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The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.

The purpose of this paper is to examine the relationship between foreign subsidiary staffing and subsidiary performance by focussing on two staffing practices: first, the ratio of parent country nationals (PCNs) to foreign subsidiary employees and second, the number of PCNs assigned to the foreign subsidiary.

Hypotheses predicting curvilinear relationships between the assignment of PCNs and subsidiary performance are tested using a panel data set consisting of 4,858 foreign subsidiaries of Japanese multinational corporations (MNCs).

The results demonstrate that the two staffing practices have different effects on subsidiary performance. The ratio of PCNs to foreign subsidiary employees has an inverted U-shaped relationship with subsidiary performance, while the number of PCNs assigned to the subsidiary has a linear and negative effect on subsidiary performance.

The results of this study are subject to limitations. First, the sample used in this study consists solely of the foreign subsidiaries of Japanese firms. This research design limits the generalizability of the findings of this study. Second, other decisions related to subsidiary staffing such as the ratio of PCNs in the subsidiary's top management team need to be examined to advance understandings of the relationship between subsidiary staffing and subsidiary performance.

MNCs need to identify the appropriate number of PCNs at which they can achieve the optimal trade-off with the PCN ratio to enhance the competitiveness and the performance of a foreign subsidiary. In doing so, they need to take into consideration that an increase in the number of PCNs has an immediate negative effect on the workplace morale of host country nationals.

This study incorporates two staffing practices into its analyses and shows that they have different implications for subsidiary performance. The results suggest that focussing on one staffing practice alone limits understanding of the complex relationship between foreign subsidiary staffing and subsidiary performance.

The present study tries to explore the various fund attributes that influence the mutual fund performance. Further, study examined the effect of mutual fund attributes namely, Net Asset Value (NAV), Portfolio turnover ratio (PTR), fund size (AUM), expense ratio (ExpR) and fund age (Age) on mutual fund's performance using gross return and risk-adjusted performance measures.

The study evaluated balanced panel data (short panel) comprising 81 Indian equity mutual fund schemes for the period of 2013–2019. The study estimated relationship between fund attributes (Net asset value, Portfolio turnover ratio, Fund age, fund size and Expense ratio) and fund performance (using gross return and risk-adjusted performance measures), through panel data regression using fixed-effects model as suggested by Hausman specification test on transformed data (due to high multicollinearity), with cluster-robust estimators due to the presence of heteroskedasticity in the model.

The findings of the study suggested that using gross return as fund performance measure, PTR, NAV, AUM, Age exhibit significant relationship with the fund performance whereas using risk-adjusted performance measures (Treynor ratio and Jensen alpha) NAV and ExpR significantly influences the fund performance. Identification of the significant relationship between fund characteristics and fund performance offers valuable insights to the investors and fund managers for rationally managing their portfolio with the ultimate objective of the wealth maximization.

The study considered only 81 equity mutual fund schemes. Some of the data were not available at the time of the study due to the policy of the company. The present study contributes significantly in examining the expected association between fund attributes and fund performance in the context of Indian mutual fund industry where this relationship were explored less.

The findings of the present study will help the investors to take the rational investment decision with the ultimate objective of maximum return with minimal risk. The findings also offer significant germane to the stakeholders in making rational decision-making process.

There is dearth of study concerning the relationship between mutual fund characteristics and fund performance with respect to Indian mutual fund industry. Therefore, study provides valuable insights to the area of the portfolio selection and management with respect to Indian mutual funds.

The purpose of this paper is to evaluate firm financial success across a broad range of performance measures and identify areas of the performance spectrum for which positive results were most difficult to achieve. Simultaneously, the authors identify the firms that most frequently ranked among the top five in terms of composite financial performance.

The dichotomous Rasch model was applied to 13 financial ratios for two industries for the years 2002‐2011. Of these ratios, the authors identify those that are consistent with the requirements of the Rasch model and suitable for ranking composite firm financial performance in each industry during the sample years. Ratio difficulty rankings are obtained, along with firm rankings reflecting managers' ability to achieve broad‐based financial success.

For the Foods and Aerospace/Defense industries during 2002‐2011, above average performance was most difficult to achieve in the areas of liquidity, financial leverage, and market valuation. Above average profitability and returns on investment seem to have been easier performance targets during this sample period. The authors also list the ticker symbols of firms with managers who consistently achieved top overall financial performance.

