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 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.
This paper reviews digital transformation research from 2011-2024, focusing on corporate finance.
problem Lack of systematic review in digital transformation from corporate finance perspective.
method Combines bibliometric and content analysis methods.
result Emerging and rapidly growing focus on digital transformation, particularly in developed countries.
Study finds Twitter sentiment analysis useful for retail finance analysis.
problem Determining if Twitter sentiment correlates with financial metrics.
method Comparative analysis of Twitter sentiment, stock returns, and volume.
result Social media sentiment analysis is valuable for retail finance analysis.
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.
New tool helps analyze complex financial data.
problem Difficulty in comprehending high-dimensional financial data.
method Topological Data Analysis Ball Mapper algorithm.
result Shows new way to see detail in financial data.
LLMs improve financial sentiment analysis in finance.
problem Defining and measuring financial sentiment.
method Investigation of sentiment measurement methods and LLMs.
result LLMs enhance financial sentiment analysis.
FinTMMBench benchmarks RAG systems for finance tasks across multiple data types and time periods.
problem Evaluating temporal-aware multi-modal retrieval augmented generation in finance.
method TMMHybridRAG method that converts and integrates data from various modalities and temporal information.
result Demonstrated effectiveness of TMMHybridRAG in diverse financial analysis tasks.
This review explores XAI in finance, highlighting common techniques and areas needing improvement.
problem Balancing accuracy and transparency in financial AI models.
method Bibliometric and content analysis of XAI applications in finance.
result Post-hoc interpretability techniques are most used in financial XAI.
Study assesses consistency and reproducibility of LLMs in finance and accounting tasks.
problem Consistency and reproducibility of LLM outputs in finance and accounting research.
method Extensive experimentation with 50 independent runs across 5 tasks using 3 OpenAI models.
result Task-specific patterns of consistency and reproducibility, with binary classification and sentiment analysis achieving near-perfect reproducibility.
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.
Improved sentiment analysis in Korean finance using masked PLMs.
problem Fine-grained sentiment analysis in non-English finance literature is lacking due to limited annotated data.
method Developed KorFinASC dataset and applied TGT-Masking to PLMs to remove non-stationary knowledge.
result Improved classification accuracy by 22.63% on KorFinASC.
Extends Itô's formula for path-dependent functions in finance.
problem Modeling and hedging of path-dependent financial options.
method Functional extension of Itô's formula for C^{0,1}-functions of continuous weak Dirichlet processes.
result Validates the hedging or superhedging problems for path-dependent options.
We develop a framework for analyzing extreme values in correlated financial data.
problem Quantifying and mitigating risk in complex financial systems.
method Developed a practical framework for handling finite, multivariate, and correlated time series in finance.
result We successfully analyze high-frequency stock returns using univariate extreme value tools.
New method maps high-dimensional data using Correspondence Analysis.
problem Data scaling in very high dimensional spaces.
method Correspondence Analysis for orthonormal mapping.
result Power law distributed data can be effectively mapped.
Paper proves existence of Lévy term structure models.
problem Existence proof for Lévy term structure models.
method Proof of existence and uniqueness for Heath-Jarrow-Morton type equation.
result Full proof of existence and uniqueness of Lévy term structure models.
Analyzes how venture investment strategies have evolved over time in different sectors.
problem Understanding changes in venture investment strategies across sectors over time.
method Applied PCA and TCA to analyze a dataset of 52,000 startups and 110,000 funding rounds.
result There has been a shift in venture investment towards lower-tech sectors and a rise in accelerator investments.
This study compares decentralized banks and finds some lack decentralization.
problem Decentralized banks do not fully decentralize transactions as expected.
method Network analysis of transaction data from four banks using core-periphery features.
result MakerDao and Compound are more decentralized than Aave and Liquity.
AI in finance uses quantum logic for better decision-making.
problem Improving financial decision-making models using AI.
method Application of quantum logic in machine learning techniques.
result Advantages of quantum-inspired neural networks in finance.
This paper examines market misconduct in DeFi and proposes regulatory solutions.
problem Novel forms of market misconduct in DeFi.
method Comprehensive analysis, comparative study, empirical measurements, and tailored regulatory framework investigation.
result Identification of key areas for regulatory enhancement in DeFi.
AI helps simplify complex ship finance processes.
problem Complexity in ship finance due to data and regulatory requirements.
method Integrates large language models for document comprehension, information extraction, and workflow automation.
result AI-assisted systems can support maritime finance professionals in managing complex information and reporting requirements.
Study on women entrepreneurs' access to finance in France.
problem Inequalities in accessing external finance for women entrepreneurs in France.
method Quantitative approach using data from a representative sample of women entrepreneurs.
result Founder status affects access to external finance; increases success in fundraising but reduces bank finance.
Study finds Aave token network has core-periphery structure, with high decentralization predicting better returns.
problem Understanding the actual decentralization in DeFi token transactions on the Ethereum blockchain.
method Applied social network analysis to measure decentralization in Aave token transactions.
result A more decentralized Aave token network predicts higher returns and lower volatility.
The paper studies BSDEs and their densities in biology and finance.
problem Existence of densities for solutions of BSDEs.
method Conditions for Malliavin differentiability and application to gene expression and finance.
result Results on existence of densities for BSDEs solutions.
This paper proposes a general duality framework for the problem of minimizing a convex integral functional over a space of stochastic processes adapted to a given filtration. The framework unifies many well-known duality frameworks from operations research and mathematical finance. The unification allows the extension …
Entropy-based models analyze bipartite networks in ecology and finance.
problem Nestedness in bipartite networks across different systems.
method Entropy-based null models for bipartite networks.
result Entropy-based models provide a versatile tool for network analysis.
