Study finds corporate boards with women appoint more women, leading to better profitability.
problem Influence of female board members on corporate profitability.
method Analysis of Japanese corporate boards and their interlocks.
result Corporate boards with women appoint more women, leading to higher profitability.
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.
Current study aims to provide new empirical evidence on the impact of debt on corporate profitability. This impact can be explained by three essential theories: signaling theory, tax theory and the agency cost theory. Using panel data sample of 2240 French non listed companies of service sector during 1999-2006. By uti…
In a market system, regulations are designed to prevent or rectify market failures that inhibit fair exchange, such as monopoly or transactions with hidden costs. Because regulations reduce profits to those possessing unfair advantage, these advantaged corporations (whether individuals, companies, or other collective o…
Keywords: corporate finance, Wrocław University of Economics, net profit margin lub net sales profitability
Study upper hedging prices for contingent claims in models with various types of arbitrage.
problem Valuation of contingent claims in market models with different types of arbitrage.
method Analysis of market models with increasing profit, strong arbitrage, and arbitrage of the first kind.
result Option prices are reduced when increasing profit is present, and corporate stock price processes can be derived from issuance and repurchase plans.
Gradient boosted trees outperform other models in predicting corporate bankruptcy.
problem Predicting financial distress of publicly traded U.S. firms.
method Benchmarked various machine learning models using a comprehensive sample of bankruptcies.
result Gradient boosted trees outperform other models in one-year-ahead forecasts.
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 study predicts bankruptcy in Indian companies using financial ratios.
problem Predicting early signs of corporate bankruptcy in Indian companies.
method Logistic regression considering profitability, leverage, and efficiency ratios for one and two years before bankruptcy.
result The model accurately predicts bankruptcy with 81.4% and 85.1% accuracy one and two years before filing, respectively.
We describe and document three mechanisms by which corporations can influence or even control stock prices. (i) Parent and holding companies wield control over other publicly traded companies. (ii) Through clever management of treasury stock based on buyback programs and stock issuance, stock price fluctuations can be …
We study a model of a corporation which has the possibility to choose various production/business policies with different expected profits and risks. In the model there are restrictions on the dividend distribution rates as well as restrictions on the risk the company can undertake. The objective is to maximize the exp…
Out of the companies, Dolby is the company with the best overall financial and operation health. According to the table that accounted its financial statements for the past three years, Dolby has stable profit margins that generates a revenue in the billions, the only company in ten figures. Corporate competition to ga…
The basic financial purpose of corporation is creation of its value. Liquidity management should also contribute to realization of this fundamental aim. Many of the current asset management models that are found in financial management literature assume book profit maximization as the basic financial purpose. These boo…
Optimizes social interactions for profit, people, and planet using mathematical models.
problem Determining the most effective social configurations for mutual objectives.
method Formulated as a mathematical optimization problem, using (meta)relational models theory.
result Identifies the most suitable combination of sociality forms for mutual objectives.
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.
Study shows Bitcoin mining with surplus electricity can boost KEPCO's financial stability.
problem Improving energy resource efficiency and reducing KEPCO's debt.
method Utilized surplus electricity for Bitcoin mining using Antminer S21 XP Hyd, analyzed with Random Forest Regressor and Long Short-Term Memory models.
result Bitcoin mining with surplus electricity generates economic revenue, minimizes energy loss, and resolves payment issues for KEPCO.
We study the profitability of optimal mean reversion trading strategies in the US equity market. Different from regular pair trading practice, we apply maximum likelihood method to construct the optimal static pairs trading portfolio that best fits the Ornstein-Uhlenbeck process, and rigorously estimate the parameters.…
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.
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.
Corporate venture capital is in the midst of a renaissance. The end of 2015 marked all-time highs both in the number of corporate firms participating in VC deals and in the amount of capital being deployed by corporate VCs. This paper explores, rather than defines, how these firms find success in the wake of this sudde…
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%.
