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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.

169,341 papers · 148 categories

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25.0%50.0%75.0%100.0% · Feb 199419922001200920182026
48 results for global finance

Study on how China's SMEs finance changed post-crisis, focusing on internal vs. external financing.

problem Analyzing SME financing problems before and after the global financial crisis.
method Regression analysis based on Trade-Off Theory, empirical research on 158 firms.
result SMEs with high growth rates are more likely to obtain external financing after a financial crisis.

Study uses AI to predict changes in international public finances based on US markets.

problem Understanding correlations between US and international public finances.
method Artificial intelligence and neural networks to model and predict changes.
result Neural network model achieved MSE of 2.79, indicating significant correlation and impact of US market volatility on international markets.

Study maps research streams in biodiversity finance, identifies key areas.

problem Biodiversity loss and need for finance to reverse trends.
method Quantitative bibliometric analysis of 189,456 references.
result Identifies eight primary research streams in biodiversity finance.

Study analyzes global public sentiment on DeFi from 2012-2022.

problem Global public sentiment on DeFi is understudied.
method Sentiment analysis, spatial econometrics, clustering, topic modeling.
result Economic development significantly influences DeFi engagement, especially after 2015.

The study identifies different global dependence regimes in equity and volatility indices.

problem Varying correlations and higher moments between equity and volatility indices across continents.
method Markov-switching RR-vine models to investigate changing dependence structures.
result Global regime switching identified in times of 'normal' and 'abnormal' states.

Study interprets deep learning models for Heston model in finance.

problem Interpreting black-box deep learning models in finance.
method Investigated Heston model using local and global strategies from cooperative game theory.
result Shapley values can effectively explain neural networks and improve model architecture selection.

The DAO Report led to a significant shift of ICO activity to Europe.

problem The impact of U.S. regulatory changes on global ICO activity.
method Analysis of a global dataset of ICOs from 2014 to 2021, focusing on the DAO Report's effects.
result A substantial and persistent reallocation of ICO activity to Europe following the DAO Report.

The paper develops methods to analyze sensitivity in stochastic models using surrogate models.

problem Quantifying the impact of input variability on stochastic simulators with randomness.
method The authors propose using generalized lambda models to emulate response distributions of stochastic simulators and estimate sensitivity indices.
result The proposed method can estimate sensitivity indices even with strong heteroskedasticity and small signal-to-noise ratio.

We describe the innovations in finances, introduced over the recent decades, and analyze most of the business and regulatory challenges, faced by the financial industry, because of the present disruptive changes in the global capital markets. We use the integrative thinking approach to formulate the new central bank st…

2012-11-08abs ↗pdf ↗

Proposes a Carbon Equivalence Principle for financial products to align incentives and drive sustainability.

problem Align financial market incentives with carbon emissions to limit global warming.
method Introduces a Carbon Equivalence Principle requiring financial products to describe equivalent carbon flows alongside cash flows.
result Transparency of carbon flows in financial products can align incentives and reduce future costs, necessitating project re-structuring and financial net-zero designs.

TPLVM models portfolio construction for non-Gaussian financial data.

problem Optimal asset allocation in finance with non-Gaussian fluctuations.
method Student's t-process latent variable model (TPLVM) for portfolio optimization.
result TPLVM outperforms Gaussian process latent variable model in minimum-variance portfolio construction.

New strategy uses consumer and government actions for climate change.

problem Insufficient low-carbon investments despite ethical savings potential.
method Voluntary low-carbon fund and ethical investments for sustainable development.
result Potential for global climate change response through individual actions and investments.

This paper was presented and written for two seminars: a national UK University Risk Conference and a Risk Management industry workshop. The target audience is therefore a cross section of Academics and industry professionals. The current ongoing global credit crunch has highlighted the importance of risk measurement i…

2009-04-06abs ↗pdf ↗

Defines risk-free portfolios and risk-free rate using gauge symmetries.

problem Identifying a consistent definition of risk-free rate in economics.
method Introduces three gauge invariant differential operators to define risk-free portfolios and identifies the risk-free rate as the return of an infinitely diversified portfolio.
result Identifies the risk-free rate as the return of an infinitely diversified portfolio and connects it to global price rescaling as a gauge symmetry.

