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arXiv research

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.

168,695 papers · 148 categories

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147295442589 · Jun 202019922001200920172026
48 results for economic efficiency

Proposes a machine learning framework for more efficient economic dispatch.

problem Temporal and spatial correlations between system cost and load prediction errors.
method End-to-end machine learning approach with task-specific learning criteria and an efficient optimization kernel.
result Demonstrates the effectiveness and efficiency of the proposed learning framework.

New framework for interpretable firm characteristics factors.

problem Creating statistically efficient and economically interpretable factors from firm characteristics.
method Grouping related characteristics and deriving one factor per group, combining economic intuition with data-driven clustering.
result Parsimonious, transparent factors outperform benchmarks in out-of-sample tests.

Originally, the Carnot cycle is a theoretical thermodynamic cycle that provides an upper limit on the efficiency that any classical thermodynamic engine can achieve during the conversion of heat into work, or conversely, the efficiency of a refrigeration system in creating a temperature difference by the application of…

2018-11-06abs ↗pdf ↗

Deep-MacroFin uses neural networks to solve complex economic models efficiently.

problem Solving high-dimensional partial differential equations in continuous time economics.
method Leverages deep learning, specifically Multi-Layer Perceptrons and Kolmogorov-Arnold Networks, optimized with HJB equations.
result Offers a more efficient solution (5imes imes less memory, 40imes imes fewer FLOPs) for 50D economic models.

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.

Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

2015-07-01abs ↗pdf ↗

The origin of economic crises is a key problem for economics. We present a model of long-run competitive markets to show that the multiplicity of behaviors in an economic system, over a long time scale, emerge as statistical regularities (perfectly competitive markets obey Bose-Einstein statistics and purely monopolist…

2010-10-07abs ↗pdf ↗

By analyzing a large data set of daily returns with data clustering technique, we identify economic sectors as clusters of assets with a similar economic dynamics. The sector size distribution follows Zipf's law. Secondly, we find that patterns of daily market-wide economic activity cluster into classes that can be ide…

2002-07-05abs ↗pdf ↗

Economies are complex man-made systems where organisms and markets interact according to motivations and principles not entirely understood yet. The increasing dissatisfaction with the postulates of traditional economics i.e. perfectly rational agents, interacting through efficient markets in the search of equilibrium,…

2012-05-14abs ↗pdf ↗

LemonadeBench evaluates LLMs' economic intuition through a simulated lemonade stand.

problem Evaluating LLMs' economic understanding and decision-making in simple markets.
method Simulated lemonade stand business to test LLMs' long-term planning and profit maximization.
result Models achieve profitability but exhibit local rather than global optimization.

The paper proposes a new model for predicting and analyzing economic variables.

problem Predicting and analyzing economic variables in developed regions.
method Time-varying parameter global vector autoregressive (TVP-GVAR) framework combined with machine learning models.
result The proposed model provides high precision out-of-sample predictions and novel insights into economic variable connectedness.

The paper introduces GAER to assess market feasibility under geopolitical and institutional constraints.

problem Feasibility of adaptive market efficiency under heterogeneous institutional and geopolitical conditions.
method Structural framework integrating adaptive market theory, institutional economics, and political economy.
result GAER as a diagnostic indicator for portfolio construction feasibility.

Optimal intervention in economic networks modeled as influence maximization, with hard computational problems.

problem Optimal intervention in economic networks modeled as influence maximization.
method Transformed into influence maximization-like form, with theoretical and practical implications.
result Optimal intervention is NP-hard and cannot be approximated to a constant factor in polynomial time.

Paper extends quantile factor analysis with probabilistic methods for better economic policy and financial condition prediction.

problem Improving accuracy in economic and financial condition prediction.
method Probabilistic quantile factor analysis with regularization and variational approximations.
result The probabilistic estimator outperforms a recent loss-based estimator in many cases.

Deep RL solves complex economic models with heterogeneous agents.

problem Solving models with heterogeneous economic actors is difficult.
method Reinforcement Learning techniques for solving general equilibrium models.
result Successfully captures economic behaviors induced by age-based health risks.

This study assesses how economic shocks affect the efficiency and robustness of international pesticide trade networks.

problem Economic shocks impact the efficiency and robustness of international pesticide trade networks.
method Simulations were used to quantify efficiency and robustness under different economic shocks. Three strategies were tested: descending, random, and ascending node removal.
result The international pesticide trade networks became more efficient and robust except for clustering coefficient. Import-oriented economies were more vulnerable to shocks.

This work explains crises in markets without external news using bounded rational agents.

problem Inability to model out-of-equilibrium dynamics in economic markets.
method Modeling bounded rational strategic reasoning in multi-agent market games.
result Bounded rational strategic reasoning can lead to endogenously emerging crises.

