Economic Moats and Stock Performance: Is Warren Buffett Wrong?

N several occasions in the past I have presented to the Trustees of the University of Rochester the performance record of individual particularly those held by the University, over a period of time. Since the portfolio of the University includes a very large proportion of so-called stocks, the performance of these stocks has been compared with the performance of a few stocks held in the account at one time or another, and it has been quite clear that the stocks in this account have been better holdings than the stocks. In a theoretical sense, at any given time it would seem difficult to defend the indiscriminate purchase of stocks because, while definitions of vary, the companies selected usually possess a strong increase in unit demand for the company's products, a high cash flow, a low current return, and the investor in usually adopts a long-term view. Since many of the stocks purchased for the University of Rochester's endowment fund have been held for only a few years, it is difficult to prove anything by citing the performance of these particular stocks in the short time they have been held. We have, therefore, selected ten stocks which can be termed growth stocks (all of which, incidentally, are held in the University account) and ten stocks which can be termed as income stocks (all held by the University at one time; only one of them is now held). The two groups selected are as follows:

During the period 1994 to 2020, a total of 18 firms in Kenya floated 16,530,781,060 shares at the Nairobi Securities Exchange (NSE) under Initial Public Offerings (IPOs) raising over Kshs 91 billion. These stocks were significantly over-subscribed with the highest hitting 830%. The NSE became fully automated in 2006. Similarly, in Africa between 2010 and 2019 there were a total of 215 IPOs raising over Kshs 1.6 trillion. This could be explained by divergence of opinion hypothesis. The initial returns were positive. However, in the long run, most of the firms underperformed. This under performance leads to losses incurred by investors and possible collapse of brokerage and investment firms leaving investors with a bitter taste. This study will undertake to establish the effects of firm specific factors on IPO stock performance at the NSE in Kenya. The specific objectives will be: to establish the effect of firm size on performance of IPO stocks at the NSE in Kenya, to determine the effect of age of firm on performance of IPO stocks at the NSE in Kenya, to evaluate the effect of firm board composition on performance of IPO stocks at the NSE in Kenya, to establish the effect of firm ownership structure on performance of IPO stocks at the NSE in Kenya, and to analyze the moderating effect of automation on the firm specific factors and performance of IPO stocks at the NSE in Kenya. The study will be built upon major theoretical streams: Random Walk theory, Winners curse theory, Dow Theory, Signaling theory and Agency theory and contextualize them to firm specific factors and performance of IPO stocks. More studies have previously been undertaken on the pricing of IPO at the NSE in Kenya and the few that studied on performance of IPO stocks at the NSE in Kenya have provided mixed findings depending on the methodology used. None of the studies as far as research has shown have considered the automation of NSE in Kenya as a moderating effect of performance of IPO stocks. The sample size will be the same as population of 18 IPO firms between 1994 and 2020 with 8 IPOs during pre-automation and 10 IPOs post-automation period. This will be a longitudinal and event study that will adopt a descriptive study design. Data will be analyzed using the Econometric Views (Eviews). Hausman test, Augmented Dickey Fuller (ADF) test and other diagnostic tests will be applied to the panel data. The Capital Assets Pricing Model (CAPM) and the Nairobi 20 Share Index will be used as the benchmarks of performance of IPO stocks.

Abstract: Purpose: The purpose of this study was to analyze the effect of corporate governance and financial performance on stock performance during the covid-19 pandemic in Indonesia. Research Methodology: This research used quantitative analysis method using seconder data of financial reports on Manufacturing companies listed on the Indonesia Stock Exchange (IDX) in 2019-2021. Results: The results of this study are managerial ownership has no significant effect on stock performance, the board of commissioners has no significant effect on stock performance, the board of directors has an effect on stock performance, return on assets has no significant on stock performance, return on equity has no effect on stock performance and earnings per share affect stock performance. Limitations: This study only includes six of the factors that affect stock performance, which results in the effect of the independent variable research on the dependent variable of 4%. Contribution: This research can be used as a reference for company management in order to improve governance and financial performance to improve the company's stock performance will increase. Keywords: 1. Good Corporate Governance 2. Financial Performance 3. Stock Performance

This study provides empirical evidence on the short term and the long term effects of initial public offering (IPOs) by firms, on their competitor firms’ performance in Indonesia. We perform short-run and long-run event studies and cross sectional regressions over the period 2010 to 2017 and find that both IPO firms and their competitors experience positive stock returns in the short-run and in the long-run. We find that IPO firms’ stock performance is relatively stable in the long-run that enables the competitor firms’ stock returns to catch up with IPO firms’ stock performance. We find negative effect of IPO firms’ stock performance on their competitors’ stock performance in the short-run, and a positive effect in the long-run. Our findings imply that IPO firms provide good information to the industry and no obvious competitive landscape changes are observed.