This study aims to improve communication between fragmented blockchain systems in finance.
problem Inefficient and insecure communication in fragmented blockchain systems.
method Analysis of cross-chain interoperability protocols and their properties.
result Comparison and evaluation of cross-chain interoperability protocols.
Symmetry in finance is a neglected but potentially valuable concept.
problem The underutilization of symmetry in financial markets.
method Examining symmetry in game theory, technical analysis, and long-term economic growth.
result Symmetry principles can be applied to financial strategies and market dynamics.
Quantum neural networks can approximate noisy functions accurately.
problem Approximating noisy functions with quantum neural networks.
method Universal approximation theorem with error bounds for noisy quantum neural networks.
result Quantum neural networks can approximate noisy functions with precise error bounds.
Pipeline for comparing trading algorithms in finance and crypto.
problem Disconnected research and applications in algorithmic trading.
method General pipeline for designing, programming, and evaluating trading strategies.
result Systematic comparison of trading algorithms in finance and crypto.
ARCH and GARCH models assume either i.i.d. or (what economists lable as) white noise as is usual in regression analysis while assuming memory in a conditional mean square fluctuation with stationary increments. We will show that ARCH/GARCH is inconsistent with uncorrelated increments, violating the i.i.d. and white ass…
A new time definition simplifies financial analysis by enforcing scale invariance and quantifying overnight returns.
problem Simplifying analysis of financial series with recurrent patterns and seasonalities.
method Symmetry-guided definition of time enforcing simple-scaling and stationarity of returns.
result Identifies a successful protocol of time definition in Finance, reducing multiscaling and quantifying overnight returns.
The paper explores how innovative financing solutions boost Moroccan businesses' performance.
problem Market volatility, ecological transitions, and technological change pose challenges to business sustainability.
method Examines innovative financing solutions like venture capital, green finance, crowdfunding, and blockchain.
result Embracing innovative financial strategies can transform business challenges into opportunities.
Generative model evaluates text emotion intensity, outperforming classification.
problem Limitations of discrete emotion classification in applied domains.
method Fine-tuning generative language models to output continuous emotion intensity scores.
result Generative model outperforms classification baselines and reveals generalization capabilities.
Study uses FinBERT for financial sentiment analysis to predict stock movement.
problem Predicting stock movement with greater accuracy.
method Integrates sentiment analysis with FinBERT and LSTM networks.
result FinBERT enhances model's ability to predict market fluctuations.
This overview article concerns the notion of fractional smoothness of random variables of the form g(XT), where X=(Xt)t∈[0,T] is a certain diffusion process. We review the connection to the real interpolation theory, give examples and applications of this concept. The applications in stochastic finance main…
New methods solve complex PDEs with mixed boundary conditions.
problem Solving inhomogeneous Robin type boundary value problems for linear PDEs.
method Odd and even Hilbert transforms.
result Non-standard solutions to various PDEs in finance, stochastic analysis, etc.
GBST model improves credit risk quantification using survival analysis.
problem Quantifying credit risk in heterogeneous consumer finance data.
method Gradient boosting survival tree (GBST) model integrating survival analysis and gradient boosting.
result GBST model outperforms existing survival models in credit risk quantification.
We analyze how uncertainty in models affects optimization outcomes using Wasserstein distances.
problem Sensitivity of optimization problems to model uncertainty.
method Non-parametric approach using Wasserstein balls to capture uncertainty, providing explicit corrections for value function and optimizer.
result Explicit formulae for first-order corrections to value function and optimizer.
The paper examines extreme value statistics of high-dimensional sample covariances, with applications in finance and image analysis.
problem Statistical validation of normal conditions in high-dimensional time series data.
method Generalizes the maximal deviation of sample autocovariances to high dimensions and applies Gumbel-type extreme value asymptotics.
result Gumbel-type extreme value asymptotics holds true for high-dimensional sample covariances.
Study on decentralization in DAOs and its effect on financial efficiency in DeFi.
problem Understanding the impact of decentralization on financial efficiency in blockchain-based governance.
method Analysis using Gini coefficient as an inequality indicator, comparing ROI of token owners.
result Real decentralization affects financial efficiency positively in DeFi.
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.
Survey of RL in finance, tackling complex decision-making.
problem Complex financial decision-making problems with limited model assumptions.
method Value and policy-based RL algorithms, neural networks, deep RL.
result Improved financial decision-making with less model assumptions.
Factor Engine simplifies financial factor computation and analysis in Python.
problem Efficient computation and analysis of financial factors.
method Modular, extensible Python library with decorators, integrates with data science ecosystem.
result Mispricing factors computed by Factor Engine and Stata implementation are highly similar.
Survey on nonlinear parabolic equations in finance.
problem Nonlinear extensions of the Black-Scholes theory.
method Qualitative and numerical analysis of nonlinear parabolic equations.
result Existence and uniqueness of solutions to nonlinear parabolic equations.
Neural model improves volatility estimation and prediction in finance.
problem Improving volatility estimation and prediction in finance.
method Integrates deep neural networks with stochastic volatility models.
result Proposed model outperforms existing methods on average negative log-likelihood.
DECS tool assesses swap rates of DEXes and Fusion outperforms competitors.
problem Lack of unbiased swap rate comparisons in decentralized finance.
method Swap transaction monitoring and simulation techniques.
result 1inch Classic and Fusion consistently outperform competitors in swap rates.
The paper discusses the importance of infinite-mean models in finance and risk management.
problem Classic statistical models assume finite mean or variance, which is not suitable for heavy-tailed data.
method Discussion and recent results on infinite-mean models in economics and finance.
result Classic statistical results for finite-mean models often fail or flip for infinite-mean models.