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,…
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48 results for “economic constraints”
We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in a classic expected return maximization problem. For what we call the infimum of expectations class of risk measures, we show that if the decision maker (DM) maximizes the expectation of a random return unde…
Sigma simplifies collaboration in economics with a streamlined computational representation.
problem Lack of effective collaboration tools in economics for large-scale projects.
method Introduces Sigma, a domain-specific computational representation for economics based on facets, contributions, and constraints of data.
result Sigma enables sharing and formalizing domain-specific concepts in economics for crowd-based scientific investigations.
This paper extends forecast reconciliation to non-linearly constrained time series.
problem Forecasting time series with non-linear constraints.
method Non-linearly Constrained Reconciliation (NLCR) algorithm that adjusts forecasts to meet non-linear constraints.
result NLCR significantly improves forecast accuracy compared to benchmarks.
Maximum Entropy Framework for a Universal Rank Order distribution with Socio-economic Applicationsphysics.soc-ph
Paper derives the maximum entropy characteristics of a rank order distribution for socio-economic applications.
problem Deriving the maximum entropy characteristics of a rank order distribution for socio-economic applications.
method Maximum entropy framework, deriving the discrete generalized beta distribution under a bivariate utility constraint.
result The discrete generalized beta distribution is a natural maximum entropy distribution under an appropriate bivariate utility constraint.
Kernel-based tests for shape constraints in finance.
problem Enforcing shape relations on latent functions in financial econometrics.
method Kernel-based nonparametric framework for mean-variance optimization.
result Established statistical properties and a joint Wald-type statistic for testing shape constraints.
Recent work has shown that a country's productive structure constrains its level of economic growth and income inequality. Here, we compare the productive structure of countries in Latin America and the Caribbean (LAC) with that of China and other High-Performing Asian Economies (HPAE) to expose the increasing gap in t…
Cost-sensitive learning improves predictive maintenance by reducing costs.
problem Predictive maintenance models often lead to higher costs than expected.
method Propose selecting models based on economic costs rather than traditional metrics.
result Cost reduction and fault-tolerant policies achieved through cost-sensitive learning.
DRL enhances economic modeling with deep learning methods.
problem Complex dynamic business environments in economics.
method Comprehensive review of DL, RL, and deep RL methods applied to economics.
result DRL provides better performance and higher accuracy in economic applications.
Solves risk minimization problem with SSD constraints.
problem Finding SSD-minimal quantile function under mixed constraints.
method Explicitly works out SSD-minimal solution and relates to Skorokhod problem.
result Explicit solution to risk minimizing problem.
The study explains YouTube commenters' behavior using rational inattention models.
problem Understanding and predicting YouTube commenters' behavior.
method Deep embedded clustering for user grouping, Bayesian revealed preferences for rationality testing, and behavioral economics constraints for attention span modeling.
result Most YouTube user groups optimize a Bayesian utility with rationally inattentive constraints.
Paper tackles hard shape constraints in kernel machines.
problem Enforcing shape requirements in a hard fashion is challenging.
method Tightened second-order cone constrained reformulation for kernel machines.
result Performance guarantees and efficiency demonstrated in various applications.
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.
The paper presents instructive interdisciplinary applications of constrained mechanics calculus in economics on a level appropriate for the undergraduate physics education. The aim of the paper is: 1. to meet the demand for illustrative examples suitable for presenting the background of the highly expanding research fi…
Econophysics, is based on the premise that some ideas and methods from physics can be applied to economic situations. We intend to show in this paper how a physics concept such as entropy can be applied to an economic problem. In so doing, we demonstrate how information in the form of observable data and moment constra…
In this paper, we work in the framework of the Merton problem but we impose a drawdown constraint on the consumption process. This means that consumption can never fall below a fixed proportion of the running maximum of past consumption. In terms of economic motivation, this constraint represents a type of habit format…
Solves ambiguity in incomplete markets by minimizing price measure entropy.
problem Ambiguity in pricing incomplete markets.
method Minimizes the entropy of the price measure from the economic measure, subject to mark-to-market constraints.
result Resolves ambiguity and provides a consistent pricing measure.
