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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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52103155206 · Jun 202019922001200920172026
48 results for Economic Factors

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.

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.

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.

The study examines how global economic policy uncertainty affects crude oil futures volatility.

problem Predicting crude oil futures volatility using global economic policy uncertainty.
method Established single-factor and two-factor models under the GARCH-MIDAS framework, tested with rolling-window and fixed-span specifications.
result GEPU changes have stronger predictive power than the GEPU index for crude oil futures volatility.

Paper uses non-linear dimension reduction for better economic forecasting.

problem Analyzing economic effects of shocks in large datasets.
method Non-linear dimension reduction in factor-augmented vector autoregressions.
result Non-linear dimension reduction techniques improve forecasting, especially in volatile data.

Alpha-R1 uses LLMs to reason about economic factors and news for better alpha screening.

problem Challenges in data-driven investment strategies due to signal decay and regime shifts.
method Reinforcement learning trained on 8B parameters to evaluate alpha relevance under changing market conditions.
result Empirically outperforms benchmark strategies and shows improved robustness to alpha decay.

Study finds relevance of exchange and inflation rates to economic factors.

problem Determining the relevance of exchange and inflation rates to economic factors.
method Introduced concept of adequacy, established positive relation between exchange and inflation rates and other economic factors.
result Close positive relation found between exchange and inflation rates and other economic factors.

Study examines money flow network among firms' accounts in a Japanese region.

problem Understanding the relationship between money flow and economic activities of firms.
method Employed exhaustive bank transfer data, network statistics, Hodge decomposition, and non-negative matrix factorization.
result Identified a 'walnut' structure with core and upstream/downstream components, correlated with economic activities.

We report quantitative relations between corruption level and economic factors, such as country wealth and foreign investment per capita, which are characterized by a power law spanning multiple scales of wealth and investments per capita. These relations hold for diverse countries, and also remain stable over differen…

2007-05-01abs ↗pdf ↗

Enhances FAVAR models with autoencoder for better economic forecasting and interpretability.

problem Limitations of linear FAVAR models in forecasting and structural analysis.
method Introduces Grouped Sparse autoencoder with time-varying parameters.
result The Grouped Sparse autoencoder produces more interpretable factors and superior forecasting performance.

This work aims to study the Portuguese regional agglomeration process, using the linear form the New Economic Geography models that emphasize the importance of spatial factors (distance, costs of transport and communication) in explaining of the concentration of economic activity in certain locations. In a theoretical …

2011-10-25abs ↗pdf ↗

We obtain a lower asymptotic bound on the decay rate of the probability of a portfolio's underperformance against a benchmark over a large time horizon. It is assumed that the prices of the securities are governed by geometric Brownian motions with the coefficients depending on an economic factor, possibly nonlinearly.…

2016-02-05abs ↗pdf ↗

Concurrent engineering taking into account product life-cycle factors seems to be one of the industrial challenges of the next years. Cost estimation and management are two main strategic tasks that imply the possibility of managing costs at the earliest stages of product development. This is why it is indispensable to…

2010-11-26abs ↗pdf ↗

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.

Being one of the most important factors of economic growth of the country, innovations became one of the key vectors in Russian economic policy. In this field technology parks are one of the most effective instruments which can provide growth of innovative activity in sectors, regions and economies. In this paper, we m…

2014-02-21abs ↗pdf ↗

Innovation is among the key factors driving a country's economic and social growth. But what are the factors that make a country innovative? How do they differ across different parts of the world and different stages of development? In this work done in collaboration with the World Economic Forum (WEF), we analyze the …

2016-06-15abs ↗pdf ↗

Paper defines conditions for feasible correlation matrices from factor structures.

problem Feasibility of option implied correlation matrices in non-FX markets.
method Quantitative and economic approaches to solve the nearest correlation matrix problem.
result Introduces methods to ensure feasible correlation matrices from factor structures.

Novel framework analyzes economic shifts in data-poor economies.

problem Data scarcity and unreliability in LMICs hinder accurate assessment of structural transformation.
method Bayesian hierarchical modeling, machine learning, data imputation, factor analysis.
result Framework predicts structural changes even with up to 60% missing data.

The valuation process that economic agents undergo for investments with uncertain payoff typically depends on their statistical views on possible future outcomes, their attitudes toward risk, and, of course, the payoff structure itself. Yields vary across different investment opportunities and their interrelations are …

2010-01-08abs ↗pdf ↗

Model forecasts hourly electricity demand influenced by weather, socio-economic, and political factors.

problem Accurate hourly electricity demand forecasting in the face of multifaceted uncertainties.
method Interpretable probabilistic mid-term forecasting model using Generalized Additive Models (GAMs).
result Highlights vulnerability of countries to extreme weather scenarios under electric heating adoption.

Analyzes how economic policies affect wealth distribution in Bitcoin token economy.

problem Impact of economic policies on wealth distribution in token economies.
method Eliminated noise in wealth distribution data using macroeconomic and microeconomic time series. Causality analysis between BIPs and wealth distribution data.
result Proposed a structure for economic policy taxonomy in token economies.

Hybrid approach improves probabilistic forecasts for electricity trading.

problem Improving probabilistic forecasts for electricity trading markets.
method Combines QRA and factor-based averaging for probabilistic forecasting.
result The hybrid approach outperforms benchmarks in statistical measures and economic value.

In the paper portfolio optimization over long run risk sensitive criterion is considered. It is assumed that economic factors which stimulate asset prices are ergodic but non necessarily uniformly ergodic. Solution to suitable Bellman equation using local span contraction with weighted norms is shown. The form of optim…

2015-08-22abs ↗pdf ↗

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.

Paper introduces a new method for calibrating ESGs to both historical and forward-looking data.

problem Lack of a generally accepted methodology for calibrating ESGs to forward-looking information.
method Conditional Scenario Simulator framework for consistent calibration of economic and financial variables.
result Framework can embed various financial and macroeconomic models and demonstrate practical examples in frequentist and Bayesian settings.

Hierarchical analysis is considered and a multilevel model is presented in order to explore causality, chance and complexity in financial economics. A coupled system of models is used to describe multilevel interactions, consistent with market data: the lowest level is occupied by agents generating the prices of indivi…

2014-08-24abs ↗pdf ↗

Study uses ML and causal analysis to predict student performance factors.

problem Understanding socio-academic and economic factors affecting student performance.
method Employed machine learning techniques and causal analysis on 1,050 student profiles.
result Ridge Regression achieved robust predictions with MAE of 0.12 and MSE of 0.024.

Study uses Perelman and Ricci flow methods to analyze economic inequality.

problem Impact of socio-economic challenges and technological progress on economic inequality.
method Perelman model and Ricci flow methods.
result Technological innovations and social protection programs reduce inequality.