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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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17345067 · Jul 202019922001200920172026
48 results for economic vulnerabilities

Survival analysis models predict economic convergence across Americas.

problem Analyzing GDP per capita trajectories and convergence across the Americas.
method Survival analysis, machine learning, economic interpretation.
result DeepSurv captures non-linear interactions in GDP per capita trajectories.

Boosting algorithms predict financial vulnerability of farmers in Chile and Tunisia.

problem Predict financial vulnerability of farmers in Chile and Tunisia using environmental data.
method Interpretable boosting algorithms based on ridge-regularized generalized linear models.
result Interaction effects improve predictive power only when included in two-step boosting.

The paper analyzes tech specialization and diversification at various scales.

problem Trade-offs between specialization and diversification in economic development.
method Patent data and Economic Complexity framework.
result Technological Coherence positively impacts growth at metropolitan areas but negatively at larger scales.

In the current era of worldwide stock market interdependencies, the global financial village has become increasingly vulnerable to systemic collapse. The recent global financial crisis has highlighted the necessity of understanding and quantifying interdependencies among the world's economies, developing new effective …

2014-08-03abs ↗pdf ↗

Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understanding where these settlements are is of paramount importance to both gove…

2018-11-30abs ↗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.

This article derives prognostic expressions for the evolution of globally aggregated economic wealth, productivity, inflation, technological change, innovation and growth. The approach is to treat civilization as an open, non-equilibrium thermodynamic system that dissipates energy and diffuses matter in order to sustai…

2013-06-15abs ↗pdf ↗

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.

The study examines how climate risk influences sovereign debt default decisions.

problem The relationship between climate risk and sovereign debt default decisions.
method Calibration of a model to analyze the credit spreads of sovereign bonds and the impact of climate vulnerability on bond spreads.
result Climate risk does not significantly influence the decision to default on sovereign debt.

Inspired by the bankruptcy of Lehman Brothers and its consequences on the global financial system, we develop a simple model in which the Lehman default event is quantified as having an almost immediate effect in worsening the credit worthiness of all financial institutions in the economic network. In our stylized desc…

2010-02-04abs ↗pdf ↗

We develop a model to study the role of rationality in economics and biology. The model's agents differ continuously in their ability to make rational choices. The agents' objective is to ensure their individual survival over time or, equivalently, to maximize profits. In equilibrium, however, rational agents who maxim…

2015-07-14abs ↗pdf ↗

Unified framework deciphers global central bank communications.

problem Misinterpretations of central bank communications can disproportionately impact vulnerable populations.
method Developed the World Central Banks (WCB) dataset, annotated and reviewed sentences, defined tasks, and benchmarked models.
result A model trained on aggregated data across banks outperforms models trained on individual bank data.

Trade networks, across which countries distribute their products, are crucial components of the globalized world economy. Their structure is strongly heterogeneous across products, given the different features of the countries which buy and sell goods. By using a diversified pool of indicators from network science and …

2018-02-23abs ↗pdf ↗

Study reveals widespread manipulation of meme coins, leading to significant economic losses.

problem Widespread manipulation of meme coins leading to economic losses.
method Cross-chain analysis of 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base.
result 82.8% of high-return tokens show evidence of artificial growth strategies.

Despite the remarkable performance of deep neural networks on various computer vision tasks, they are known to be susceptible to adversarial perturbations, which makes it challenging to deploy them in real-world safety-critical applications. In this paper, we conjecture that the leading cause of adversarial vulnerabili…

2019-08-12abs ↗pdf ↗

This paper proposes non-stationary factor models for financial stress in the UK.

problem Managing financial vulnerabilities in the UK's complex financial system.
method Creation of non-stationary factor models to capture financial stress.
result Non-stationary factor models can better capture financial stress, especially tail events.

A membership inference attack (MIA) against a machine-learning model enables an attacker to determine whether a given data record was part of the model's training data or not. In this paper, we provide an in-depth study of the phenomenon of disparate vulnerability against MIAs: unequal success rate of MIAs against diff…

2019-06-02abs ↗pdf ↗

Research creates a taxonomy to bridge AI security and regulatory gaps.

problem Disciplinary disconnect between technical and legal teams in AI risk assessment.
method Developed an AI System Threat Vector Taxonomy with 9 domains and 53 sub-threats.
result Empirically validated and aligned with ISO/IEC 42001 controls and NIST AI RMF functions.

Confounding biases recommender systems, even when data seems fully observed.

problem Unmeasured features influencing both treatment and outcome in recommender systems.
method Illustrations and simulation studies showing how common practices introduce confounding.
result Standard recommender system practices can introduce confounding, reducing performance.

New risk measures assess cryptocurrency market vulnerabilities during financial distress.

problem Capturing systemic risk in cryptocurrency markets during financial distress.
method Introducing Vulnerability Conditional Risk Measures (VCoES) and related measures.
result Validated theoretical insights and demonstrated practical relevance in cryptocurrency market.

Adversarial attacks can fool ML energy theft detection models.

problem Vulnerability of ML-based energy theft detection models to adversarial attacks.
method Design of an adversarial measurement generation algorithm.
result ML models can be significantly fooled by adversarial attacks, reducing their detection accuracy.

This paper analyzes how banking risks spread through sentiment and policy shocks.

problem Systemic risk in the U.S. banking system during the 2023 crisis.
method Time-Varying Parameter Vector Autoregression (TVP-VAR) model with 30-day rolling windows.
result Risk spillovers were driven by perceived similarities in bank business models under interest rate pressure.

Preschool attendance correlates with lower developmental vulnerabilities in Queensland, Australia.

problem Understanding the relationship between preschool attendance and developmental vulnerabilities in different regions.
method Data Analysis and Machine Learning to identify clusters of socio-demographic variables.
result Identified three clusters with varying socio-demographic variables affecting the relationship between preschool attendance and developmental vulnerabilities.

Study on measuring vulnerability of neural network parameters via corruption.

problem Understanding the robustness and generalization of deep neural networks.
method Proposes an indicator to measure parameter robustness via parameter corruption and provides a gradient-based estimation.
result Demonstrates the effectiveness of the proposed indicator and training method in improving parameter robustness and accuracy.

Study reveals clusters of resilient and vulnerable Spanish agri-food firms post-Ukraine-Russia war.

problem Financial resilience of agri-food companies in Spain during the Ukraine-Russia conflict.
method Cluster analysis using centred log-ratios for compositional data of financial ratios.
result Increase in resilient firms by 2023, highlighting sectoral adaptation to economic challenges.

Study reveals how high-dimensional models are vulnerable to consistent adversarial attacks.

problem Understanding the vulnerability of high-dimensional linear classifiers to adversarial attacks.
method Introducing a new error metric to quantify model vulnerability, and rigorously characterizing these metrics in asymptotic settings.
result As models become more overparameterized, their vulnerability to label-preserving perturbations increases.

Thousands of security vulnerabilities are discovered in production software each year, either reported publicly to the Common Vulnerabilities and Exposures database or discovered internally in proprietary code. Vulnerabilities often manifest themselves in subtle ways that are not obvious to code reviewers or the develo…

2018-02-14abs ↗pdf ↗

The paper analyzes how much data points can be altered to change their rank in nearest neighbor searches.

problem Vulnerability of nearest neighbor search in high-dimensional data.
method Statistical analysis of perturbation needed to change neighbor rank.
result Derived statistical distribution of perturbation needed to modify neighbor rank.