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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.

168,742 papers · 148 categories

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36912 · May 202619922001200920172026
48 results for corporate boards

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.

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.

Study shows activist board representation improves Japanese companies' performance.

problem Lack of innovation and improvement in Japanese companies.
method Examined two Japanese companies with activist board representation, analyzing performance metrics.
result Companies with activist board representation experienced significant improvements in stock returns and operational metrics.

Study finds optimal board gender diversity for emissions performance.

problem Association between board gender diversity and emissions performance.
method Panel regressions, machine learning, explainable AI.
result Optimal board gender diversity for emissions performance is approximately 35%.

Study assesses environmental management accounting practices in Bangladesh.

problem Low environmental management accounting practices in Bangladeshi manufacturing companies.
method Developed a compliance checklist and evaluated practices using binary scoring.
result Environmental management accounting practices are poor in Bangladeshi manufacturing companies.

In this work, we consider Corporate Governance (CG) ties among companies from a multiple network perspective. Such a structure naturally arises from the close interrelation between the Shareholding Network (SH) and the Board of Directors network (BD). In order to capture the simultaneous effects of both networks on CG,…

2014-01-17abs ↗pdf ↗

Study improves pension scheme efficiency in Kenya through governance and risk management.

problem Limited research on efficiency of Kenyan pension schemes under governance structures.
method Quantitative panel regression analysis on 128 Kenyan pension schemes over 7 years.
result Employee board members have a significant positive effect on pension scheme efficiency.

Study finds risk management significantly improves pension scheme efficiency in Kenya.

problem Improving efficiency of pension schemes in Kenya.
method Panel data analysis of 128 pension schemes from 2015-2021.
result Risk management significantly mediates the relationship between corporate governance and pension scheme efficiency.

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.

Achieving superhuman playing level by AlphaGo corroborated the capabilities of convolutional neural architectures (CNNs) for capturing complex spatial patterns. This result was to a great extent due to several analogies between Go board states and 2D images CNNs have been designed for, in particular translational invar…

2017-11-17abs ↗pdf ↗

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.

Proposes proactive bed requests to reduce ED boarding and patient wait times.

problem Reduces ED boarding and patient wait times by proactively requesting inpatient beds.
method Formulates as a Markov decision process, uses predictions of admission probability and time to disposition to guide bed requests.
result Proactive aggregate bed requests can reduce boarding times by 30-70% and length of stay by 6-15%.

Taylor's law of temporal fluctuation scaling, variance \sim a(a(mean)b)^b, is ubiquitous in natural and social sciences. We report for the first time convincing evidence of a solid temporal fluctuation scaling law in stock illiquidity by investigating the mean-variance relationship of the high-frequency illiquidity o…

2016-10-04abs ↗pdf ↗

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.

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.

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 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.

Node centrality is one of the most important and widely used concepts in the study of complex networks. Here, we extend the paradigm of node centrality in financial and economic networks to consider the changes of node "importance" produced not only by the variation of the topology of the system but also as a consequen…

2019-07-18abs ↗pdf ↗

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.

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.

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.

Model for corporate bond pricing with credit rating migration, solving a double free boundary problem.

problem Corporate bond pricing with credit rating migration risks.
method Established a pricing model as a double free boundary problem, proving existence, uniqueness, and regularity of the solution.
result Two free boundaries are shown to be smooth and converge to a traveling wave solution as time goes to infinity.

Study evaluates neural networks for corporate credit rating assessment.

problem Improving machine learning algorithms for credit assessment.
method Analysis of four neural network architectures (MLP, CNN, CNN2D, LSTM) on financial data from energy, financial, and healthcare sectors.
result LSTM architecture consistently outperforms others in predicting corporate credit ratings.

This study examines the execution phase of corporate share buy-backs, highlighting inefficiencies and costs.

problem Lack of research on share buy-back execution practices and associated costs.
method Comparative analysis of execution practices and fees charged to corporations and investors.
result Uncovered inefficiencies and frictional costs in share buy-back executions, advocating for transparency and fairness.