Chinese securities investment funds: the role of luck in performance

Purpose The Chinese fund market has witnessed significant developments in recent years. However, although there has been a range of studies assessing fund performance in developed industries, the rapidly developing fund industry in China has received very little attention. This study aims to examine the performance of open-end securities investment funds investing in Chinese domestic equity during the period May 2003 to September 2020. Specifically, applying a non-parametric bootstrap methodology from the literature on fund performance, the authors investigate the role of skill versus luck in this rapidly evolving investment funds industry. Design/methodology/approach This study evaluates the performance of Chinese equity securities investment funds from 2003–2020 using a bootstrap methodology to distinguish skill from luck in performance. The authors consider unconditional and conditional performance models. Findings The bootstrap methodology incorporates non-normality in the idiosyncratic risk of fund returns, which is a major drawback in “conventional” performance statistics. The evidence does not support the existence of “genuine” skilled fund managers. In addition, it indicates that poor performance is mainly attributable to bad stock picking skills. Practical implications The authors find that the top-ranked funds with positive abnormal performance are attributed to “good luck” not “good skill” while the negative abnormal performance of bottom funds is mainly due to “bad skill.” Therefore, sensible advice for most Chinese equity investors would be against trying to “pick winners funds” among Chinese securities investment funds but it would be recommended to avoid holding “losers.” At the present time, investors should consider other types of funds, such as index/tracker funds with lower transactions. In addition, less risk-averse investors may consider Chinese hedge funds [Zhao (2012)] or exchange-traded fund [Han (2012)]. Originality/value The paper makes several contributions to the literature. First, the authors examine a wide range (over 50) of risk-adjusted performance models, which account for both unconditional and conditional risk factors. The authors also control for the profitability and investment risks in Fama and French (2015). Second, the authors select the “best-fit” model across all risk-adjusted models examined and a single “best-fit” model from each of the three classes. Therefore, the bootstrap analysis, which is mainly based on the selected best-fit models, is more precise and robust. Third, the authors reduce the possibility that findings may be sample-period specific or may be a survivor (upward) biased. Fourth, the authors consider further analysis based on sub-periods and compare fund performance in different market conditions to provide more implications to investors and practitioners. Fifth, the authors carry out extensive robustness checks and show that the findings are robust in relation to different minimum fund histories and serial correlation and heteroscedasticity adjustments. Sixth, the authors use higher frequency weekly data to improve statistical estimation.

Evading the Entrepreneurship: A Study to Discover Implementable Online Approaches to Avoid Greenhouse Consequences

Greenhouse gases emissions due to climate change are a continuous threat to the global world, mainly relying on the pervasive consumption of numerous products, including synthetic and non-synthetic products. This research focused on the green purchase intentions of students in Pakistan towards different products, which are related to minimising the greenhouse effect and are available for sale on numerous e-commerce websites, ultimately proceeding to green entrepreneurship. The main objective of this study was to determine which methodology was better among product listing, social media advertising, and online virtual community to enhance customer online green purchase intention while considering online information about the greenhouse effect as a mediating variable. The AMOS 24 was used for this research. SEM was performed with the help of bootstrap methodology. The research was conducted on 280 students at different educational institutes in Pakistan, using a simple random sampling technique. A finding of this study suggested that all three methods positively impacted the green purchase intention of consumers and green entrepreneurship, but online virtual communities could be considered in a more effective way to enhance the green purchase intention of its targeted customers.

Battling for Consumer's Positive Purchase Intention: A Comparative Study Between Two Psychological Techniques to Achieve Success and Sustainability for Digital Entrepreneurships

This research focuses on students' online purchase intentions in Pakistan toward different products available for sale on numerous e-business websites. This study's main objective is to determine which methodology is better to enhance customer online purchase intention. It also aims to discover how to improve perceived benefits and lower perceived risks associated with any available online product and entrepreneurship. AMOS 24 has been used to deal with the mediation in study design with bootstrap methodology. The study was conducted on 250 students from different educational institutes in Pakistan using a simple random sampling technique. A finding of this study suggests that both methods positively impact online purchase intention of consumers and sustainable digital economy. But social media advertisement is more effective through enhancing the perceived benefits of products. In contrast, product content factors are more effective at lowering the perceived risks associated with available online products.

