Develops Merton's model for private companies using DDM.
problem Lack of observable asset values for private companies.
method Uses dividend discount model (DDM) to develop structural model.
result Obtains closed-form formulas for equity and liability values, default probability.
This paper develops a valuation model for private companies.
problem Lack of pricing and hedging models for private companies.
method Dynamic Gordon growth model, Maximum Likelihood (ML) estimators, Expectation Maximization (EM) algorithm.
result Closed-form pricing and hedging formulas for private companies.
A key factor in developing high performing machine learning models is the availability of sufficiently large datasets. This work is motivated by applications arising in Software as a Service (SaaS) companies where there exist numerous similar yet disjoint datasets from multiple client companies. To overcome the challen…
Model predicts exit of private companies using voting of three classifiers.
problem Predicting the exit of privately held companies from limited data.
method Combines three classifiers (Logistic Regression, Random Forest, SVM) on extracted data.
result Achieves 63% predictive accuracy for Private Equity investors.
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.
The paper develops a model to predict IPO events in private equity investments.
problem Lack of publicly available quantitative information for predicting IPO events.
method Combines neural network and survival analysis for predicting IPO probability.
result The neuro-survival model accurately predicts IPO events across various sectors.
The present work has as principal objective analyze the evolution of the process of privatization, mergers and acquisitions of the big companies in the country in the last decades, to understand the conductive threads that formed the structural changes of the economy, in order world oligopólicas to insert it to the glo…
TechRank ranks companies and technologies based on investor preferences.
problem Estimating influence and ranking companies and technologies.
method Recursive algorithm based on a bi-partite graph with weighted nodes, incorporating investor preferences.
result Provides investors with a quantitative ranking of technologies for optimal portfolio design.
Security, privacy, and fairness have become critical in the era of data science and machine learning. More and more we see that achieving universally secure, private, and fair systems is practically impossible. We have seen for example how generative adversarial networks can be used to learn about the expected private …
I studied what role the US stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001, Gross Private Domestic Investment refers to the total amount of investment spending by businesses and firms located within the borders…
This work uses the stocks of the 197 largest companies in the world, in terms of market capitalization, in the financial area in the study of causal relationships between them using Transfer Entropy, which is calculated using the stocks of those companies and their counterparts lagged by one day. With this, we can asse…
Private equity deals predict public market returns with up to 70% accuracy.
problem Predicting public market behavior from private equity transactions.
method Logit model using detailed analysis of private equity diligence process.
result Model predicts public market returns with up to 70% accuracy in specific sectors.
Paper uses time series transformers to predict investment success.
problem Optimizing investment sourcing in VC and GC.
method Transformer-based Multivariate Time Series Classifier (TMTSC).
result TMTSC improves decision making in VC and GC investments.
First private Bayesian optimization algorithm with provable performance.
problem Privacy-preserving Bayesian optimization in outsourced settings.
method Random projection-based transformation to preserve privacy and distances.
result Regret bound similar to non-private GP-UCB established for PO-GP-UCB.
Suppliers (including companies and individual prosumers) may wish to protect their private information when selling items they have in stock. A market is envisaged where private information can be protected through the use of differential privacy and option contracts, while privacy-aware suppliers deliver their stock a…
Study of public and private VC relationships in France using qualitative methods.
problem Understanding interactions between public and private venture capitalists in France.
method Qualitative approach with semi-structured interviews and thematic content analysis.
result Formal or informal relationships between public and private VCs are a 'economico-cognitive' approach to networking and innovation.
Federated learning platform for drug discovery without sharing data.
problem Lack of secure collaboration in drug discovery.
method Industry-scale federated learning platform using cryptographic aggregation.
result Generated new scientific discoveries in drug discovery.
Study introduces new methods to estimate stock return rates.
problem Estimating the required rate of return for stocks and private companies.
method Maximum likelihood, Bayesian, and Kalman filtering methods applied to historical data.
result Suggested methods can accurately estimate the required rate of return.
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.
Companies increasingly expose machine learning (ML) models trained over sensitive user data to untrusted domains, such as end-user devices and wide-access model stores. We present Sage, a differentially private (DP) ML platform that bounds the cumulative leakage of training data through models. Sage builds upon the ric…
Study designs statistical inference for collaborative science teams.
problem Maintaining scientific rigor in distributed, collaborative research.
method Analyzes hypothesis testing with strategic agents and principals.
result Principal can design policies to control posterior probability of null.
This study improves valuation of post-revenue biopharmaceutical assets using Pfizer's data.
problem Accurate valuation of post-revenue drug assets in biotech and pharma.
method Historical sales data analysis to forecast future sales and calculate Net Present Value.
result Demonstrates a method for more informed investment decisions in biotech and pharma.
Study introduces new methods to estimate equity and liability required rates of return.
problem Estimating the required rates of return for equity and liabilities of companies.
method Used maximum likelihood, Bayesian, Kalman filtering, and market value evaluation methods.
result The new methods can accurately estimate the required rates of return.
Milken revolutionized finance with junk bonds, boosting private equity and tech growth.
problem Lack of financing options for risky but potentially profitable companies.
method Innovative use of junk bonds and leveraged buyouts (LBOs).
result Milken's financial strategies led to significant economic growth and the rise of tech companies.
Most approaches in algorithmic fairness constrain machine learning methods so the resulting predictions satisfy one of several intuitive notions of fairness. While this may help private companies comply with non-discrimination laws or avoid negative publicity, we believe it is often too little, too late. By the time th…
Study finds similar companies in Dhaka Stock Exchange using technical data.
problem Analyzing all companies in Dhaka Stock Exchange is impractical.
method Used technical data to identify companies moving together.
result Technical data can reveal company relationships without fundamental data.
