Research
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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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13274053 · Oct 202519922001200920172026
48 results for innovative financing

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.

Regulating crypto and DeFi for inclusive economic advancement.

problem Innovative financial systems pose challenges to traditional regulatory frameworks.
method Formulating regulatory structures that balance innovation and consumer protection.
result Regulatory frameworks are essential for leveraging crypto and DeFi for inclusive economic growth.

Small Medium-sized Enterprises (SMEs) face many obstacles when they try to access credit market. These obstacles are increased if the SMEs are innovative. In this case, financial data are insufficient or even not reliable. Thus, when building a judgemental rating model, mainly based on qualitative criteria (soft inform…

2013-08-05abs ↗pdf ↗

We give a rough sketch of the Judaic, Greek, Islamic and Christian positions in the matter of interest prohibition during the last few millennia and discuss the way in which interest prohibition is dealt with in Islamic finance, the problems with authority-based arguments for interest prohibition, and the prospects of …

2011-04-13abs ↗pdf ↗

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.

RD-Agent(Q) automates quantitative finance research and development.

problem Challenges in asset return prediction due to high dimensionality and volatility.
method Data-centric multi-agent framework for automated research and development of quantitative strategies.
result Up to 2X higher annualized returns with 70% fewer factors.

This study finds ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

problem The impact of ESG rating disagreement on corporate productivity.
method Analysis of A-share listed companies data from 2015 to 2022 using XGBoost regression and SHAP.
result ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

Novel method reconstructs liquidity data for CLMMs, optimizing dynamic liquidity strategies.

problem Challenges in evaluating and optimizing CLMMs due to lack of historical liquidity data.
method Reconstructs historical liquidity states from swap transaction data using machine learning.
result Identifies outperformance of dynamic liquidity strategies over uniform allocation benchmarks.

FinRL-Podracer accelerates DRL trading strategies in finance with high performance and scalability.

problem Challenges in applying deep reinforcement learning to finance trading models.
method Proposes an RLOps framework and high-performance cloud solution for DRL trading.
result FinRL-Podracer outperforms existing DRL libraries by 12-35% in annual return, 0.1-0.6 in Sharpe ratio, and 3-7 times in training time.

This review analyzes RL in finance, highlighting its advantages and challenges.

problem Complex financial decision-making problems where traditional methods fail.
method Systematic review of 167 articles from 2017-2025, focusing on market making, portfolio optimization, and algorithmic trading.
result RL offers advantages over traditional methods, particularly in market making, but challenges remain.

FinGPT democratizes financial data for LLMs, enabling innovation.

problem Limited financial text datasets and disparities between general and financial text data.
method Automates collection and curation of real-time financial data from diverse Internet sources, fine-tuning with RLSP and LoRA.
result Democratizes access to financial data for LLMs, enabling innovation.

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 ↗

Study predicts startup outcomes like funding, patenting, IPOs using machine learning.

problem Forecasting startup success metrics like funding, patenting, IPOs.
method Developed interpretable machine learning framework, used preprocessing, class imbalance handling, and compared multiple models.
result Achieved high AUROC values for patent, funding, and exit predictions.

This study examines how DEXs impact traders' behavior in perpetual futures contracts.

problem Understanding trader behavior in decentralized exchanges.
method Categorizing DEX models and analyzing their impact on trading patterns.
result DEXs, particularly those using VAMM, show differential effects on long and short positions.

Quantum walk algorithm optimizes quantum state preparation for financial simulations.

problem Efficiently loading classical data into quantum states for quantum computers.
method Split-step quantum walks (SSQW) to design parameterized quantum circuits (PQC).
result SSQW facilitates generating desired probability amplitude distributions for quantum simulations.

Deep learning models struggle with new data in stock price trend prediction.

problem Stock price trend prediction using Deep Learning models.
method Examination of fifteen state-of-the-art DL models on LOB data, using LOBCAST framework.
result All models show significant performance drop with new data, questioning their market applicability.

New framework IIA identifies innovations in general nonlinear vector autoregressive processes.

problem Limited generality of NVAR models due to additive innovation assumption.
method Independent Innovation Analysis (IIA) framework, assuming mutual independence and modulation by an auxiliary variable.
result Guarantees identifiability of innovations with arbitrary nonlinearities, up to permutation and component-wise invertible nonlinearities.

Survey of AI in finance covering models, strategies, and knowledge systems.

problem Challenges in applying AI to financial markets, especially in high-frequency trading.
method Systematic analysis of financial AI across predictive models, decision frameworks, and knowledge augmentation systems.
result Critical trade-offs and gaps between theoretical advances and practical implementation in financial AI.

Stablecoins are reshaping global monetary systems, offering hybrid structures with public and private monies.

problem The evolution of stablecoins from crypto innovation to a global monetary component.
method Econometric analysis and hybrid system design modeling.
result Stablecoins maintain strong peg stability, and a hybrid system design ensures financial resilience.

Machine learning models predict which ideas will be innovated based on subjective perspectives.

problem Predicting high-impact innovation based on subjective perspectives and interpersonal innovation opportunities.
method Quantifying subjective perspectives and their interaction based on innovator positions within a geometric space of concepts.
result Subjective perspectives predict which ideas individuals and groups will creatively attend to and successfully combine in the future.

New model predicts financial market abnormalities using stock index uncertainties.

problem Forecasting abnormal financial fluctuations in the market.
method Quantitative analysis of mean and volatility uncertainties, constructing early warning indicators.
result Established a new abnormal fluctuations warning model.

Metaheuristics optimize portfolios with pre-assignment and margin trading for better risk-adjusted returns.

problem Maximizing returns while minimizing risk in portfolio optimization.
method Incorporates pre-assignment constraints and margin trading strategies using Genetic Algorithms and Particle Swarm Optimization.
result Metaheuristic-based portfolio optimization yields superior risk-adjusted returns compared to traditional methods.

AlphaSAGE mines diverse alphas via GFlowNets, overcoming RL issues.

problem Reward sparsity, inadequate sequential representations, and single optimal mode issues in RL for alphas.
method Structure-aware encoder (RGCN), GFlowNets, dense reward structure.
result Empirically outperforms existing baselines in mining diverse alphas.

Examines AI regulation in finance, highlighting risks and gaps in current laws.

problem Rapid AI adoption in finance introduces risks and compliance challenges.
method Reviews current legislation, industry guidelines, and real-world use cases.
result Need for adaptive, technology-neutral policies to balance innovation and consumer protection.

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 ↗

Nanotechnology is the first major worldwide research initiative of the 21st century and probably is the solution vector in the economic environment. Also, innovation is widely recognized as a key factor in the economic development of nations, and is essential for the competitiveness of the industrial firms as well. Pol…

2013-03-20abs ↗pdf ↗

The idea of Innovation Search was proposed as a data clustering method in which the directions of innovation were utilized to compute the adjacency matrix and it was shown that Innovation Pursuit can notably outperform the self representation based subspace clustering methods. In this paper, we present a new discovery …

2019-12-30abs ↗pdf ↗