Service Innovation in Human Resource Management During COVID-19: A Study to Enhance Employee Loyalty Using Intrinsic Rewards

This research focuses on the employee loyalty aspect of private hospitals in Pakistan during the COVID-19 pandemic, seriously impacted by strict work demand and work-family conflict. To manage this issue, social rewards and psychological rewards played a role as a mediator. The study uses a causal research design with a correlational study design in a non-contrived environment. Minimal researcher interference has been assured. AMOS 24 has been used to deal with the mediation in study design with bootstrap methodology. The study was conducted on 250 nurses of different private hospitals across Punjab province using a proportionate stratified sampling technique. A finding of this study suggests that nurses remain loyal to their organizations despite having uncompromising work demands and facing work-family conflict when they are provided with social and psychological rewards on their job by their organizations.

The R-package surveysd: Estimating standard errors for complex surveys with a rotating panel design

Surveys with a rotating panel design are a prominent tool for producing more efficient estimates for indicators regarding trends or net changes over time. Variance estimation for net changes becomes however more complicated due to a possibly high correlation between the panel waves. Therefore, these estimates are quite burdensome to produce with traditional means. With the R-package surveysd, we present a tool which supports a straightforward way for producing estimates and corresponding standard errors for complex surveys with a rotating panel design. The package uses bootstrap techniques which incorporate the panel design and thus makes it easy to estimate standard errors. In addition the package supports a method for producing more efficient estimates by cumulating multiple consecutive sample waves. This method can lead to a significant decrease in variance assuming that structural patterns for the indicator in question remain fairly robust over time. The usability of the package and variance improvement, using this bootstrap methodology, is demonstrated on data from the user database (UDB) for the EU Statistics on Income and Living Conditions of selected countries with various sampling designs.

Inferência bootstrap para intervalo de confiança de modelo de regressão quadrática

This study was carried out with the purpose of proposing a construction of confidence intervals for the critical point of a second degree regression model using a parametric bootstrap methodology. To obtain the distribution of the critical point, height growth data of the plants were used. From the analysis, the theoretical variables for the error and the confidence intervals were constructed. In addition, we examined different variance expressions with the purpose of the bootstrap-t confidence interval. The point estimate of the critical point was 10.7423 g L-1 of fertilizer doses without growth of C. canjerana plants. It was verified that the confidence intervals that considered the expression of the variance with the covariance between the regression models, present more satisfactory results, that is, results with more precision.

Bootstrap Methods for Statistical Inference. Part II: Extreme-Value Analysis

This paper is the sequel to a companion paper on bootstrap resampling that reviews bootstrap methodology for making statistical inferences for atmospheric science applications where the necessary assumptions are often not met for the most commonly used resampling procedures. In particular, this sequel addresses extreme-value analysis applications with discussion on the challenges for finding accurate bootstrap methods in this context. New bootstrap code from the R packages “distillery” and “extRemes” is introduced. It is further found that one approach for accurate confidence intervals in this setting is not well suited to the case when the random sample’s distribution is not stationary.

On the Bound of Cumulative Return in Trading Series

There is no doubt that cumulative return is one of fundamental concerns in financial markets. In this paper, we first reveal the upper bound of cumulative return, and then propose a method to evaluate the performance of trading strategies by using proposed upper bound. Furthermore, with the help of bootstrap methodology, we conduct numerous experiments on distinct international stock markets, including developed markets and emerging markets, to verify the validity of the proposed upper bound. And both the theoretical and empirical results show that the effectiveness of the proposed upper bound and reveal its significant potentials on evaluating performance of trading rules.

Bootstrapping Inequality of Opportunity in Europe. Are changes significant?

The aim of this article is to shed some light on the behaviour of income inequality and inequality of opportunity over time for 26 European countries. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporate a wide variety of personal harmonised variables, allowing comparability between countries. The availability of this database for the years 2004 and 2010 is particularly relevant to assess changes over time in the main inequality indices and the contribution of “circumstance” to inequality of opportunity. Bootstrap methodology is used with the aim of testing if the differences between the two years are statistically significant. Results show that observed changes in inequality of opportunity and income inequality are in most cases significant and also prove the robustness of the bootstrap methods to analyse the evolution of income inequality and inequality of opportunity.