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The purpose of this study is to investigate the value investors place on S&P index additions relative to uncertainty surrounding the firm and the market. Investors look for reassuring signals or tell-tale signs around uncertainty.

Variation in the market response to announcements of S&P additions to the 400, 500 and 600 indices is examined against measures of risk factors. Internal risk factors include firm size relative to the index, total firm risk and liquidity, and whether the firm is a brand new index entrant. External risk factors related to market uncertainty are measured by the Chicago Board of Exchange volatility index.

Firms with lower market capitalization relative to the index, higher total risk, lower trading volume and first-time entrants to any S&P index elicit a positive market reaction compared to firms with less pricing uncertainty. In times of increased market uncertainty, investors tend to place more value on signals from respected institutions such as S&P, and riskier firms benefit more from inclusion in the S&P index. Overall, this study finds that the market overreaction is explained by the degree of uncertainty surrounding the added firms, as well as by the degree of market uncertainty at the time of the announcement.

The findings of this study suggest that investors interpret the prospect of S&P index addition as an opportunity for firms to reduce uncertainty surrounding them, and thus partially hedge their exposure to market uncertainty by joining an index tracked by dozens of index funds. The value of such a hedging strategy rises for riskier firms during market turbulence.

The purpose of this paper is to reveal the limitations of h-index in assessing research performance through citation analysis and suggest two new indexes called prime index (P-index) and value added index (V-index), which are simpler to compute than g-index and more informative. For more serious research performance evaluation, analytic hierarchy process (AHP) methodology is proposed.

The methodology adopted is to compare existing indexes for citation-based research assessment and identify their limitations, particularly the h-index, which is most commonly employed. It gives advantages of g-index over h-index and then proposes P-index which is simpler to compute than g-index but is more powerful in information content than g-index. Another V-index is proposed on a similar philosophy as P-index by considering total number of citations/author. For serious evaluation of finite candidates for awards/recognitions, a seven-criteria-based AHP is proposed. All new approaches have been illustrated by drawing raw data from Google scholar-powered website H-POP.

This paper demonstrates over-hype about use of h-index over g-index. However, it shows that newly proposed P-index is much simpler in computation than g but better than g-index. V-index is a quick way to ascertain the value added by a research scientist in multiple-authored research papers. P-index gives a value 3–4 percent higher than g and it is holistic index as it uses complete data of citations. AHP is a very powerful multi-criteria approach and it also shows g-index to be a more important factor, whereas h-index is the least important but frequently used approach. It is hoped that the findings of this paper will help in rectifying the misplaced emphasis on h-index alone.

The research focus has been to suggest new faster, better methods of research assessment. However, a detailed comparison of all existing approaches with the new approaches will call for testing these over a large number of data sets. Its limitation is that it has tested the approaches on 5 academics for illustrating AHP and 20 researchers for comparing new indexes with some of the existing indexes. All existing indexes are also not covered.

The outcomes of this research may have major practical applications for research assessment of academics/researchers and rectify the imbalance in assessment by reducing over-hype on h-index. For more serious evaluation of research performance of academics, the seven-criteria AHP approach will be more comprehensive and holistic in comparison with a single criterion citation metric. One hopes that the findings of this paper will receive much attention/debate.

Research assessment based on proposed approaches is likely to lead to greater satisfaction among those evaluated and higher confidence in the evaluation criteria.

P- and V-indexes are original. Application of AHP for multi-criteria assessment of research through citation analysis is also a new idea.

The purpose of this paper is to investigate the initial public offerings (IPOs) of the firms that are eventually included in one of the S&P 400, the S&P 500, or the S&P 600 Indices. Do these firms have very different IPO features than the rest of the IPOs?

The control sample is formed of IPOs that are not included in the corresponding index, and the IPOs that end up in each S&P index are compared to this control sample. Logistic regressions are utilized to estimate the odds of inclusion into one of these indices.

The author finds that the IPO features, such as underpricing, offer price, underwriter's reputation, venture capital presence, and so on, are found to be substantially different for the index samples. The index firms are found to be “superstars” that deliver extremely high long‐run returns between their IPO date and their index inclusion date. The above results suggest that the quality of index firms has a persistent component to it that can be detected even during the IPO process. After estimating the determinants of the index inclusion, the author discovers that factors implying lower asymmetric information about firm's business (such as, the firm being a spinoff, or being certified by a venture capitalist or a prestigious underwriter, etc.) increase its odds of inclusion.

The paper proposes and tests two new hypotheses related to inclusion into an S&P index. Discoveries made in this paper can help someone recognize which IPOs could become “superstars” that end up in an S&P index.

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

The purpose of this paper is to demonstrate the new application of a performance index (p‐index), extending its use to libraries for measuring and evaluating library circulation statistics in terms of quality and quantity of library books usage by subjects.

The study uses NISCAIR library circulation data and computes p‐index as well as h‐index for comparing usage in different subjects.

The results indicate that a two dimensional map of quality vs quantity of transactions can be used for better understanding and evaluation of library usage.

The h‐ and p‐indices and the quality‐quantity maps can be used as a benchmark for monitoring library performance in addition to finding out high value areas in the library collection, high value users, and high value books.

The paper is able to supplement the insights normally available from routine statistical analysis of circulation data.

This study may help in providing knowledge/insights in building up collections.

The purpose of this paper is to develop new tools to interpret changes in risk neutral probability distributions (RNPDs). It distinguishes between changes attributable to upside potential and those attributable to downside risk, and shows that the distinction is supported empirically.