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.
Study finds it hard to establish common factor pricing in corporate bonds.
problem Difficulty in establishing common factor pricing in corporate bonds.
method Portfolio- and bond-level analyses using multifactor models.
result Common factor pricing in corporate bonds is not significantly explanatory.
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 …
Study examines UK firms' financial performance linked to corporate governance.
problem Impact of corporate governance on UK firms' financial performance.
method Cross-sectional regression analysis of 252 firms in 2014.
result Corporate governance mechanisms have mixed effects on financial performance.
Sentiment analysis from LLMs improves financial trading performance.
problem Improving dynamic strategy optimization in financial markets.
method Integration of sentiment analysis from LLMs into RL frameworks.
result Sentiment-enhanced RL models outperform traditional RL models in net worth and cumulative profit.
The VIX is used to model corporate bond volatility and returns.
problem Modeling volatility and returns for corporate bonds using observable data.
method Applied stochastic volatility models using the VIX index to corporate bond rates and spreads.
result Residuals of corporate bond returns divided by VIX are closer to Gaussian white noise.
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.
AI analyzes corporate ESG filings to identify key dimensions and investor reactions.
problem Lack of reliable ESG ratings systems in corporate filings.
method AI techniques to separate and measure ESG dimensions and investor responses.
result AI can improve ESG ratings systems by identifying key dimensions and investor reactions.
Religious adherence reduces corporate greenwashing behavior.
problem Greenwashing behavior by corporations.
method Analysis of a large US firm sample (2005-2019), focusing on selective disclosure.
result Religious adherence correlates with lower greenwashing behavior.
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.
Traded corporations are required by law to have a majority of outside directors on their board. This requirement allows the existence of directors who sit on the board of two or more corporations at the same time, generating what is commonly known as interlocking directorates. While research has shown that networks of …
The paper introduces ESE scores for farmers to assess climate change risks.
problem Assessing climate change risks in individual farmers' credit evaluations.
method Integrating ESG variables into joint liability models and using a mean-variance utility function.
result Optimal group sizes and individual-ESE score relationships under various climatic conditions.
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.
China integrates ESG into corporate strategy for sustainable growth.
problem Corporate focus on short-term financial metrics.
method Deep integration of ESG principles into corporate culture and strategy.
result Companies are expected to fulfill social responsibilities and create long-term value.
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.
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.
QCML improves bond similarity learning in illiquid markets.
problem Improving similarity learning for illiquid corporate bonds.
method Quantum Cognition Machine Learning (QCML) for supervised distance metric learning.
result QCML outperforms classical tree-based models in high-yield markets.
This paper uses RL to optimize bid-ask spreads for illiquid corporate bonds.
problem Optimizing bid-ask spreads for illiquid corporate bonds.
method Data-driven approach using Reinforcement Learning.
result Trained RL agent's behavior shows reasonable optimal bid-ask spreads.
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.
We compare observed corporate cumulative default probabilities to those calculated using a stochastic model based on an extension of the work of Black and Cox and find that corporations default as if via diffusive dynamics. The model, based on a contingent-claims analysis of corporate capital structure, is easily calib…
Corporate governance struggles to curb fraud in a globalized economy.
problem Lack of effective international regulations against corporate fraud.
method Analyzes historical economic crises and the role of corporate governance.
result Corporate governance is insufficient to prevent large business fraud.
Blockchain disrupts corporate finance, but challenges remain.
problem Challenges in adopting blockchain for corporate finance.
method Exploring the impact of blockchain on corporate finance valuation and capital allocation.
result Blockchain offers new perspectives but faces regulatory, environmental, and legal challenges.
The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international …
Inappropriate and profane content on social media is exponentially increasing and big corporations are becoming more aware of the type of content on which they are advertising and how it may affect their brand reputation. But with a huge surge in content being posted online it becomes seemingly difficult to filter out …