences in a …
We fill a void in merging empirical and phenomenological characterisation of the dynamical phase transitions in complex systems by identifying three of them on real-life financial markets. We extract and interpret the empirical, numerical, and semi-analytical evidences for the existence of these phase transitions, by c…
During the last two years, Europe has been facing a debt crisis, and Greece has been at its center. In response to the crisis, drastic actions have been taken, including the halving of Greek debt. Policy makers acted because interest rates for sovereign debt increased dramatically. High interest rates imply that defaul…
Geometric approach to quantum thermodynamics models state spaces and processes.
The paper studies minimal resistance dynamics in radial fields, finding unique solutions for incompressible flows.
MEP-Net uses MEP to generate solutions from limited data.
An interacting Black-Scholes model for option pricing, where the usual constant interest rate r is replaced by a stochastic time dependent rate r(t) of the form r(t)=r+f(t) dW/dt, accounting for market imperfections and prices non-alignment, was developed in [1]. The white noise amplitude f(t), called arbitrage bubble,…
In this work a relation between a measure of short-term arbitrage in the market and the excess growth of portfolios as a notion of long-term arbitrage is established. The former originates from "Geometric Arbitrage Theory" and the latter from "Stochastic Portfolio Theory". Both aim to describe non-equilibrium effects i…
New method samples from multi-modal distributions on Riemannian manifolds without training.
We study properties of the cross-sectional distribution of returns. A significant anti-correlation between dispersion and cross-sectional kurtosis is found such that dispersion is high but kurtosis is low in panic times, and the opposite in normal times. The co-movement of stock returns also increases in panic times. W…