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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.

168,742 papers · 148 categories

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48 results for experimental economics

The algebra of transactions as fundamental measurements is constructed on the basis of the analysis of their properties and represents an expansion of the Boolean algebra. The notion of the generalized economic measurements of the economic quantity and quality of objects of transactions is introduced. It has been shown…

2014-12-18abs ↗pdf ↗

Study uses remotely sensed data to infer economic outcomes in experiments and quasi-experiments.

problem Imperfect measurement of economic outcomes by remotely sensed variables.
method Combines experimental and observational data to identify causal parameters, using satellite imagery and mobile phone activity.
result Developed a robust method for n^{-1/2} inference that does not restrict remotely sensed variable processing algorithms.

Examines predictability and complexity of economic time series using symbolic dynamics and entropy.

problem Understanding the predictability and complexity of economic time series.
method Symbolic dynamics and Information theory (entropy and uncertainty).
result Economic time series are complex and can be expressed in terms of information production.

The paper proposes a method of financial time series forecasting taking into account the semantics of news. For the semantic analysis of financial news the sampling of negative and positive words in economic sense was formed based on Loughran McDonald Master Dictionary. The sampling included the words with high frequen…

2017-05-23abs ↗pdf ↗

Experimental economics has repeatedly demonstrated that the Nash equilibrium makes inaccurate predictions for a vast set of games. Instead, several alternative theoretical concepts predict behavior that is much more in tune with observed data, with the quantal response equilibrium as the most prominent example. However…

2010-12-03abs ↗pdf ↗

This paper converts NACE classification into embeddings to preserve hierarchical structure.

problem Preserving hierarchical structure in NACE classification while reducing dimensions.
method Custom metrics for hierarchical structure retention; state-of-the-art models and dimensionality reduction.
result The proposed approach effectively preserves hierarchical structures in NACE classification.

This paper gives a critical account of the minority game literature. The minority game is a simple congestion game: players need to choose between two options, and those who have selected the option chosen by the minority win. The learning model proposed in this literature seems to differ markedly from the learning mod…

2007-06-29abs ↗pdf ↗

Financial markets provide a natural quantitative lab for understanding some of the most advanced human behaviours. Among them is the use of mathematical tools known as financial instruments. Besides money, the two most fundamental financial instruments are bonds and equities. More than 30 years ago Mehra and Prescott f…

2015-07-26abs ↗pdf ↗

This study measures price risk aversion using indirect utility functions in a lab experiment.

problem Measuring risk aversion with uncertain prices in experimental economics.
method Using indirect utility functions and a multiple price list method in a lab experiment.
result Price risk aversion is statistically greater than payoff risk aversion.

In this article, we present a brief narration of the origin and the overview of the recent developments done on the Kolkata Paise Restaurant (KPR) problem, which can serve as a prototype for a broader class of resource allocation problems in the presence of a large number of competing agents, typically studied using co…

2017-12-18abs ↗pdf ↗

The power law has been observed in the degree distributions of many biological neural networks. Sparse deep neural networks, which learn an economical representation from the data, resemble biological neural networks in many ways. In this paper, we study if these artificial networks also exhibit properties of the power…

2018-05-04abs ↗pdf ↗

GEAR uses auxiliary data to estimate optimal decisions in studies with limited primary outcomes.

problem Estimating optimal decisions when primary outcomes are not available in experimental samples.
method GEAR uses augmented inverse propensity weighting to estimate optimal decisions based on auxiliary data.
result GEAR estimators and value estimators have established asymptotic properties and are validated in simulations and a real application.

Study preferences over uncertain time payments, finds growth-optimality better than expected utility theory.

problem Understanding how people make decisions with uncertain timing of payments.
method Normative model of growth-optimality, revisiting experimental evidence on time lotteries.
result Growth-optimality better explains experimental data on time lotteries than expected discounted utility theory.

