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Purpose World Cup tournament is one of the most popular international organizations in football. The purpose of this paper is to investigate the overall performance of World Cup 2018 teams via multi-criteria decision-making (MCDM) approaches. Design/methodology/approach The presented approach adopts entropy integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches to weight the criteria and evaluate the performance of World Cup 2018 teams. Initially, the authors compute weight criteria via Shannon Entropy method. Then, the authors compute and compare the results of TOPSIS and WASPAS methods so as to evaluate the performance of World Cup 2018 teams. Findings According to TOPSIS and WASPAS results, Belgium has demonstrated better performance in comparison to other teams. As per to the empirical results, both methods have shown a significant harmony in terms of performance figures. There is also strong positive correlation between TOPSIS and WASPAS method results. This result confirms the stability of the analysis. Originality/value This paper contributes to sport performance management literature by using MCDM methods in FIFA World Cup 2018 teams. To the best of the authors’ knowledge, this is the first paper to measure performance of an international football organization via MCDM methods.

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Measuring the financial efficiencies of mutual funds in emerging markets has played an important role in finance literature. Charnes et al. (1978) advocated Data Envelopment Analysis (DEA), a valuable mathematical programming technique, which is used to measure the technical, pure and scale efficiencies of decision making units. The general form of DEA is the CCR model that depends on the assumption of constant returns to scale. Subsequently, Banker et al. (1984) developed an alternative DEA model which includes a variable returns to scale approach. The aim of this study is to measure and compare the financial efficiencies of Turkish securities and pension funds in the 2006–2007 period. In this respect, 36 securities mutual funds (SMFs) and 41 pension mutual funds (PMFs) have been evaluated comparatively according to classical portfolio performance measures and DEA models. Results from performance indices and DEA models reveal that PMFs have higher portfolio performances and financial efficiencies than SMFs in the 2006–2007 period. However, SMFs and PMFs have shown considerable increases in efficiency in the 2006–2007 period according to CCR and BCC models. Of the 77 funds studied, 23 funds in 2007 and 20 funds in 2006 demonstrated scale efficiency. Furthermore, the input ratios should be considerably improved for 2006 and 2007. But, mostly the output values of the funds were found to have remained unchanged in the case of PMFs and SMFs in 2007. The output ratios for 2006 should be considerably improved, especially in the case of SMFs. Finally, the DEA method is evaluated as a substantial quantitative tool for investors in analysing the financial efficiencies of funds in the capital markets.

In finance literature, Capital Asset Pricing Model predict only systematic risk is priced in equilibrium and neglect firm specific (idiosyncratic) risk which can be eliminated by diversification. However in real world investors, who are disable to diversify their portfolios, should take into consideration idiosyncratic risk beside of systematic risk in prediction of expected return. In this article, we examine real market conditions in Istanbul Stock Exchange (ISE), an emerging market stock exchange, over the period 2007:01 to 2010:12 by studying market wide and idiosyncratic volatility following the methodology of Campbell et al.(2001). Our findings suggest that, in 2007-2010 period, idiosyncratic volatility is the biggest component of total volatility and shows no trend in this period. Beside that our analyses about the predictive ability of various measures of idiosyncratic risk provide evidence that idiosyncratic volatility is not a significant predictor for future return. ARTICLE INFO