Volume of the steady-state space of financial flows in a monetary stock-flow-consistent modelphysics.soc-ph
We show that a steady-state stock-flow consistent macro-economic model can be represented as a Constraint Satisfaction Problem (CSP).The set of solutions is a polytope, which volume depends on the constraintsapplied and reveals the potential fragility of the economic circuit,with no need to study the dynamics. Several …
These notes discuss several topics in neoclassical economics and alternatives, with an aim of reviewing fundamental issues in modeling economic markets. I start with a brief, non-rigorous summary of the basic Arrow-Debreu model of general equilibrium, as well as its extensions to include time and contingency. I then ar…
Micro-economic Analysis of the Physical Constrained Markets: Game Theory Application to Competitive Electricity Marketsphysics.soc-ph
Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower and a lower price, leading to higher market efficiency. Electricity …
Study develops time-continuous models and probabilistic descriptions for agent-based economic market models.
problem Formulating and describing agent-based economic market models in a time-continuous and probabilistic manner.
method Derived time-continuous formulations, discussed impact of time-scaling, proved stability, presented probabilistic descriptions using kinetic theory.
result Time-continuous formulations and probabilistic descriptions for agent-based economic market models.
Comonotonic allocations are restored under certain constraints, improving risk-sharing.
problem Feasibility constraints can distort optimal risk-sharing allocations.
method Identified componentwise convex-order solidity as a sufficient condition to restore comonotonic allocations.
result Componentwise convex-order solidity ensures comonotonic improvements under feasible constraints.
In economic and financial networks, the strength of each node has always an important economic meaning, such as the size of supply and demand, import and export, or financial exposure. Constructing null models of networks matching the observed strengths of all nodes is crucial in order to either detect interesting devi…
SOFARI improves inference on multi-task learning latent factors.
problem Challenges in precise inference on multi-task learning latent factor matrices.
method High-dimensional manifold-based Neyman near-orthogonality inference on Stiefel manifold structure.
result Easy-to-use bias-corrected estimators for latent factor vectors and singular values with asymptotic normal distributions.
A new VAR model with low-rank constraint for high-dimensional correlated series.
problem Predicting high-dimensional correlated series with hidden factors.
method Vector auto-regressive (VAR) model with low-rank transition matrix.
result Our method shows excellent performances on various simulated datasets and competitive/predictive in real macro-economic data.
ARTEMIS combines deep learning and symbolic reasoning for financial predictions.
problem Lack of interpretability and economic principles in deep learning models in finance.
method Neuro-symbolic framework combining neural operators, stochastic differential equations, and symbolic distillation.
result ARTEMIS achieves state-of-the-art directional accuracy, outperforming all baselines on synthetic crash regime.
Optimizing post-crisis recovery in scale-free networks by stimulating high-degree nodes.
problem Determining the most cost-effective nodes to stimulate in scale-free networks for economic recovery.
method Utilized the Ising model to analyze metastable features and costs of stimulating nodes in scale-free networks.
result Stimulation of high-degree nodes is more cost-effective in scale-free networks compared to regular networks.
Emerging economies use countercyclical policies to manage crises and dominant currencies.
problem Managing economic crises and fluctuations in dominant currencies like USD and EUR.
method Theoretical analysis, case studies, econometric modeling.
result Emerging economies can stabilize growth with countercyclical monetary policies.
Statistical models of economic distributions lead to Boltzmann distributions rather than a Pareto power law. This result is supported by two facts: 1. the distributions of income, car sales, marriages or jobs are a matter of chances and luck and not of reason! 2. Data for property, automobile sales, marriages and job m…
Sparse oblique decision tree improves security rules for renewable power systems.
problem Identifying secure operating conditions in power systems with high renewable energy.
method Sparse weighted oblique decision tree to learn and embed linear security rules.
result The method significantly increases secure states and reduces solution time.
The global financial crisis, beginning in 2008, took an historic toll on national economies around the world. Following equity market crashes, unemployment rates rose significantly in many countries: Italy was among those. What will be the impact of such large shocks on Italian healthcare finances? An empirical model f…
Model explains money creation under regulatory constraints.
problem Understanding money creation dynamics under regulatory pressures.
method Agent-based model of secured interbank network.
result Excess liquidity and repurchase agreements emerge due to regulatory constraints.
Study arbitrage in financial markets with trading restrictions.
problem Arbitrage in financial markets with trading constraints.
method Portfolio optimization problems and discrete-time setup.
result Solvability of portfolio optimization problems equivalent to absence of first kind arbitrage.