We analyze complexity of financial (and general economic) processes by comparing classical and quantum-like models for randomness. Our analysis implies that it might be that a quantum-like probabilistic description is more natural for financial market than the classical one. A part of our analysis is devoted to study t…

2007-04-22abs ↗pdf ↗

Current economic theories miss most of economic dynamics.

problem Accuracy of economic theories and policies depend on economic variables and processes.
method Identify and analyze overlooked economic variables and processes.
result Many economic variables and processes not accounted for in current theories.

Modeling business cycles via collective risk fluctuations in economic agents' risk space.

problem Understanding and predicting business cycles through economic agents' risk dynamics.
method Continuous numerical risk grades for economic agents, modeling collective economic variables and flows as functions of risk coordinates, deriving equations for their evolution.
result Business and credit cycles are explained as fluctuations of collective economic variables and their mean risks in the risk space of economic agents.

Olympus benchmarks optimization algorithms for noisy experiments.

problem Benchmarking optimization algorithms on realistic experimental scenarios is challenging.
method Introduces Olympus, a software package for benchmarking optimization algorithms on synthetic experiments.
result Mitigates barriers in benchmarking optimization algorithms on realistic experimental scenarios.

LLMs mimic human traders in finance, but not as much as expected.

problem Evaluating how LLMs behave in financial markets.
method Adapted experimental design with LLMs and human traders, analyzed in single and mixed model settings.
result LLMs tend to price assets near their fundamental value, but not as much as humans, and show less trading strategy variance.

This mathematical essay brings together ideas from Economics, Geobiodynamics and Thermodynamics. Its purpose is to obtain real models of complex evolutionary systems. More specifically, the essay defines Roegenian Economy and links Geobiodynamics and Roegenian Economy. In this context, we discuss the isomorphism betwee…

2018-11-06abs ↗pdf ↗

The dynamic network of relationships among corporations underlies cascading economic failures including the current economic crisis, and can be inferred from correlations in market value fluctuations. We analyze the time dependence of the network of correlations to reveal the changing relationships among the financial,…

2010-11-16abs ↗pdf ↗

Paper classifies economic states and optimizes portfolios for stagflationary environments.

problem Economic uncertainty and stagflationary conditions.
method Mathematical techniques for analyzing multivariate time series, economic driver analysis, self-similarity identification, and portfolio optimization.
result Constructs economic state classifications and computes economic state integrals.

Surveying machine learning methods for economic forecasting.

problem Improving accuracy of economic forecasts using machine learning.
method Nowcasting, textual data, panel and tensor data, high-dimensional Granger causality tests, time series cross-validation, classification with economic losses.
result Recent advances in machine learning methods enhance economic forecasting accuracy.

Second-order economic theory considers new variables to improve price volatility predictions.

problem Current economic models focus on first-order variables, missing second-order variables that affect price volatility.
method Introduces second-order economic theory with new variables composed of sums of squares of agents' transactions.
result Second-order economic theory complements first-order variables and introduces new macroeconomic variables.

The paper provides bounds and methods for estimating causal effects from observational data.

problem Estimating individual-level causal effects from non-experimental data.
method Generalization bounds, sample re-weighting, representation learning algorithms.
result The proposed methods reduce treatment group distances and improve estimation accuracy.

Data describing historical economic growth are analysed. Included in the analysis is the world and regional economic growth. The analysis demonstrates that historical economic growth had a natural tendency to follow hyperbolic distributions. Parameters describing hyperbolic distributions have been determined. A search …

2015-09-09abs ↗pdf ↗

We recall the similarities between the concepts and techniques of Thermodynamics and Roegenian Economics. The Phase Diagram for a Roegenian economic system highlights a triple point and a critical point, with related explanations. These ideas can be used to improve our knowledge and understanding of the nature of devel…

2018-11-06abs ↗pdf ↗

Economics does not need a scientific revolution. Economics needs accurate measurements according to high standards of natural sciences and meticulous work on revealing empirical relationships between measured variables.

2009-04-04abs ↗pdf ↗