The performance data for each industry and time period have to fit the requirements of the Rasch model. In addition, it must be possible to translate continuous metric readings into binary measures without losing relevant information. Future research might explore the use of more sophisticated Rasch models, measures of non‐financial firm performance dimensions, additional industries and time periods.

This research offers managers, investors and regulators a fresh perspective on the evaluation of firm financial performance and managerial ability.

Rasch models are widely used in the human sciences. Application of this methodology to firms offers a more comprehensive view of firm performance and may reveal factors relevant to firm valuation that have previously been ignored, thus possibly impacting the allocation of capital across firms and industries.

To the authors' knowledge, this research represents a first attempt to apply the Rasch approach to an evaluation of managerial ability as reflected in a firm's overall financial performance.

The purpose of this paper is to compare companies in a developing country with those of a first‐world country. For this purpose South African (SA) companies in the chemical, food and electronic industries are to be evaluated on the hand of cash flow ratios and compared with companies in the USA in similar industries.

Giacomino and Mielke proposed nine cash flow ratios for performance evaluation. Ratios were calculated for companies in the USA in the chemical, food and electronic industries for 1986‐1988. Industry norms were calculated for the period, indicating that the potential existed to develop benchmarks for the ratios by industry. Jooste calculated cash flow ratios for listed companies in SA, similar to those calculated by Giacomino and Mielke. The results of the SA companies were then compared with the US companies.

The comparison revealed some similarities and differences. The cash flow sufficiency ratio showed that the SA industries had enough cash to pay primary obligations, whereas the US industries did not. At the levels of cash generated by SA industries the investments in assets and dividend payouts were more than for US industries. The cash flow generated by assets used in SA is also more than that of the USA but US industries retire long‐term debt in a shorter period than SA industries.

The periods used in the comparison differ. Research using the same periods was not available. No information was available on the state of the economies in each country for those periods.

The work done by Giacomino and Mielke is to be recommended. Further studies on the utility of cash flow data would be necessary to develop a set of cash flow‐based ratios. Such ratios used in conjunction with traditional balance‐sheet and income statement ratios should lead to a better understanding of the financial strengths and weaknesses of a company.

By comparing industries of a developing country with those of a first‐world country one may have an indication of the performance of SA companies in a global market.

In view of the significant changes in the capital structure of China’s real estate industry and enterprises in recent years, this chapter employs financial indicators and the linear regression function to analyze the relationship between corporate debt ratio and the performance of 111 A-share listed real estate enterprises in China. This study finds that the corporate debt ratio of China’s real estate enterprises in the past decade has a significant negative impact on enterprises’ performance. The study also finds that among China’s real estate companies, the corporate debt ratio has a more significant negative impact on the performance of non-state-owned enterprises than state-owned enterprises. In addition, a high debt ratio has a more significant negative impact on return on equity (ROE) than on return on assets (ROA). However, when Tobin’s Q serves as a proxy for firm performance, the negative impact of the corporate debt ratio becomes insignificant in the presence of the firm size factor. The research results of this chapter can provide some reference for subsequent policy-making and investment decisions in the Chinese real estate market.

The purpose of this study is to examine the impact of position adjusted turnover ratio on mutual fund performance.

The author calculates position adjusted turnover ratio in the same three steps as Edelen et al. (2013). Position adjusted turnover ratio is intended to be a trading cost proxy that captures both fund trading volume and per-trade costs. A metric of eight Morningstar performance measures is utilized.

Results show that funds with a higher position adjusted turnover ratio tend to have a lower risk-adjusted performance, such as indicated by both Sharpe and Sortino ratios, and even though these funds may have a higher annualized return.

The sample selection process is subject to a survival bias. Also, this study utilizes Morningstar performance measures rather than the widely used factors models.

This study examines the impact of invisible costs from fund trading. These findings encourage fund managers to take strategic steps to reduce the overall invisible cost impact to improve fund performance.

Few studies have investigated fund trading cost measured by position adjusted turnover ratio and its impact on fund performance. Further, this study contributes to current literature by using eight Morningstar fund performance variables, which are practitioner-oriented and are accessible by investors.

Determining the relevant information using financial measures is of great interest for various stakeholders to analyze the performance of the firm. This paper aims at identifying these financial measures (ratios) which critically affect the firm performance. The authors specifically focus on discovering the most prominent ratios using a two-step process. First, the authors use an exploratory factor analysis to identify the underlying dimensions of these ratios, followed by predictive modeling techniques to identify the potential relationship between measures and performance.