The reason of this observe is to analyze and decide the effect of profitability, leverage, and growth on the performance of property sector company shares, to analyze and determine the effect of profitability, leverage, growth and stock performance on the company value of property sector companies and to analyze and determine the effect of profitability, leverage, and growth on company value with stock performance as an intervening variable for property sector companies listed on the IDX in 2017-2021. This research is protected in quantitative research the usage of secondary facts. This research is a quantitative research conducted to see the effect of profitability, leverage, growth on company value with stock performance as an intervening variable with case studies on businesses within the belongings, actual estate and constructing creation sectors indexed at the IDX in 2017-2021. In this study the authors used secondary statistics from annual reviews and financial reports. This study concludes that there is no effect of profitability on stock performance, there is an effect of profitability on firm value, there is an effect of leverage on stock performance, there is an effect of leverage on firm value, there is an effect of growth on stock performance, there is an effect of growth on firm value, there is an effect on performance stock on firm value, on firm value with stock performance as an intervening variable, there is an influence between growth on firm value and stock performance as an intervening variable.

Firm growth has various undertones which can describe it in the perspective of market share change, sales growth, employment growth, total assets growth and also level of community participation. The aspect of sales growth involves revenue from sales which was considered in this study and applied as revenue change. Total assets growth was also applied to measure firm growth. Firms that create value through selling their products are rewarded by the market through generation of more revenue, which translates to profit and operating cash flow that finally accrues to the stockholders. Hence, stock performance was studied to determine if it is affected by firm growth. This study, therefore, aimed to investigate the effect of firm growth on stock performance. The study targeted the non-financial firms quoted at the Nairobi Securities Exchange in Kenya. Firm growth was measured using revenue change and total assets change. Thus, the study’s specific objectives were to determine the effect of revenue change on stock performance and establish the effect of total assets change on stock performance of non-financial firms quoted at the Nairobi Securities Exchange. The descriptive statistics indicated that the standard deviation values are all clustered around the corresponding mean. The ANOVA results depicted a statistically significant model at 5 percent. The variables are good predictors of stock performance as justified by an F statistic of 39.14 and the reported p-value of 0.0000 which is less than the 0.05 significance level. The Pearson’s coefficient findings observed that there was no correlation between revenue change and total assets change with stock performance. The panel regression results showed that revenue change and total assets change to a large extent affect stock performance of the listed firms. The study revealed that revenue change has a positive impact on stock performance and also total asset change has a positive effect on stock performance. The study therefore concluded that firm growth has a positive effect on stock performance of listed non-financial firms in Kenya

The purpose of this study was to explain the individual stock returns, systematic risk of the stock, stock performance and stock performance ratings of BUMN’s stock that start from Januari to Desember 2010. The Stocks performance were analyzed by calculating stock performance that using Jensen approach (αJ), rank the result, starting from the largest positive value to the smallest. The highest return of the stock was 0,2248 and the higest systematic risk was 114,618, ie., PT Semen Gresik Persero stocks, the best performance of the stock was 0,0361, i.e., PT Bank Negara Indonesia Persero stocks, and the worst performance was -0,1015 i.e., PT Semen Gersik Persero stock. This research result can be used as an investor consideration in assessing the performance of the company stock incorporated in BUMN that can provide the benefit as expected and indicate low systematic risk.Keywords: Stock Return, systematic risk of the stock, stock performance, Jensen Index(αJ),BUMN

The aim of this study is comparing the performance of common stock & treasury bills, according to the central bank of Egypt and their monetary policy during the time period between “1994-2017”, using descriptive & inferential statistical methods. The Study concluded that there is a strong positive relationship between inflation rate & returns of Egyptian treasury bills, as the same relation as with floating Egyptian pound. in addition, the study found the impact of Inflation and Floating on the return of Egyptian T-bills, but don’t found this impact on the return of Egyptian common stock. Finally, the study founds the same average return but a different at variances of this return & the Coefficient of variation.

