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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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9172634 · Dec 202419922001200920172026
48 results for corporate finance

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.

Large corporate credit models may be adapted for small business risk assessment.

problem Limited data and lack of credit analysts for small businesses.
method Adapting large corporate credit risk models for small businesses.
result Adapted models can predict small business credit risk effectively.

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.

Paper presents a faster method for computing cost of equity and performing comparable company analysis.

problem Tedium and subjectivity in traditional cost of equity and comparable company analysis methods.
method Uses spectral and agglomerative clustering to compute cost of equity and perform comparable company analysis.
result Reduces time required for comps by orders of magnitude and improves consistency and reliability.

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.

Visualizes board connections for socially responsible investing insights.

problem Understanding corporate governance and sustainability through board connections.
method Data Visualization tool to reveal connections between Directors and Executives.
result Strength of tool in investigating corporate governance and sustainability.

Paper finds political networks reduce bond issuance costs in China.

problem The financial value of within-government political networks in China.
method Using municipal leaders' working experience to measure political networks, the study examines the effect on bond issuance yield spreads.
result Political networks reduce bond issuance yield spreads by improving issuer credit ratings, especially in less developed financial markets.

New method estimates corporate default probabilities using indirect data.

problem Lack of direct default rate data for corporate companies.
method Modeling default probability dynamics using Bank of Russia overdue debt data.
result Validated method produces trustworthy default probability series.

Paper forecasts corporate default risk using Particle MCMC with expert opinions.

problem Predicting corporate default risk in the U.S. market.
method Bayesian approach with Particle Markov Chain Monte Carlo (Particle MCMC) algorithm.
result Volatility and mean reversion of hidden factor significantly impact default intensities.

The study examines how board diversity and CSR committee composition affect corporate governance and financial performance.

problem The relationship between corporate social responsibility (CSR) and corporate governance.
method Theoretical model development based on management and corporate governance theories, focusing on board diversity and CSR committee composition.
result Cognitive and demographic characteristics of board members provide more insights into the link between corporate governance and CSR.

Paper proposes deep learning model for dynamic stock repurchase forecasting.

problem Complex temporal dependencies in corporate financial conditions.
method Hybrid Temporal Convolutional Network (TCN) and Attention-based LSTM.
result Model significantly outperforms static baselines in stock repurchase forecasting.

CCR-CNN uses CNN to predict corporate credit ratings from financial data.

problem Lack of data and limited model performance in predicting corporate credit ratings.
method Transform corporations into images and use CNN to analyze complex feature interactions.
result CCR-CNN outperforms state-of-the-art methods in predicting corporate credit ratings.

Framework integrates financial and annual report data for better corporate credit ratings.

problem Lack of insights from non-financial data in credit rating models.
method Uses FinBERT to extract features from annual reports and combines them with financial data.
result Improves credit rating accuracy by 8-12%.

CAI automates extraction and validation of corporate GHG emission metrics.

problem Manual extraction of corporate GHG emission metrics is labor-intensive and error-prone.
method CAI uses LLMs to automate extraction and validation of metrics from corporate disclosures.
result CAI improves data collection efficiency and accuracy by automating the process.

Our main task is to study the effect of corporate governance on the market liquidity of listed companies' stocks. We establish a theoretical model that contains the heterogeneity of investors' beliefs to explain the mechanisms by which corporate governance improves liquidity of the corporate stocks. In this process we …

2020-01-17abs ↗pdf ↗

New eco-systemic prudential policies aim to finance green companies, reducing systemic financial risk.

problem Insufficient financing for green companies despite available savings and monetary management.
method Reorient corporate accounting towards socio-environmental solvency, facilitating access with public guarantees.
result Green financing increases, reducing systemic financial risk and promoting less leveraged investments.

Study compares information flow between Chinese and US stock sectors.

problem Analyzing how information flows between sectors in Chinese and US stock markets.
method Daily sector indices, transfer entropy of daily returns, comparing 2000-2017.
result Most active sectors in information exchange differ between China and US, reflecting market dynamics.

Develops a new model to better predict corporate bond yields.

problem Persistent shifts in interest rates undermine single-regime models.
method Regime-switching generalized CIR model with two-state short-rate process and credit factors.
result The model improves joint curve fit and delivers interpretable probabilities.

Paper proposes a new trading strategy using corporate event detection from news articles.

problem Predicting stock movements based on corporate events from news articles.
method Bi-level event detection model: low-level for token-level event identification, high-level for article-level event identification.
result The proposed strategy outperforms existing models in stock prediction metrics.

The AAA credit rating may have been overly precise given available data.

problem The feasibility of achieving high reliability targets for structured credit products.
method Bayes' theorem and historical data analysis.
result High reliability targets for structured products require substantial statistical discrimination, which was not achievable with available data.

Corporate bond factor research is flawed due to measurement errors and ex-post filtering.

problem Replication crisis in corporate bond factor research.
method Analysis of 108 signals across nine thematic clusters, correction of transaction prices and return filtering.
result Majority of previously documented factors do not produce statistically significant alphas after correction.

Two firms compete in a financial market, choosing dividend strategies to avoid default and maximize profits.

problem Strategic interaction between two financially constrained firms in a market with default risk.
method Construct Nash equilibria in feedback form for a class of two-person stochastic games of singular control.
result Explicit identification of optimal strategies and equilibrium payoffs for different initial conditions.

This study identifies financial risk paths in digital-transformed enterprises.

problem Identifying financial risks in digital-transformed enterprises.
method DEMATEL-ISM-MICMAC method.
result Political and economic environment affects enterprise's financial structure.

Corporate transparency reduces investors' disposition effect by increasing confidence in holding profitable and losing stocks.

problem Irrational disposition effect in investors selling profitable assets too soon and holding onto losing assets for too long.
method Examined the impact of corporate transparency on individual investors' disposition effect.
result Increased corporate transparency significantly reduces the disposition effect.