Developed Merton's model for public companies using observed liabilities.
problem Estimating default risk for public companies.
method Campbell and Shiller's approximation method for risk-neutral values and default probabilities.
result Formulas and ML estimators for public companies' default probabilities.
Company2Vec creates embeddings from company websites for fine-grained business analytics.
problem Lack of fine-grained company labels for analytics.
method Word2Vec and dimensionality reduction on company website data.
result Semantic company embeddings for various applications.
Introduces an artificial cyber lab to test and identify cyber resilience measures.
problem Systemic cyber risks and their control methods.
method Classical contagion models and artificial cyber lab simulations.
result Identified two classes of measures: security- and topology-based interventions.
This paper studies trade-offs in private prediction methods.
problem Leakage of training data information in machine learning predictions.
method Private training and private prediction methods with trade-offs.
result Private training methods outperform private prediction methods in various settings.
We present an analytical study of an insurance company. We model the company's performance on a statistical basis and evaluate the predicted annual income of the company in terms of insurance parameters namely the premium, total number of the insured, average loss claims etc. We restrict ourselves to a single insurance…
Private method measures nonlinear correlations between data hosted across two entities.
problem Measuring nonlinear correlations between sensitive data hosted across multiple parties while preserving privacy.
method Differentially private estimator of distance correlation.
result First private estimator of nonlinear correlations in a multi-party setup.
This paper evaluates financial competitiveness of Indian real estate companies using entropy method.
problem Improving financial competitiveness of Indian real estate companies in a competitive market.
method Financial competitiveness evaluation index system using key financial ratios and a scoring system.
result Companies with high scores have strong profitability and operational capacity, while those with lower scores struggle with solvency and working capital.
Employing profits data of Japanese companies in 2002 and 2003, we confirm that Pareto's law and the Pareto index are derived from the law of detailed balance and Gibrat's law. The last two laws are observed beyond the region where Pareto's law holds. By classifying companies into job categories, we find that companies …
The paper analyzes how news sentiment of companies can affect market movements.
problem Understanding how news sentiment impacts market performance and volatility.
method Applied NLP techniques to analyze news sentiment of 87 companies over 7 years.
result Strong media sentiment towards one company can indicate significant changes in sentiment towards related companies.
Large language models learn company embeddings from SEC filings.
problem Lack of a rigorous definition of company similarity.
method Pre-trained and finetuned large language models (LLMs) to learn embeddings from SEC filings.
result LLMs can reproduce GICS classifications and indicate similar financial performance.
In a stock market, the price fluctuations are interactive, that is, one listed company can influence others. In this paper, we seek to study the influence relationships among listed companies by constructing a directed network on the basis of Chinese stock market. This influence network shows distinct topological prope…
The model is aimed to discriminate the 'good' and the 'bad' companies in Russian corporate sector based on their financial statements data based on Russian Accounting Standards. The data sample consists of 126 Russian public companies- issuers of Ruble bonds which represent about 36% of total number of corporate bonds …
In this study we consider relations between companies in Poland taking into account common branches they belong to. It is clear that companies belonging to the same branch compete for similar customers, so the market induces correlations between them. On the other hand two branches can be related by companies acting in…
Study compares sentiment spillover networks from news and social media in tech companies.
problem Understanding how sentiment information flows between companies through news and social media.
method Network-based transfer entropy method to measure and compare sentiment spillover.
result News shows stronger information flow among tech companies after COVID-19.
A new method to value IPOed companies.
problem Valuing companies after IPO.
method Growth Average U1 method.
result Benchmark stocks using linear extrapolation of revenues and profits.
New algorithms for privately learning decision lists and halfspaces.
problem Private learning of decision lists and halfspaces.
method Differentially private algorithms for PAC and online models.
result Private algorithms match or surpass non-private guarantees.
Private PGB boosts synthetic data quality using GANs and privacy techniques.
problem Differentially private GANs struggle with convergence and poor output quality.
method Combines reweighted samples from GAN training using Private Multiplicative Weights method.
result Improves synthetic data quality across various datasets and tasks.
Audit fees change based on company and economic factors during auditor switching.
problem Understanding how audit fees change when auditors switch firms.
method Examined the impact of auditor switching on audit fees, considering company characteristics and economic data.
result The direction and magnitude of audit fee changes during switching depend on economic stability and company characteristics.
We consider the problem of evaluating the quality of startup companies. This can be quite challenging due to the rarity of successful startup companies and the complexity of factors which impact such success. In this work we collect data on tens of thousands of startup companies, their performance, the backgrounds of t…
Near-optimal private tests for simple and MLR hypotheses developed under Gaussian differential privacy.
problem Developing private tests for simple and MLR hypotheses under Gaussian differential privacy.
method A private mean estimator with data-driven clamping bounds, constructing private test statistics.
result Private tests achieve the same asymptotic relative efficiency as non-private most powerful tests.
Model predicts default risk based on company's financial forecasts and credit conditions.
problem Estimating the risk of a company defaulting on its financial obligations.
method Developed an equilibrium model linking interest rates to corporate performance and credit supply.
result Estimates idiosyncratic default risk and provides forward-looking probability of default (PD).
The real estate is a pillar industry of China's national economy. Due to changes in policy and market conditions, the real estate companies are facing greater pressures to survive in a competitive environment. They must improve their financial competitiveness. Based on the conceptual framework of financial competitiven…