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…
arXiv research
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New learning algorithm mimics biological neural networks.
EP algorithm improved for CNNs and real-time learning.
EP learns like BPTT but with local weight updates.
New algorithm for solving minimax problems over distributions converges to Nash equilibrium.
The paper analyzes arbitrage opportunities in a large investor market with common stock noises.
Finding biologically plausible alternatives to back-propagation of errors is a fundamentally important challenge in artificial neural network research. In this paper, we propose a learning algorithm called error-driven Local Representation Alignment (LRA-E), which has strong connections to predictive coding, a theory t…
The biological plausibility of the backpropagation algorithm has long been doubted by neuroscientists. Two major reasons are that neurons would need to send two different types of signal in the forward and backward phases, and that pairs of neurons would need to communicate through symmetric bidirectional connections. …
Sector specific multifactor CES elasticity of substitution and the corresponding productivity growths are jointly measured by regressing the growths of factor-wise cost shares against the growths of factor prices. We use linked input-output tables for Japan and the Republic of Korea as the data source for factor price …
Deep neural networks show some layers better align with data than others.
We provide a microfoundation for linear price impact models in a stationary market.
Markov state models (MSMs) and Master equation models are popular approaches to approximate molecular kinetics, equilibria, metastable states, and reaction coordinates in terms of a state space discretization usually obtained by clustering. Recently, a powerful generalization of MSMs has been introduced, the variationa…
Model predicts asset prices from initial shocks using neural networks.
This paper tackles traffic volume estimation challenges with a deep learning method.
This systemic risk paper introduces inhomogeneous random financial networks (IRFNs). Such models are intended to describe parts, or the entirety, of a highly heterogeneous network of banks and their interconnections, in the global financial system. Both the balance sheets and the stylized crisis behaviour of banks are …
A \emph{new} notion of equilibrium, which we call \emph{strong equilibrium}, is introduced for time-inconsistent stopping problems in continuous time. Compared to the existing notions introduced in ArXiv: 1502.03998 and ArXiv: 1709.05181, which in this paper are called \emph{mild equilibrium} and \emph{weak equilibrium…
New framework for estimating treatment effects in experiments with network interference.
Two-cycle GEILA equilibria are OLG equilibria and vice versa, with applications to indeterminacy and bubbles.
We prove the existence of a Radner equilibrium in a model with proportional transaction costs on an infinite time horizon and analyze the effect of transaction costs on the endogenously determined interest rate. Two agents receive exogenous, unspanned income and choose between consumption and investing into an annuity.…
A new method relaxes molecules without needing non-equilibrium data.
Deep neural networks near edge of chaos show universal scaling laws.
Existence of Radner equilibrium proven with growing population.
Study how transaction costs impact stock returns and holdings in equilibrium.
Equilibrium found for multi-agent trading with transaction costs.
The paper examines Nash equilibrium in GANs for stationary Gaussian processes.
Analog method solves portfolio optimization problems faster and more efficiently.
Study on equilibrium with non-convex preferences.
We combine general equilibrium theory and theorie generale of stochastic processes to derive structural results about equilibrium state prices.
Equilibrium Propagation (EP) is a biologically inspired learning algorithm for convergent recurrent neural networks, i.e. RNNs that are fed by a static input x and settle to a steady state. Training convergent RNNs consists in adjusting the weights until the steady state of output neurons coincides with a target y. Con…
Bayesian learning in undirected graphical models|computing posterior distributions over parameters and predictive quantities is exceptionally difficult. We conjecture that for general undirected models, there are no tractable MCMC (Markov Chain Monte Carlo) schemes giving the correct equilibrium distribution over param…
The theorems we proved describe the structure of economic equilibrium in the exchange economy model. We have studied the structure of property vectors under given structure of demand vectors at which given price vector is equilibrium one. On this ground, we describe the general structure of the equilibrium state and gi…
Proof-of-Stake networks with EIP-1559 exhibit stable token prices and secure network security.
Study equilibrium consumption habits in a large population using mean field games.
By generalizing the measurements on the game experiments of mixed strategy Nash equilibrium, we study the dynamical pattern in a representative dynamic stochastic general equilibrium (DSGE). The DSGE model describes the entanglements of the three variables (output gap [], inflation [] and nominal interest rate [$…
We construct continuous-time equilibrium models based on a finite number of exponential utility investors. The investors' income rates as well as the stock's dividend rate are governed by discontinuous Levy processes. Our main result provides the equilibrium (i.e., bond and stock price dynamics) in closed-form. As an a…
Study analyzes market equilibrium returns with price impact and transaction costs.
DEQs converge to optimal solutions with mild over-parameterization.
Kyle's equilibrium model stability proven for 1-2 trading times, but not for 3 or more.
Geometric programming approach for traffic equilibrium problems.
In this paper, we study dynamics of geodesic flows over closed surfaces of genus greater than or equal to 2 without focal points. Especially, we prove that there is a large class of potentials having unique equilibrium states, including scalar multiples of the geometric potential, provided the scalar is less than 1. Mo…
Quasitoric manifolds, introduced by M. Davis and T. Januskiewicz in 1991, are topological generalizations of smooth complex projective spaces. In 1992, Banchoff and Kühnel constructed a 10-vertex equilibrium triangulations of $\CP^2$. We generalize this construction for quasitoric manifolds and construct some equilibri…
A Systemic Optimal Risk Transfer Equilibrium (SORTE) was introduced in: "Systemic optimal risk transfer equilibrium", Mathematics and Financial Economics (2021), for the analysis of the equilibrium among financial institutions or in insurance-reinsurance markets. A SORTE conjugates the classical Bühlmann's notion of a …
Existence of incomplete Radner equilibrium with endogenous noise tracker.
Study proves existence of equilibrium in incomplete economies with discontinuous volatility.
We present a simple dynamic equilibrium model for an online exchange where both buyers and sellers arrive according to a exogenously defined stochastic process. The structure of this exchange is motivated by the limit order book mechanism used in stock markets. Both buyers and sellers are elastic in the price-quantity …
Study dynamic equilibrium with insider and general uninformed agent preferences.
The paper solves stochastic control problems with implicit objectives, finding equilibrium strategies.
Proves existence of equilibrium in limited participation economy.