The information content of portfolio performance history and persistence in fund performance: An examination of rollover funds

1999 ◽  
Vol 39 (3) ◽  
pp. 255-274 ◽  
Author(s):  
Terrence A. Hallahan
Keyword(s):  
Information Content ◽  
Fund Performance ◽  
Portfolio Performance ◽  
Performance History

Impact of ESG Rating of Companies on the Portfolio Performance

2021 ◽  
Vol 8 (4) ◽  
pp. 34-42
Author(s):  
Ramkumar Samyukth
Keyword(s):  
Fund Performance ◽  
Minimum Variance ◽  
Socially Responsible Investing ◽  
Sharpe Ratio ◽  
Portfolio Performance ◽  
Socially Responsible ◽  
Responsible Investing ◽  
Service Companies ◽  
Minimum Variance Portfolio ◽  
Mean Variance Portfolio

Socially responsible investing is becoming more popular among people because people are becoming more concerned about the environment and society. Socially responsible investors screen the company by considering the ESG factors. The question raced is whether socially responsible investing improves the portfolio performance and how the funds perform during uncertain times like the Covid-19 pandemic. Since many critics of ESG funds say that the ESG funds’ performance highly depends on Software and Service company stocks, so the relevance of Software and Service companies in the fund has been analyzed in this research. The portfolios have been formed by using the Markowitz mean-variance portfolio model, and the performance of the minimum variance portfolio has been studied. The fund performance has been analyzed using the Sharpe ratio, and the result concludes that the ESG fund performance with minimum variance has an abnormally high Sharpe Ratio of 10.8. A similar type of performance was identified during the Covid-19 pandemic. The abnormally high Sharpe ratio will encourage investors to move towards socially responsible investing.

scholarly journals Private Pension Fund Performance and Comparison with Basic Investment Instruments in Turkey

2015 ◽  
Author(s):  
Turgut Özkan ◽  
Özge Demirkale
Keyword(s):  
Pension Fund ◽  
Fund Performance ◽  
Pension Funds ◽  
Private Pension ◽  
Portfolio Performance ◽  
Social Expectation ◽  
The Social ◽  
Retirement Funds ◽  
Additional Income

In 2001, after the preparation of legal infrastructure in Turkey, private pension fund system started to be complementary to the Social Security system. There are many expectations from the private pension fund system both socially and economically. Social expectation is to direct individuals to alternative investment instruments to provide additional income for retirement. Economic expectation is to provide long-term funding to support the economic development. Pension fund companies have the most important responsibility to meet these expectations. In this study, the profits of investment instruments and individual pension funds are compared in a long term perspective, using three basic portfolio performance measures. The term between January 2004 and September 2014 have been considered. Investment alternatives have been discussed in detail. BIST100, deposit, gold and currency basket (USD+EUR) are the investment instruments that are compared with individual pension funds. In addition, individual pension funds have been analyzed on company basis and the achievements of the pension fund companies have been revealed during the term mentioned above. According to our analysis, it has been concluded that personal retirement funds lost value considerably, especially due to inflation.

Is all that glitters gold? A look at Fortune magazine’s 100 Fastest-Growing Companies

2019 ◽  
Vol 45 (7) ◽  
pp. 827-841
Author(s):  
Anthony Thomas Garcia ◽  
Anthony Loviscek ◽  
Kangzhen Xie
Keyword(s):  
Information Content ◽  
Performance Metrics ◽  
Editorial Staff ◽  
Selection Strategy ◽  
Portfolio Performance ◽  
Stock Selection ◽  
Significant Information ◽  
Content Type ◽  
Stock Portfolios ◽  
S 100

Purpose Does Fortune magazine’s list of the 100 Fastest-Growing Companies have information content; that is, is the list a source for market-beating performance? The paper aims to discuss this issue. Design/methodology/approach Using data for 26 annual periods, 1991–2016, the paper examines the top 5, 10, 25, 50 and all 100 stocks on a return-risk basis, including an application of Modern Portfolio Theory. To generate portfolio performance metrics, the study uses conventional mean-variance analysis, which includes the estimation of returns and risks, where risk will be measured by standard deviation and β. To arrive at the performance metrics and to determine whether information content is embedded in the list, the study reviews a series of tests. Because Fortune ranks the companies from 1 to 100, the data can be used to test if information content is displayed in sub-groups, such as in the first five to ten companies, even if it does not exist in the 100-stock portfolios. Findings The study finds that the returns are not high enough nor are the risks low enough statistically to conclude the existence of significant information content. Research limitations/implications As part of the authors’ efforts to move to the population of 2,600 firms as closely as possible, the authors use “delisting” returns from CRSP on 120 firms to account for missing observations, with a final sample size of 2,594 firms. Practical implications The evidence indicates that investors drawn to Fortune’s “100 Fastest-Growing Companies” should view them skeptically as a source for an effective stock selection strategy. Originality/value On the basis of the results of this study, readers will conclude that subscribers drawn to Fortune’s “100 Fastest-Growing Companies” should view them skeptically for investment recommendations. From a portfolio perspective, the study is unable to uncover information content that could lead to a market-beating performance, suggesting that the published criteria Fortune uses to select the Fastest-Growing Companies is embedded in the prices of the stocks even before Fortune publishes its list. The study notes that the selection criteria used by Fortune do involve some judgments on the part of the editorial staff (e.g. whether an announced restatement of previously reported financial data appears to have a significant impact), which means that someone who wished to anticipate the publication of the next list of the “Fastest-Growing Companies” would not only have to gather information but would also have to correctly anticipate these judgment calls.

Applications of Scanning Microscopy in Biomedical Research

1968 ◽  
Vol 26 ◽  
pp. 354-355
Author(s):  
T. L. Hayes
Keyword(s):  
Information Content ◽  
Biomedical Research ◽  
Biomedical Applications ◽  
Three Dimensional ◽  
Dental Enamel ◽  
Resolving Power ◽  
Whole Mount ◽  
Two Parameters ◽  
Content Information ◽  
Sectioned Tissue

Biomedical applications of the scanning electron microscope (SEM) have increased in number quite rapidly over the last several years. Studies have been made of cells, whole mount tissue, sectioned tissue, particles, human chromosomes, microorganisms, dental enamel and skeletal material. Many of the advantages of using this instrument for such investigations come from its ability to produce images that are high in information content. Information about the chemical make-up of the specimen, its electrical properties and its three dimensional architecture all may be represented in such images. Since the biological system is distinctive in its chemistry and often spatially scaled to the resolving power of the SEM, these images are particularly useful in biomedical research.In any form of microscopy there are two parameters that together determine the usefulness of the image. One parameter is the size of the volume being studied or resolving power of the instrument and the other is the amount of information about this volume that is displayed in the image. Both parameters are important in describing the performance of a microscope. The light microscope image, for example, is rich in information content (chemical, spatial, living specimen, etc.) but is very limited in resolving power.

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