Multivariate volatility modeling and forecasting are crucial in financial economics. This paper develops a copula-based approach to model and forecast realized volatility matrices. The proposed copula-based time series models can capture the hidden dependence structure of realized volatility matrices. Also, this approa…

2020-02-20abs ↗pdf ↗

We study a novel economic network (supply chain) comprised of wire transfers (electronic payment transactions) among the universe of firms in Brazil (6.2 million firms). We construct a directed and weighted network in which vertices represent cities and edges connote pairwise economic dependence between cities. Cities …

2020-01-19abs ↗pdf ↗

We test a historical price time series in a financial market (the NASDAQ 100 index) for a statistical property known as detailed balance. The presence of detailed balance would imply that the market can be modeled by a stochastic process based on a Markov chain, thus leading to equilibrium. In economic terms, a positiv…

2014-03-14abs ↗pdf ↗

ARISE models efficient markets without periodogram or Gaussianity assumptions.

problem Mimicking and learning long-term memory in efficient markets.
method ARISE process using aperiodic spectrum estimation and infinite-sum function of known processes.
result ARISE process has mean-square convergence, consistency, and asymptotic normality without periodogram and Gaussianity assumptions.

Corporate governance struggles to curb fraud in a globalized economy.

problem Lack of effective international regulations against corporate fraud.
method Analyzes historical economic crises and the role of corporate governance.
result Corporate governance is insufficient to prevent large business fraud.

Determining contributions by sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often economic capital is measured as Value-at-Risk (VaR) of the portfolio loss distribution. For many of the credit portfolio risk models used in practice, the VaR c…

2006-12-16abs ↗pdf ↗

QLSTM outperforms LSTM in predicting KSE 100 index movements.

problem Predicting stock market movement in uncertain economic conditions.
method Used LSTM and QLSTM models on monthly data of economic indicators.
result QLSTM provided more accurate predictions of KSE 100 index values.

A new ML algorithm solves complex economic control problems.

problem Solving high-dimensional, finite-horizon stochastic control problems in economics.
method Deep neural network representation of optimal policy functions with three key features.
result Efficiently solves various economic control problems including recursive utility and growth models.

This paper examines allocation mechanisms in markets with transfer costs, showing how these costs affect economic efficiency.

problem Transfer costs in decentralized exchange markets reduce economic efficiency.
method An axiomatic study of allocation mechanisms in the presence of transfer costs, providing robust and conditional mean allocation mechanisms.
result Robust and conditional mean allocation mechanisms are identified, relating to risk sharing in agent pools.

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.

The importance of counterparty credit risk to the derivative contracts was demonstrated consistently throughout the financial crisis of 2008. Accurate valuation of Credit value adjustment (CVA) is essential to reflect the economic values of these risks. In the present article, we reviewed several different approaches f…

2010-10-08abs ↗pdf ↗

We introduce a new diffusion process Xt to describe asset prices within an economic bubble cycle. The main feature of the process, which differs from existing models, is the drift term where a mean-reversion is taken based on an exponential decay of the scaled price. Our study shows the scaling factor on Xt is crucial …

2018-03-21abs ↗pdf ↗

By Markowitz geometry we mean the intersection theory of ellipsoids and affine subspaces in a real finite-dimensional linear space. In the paper we give a meticulous and self-contained treatment of this arch-classical subject, which lays a solid mathematical groundwork of Markowitz mean-variance theory of efficient por…

2017-07-12abs ↗pdf ↗

New method quantifies systemic risk of firms in supply networks.

problem Quantifying economic systemic risk of firms from supply networks.
method Unique value-added tax dataset; novel approach for computing ESR.
result A tiny fraction of companies have high systemic risk impacting 23% of national production.

Study shows how China's stock market reflects economic demand changes during COVID-19.

problem Understanding how stock market volatility is influenced by economic demand changes.
method Divided industries into demand-oriented groups and analyzed spillover networks.
result Spillover effects from demand-oriented sectors to consumption-oriented sectors increased during the outbreak.

FinML-Chain integrates blockchain data for financial machine learning.

problem Challenges in financial machine learning, including missing data, lack of transparency, and incompatible data sources.
method Blockchain technology integrated with machine learning techniques to address financial market challenges.
result Framework generates datasets for analyzing economic mechanisms, advancing financial research.

Using the new data from the OECD-WTO world network of economic activities we construct the Google matrix GG of this directed network and perform its detailed analysis. The network contains 58 countries and 37 activity sectors for years 1995, 2000, 2005, 2008, 2009. The construction of GG, based on Markov chain transi…

2015-07-12abs ↗pdf ↗