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In this paper, we develop various valuation models for closed-end mutual funds under different sets of stochastic processes for the underlying assets. Since we used different stochastic processes from previous literature, it was possible to derive more interesting implications regarding investment strategies, discount puzzles of the funds, and valuation models. In particular, by utilizing Brownian motions and optimal stopping time framework, we succeeded in developing more realistic valuation model, which indicates that we can understand more easily about decision makings regarding optimal timing of reorganization from the closed-end funds to open-ended funds, optimal timing of trading of closed-end funds to realize maximum profits, and optimal design of closed-end fund structure.

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.

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.

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.

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)].

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.

This article examines whether deviations from fundamental value or closed-end country fund's discounts or premiums forecast future share price returns or net asset returns.

The main empirical (econometric) tool is a vector autoregressive (VAR) model. The authors model share price returns and net asset returns as a function of their lagged values, the discounts or premiums, and a control variable for local market returns. The authors also conduct Dickey Fuller and Granger causality tests as well as impulse response functions.

It was found that deviations from fundamental value do predict share price returns. This predictability is contrary to weak-form market efficiency. Premiums or discounts predict net asset returns but weakly.

The findings point to the idea that the closed-end fund market is somewhat predictable and inefficient (in its weak form) since the market appears to be able to anticipate a fund's future returns using information contained in the premiums (or discounts). In particular, the market has the ability to anticipate future behaviour because growing premiums forecast declining share price returns for one or two periods ahead.

Mutual funds are the second most preferred investment option in India and have garnered considerable research interest. The focus of Indian studies thus far has been restricted to the bottom-up approach of investing which rewards a fund manager for picking winner stocks and generates superior returns. While changing portfolio allocation as per varying macro-trends has been instrumental in generating superior returns, it has not been given the desired attention. This study addresses this important research gap.

The authors analyze the industry selection ability of the fund manager on a robust sample by decomposing alpha into alpha due to industry selection and alpha attributable to stock selection. Alpha estimates are computed on a robust sample of 34 open-ended Indian equity mutual funds for a 10-year duration 2011–2020 using three base models of asset pricing – single-factor, four-factor and five-factor alpha under panel data methodology.

The study leads us to four major findings. One, industry selection explains more than two-fifth of the alpha both in cross-section and time series of returns; two, industry selection exhibits persistence for more than four quarters across asset pricing model; third, younger funds have level playing when alpha from picking right industries is concerned; four, broad industry allocation continues to explain superior returns as sector allocation undergoes consolidation during ongoing COVID-19 pandemic and funds increase exposure to defensive stocks, consistent with folio allocations as per macroeconomic conditions.

The authors find strong evidence of persistence in the case of alpha attributable to the industry selection component, and the findings are consistent with the persistence results reported in the empirical literature. While some funds excel in stock-picking skills and others excel in picking the right industries, both skills together make for winner funds that attract larger investor flows as investors chase superior performance. The authors also find no evidence of diseconomies of scale in the case of industry allocation alpha generated by the fund managers.

The results suggest a fresh approach for investors while making mutual fund investment decisions; the investors can achieve superior returns by assessing industry selection skills as it tends to provide a more holistic picture concerning a perennial question – why some funds outperform and continue to contribute to investor's wealth?

Mutual funds have become a favored investment option for Indian investors more so as a disciplined investment option owing to dismal financial literacy rates. The study throws light on a relatively unaddressed dimension of choosing winner funds. The significance of right sector allocation assumed even more significance with the onset of the pandemic which lends further credence to the findings of the study.

Research has been conducted on secondary data extracted from a well-cited database for Indian mutual funds. Empirical analysis and conclusion drawn are based on authentic statistical analysis and adds to the existing literature.

This paper analyses whether the active management and the fundamentals of the pension fund allow products that beat their peers to be identified in terms of risk-adjusted performance.

The sample is composed of all the pension funds active in the period 2000 to 2017 investing in the Eurozone. What this means is that a greater similarity is guaranteed in terms of benchmark, assets available for investment and currency. All the data have been retrieved from the Morningstar Direct database.

The paper reveals that the degree of concentration and value for money are important determinants of performance. In this sense, the strategies of investing in concentrated portfolios that differ from the benchmark and with undervalued assets in terms of price earnings ratio (PER)-return on assets (ROA) achieve better results.

This is one of the few papers that shows the effect of active management and value investing strategies’ on the performance of pension funds.

本文旨在分析、我們能否根據退休基金的積極管理及其基本原理, 找到就風險調整表現而言之最優勝產品.

我們的樣本包括於2000年至2017年期間活躍於歐元區內投資活動的所有退休基金。這意味著、樣本確保了相關之退休基金就基準、可供投資的資產及貨幣而言、均擁有較大的相似性。所有數據均從晨星基金資料庫檢索得來的。.

本文顯示、集中程度和價值比率是決定表現的重要因素。在這個意義上說，如投資在與基準不同的及附有就本益比 – 資產收益率 (PER - ROA) 而言被低估的資產的那些集中投資組合上, 這會是效果較佳的策略.

探討積極管理和價值投資策略如何影響退休基金表現的學術研究為數不多, 本文乃屬這類研究。.

The purpose of this paper is to examine the determinants of mutual funds’ performance at both a country level and a fund level in Vietnam.

The different types of funds with more than three-year operation are selected to remove outliers of the stock market boom from 2015 to 2018. The data set includes 54 mutual funds operating during the period from 2008 until November 2018.

The research finds that there is a positive relationship between macroeconomics and mutual funds’ performance. Furthermore, country-level governance such as regulation effectiveness, political stability, economic growth and financial development has a positive correlation with mutual funds’ performance. However, the impact of fund-level factors is diverse with the no significant impact of board size on mutual fund’s performance, while passive funds perform better than active funds in Vietnam.

The research results suggest that investors should pay attention to the types of funds and operating expense when making an investment decision in mutual funds. There are some recommendations for both government policy-makers and the mutual fund industry that are likely to facilitate the development of this field in Vietnam.

The research contributes to the understanding of what are the factors that should be considered when investing in mutual funds.

This paper empirically investigates the performance of Islamic funds, which have been praised for weathering the 2008 financial storm relatively well and compares it to a European product designed to protect the most vulnerable of investors, UCITS funds.

This paper builds on 128 time-series regressions using various factor models to analyse the risk-return relationship of 242 Islamic and UCITS funds relative to a market benchmark, over a 10-year period starting January 2006, to capture severe bear and bull market conditions.

Islamic funds do not face a competitive disadvantage arising from their strict compliance with Sharīʿah principles, and their performance and investment style is relatively similar to UCITS schemes.

Islamic funds represent a low risk investment due to their very mild betas. Therefore, when forming part of a diversified portfolio, they can act as a hedging tool against adverse market movements.

Muslim investors are not punished relative to conventional retail investors when following their own beliefs. Other investors can consider Islamic funds in their portfolio allocation, especially those who seek socially and ethically responsible investments.

This paper fills a lacuna in the existing literature, because the sample is made up of Islamic funds established worldwide and includes not only equity, but also fixed income and mixed allocation funds.