Productivity and credit limits affect aggregate production in non-monotonic ways.
problem Understanding how aggregate production is influenced by individual characteristics and financial constraints.
method Analytical proof of non-monotonic effects of productivity and credit limits on aggregate production in a general equilibrium model.
result Equilibrium aggregate production can be non-monotonic in both individual productivity and credit limit.
The paper extends utility maximization by integrating partial information and robust VaR constraints.
problem Optimal investment under partial information and robust VaR-type constraints.
method Combines partial information and robust regulatory constraints (VaR) to solve the utility maximization problem.
result Optimal wealth is a decreasing function of state price density, and depends on the overall evolution of the estimated market price of risk.
LLMs detect market patterns through causal reasoning, not just temporal association.
problem Detecting structural market patterns in financial data.
method Obfuscation testing using the WHO-WHOM-WHAT framework.
result LLMs achieve 71.5% detection rate of market patterns without temporal context.
Study optimal consumption and portfolio strategies with no-borrowing constraint in financial markets.
problem Maximizing utility from consumption under constraints in a stochastic environment.
method Lagrange duality and singular control problem to solve dynamic no-borrowing constraint.
result Retrieve optimal portfolio and consumption plans via dual singular control problem.
This research tackles information design in multi-agent reinforcement learning.
problem Designing information to influence other adaptive agents in a non-stationary environment.
method Formulated Markov signaling game, introduced signaling gradient and extended obedience constraints.
result Developed efficient algorithm for mixed-motive tasks in multi-agent reinforcement learning.
Minimal model reveals power laws in financial markets.
problem Understanding universal behaviors in financial markets.
method Analytical solution of a minimal model based on symmetry constraints.
result Various power-law behaviors are interconnected, similar to critical exponents.
Machine learning improves air pollution predictions in low-cost sensor networks.
problem Invalid predictions from low-cost sensors in resource-constrained countries.
method Probabilistic machine learning to model sensor calibration as distributions or Gaussian processes.
result Improves air pollution predictions and decision-making processes.
Differential privacy for simple linear regression protects small datasets from individual data leaks.
problem Protecting sensitive personal information in small datasets from individual data leaks.
method Differential privacy algorithms for simple linear regression tailored for small datasets (tens to hundreds of datapoints).
result Robust estimators like Theil-Sen perform well on small datasets, but standard algorithms improve as dataset size increases.
New method separates model and non-model risks for more practical asset pricing.
problem Asset pricing under model-uncertainty.
method Binary model-risks and constraints over preferences; unique model-risk pricing formula.
result Unique model-risk pricing formula with dynamically conserved constant.
We study the performance of the euro/Swiss franc exchange rate in the extraordinary period from September 6, 2011 and January 15, 2015 when the Swiss National Bank enforced a minimum exchange rate of 1.20 Swiss francs per euro. Based on the analogy between Brownian motion in finance and physics, the first-order effect …
Study tests five popular trading signal families and finds four refuted, one inconclusive, and one not refuted.
problem Testing the viability of five popular trading signal families for generating a positive edge.
method Statistical edge testing, economic viability assessment, and finite-bankroll survival under leverage using exposure-matched benchmarks, stationary-bootstrap confidence intervals, and hierarchical Benjamini-Yekutieli control.
result Four out of five signal families are refuted, one is inconclusive, and one is not refuted.
This paper considers an optimal control of a big financial company with debt liability under bankrupt probability constraints. The company, which faces constant liability payments and has choices to choose various production/business policies from an available set of control policies with different expected profits and…
This work relaxes OT problems with marginal moments constraints, achieving finite discrete measures.
problem Solving Optimal Transport problems with marginal moments constraints.
method Relaxation of OT problems using moment constraints and Tchakaloff's theorem.
result The Moment Constrained Optimal Transport problem (MCOT) is achieved by a finite discrete measure.
Develops a new framework for integrating satellite allocations in small portfolios.
problem Feasibility constraints in small portfolios, not return predictability, are the primary concerns.
method A four-layer feasibility framework: physical, economic, structural, and epistemic.
result Closed-form feasibility bounds on satellite size, turnover, and breadth without return forecasts.
Deep learning models improve stock market portfolio returns.
problem Optimizing portfolio returns using deep learning methods.
method Deep neural networks (feedforward and LSTM) applied to stock market excess returns forecasting.
result Deep learning models deliver significant gains in portfolio certainty equivalent returns and Sharpe ratios.