Market Capitalization

Cracking the code: Lessons from 15 years of digital health IPOs for the era of AI ArXiv ID: 2410.02709 “View on arXiv” Authors: Unknown Abstract Introduction: As digital health evolves, identifying factors that drive success is crucial. This study examines how reimbursement billing codes affect the long-term financial performance of digital health companies on U.S. stock markets, addressing the question: What separates the winners from the rest? Methods: We analyzed digital health companies that went public on U.S. stock exchanges between 2010 and 2021, offering products or services aimed at improving personal health or disease management within the U.S. market. A search using Google and existing IPO lists identified eligible companies. They were categorized based on the presence or absence of billing codes at the time of their initial public offering (IPO). Key performance indicators, including Compound Annual Growth Rate (CAGR), relative performance to benchmark indices, and market capitalization change, were compared using Mann-Whitney U and Fisher’s Exact tests. Results: Of the 33 companies analyzed, 15 (45.5%) had billing codes at IPO. The median IPO price was $17.00, with no significant difference between groups. Those with billing codes were 25.5 times more likely to achieve a positive CAGR. Their median market capitalization increased 56.3%, compared to a median decline of 80.1% for those without billing codes. All five top performers, in terms of CAGR, had billing codes at IPO, whereas nine of the ten worst performers lacked them. Companies without billing codes were 16 times more likely to experience a drop in market capitalization by the study’s end. Conclusion: Founders, investors, developers and analysts may have overestimated consumers’ willingness to pay out-of-pocket or underestimated reimbursement complexities. As the sector evolves, especially with AI-driven solutions, stakeholders should prioritize billing codes to ensure sustainable growth, financial stability, and maximized investor returns. ...

Macroscopic properties of equity markets: stylized facts and portfolio performance ArXiv ID: 2409.10859 “View on arXiv” Authors: Unknown Abstract Macroscopic properties of equity markets affect the performance of active equity strategies but many are not adequately captured by conventional models of financial mathematics and econometrics. Using the CRSP Database of the US equity market, we study empirically several macroscopic properties defined in terms of market capitalizations and returns, and highlight a list of stylized facts and open questions motivated in part by stochastic portfolio theory. Additionally, we present a systematic backtest of the diversity-weighted portfolio under various configurations and study its performance in relation to macroscopic quantities. All of our results can be replicated using codes made available on our online repository. ...

A Comparative Study of Portfolio Optimization Methods for the Indian Stock Market ArXiv ID: 2310.14748 “View on arXiv” Authors: Unknown Abstract This chapter presents a comparative study of the three portfolio optimization methods, MVP, HRP, and HERC, on the Indian stock market, particularly focusing on the stocks chosen from 15 sectors listed on the National Stock Exchange of India. The top stocks of each cluster are identified based on their free-float market capitalization from the report of the NSE published on July 1, 2022 (NSE Website). For each sector, three portfolios are designed on stock prices from July 1, 2019, to June 30, 2022, following three portfolio optimization approaches. The portfolios are tested over the period from July 1, 2022, to June 30, 2023. For the evaluation of the performances of the portfolios, three metrics are used. These three metrics are cumulative returns, annual volatilities, and Sharpe ratios. For each sector, the portfolios that yield the highest cumulative return, the lowest volatility, and the maximum Sharpe Ratio over the training and the test periods are identified. ...