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 …
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48 results for “corporate control”
Optimizes control interventions in real-world networks using deep-learning and network science.
problem Optimizing control over socioeconomic networks subject to constraints.
method Integrates optimization tools from deep-learning with network science.
result Characterizes vulnerability of corporate networks to takeovers.
Network analysis shows FDI indirectly boosts trade.
problem Understanding indirect effects of FDI on trade.
method Corporate control network analysis using shortest path length and communicability.
result Corporate control positively affects trade both directly and indirectly.
The paper challenges the assumption that majority voting rights equate to 'effective control' in foreign ownership regulations.
problem The assumption that majority voting rights determine 'effective control' in foreign ownership regulations is flawed.
method The paper proposes and demonstrates a method for calculating 'effective control' based on voting thresholds and weights.
result The 'effective control' of a foreign minority stockholder can be higher than their shareholding size, challenging the assumption that majority voting rights equate to 'effective control'.
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.
The Canonical Regression Quantile method predicts CEO compensation and future performance.
problem Determining fair CEO compensation and its impact on company performance.
method Canonical Regression Quantile method to assess CEO pay and performance.
result The method can predict future CEO performance and distinguish over/underpaid CEOs.
Stock markets are not what we think they are: the key roles of cross-ownership and corporate treasury stockcond-mat.other
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 …
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…
In this paper we solve the dividend optimization problem for a corporation or a financial institution when the managers of the corporation are facing (regulatory) implementation delays. We consider several cash reservoir models for the firm including two mean-reverting processes, Ornstein-Uhlenbeck and square-root proc…
ChatGPT and Corporate Policiesq-fin.CP
ChatGPT scores corporate investment plans, predicting future spending and returns.
problem Measuring and predicting corporate investment plans.
method Created a firm-level ChatGPT investment score based on conference calls.
result The investment score predicts future capital expenditures and returns.
We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us…
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.
Corporate VC firms struggle with internal conflicts despite growth.
problem Internal conflicts among corporate VC investment teams.
method Conducted interviews with corporate VC firms to identify issues.
result Executive-level attention and commitment are lacking, leading to conflicts.
This paper improves bond market making by adjusting hit-ratios for client flow quality.
problem Economic misleading of raw hit-ratios in corporate bond market making.
method Stochastic-control framework with residual-quality-adjusted hit-ratio.
result Optimal quotes decompose into various components, improving service/economics frontier.
Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networksq-fin.RM
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.
Study shows corporate governance improves stock liquidity with noise traders' participation.
problem Improving liquidity of listed companies' stocks.
method Theoretical model with heterogeneity of investors' beliefs.
result Corporate governance and noise traders' participation synergistically improve stock liquidity.
We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is marked by a central, tightly connected "core" made of a small number of large companies which control a significant part of the global economy.…
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%.
Priced risk in corporate bondsq-fin.PR
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.
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.
Optimal dividend control for a generalized risk model with investment incomes and debit interestmath.OC
This paper investigates dividend optimization of an insurance corporation under a more realistic model which takes into consideration refinancing or capital injections. The model follows the compound Poisson framework with credit interest for positive reserve, and debit interest for negative reserve. Ruin occurs when t…
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.
Optimizes trading co-integrated assets considering price impact and informational advantage.
problem Executing a basket of co-integrated assets with price impact.
method Optimal stochastic control problem, closed-form solution, verification theorem.
result Improves trading strategy by including additional assets, outperforming existing models.
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.
Study proposes new framework for Board-CEO relationship.
problem Recent corporate failures highlight Board's role in governance effectiveness.
method Analyzes Board-CEO relationship and role reversal in Principal-Agent Theory.
result Role reversal in governance may lead to organizational collapse.
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.
Corporate Bond Yield Curve Modeling: A Rating-Based Regime-Switching Generalized CIR Approachq-fin.PR
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.
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.
Stock fluctuations are correlated and amplified across networks of interlocking directoratesq-fin.GN
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 …
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.
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.
This paper presents a method to estimate mid-prices of European corporate bonds using real-time dealer information.
problem Estimating mid-prices in illiquid markets where direct market prices are not available.
method Bayesian approach using particle filtering and sequential Monte Carlo.
result A new method for real-time mid-price estimation of corporate bonds.
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.
Analyzes transaction costs for corporate bonds using a new analytical methodology.
problem Challenges in assessing the quality of corporate bond executions via Transaction Cost Analysis.
method Analyzes TRACE Enhanced dataset to estimate initiator, bid-ask spread, and mid-price dynamics; applies regularized regression models and transient impact models.
result Identifies price impact asymmetry between customer-buy and consumer-sell orders.
Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Networkphysics.soc-ph
New approach identifies offshore financial centers in global corporate network.
problem Political scrutiny of offshore financial centers facilitating tax avoidance.
method Data-driven approach using a global corporate ownership network.
result Identification of 24 sink-OFCs and a set of five conduit-OFCs.
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.
Machine learning extracts features from illiquid corporate bond yields.
problem Extracting features from illiquid corporate bond yields.
method Applied Denoising Autoencoder algorithm to learn features from liquid market data.
result Trained machine learning algorithm's results compared with 2D interpolation.
System filters inappropriate YouTube content for advertisers.
problem Inadequate detection of inappropriate content on YouTube ads.
method Proposes a system for identifying and filtering inappropriate content.
result Current countermeasures are ineffective in detecting inappropriate content.
Machine learning predicts corporate bankruptcy with high accuracy.
problem Predicting corporate insolvency to mitigate economic disruption.
method Applied machine learning techniques like SVM, boosting, neural networks, and Gaussian processes.
result Achieved predictions with over 95% accuracy using expert assessments.
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.
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.
The paper tackles uncertainties in corporate default risk predictions.
problem Evaluating uncertainties associated with corporate default risk predictions.
method Developed a procedure to quantify uncertainties by disentangling multiple contributing sources.
result Substantial uncertainties exist in default risk assessments.
Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learningq-fin.ST
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.
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…