Designed to compete with fiat currencies, bitcoin proposes it is a crypto-currency alternative. Bitcoin makes a number of false claims, including: solving the double-spending problem is a good thing; bitcoin can be a reserve currency for banking; hoarding equals saving, and that we should believe bitcoin can expand by …

2013-12-07abs ↗pdf ↗

New multifractional processes model stock price roughness over time.

problem Modeling stock price roughness and informativeness over time.
method Introduced a new class of multifractional processes and estimated their PHEs using LGQV.
result Our estimator outperforms existing methods in estimating PHEs of multifractional processes.

New deep learning method solves complex BSDEs efficiently.

problem Solving high-dimensional nonlinear BSDEs.
method Reformulate as global optimization, approximate solution with deep neural network, globally minimize quadratic local loss functions.
result Demonstrated effectiveness on various high-dimensional nonlinear BSDEs, including finance applications.

Proposes a novel model for healthcare and SME credit risk prediction.

problem Lack of guidance from global view in sequence representation learning for time series modeling.
method Hierarchical Global View-guided (HGV) sequence representation learning framework with GGE and ββ-Attn modules.
result Competitive prediction performance compared with other known baselines.

Study shows news influences world markets, revealing correlations between The New York Times and financial indices.

problem Understanding the relationship between news and financial markets.
method Used Random Matrix Theory and information theory on news and financial indices.
result News drives world market movements, showing correlations preserved even with noise.

Experts predict significant adoption of decentralized finance by 2034, with traditional finance adapting.

problem Adoption and integration of decentralized finance (DeFi) in financial services.
method Survey analysis using New Institutional Economics and Dynamic Capabilities Theory.
result Experts expect adoption of DeFi to rise from negligible to 43% by 2034, with traditional finance likely to embrace it.

The objective of the note is to remind readers on how self-financing works in Quantitative Finance. The authors have observed continuing uncertainty on this issue which may be because it lies exactly at the intersection of stochastic calculus and finance. The concept of a self-financing trading strategy was originally,…

2015-01-12abs ↗pdf ↗

New algorithm tackles stochastic optimization with inequality constraints.

problem Stochastic optimization with inequality constraints in various applications.
method Active-set stochastic sequential quadratic programming (StoSQP) with a differentiable exact augmented Lagrangian.
result Global convergence for any initialization, KKT residuals converge to zero almost surely.

Quantitative model predicts Sri Lankan stock market using NLP, clustering, and time-series forecasting.

problem Predicting economic regimes and market signals in Sri Lankan stock indices.
method Integrates NLP, clustering, and time-series forecasting; uses FinBERT for sentiment analysis, UMAP/HDBSCAN for clustering, and GRU/LSTM for forecasting.
result GRU model achieves 80.1% R-squared for daily closing price forecasts.

Study shows 'Belt and Road' node cities boost digital finance in China.

problem Impact of 'Belt and Road' node cities on digital inclusive finance.
method Descriptive analysis, literature review, theoretical model, differential differential method.
result Establishment of 'Belt and Road' node cities promotes digital inclusive finance in China, with Internet development as a mediating variable.

Study examines Trump's crypto influence on markets, revealing conflicts and vulnerabilities.

problem Presidential power and cryptocurrency markets during Trump's second term.
method Mixed-methods approach combining quantitative and qualitative data.
result Political-linked digital assets became a distinct class with systemic vulnerabilities.

We use insight from a model of earth tectonic plate movement to obtain a new understanding of the build up and release of stress in the price dynamics of the worlds stock exchanges. Nonlinearity enters the model due to a behavioral attribute of humans reacting disproportionately to big changes. This nonlinear response …

2009-12-18abs ↗pdf ↗