Salaries of professional players are usually determined prior to the execution of the responsibilities assigned by the organizations and are often based on the expected future performance of these players as derived from their past achievement. The study first identifies criteria that would affect players' salaries through literature reviews and then utilizes grey relational analysis (GRA) and grey prediction model to calculate weights of salary impact criteria, players' annual performance index, and salary prediction for the coming year. The performance data of players from the Chinese Professional Baseball League (CPBL) are used in this study. The results are as follows: (i) CPBL teams do refer to players' past performance records and future performance prediction when deciding on their salaries and (ii) future performance prediction must be made using at least a 3-year data set. The proposed prediction model is able to effectively provide relevant and useful information to the CPBL teams' management during players' salary adjustment.
Multivariate volatilities and distribution play an important role in portfolio selection and can be used to calculate the value-at-risk (VaR) of a multipleasset financial position. This study proposes a new expected utility maximization (EUM) model that accounts for VaR (EUM model with a VaR constraint (EUM-VaR)). Additionally, using the EUM-VaR model, this study investigates the hedging effectiveness of short and long hedged portfolios constructed with multivariate generalized autoregressive conditional heteroscedasticity (GARCH)-type models that feature level effects and multivariate normal t and skewed t distributions for stock indexes and their corresponding futures in the Greater China Region. It is found that, all else equal, portfolios constructed using the multivariate skewed t distribution are far more effective in hedging than those that rely on the other distributions, and the effectiveness of hedged portfolios from the multivariate GARCHtype models with level effects outperform those without level effects. Additionally, the effectiveness of hedged portfolios from multivariate asymmetric GARCH-type models exceeds that of those from multivariate symmetric GARCH-type models. Thus, investors should select the multivariate asymmetry in volatility, multivariate asymmetry in distribution, and EUMVaR models to construct effectively hedged portfolios. The results of this study can provide useful implications for investors looking to manage risk.
This investigates the influence of major electoral information on abnormal returns around the announcement date in the developed stock market and examines whether these explanatory variables are associated with observed cumulative abnormal returns using a regression analysis. The analytical results demonstrate that average abnormal returns are significantly negative before the date of the announcement of the results of a general election, on days -6 and -3, and after that announcement date, on days +4, +6 and +10. This phenomenon can be attributed to hedging activity of the investors to reduce risk.
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