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We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved…

Econometrics · Economics 2026-05-04 Hyungsik Roger Moon , Matthew Shum , Martin Weidner

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent, rendering standard approaches…

Econometrics · Economics 2022-06-07 Victor H. Aguiar , Nail Kashaev , Roy Allen

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of…

General Finance · Quantitative Finance 2015-06-11 Joachim Kaldasch

We propose a general non-linear order book model that is built from the individual behaviours of the agents. Our framework encompasses Markovian and Hawkes based models. Under mild assumptions, we prove original results on the ergodicity…

Statistical Finance · Quantitative Finance 2019-06-14 Othmane Mounjid , Mathieu Rosenbaum , Pamela Saliba

In a model with no given probability measure, we consider asset pricing in the presence of frictions and other imperfections and characterize the property of coherent pricing, a notion related to (but much weaker than) the no arbitrage…

Mathematical Finance · Quantitative Finance 2016-09-12 Gianluca Cassese

We obtain an exact necessary and sufficient condition for the existence and uniqueness of equilibrium asset prices in infinite horizon, discrete-time, arbitrage free environments. Through several applications we show how the condition…

General Finance · Quantitative Finance 2021-03-01 Jaroslav Borovicka , John Stachurski

We propose an artificial market model based on deterministic agents. The agents modify their ask/bid price depending on past price changes. The temporal development of market price fluctuations is calculated numerically. A probability…

Statistical Mechanics · Physics 2008-12-10 Aki-Hiro Sato , Hideki Takayasu

Most finance studies are discussed on the basis of several hypotheses, for example, investors rationally optimize their investment strategies. However, the hypotheses themselves are sometimes criticized. Market impacts, where trades of…

Computational Finance · Quantitative Finance 2022-02-03 Takanobu Mizuta , Isao Yagi , Kosei Takashima

Trading a financial instrument pushes its price and those of other assets, a phenomenon known as cross-impact. To be of use, cross-impact models must fit data and be well-behaved so they can be applied in applications such as optimal…

Trading and Market Microstructure · Quantitative Finance 2022-03-30 Mehdi Tomas , Iacopo Mastromatteo , Michael Benzaquen

Starting from the characterization of the past time evolution of market prices in terms of two fundamental indicators, price velocity and price acceleration, we construct a general classification of the possible patterns characterizing the…

Statistical Mechanics · Physics 2009-10-31 J. V. Andersen , S. Gluzman , D. Sornette

We provide simple models for the utility function (or psychology) of an actor trading a multitude of goods for money. In this framework, money has no intrinsic consumption value, but is required as a medium of exchange. A collection of such…

Physics and Society · Physics 2026-05-25 Robert S. Farr

We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks…

Pricing of Securities · Quantitative Finance 2016-02-18 D. L. Wilcox , T. J. Gebbie

Deep learning searches for nonlinear factors for predicting asset returns. Predictability is achieved via multiple layers of composite factors as opposed to additive ones. Viewed in this way, asset pricing studies can be revisited using…

Machine Learning · Statistics 2018-04-27 Guanhao Feng , Jingyu He , Nicholas G. Polson

We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary…

Statistical Finance · Quantitative Finance 2016-11-22 Vygintas Gontis

Automation raises productivity and reduces paid human labor, but it also reallocates income and ownership claims. This paper studies that tradeoff in a static benchmark and in a stationary heterogeneous-agent general equilibrium. Firms…

General Economics · Economics 2026-05-07 Erhan Bayraktar

This work suggests modifications to a previously introduced class of heterogeneous agent models that allow for the inclusion of different types of agent motivations and behaviours in a unified way. The agents operate within a highly…

Trading and Market Microstructure · Quantitative Finance 2009-11-13 H. Lamba , T. Seaman

Analytical understanding of how low-dimensional latent features reveal themselves in large-dimensional data is still lacking. We study this by defining a linear latent feature model with additive noise constructed from probabilistic…

Disordered Systems and Neural Networks · Physics 2022-07-20 Philipp Fleig , Ilya Nemenman

Financial economic models often assume that investors know (or agree on) the fundamental value of the shares of the firm, easing the passage from the individual to the collective dimension of the financial system generated by the Share…

Physics and Society · Physics 2021-09-27 Yuri Biondi , Pierpaolo Giannoccolo , Serge Galam

We study factor models that combine latent factors with firm characteristics and propose a new framework for modeling, estimating, and inferring pricing errors. Following Zhang (2024), our approach decomposes mispricing into two distinct…

Econometrics · Economics 2025-11-06 Jungjun Choi , Ming Yuan

The methodology presented provides a quantitative way to characterize investor behavior and price dynamics within a particular asset class and time period. The methodology is applied to a data set consisting of over 250,000 data points of…

General Finance · Quantitative Finance 2020-04-22 Gunduz Caginalp , Mark DeSantis
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