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.
Study examines how economic policy uncertainty impacts stock markets.
The study examines tail dependence between global economic uncertainty and BRICS currencies using high-frequency data.
This study analyzes economic policy uncertainty indices using visibility graphs.
Study shows oil prices but not COVID-19 cases affect US economic policy uncertainty.
Study shows economic policy uncertainty increases stock market crash risk during pandemic.
This study examines how economic policy uncertainty impacts commodity prices across different crises.
Elevating houses to flood risk increases uncertainty, leading to higher optimal elevations.
Paper extends quantile factor analysis with probabilistic methods for better economic policy and financial condition prediction.
The study examines how global economic policy uncertainty affects crude oil futures volatility.
Study finds multifractal cross-correlations between agricultural markets and external uncertainties.
From positions, attained by modern theoretical physics in understanding of the universe bases, the methodological and philosophical analysis of fundamental physical concepts and their formal and informal connections with the real economic measurings is carried out. Procedures for heterogeneous economic time determinati…
In this article, we address the question of how non-knowledge about future events that influence economic agents' decisions in choice settings has been formally represented in economic theory up to date. To position our discussion within the ongoing debate on uncertainty, we provide a brief review of historical develop…
Examines predictability and complexity of economic time series using symbolic dynamics and entropy.
This work introduces uncertainty principles to mitigate Maximal Extractable Value in blockchain systems.
The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakt…
This paper attempts to provide a decision-theoretic foundation for the measurement of economic tail risk, which is not only closely related to utility theory but also relevant to statistical model uncertainty. The main result is that the only risk measures that satisfy a set of economic axioms for the Choquet expected …
This paper presents an assessment of global economic energy potentials for all major natural energy resources. This work is based on both an extensive literature review and calculations using natural resource assessment data. Economic potentials are presented in the form of cost-supply curves, in terms of energy flows …
The study optimizes supply chain management through a dice-based model to predict cleaner production.
There is empirical evidence that recovery rates tend to go down just when the number of defaults goes up in economic downturns. This has to be taken into account in estimation of the capital against credit risk required by Basel II to cover losses during the adverse economic downturns; the so-called "downturn LGD" requ…
The study analyzes how probabilistic forecasts improve battery trading strategies in electricity markets.
At what level should government or companies support research? This complex multi-faceted question encompasses such qualitative bonus as satisfying natural human curiosity, the quest for knowledge and the impact on education and culture, but one of its most scrutinized component reduces to the assessment of economic pe…
DRL enhances economic modeling with deep learning methods.
Model forecasts hourly electricity demand influenced by weather, socio-economic, and political factors.
We establish explicit socially optimal rules for an irreversible investment deci- sion with time-to-build and uncertainty. Assuming a price sensitive demand function with a random intercept, we provide comparative statics and economic interpreta- tions for three models of demand (arithmetic Brownian, geometric Brownian…
Paper classifies economic states and optimizes portfolios for stagflationary environments.
The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance has produced valuable results. The principal movement which has steered this research direction is known under the name of `econophysics'. In this paper, we illustrate and advance some of the…
GP CC-OPF solves uncertain power grid optimization with Gaussian Process.
Predicting panic is of critical importance in many areas of human and animal behavior, notably in the context of economics. The recent financial crisis is a case in point. Panic may be due to a specific external threat, or self-generated nervousness. Here we show that the recent economic crisis and earlier large single…
Every production-recycling iteration accumulates an inevitable proportion of its matter-energy in the environment, lest the production process itself would be a system in perpetual motion, violating the second law of Thermodynamics. Such high-entropy matter depletes finite stocks of ecosystem services provided by the e…
LemonadeBench evaluates LLMs' economic intuition through a simulated lemonade stand.
Study models risks for low-carbon economy in Balkan countries, focusing on shadow economy and populism.
The study examines robust decision-making in volatile financial markets, finding action robustness is more impactful than uncertainty tolerance.
Uncertainty in economics still poses some fundamental problems illustrated, e.g., by the Allais and Ellsberg paradoxes. To overcome these difficulties, economists have introduced an interesting distinction between 'risk' and 'ambiguity' depending on the existence of a (classical Kolmogorovian) probabilistic structure m…
How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and economic activities of the world's 3,000 largest firms and their almost one million subsidiaries. From this information we generate a bipartite …
New methods improve uncertainty in machine learning predictions for asset returns.
Paper uses non-linear dimension reduction for better economic forecasting.
A four-pronged approach to dealing with Social Science Phenomenon is outlined. This methodology is applied to Financial Services, Economic Growth and Well-Being. The four prongs are like the four directions for an army general looking for victory. Just like the four directions, we need to be aware that there is a degre…
Unified framework for risk evaluation under uncertainty.
This paper uses a diffusion model to forecast electrical loads with uncertainty.
This paper introduces forward-looking measures of the network connectedness of fears in the financial system, arising due to the good and bad beliefs of market participants about uncertainty that spreads unequally across a network of banks. We argue that this asymmetric network structure extracted from call and put tra…
Study measures risk spillovers between US and China's agricultural futures markets.
New algorithm breaks multiagency gap in robust MARL.
GPR ensemble method predicts stock returns efficiently.
Enhances FAVAR models with autoencoder for better economic forecasting and interpretability.
This paper provides an innovative perspective on the role of gold as a hedge and safe haven. We use a quantile-on-quantile regression approach to capture the dependence structure between gold returns and changes in uncertainty under different gold market conditions, while considering the nuances of uncertainty levels. …
Novel framework analyzes economic shifts in data-poor economies.
In the late 90's, after severe financial and economic crisis, accompanied by inflation and exchange rate instability, Eastern Europe emerged into two groups of countries with radically contrasting monetary regimes (Currency Boards and Inflation targeting). The task of our study is to compare econometrically the perform…
In this article we consider the parameter risk in the context of internal modelling of the reserve risk under Solvency II. We discuss two opposed perspectives on parameter uncertainty and point out that standard methods of classical reserving focusing on the estimation error of claims reserves are in general not approp…