We evaluate whether, in addition to seeking higher stock performance from acquisitions, firm managers also seek predictable stock performance. Building on prior research, we argue that higher volatility in a firm's stock performance following an acquisition is associated with divestment of a prior acquisition. Survival analysis of a longitudinal, panel dataset of 738 matched US acquisitions with 9,973 firm‐year observations shows that higher volatility in an acquiring firm's stock performance, following an acquisition, significantly predicts divestment of a prior acquisition. This effect is independent and stronger than the effect of the mean stock performance of an acquiring firm following an acquisition. We also find moderating effects for acquisition relatedness and acquiring firm stock performance after an acquisition. When an acquired unit is related to the parent firm's operations, it will be more likely to be divested if subsequent stock performance displays higher volatility. Still, higher overall stock performance makes a parent firm less likely to divest an acquired unit, suggesting that larger mean returns override concerns about higher stock performance volatility during corporate restructuring.

Firm growth has various undertones which can describe it in the perspective of market share change, sales growth, employment growth, total assets growth and also level of community participation. The aspect of sales growth involves revenue from sales which was considered in this study and applied as revenue change. Total assets growth was also applied to measure firm growth. Firms that create value through selling their products are rewarded by the market through generation of more revenue, which translates to profit and operating cash flow that finally accrues to the stockholders. Hence, stock performance was studied to determine if it is affected by firm growth. This study, therefore, aimed to investigate the effect of firm growth on stock performance. The study targeted the non-financial firms quoted at the Nairobi Securities Exchange in Kenya. Firm growth was measured using revenue change and total assets change. Thus, the study’s specific objectives were to determine the effect of revenue change on stock performance and establish the effect of total assets change on stock performance of non-financial firms quoted at the Nairobi Securities Exchange. The descriptive statistics indicated that the standard deviation values are all clustered around the corresponding mean. The ANOVA results depicted a statistically significant model at 5 percent. The variables are good predictors of stock performance as justified by an F statistic of 39.14 and the reported p-value of 0.0000 which is less than the 0.05 significance level. The Pearson’s coefficient findings observed that there was no correlation between revenue change and total assets change with stock performance. The panel regression results showed that revenue change and total assets change to a large extent affect stock performance of the listed firms. The study revealed that revenue change has a positive impact on stock performance and also total asset change has a positive effect on stock performance. The study therefore concluded that firm growth has a positive effect on stock performance of listed non-financial firms in Kenya.

Introduction: Stock performance analysis is critical for understanding market dynamics and guiding investment decisions. Bajaj Electronics, a leading player in the electronics industry, is influenced by various historical trends, including market fluctuations, Customer preferences, and technological advancements. These trends impact stock valuation, investor confidence, and overall financial growth. Statement of the Problem: Identifying and analyzing historical trends that influence selected company's stock performance is essential for better decision-making by investors and stakeholders. Challenges include deciphering the dynamic market factors and aligning them with financial performance indicators to predict stock behavior. Objectives: The study aims to evaluate the impact of historical trends on selected company's stock performance. Specifically, it seeks to identify the correlation between market developments, technological shifts, and stock value changes, and provide actionable insights for stakeholders. Methodology: A mixed-methods approach combining quantitative analysis of historical stock data and qualitative interpretation of industry developments is employed. Statistical tools, including trend analysis, Arima, and regression, are used to identify significant patterns. Hypothesis: The stock performance of selected company is significantly influenced by historical market trends and technological innovations. It is expected that understanding these factors can enhance investment strategies and predict future stock movements with greater accuracy. Sample: The study examines historical stock data of selected company over a defined period, alongside industry reports and market analyses. Statistical Tools: Regression models, and time series analysis are utilized to determine the relationship between historical trends and stock performance. Applications: Insights from the study can guide investors, policy-makers, and corporate strategists in making informed decisions. This company can leverage these findings to enhance market positioning and investor relations. Findings: Preliminary results indicate a strong correlation between technological advancements, market trends, and stock performance. Proactive adaptation to industry changes and Customer demands has a positive impact on selected Company’s stock valuation. Limitations: The study was limited to selected company and does not encompass other players in the electronics sector. External economic factors and unforeseen events are also beyond its scope. Implications: By leveraging insights from historical trends, this company can optimize its strategic decisions, ensuring sustainable growth and enhanced investor confidence. Conclusion: The study concludes that leveraging insights from historical trends enables selected company to optimize strategic decisions, ensuring sustainable growth and enhanced investor confidence. Key words: Stock Performance and Prices, Stock Valuation, Future Prediction, Comparative Analysis, Market Developments, Technological Shifts, and Stock Value Changes Previous A Study on Stabilization of Soils by Using Egg Shell Powder and Basalt Fiber

