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.
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48 results for “IPO companies”
Study finds billing codes at IPO boost digital health companies' financial performance.
problem Identifying factors that drive long-term financial success in digital health companies.
method Analyzed 33 digital health IPOs from 2010-2021, comparing companies with and without billing codes.
result Companies with billing codes at IPO were significantly more likely to achieve positive CAGR and higher market capitalization.
Within the Private Equity (PE) market, the event of a private company undertaking an Initial Public Offering (IPO) is usually a very high-return one for the investors in the company. For this reason, an effective predictive model for the IPO event is considered as a valuable tool in the PE market, an endeavor in which …
The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki S…
Valuation of Zyngaq-fin.GN
On December 16, Zynga, the well-known social game developing company went public. This event is following other recent IPOs in the world of social networking companies, such as Groupon, Linkedin or Pandora to cite a few. With a valuation close to 7 billion USD at the time when it went public, Zynga has become the bigge…
On December 16th, 2011, Zynga, the well-known social game developing company went public. This event followed other recent IPOs in the world of social networking companies, such as Groupon or Linkedin among others. With a valuation close to 7 billion USD at the time when it went public, Zynga became one of the biggest …
IPO Finance Agent evaluates LLMs on SpaceX IPO due diligence, surpassing Finance Agent v2.
problem Evaluating language models on financial tasks like IPO due diligence.
method Introducing IPO Finance Agent and an evaluator-optimizer pipeline.
result The best-performing model reaches 79.4% accuracy at 0.30 USD per query.
IPO Finance Agent extends Finance Agent v2 for SpaceX S-1 filings, improving accuracy and cost-efficiency.
problem Evaluating IPO due diligence tasks with long-form documents.
method Extended task domain, improved agentic harness with contextual retrieval, automated rubric generation.
result Best-performing model reaches 79.8% accuracy, cost-efficient model at 77.2% with 0.05 USD per query.
Social media hype can misprice IPO stocks, leading to short-term gains but long-term losses.
problem Mispricing of IPO stocks due to social media hype.
method Analysis of investor emotions on StockTwits and Twitter.
result High pre-IPO enthusiasm leads to higher short-term returns but lower long-term returns.
Biotech IPOs in Q1 2021: advanced degrees, clinical trials, and IP key.
problem Identifying traits of biotech startups that go public.
method Database of biotech IPOs, analysis of leadership, technology, clinical trials, and financing.
result Advanced degrees, clinical trials, and IP are important for biotech startups.
Predicting the exit (e.g. bankrupt, acquisition, etc.) of privately held companies is a current and relevant problem for investment firms. The difficulty of the problem stems from the lack of reliable, quantitative and publicly available data. In this paper, we contribute to this endeavour by constructing an exit predi…
Study shows registration regime improves IPO pricing efficiency in China.
problem Improving IPO pricing efficiency in China's entrepreneurial boards.
method Examined the impacts of regime changes and rule implementations on IPO pricing efficiency.
result The registration regime is most efficient in Chinese IPO pricing.
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…
This study examines how ChiNext IPOs' initial returns are influenced by regulation regime changes.
problem Investors' behavior and pricing of ChiNext IPOs under different regulation regimes.
method Analysis of three time periods with two different regulation regimes and three sets of listing day trading restrictions.
result Regulation regime changes significantly impact ChiNext IPO pricing and overreaction.
Paper shows equivalence between two alignment methods and introduces a new algorithm.
problem Ensuring human alignment of large language models for useful, safe, and pleasant user experience.
method Introduces IPO-MD algorithm, showing equivalence between IPO and Nash-MD methods.
result Equivalence between IPO and Nash-MD methods proven when considering online version of IPO.
Study finds dividend policy has no significant effect on IPO stock prices.
problem Impact of dividend policy on IPO price performance.
method Long-run performance statistics and GARCH model, dummy variable used.
result Dividend policy has no significant effect on IPO stock prices.
Study uses LLMs to optimize VC exit timing after IPO.
problem Optimal exit timing after IPO is crucial but not well studied.
method Uses LLMs to analyze financial data and market signals.
result LLMs can improve VC exit timing and generate better returns.
This research examines relationship between staging of Venture Capital (VC) investments and social feedback visible in publicly available data on the Web. We address the question of Venture Capital investment sensitivity to performance and prospects of new venture, given as likelihood of obtaining future financing, ava…
New method accurately reconstructs Russell 3000 index, revealing crowded portfolios.
problem Crowding in index portfolios during reconstitution events.
method Developed a Python package for accurate index reconstruction using CRSP US Stock data.
result Annual Russell 3000 portfolios are more crowded than quarterly ones, suggesting lower transaction costs.
We study a practical optimization problems for venture capital investments and/or Research and Development (R&D) investments. The first problem is that, given the amount of the initial investment and the reward function at the initial public offering (IPO) market, the venture capitalist wants to maximize overall discou…
Study predicts startup outcomes like funding, patenting, IPOs using machine learning.
problem Forecasting startup success metrics like funding, patenting, IPOs.
method Developed interpretable machine learning framework, used preprocessing, class imbalance handling, and compared multiple models.
result Achieved high AUROC values for patent, funding, and exit predictions.
In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints. We propose a novel first-order policy optimization method, Interior-point Policy Optimization (IPO), which augments the…
Recent academic work has developed a method to determine, in real time, if a given stock is exhibiting a price bubble. Currently there is speculation in the financial press concerning the existence of a price bubble in the aftermath of the recent IPO of LinkedIn. We analyze stock price tick data from the short lifetime…
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.
Study investor attention using search volume data before and after mobile device popularity.
problem Accurately measure investor attention in a fast-paced market.
method Compare investor attention using search volume data before and after mobile device popularization.
result Investor attention measured using search volume data is more accurate and faster after mobile device popularization.
Empirical study of CAPM and Fama-French model in Chinese A-share market.
problem Testing and validating CAPM and Fama-French model in Chinese A-share market.
method Used Fama-MacBeth regression and Fama-French three-factor model to analyze Chinese A-share trading data from 2000 to 2019, adjusting for IPO shell value contamination.
result Fama-French model captures most of A-share market returns, with adjusted R-squared > 0.88.
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.
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.
Premium Forecasting of an Insurance Company: Automobile Insurancecond-mat.stat-mech
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…
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.
Pareto index induced from the scale of companiesphysics.soc-ph
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.
Influence network in Chinese stock marketphysics.soc-ph
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 …
Networks of companies and branches in Polandphysics.soc-ph
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.
Audit fees in auditor switchingq-fin.GN
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.
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…
To understand the relationship between news sentiment and company stock price movements, and to better understand connectivity among companies, we define an algorithm for measuring sentiment-based network risk. The algorithm ranks companies in networks of co-occurrences, and measures sentiment-based risk, by calculatin…
Modelling all possible life cycles of a company in a highly competitive economic environment gives a significant advantage to the owner in his business investment activities. This article proposes and analyses a dynamic model of a company's life cycle with known action costs and transition probabilities, that can be af…
Forecasting Company Fundamentalsq-fin.ST
Deep learning models outperform classical methods in forecasting company fundamentals.
problem Forecasting company fundamentals for investment and econometrics.
method Compared 24 deterministic and probabilistic models on real company data.
result Deep learning models provide superior forecasting performance, especially in uncertainty estimation.
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.
Investment strategy based on a company growth modelcond-mat.stat-mech
We first estimate the average growth of a company's annual income and its variance by using both real company data and a numerical model which we already introduced a couple of years ago. Investment strategies expecting for income growth is evaluated based on the numerical model. Our numerical simulation suggests the p…
A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial ti…