This paper estimates pricing kernels and RNPDs from option price data, then studies the expected excess returns on a fixed‐strategy reference portfolio composed of the claims defined by the RNPDs. The portfolio is disaggregated so that realized returns can be expressed as a value‐weighted average of returns to upside (investment) and downside (insurance) sub‐portfolios, respectively. An upside sub‐portfolio can be interpreted as defining payoffs to a call option, a downside sub‐portfolio as payoffs to a short put position.

Empirical results indicate that the realized excess returns on the reference portfolios are significantly and negatively related to both S&P index growth and volatility (measured by the Chicago Board Options Exchanges (CBOEs) volatility index (VIX)) in the original data, but neither variable is significant in regressions on data first differences. However, in regressions on both the original data and first differences, realized excess returns on the investment sub‐portfolios are significantly and negatively related to both S&P index growth and volatility, whereas the realized excess returns to insurance sub‐portfolios are significantly and positively related only to the VIX. In regressions on both original data and its first differences the ratio of realized insurance excess return to total return is positively and significantly related only to the VIX. Constant terms are significant in about half of all the regressions, suggesting the presence of additional explanatory factors not captured in currently available data.

The paper shows that upside and downside sub‐portfolios have different return distributions in different market regimes, and that while returns to upside claims depend significantly on both S&P index growth and volatility, returns to downside claims depend significantly on just S&P index volatility. Thus realized excess returns to sub‐portfolios convey more nearly precise information about changes in market attitudes than do realized excess returns to entire portfolios. Although concepts of aggregating and disaggregating information have been investigated in the context of annual earnings announcements in other research, they have not previously been applied to realized portfolio returns in the manner used here. If the paper's findings are sustained in further empirical analyses, they can potentially provide information regarding both the Grossman‐Zhou and Holmstrom‐Tirole theories of claim pricing. Overall, because they distinguish between upside potential and downside risk, these methods contribute to more discriminating ways of understanding reference portfolio returns. In contrast, the CAPM measures of return variance do not distinguish between the risks of returns fluctuating on the upside from the risk of returns fluctuating on the downside.

The target costing technique, mathematically discussed by Sauers, only uses the C_p index along with Taguchi loss function and X‐R control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the C_p value to X‐R control charts to obtain goal control limits. Studies have shown that the point estimator of the C_p index, Ĉ_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the Ĉ_p index and using both Taguchi and Spiring’s loss functions together with X‐R charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

The traditional public library met the needs of its patrons by circulating books, holding story hours, and providing readers' advisory and reference services. Today, public libraries circulate art work and garden tools, provide disco dancing and college courses, and (in New York State) help their users find jobs through library‐based Job Information Centers.

The purpose of this paper is to examine the information content in the Standard & Poor (S&P) 500 index revision and its impact on the corporate bonds and earnings of the firms whose stocks are added to or deleted from the index.

The paper uses panel regressions on a 13-year sample of the companies added and deleted from the S&P 500 index.

The regression results on the bond yields and earnings show that analysts and investors draw positive (negative) information from Index additions (deletions) and adjust their expectations of the firm performance as well as the required rates of return on corporate bonds after index revisions.

The paper suggests that deletions from the Index have significantly negative impacts on corporate bonds and earnings performance of deleted firms while additions to the index do not have significant impacts on the bonds or realized earnings of added firms.

This paper uses corporate bonds and earnings to test competing hypotheses proposed to explain the excess stock returns of index revision, including information content hypothesis and liquidity hypothesis. The results are consistent with the information content hypothesis and do not support the liquidity hypothesis.

Prior research on additions to the S & P 500 and the smaller MidCap 400 and SmallCap 600 indexes reach different conclusions regarding the key variables that explain the cross-section of announcement period abnormal returns. Most notable in this regard is that liquidity measures, long thought to be of importance, do not appear to explain abnormal returns of the S & P 500 when other factors are controlled for. By contrast, they do appear to matter for additions to the smaller stock indexes. To explore this difference, the purpose of this paper is to analyze the abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index in a cross-sectional manner, controlling for several possible alternative factors.

This paper analyzes abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index. The authors consider several possible sources of the positive price effects in a multivariate setting that controls simultaneously for measures of liquidity, arbitrage risk, operating performance and investor interest and awareness. The authors then analyze both trading volume and the bid-ask spreads. The authors finally examine analyst and investor interest, focussing on changes in analyst coverage.

The authors find that only liquidity variables are significant, but that factors representing feedback effects on the firm’s operations and level of managerial effort are not. The authors find that the average bid/ask spreads of stocks added to the Nasdaq-100 index are lower after the addition. The authors also find that the number of analysts following a stock increases significantly after addition, verifying increased analyst interest. Both forms of evidence are consistent with the hypothesis that the additions are associated with enhanced liquidity for the stocks.

The authors conclude that what does happen to a Nasdaq stock when it is announced that it will be added to the Nasdaq-100 Index is that more analysts are drawn to it, and its market liquidity is enhanced. The authors conclude that what does not happen is that there is no evidence of significant effects of enhanced managerial effort or operating performance associated with the inclusion. This difference is noteworthy because it suggests that a certification effect of additions to the S & P indexes associated with S & P’s selection process are unique to it and do not apply to the Nasdaq-100 Index additions based on market cap alone. The results provide indirect evidence on the existence and significance of the certification effect associated with additions to the S & P indexes.