This study aims to analyze the effect of environmental disclosure on financial performance and stock performance, as well as to examine the role of financial performance as a mediating variable in the relationship between environmental disclosure and stock performance in mining and energy sector companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2024 period. The study uses secondary data from annual reports, financial statements, and sustainability reports of 29 sample companies selected through purposive sampling, yielding 116 total observations. Environmental disclosure is measured using the Environmental Disclosure Index (EDI) based on 34 indicators from GRI 4 Environmental Category, financial performance is proxied by Return on Assets (ROA), and stock performance is measured using annual stock return. The analysis employs simple linear regression and mediation testing using the Baron & Kenny method through SPSS 26. The results show that: (1) environmental disclosure has a significant effect on financial performance, with R = 0.192, R² = 0.037 (3.7%), and sig. = 0.067; (2) financial performance has no significant effect on stock performance, with a regression coefficient of 0.722 and sig. = 0.239; (3) environmental disclosure has no significant effect on stock performance, with a regression coefficient of −0.292 and sig. = 0.346; and (4) financial performance is unable to mediate the effect of environmental disclosure on stock performance, as all mediation paths are statistically insignificant. These findings indicate that the Indonesian capital market has not yet optimally responded to environmental information in investment valuation for the mining and energy sectors, which may be attributed to the low level of investor ESG literacy, the dominance of external factors such as commodity price volatility and government policy, and the varying quality of environmental disclosures

This research examines the intricate relationships between company size, growth in cash flow, and stock performance, revealing complexities that challenge traditional financial analysis. While company size is often associated with stable stock performance due to advantages such as economies of scale and market power, the findings indicate that size alone does not positively impact stock performance. Furthermore, the study demonstrates that growth in cash flow does not significantly moderate the relationship between company size and stock performance. This suggests that external factors, such as regulatory changes or market sentiment, may play a more decisive role. The results underscore that cash flow, while an important indicator of financial health, does not enhance the influence of company size on stock performance, particularly in certain industries where external conditions prevail. This underscores the need for a more comprehensive evaluation approach that considers a broader range of factors when assessing stock performance. It's time to move beyond traditional metrics like profitability and cash flow growth and equip ourselves with a more robust set of tools for analysis. Ultimately, this research advocates for a multifactorial approach to stock performance evaluation, emphasizing the importance of understanding the interplay between various variables, including industry trends and macroeconomic conditions. By adopting this comprehensive perspective, investors and analysts can make more informed decisions and strategies, enhancing their ability to navigate the complexities of the financial markets.

Target and position article - Analyzing the impact of user-generated content on B2B Firms' stock performance: Big data analysis with machine learning methods

PurposeThe purpose of this paper is to analyze the correlation between the Twitter activity of two airline companies and their stock performance at the Istanbul Stock Exchange (BIST).Design/methodology/approachOverall, 113,018 tweets were divided into 34,152 semantic and 78,866 share tweets. Semantic tweets are tweets mentioning company’s products or services and were labeled manually and with deep learning models. Share tweets were divided into 13,618 relevant and 65,248 irrelevant tweets.FindingsA positive correlation was found between share tweets and stock performance. Semantic tweets did not display a correlation with stock performance. Relevant share tweets displayed as a strong correlation as all share tweets for one company. Also, the manual labeling of 8,000 tweets led to the discovery of many insights related to service provision in the airway industry, management of digital support channels, management of reputation on social media and using Twitter as a customer support platform.Practical implicationsRelevant share tweets comprise only 20% of all share tweets for one company and show the same level of correlation with stock performance. This means that the efficiency of business intelligence solutions created to monitor Twitter activity can be improved five times by saving computational power, network bandwidth and data storage.Originality/valuePrevious research has analyzed all Twitter activity taken together. By dividing tweets into semantic and share tweets, this paper illustrates that it is, in fact, share tweets that are correlated with stock performance and not semantic tweets.