The study uses data of 25 financial variables for a sample of 1923 Indian manufacturing firms which exist continuously between 2011 and 2018. For prediction models, four popular decision tree algorithms [Chi-squared automatic interaction detector (CHAID), classification and regression trees (C&RT), C5.0 and quick, unbiased, efficient statistical tree (QUEST)] were investigated, and the information fusion-based sensitivity analyses were performed to identify the relative importance of these input measures.

Results show that C5.0 and CHAID algorithms produced the best predictive results. The fusion sensitivity results find that net profit margin and total assets turnover rate are the most critical factors determining the firm performance in an Indian manufacturing context. These findings may enable managers in their decision-making process and also have vital implications for investors in assessing the performance of the firm.

To the best of the authors’ knowledge, the current paper is the first to address the application of decision tree algorithms to predict the performance of manufacturing firms in an emerging economy such as India, with the latest data. This practical perspective helps the organizations in managing the critical parameters for the firm’s growth.

Traditional statistical methods to study the financial performance of any industry have many barriers and limitations in terms of the statistical distribution of the financial ratios, and, in particular, it considers only its positive values of it. The purpose of this paper is to estimate the financial performance of 24 Indian life insurance companies for the period from 2013 to 2016 using Grey relational analysis (GRA) proposed by Deng (1982) that accommodates the negative values in the analysis.

Financial performance of 24 Indian life insurance companies for the years from 2013–2014 to 2015–2016 is examined using a total of 14 indicators from capital adequacy ratios, liquidity ratios, operating ratios and profitability ratios (PR). The methodology used is GRA to obtain the Grey grades to rank the performance indicators, where higher relational grade shows better financial performance, and a lower score depicts the scope for improving the performance.

The results rank the insurance companies according to their financial performance in which Shriram insurance stands first with higher relational grade score, followed by the companies like IDBI Insurance, Sahara Insurance and Life Insurance Corporation of India. The main finding is that PR which have negative values are playing a crucial role in determining the financial performance of Indian life insurance companies.

This study has far-reaching practical implications in twofold: first, for the Indian life insurance industry, they have to concentrate more on PR for better financial health and, second, for any financial performance analysis, ignoring negative value ratios produce biased inference and GRA can be used for better inference.

This study is the first attempt to evaluate the financial performance of Indian life insurance using the GRA methodology. The advantage of GRA is that there is no restrictions on the statistical distribution of the data and it also accommodates the negative values, whereas all the other traditional methods insist on the statistical distribution of data, and, more importantly, they cannot handle negative values in the performance analysis.

The purpose of this study is to underscore the impact of the family variable on performance. The authors were interested in understanding whether the differences between Family Firms (FFs) and Non-Family Firms (NFFs), on the one hand, and between large FFs and medium-sized FFs, on the other, were reflected in the performance achieved.

In this paper a sample of 80 industrial companies listed on the Italian Stock Market (FTSE MIB and STAR indexes) were considered, and mixed criteria to distinguish FFs and NFFs (Smyrnios-Romano et al., 1998) were used. The empirical method allowed the development of some research hypotheses by exploiting the Pearson correlation.

There are two main categories of FFs, which correspond to two different strategic and organizational categories, namely, the FFs listed on the large capitalized companies index (FTSE MIB) and the FFs listed on the medium-capitalized companies index (STAR). Each kind of FFs (large FFs and medium-sized FFs) has a specific effect on profitability and financial performance. Specifically, if a company is medium sized, family presence is a relevant variable in achieving better profitability and financial performance than NFFs of the same size; on the other hand, if the company expands to become a large one, the family presence is an irrelevant variable in terms of both profitability and financial leverage (debt ratio).

Limitations of the study concern the definition of the sample, as this paper focused on the industrial sector and the method adopted, as it could be integrated with some econometrical models. The implications of this paper are relevant for families and regulatory bodies because it helps them better understand the effects of governance and company size both on short- and long-term performance. Moreover, the findings of the study can influence the decision-making process of investors to identify the long-term outperformers listed on the Italian Stock Exchange.

This study contributes to the literature on FFs by defining two different categories of FFs, namely, large and medium-sized. It seems that larger companies record a weaker family influence on short-term profitability.