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This study investigates the performance distribution of passive funds in the Korean market and compares it with the performance distribution of active funds. The key findings are as follows, first, the performance distribution of passive funds has a thicker tail compared to that of active funds. There are passive funds that achieve outstanding performance, and both the false discovery rate (FDR) analysis and simulation analysis suggest that their outperformance is driven by managerial skill rather than luck. Second, passive fund performance is more persistent compared to active fund performance. Third, investors are less responsive to passive fund performance compared to active fund performance. The fund flow-performance relationship is significantly positive for active funds but not for passive funds. This implies that investors may not recognize the managerial skills of passive funds.

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.

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.

The purpose of this paper is to examine the performance of US mutual funds that invest primarily in emerging market equities and bonds.

The study adopts the Morningstar classification of mutual funds and uses the Lipper US Mutual Fund Database through FactSet to obtain monthly returns and various metrics for emerging market equity and bond mutual funds covering the period from January 2000 to May 2017. Several descriptive statistics for these funds are reported as well as various risk-adjusted performance measures. Alphas are computed for different sub-periods using different factor models to mitigate potential biases.

The results show that diversified emerging market funds generate some significant alphas for their investors during the study period. Emerging market bond funds, on the other hand, do not provide any significant positive alphas; mostly alphas are negative. An analysis of sub-period performance suggests that these funds do not consistently provide excess returns, showing great variations from one period to another.

The emerging market funds provide US investors with an alternative source of exposure for their portfolios. Emerging markets differ from developed markets on a wide range of market and economic characteristics, including size, liquidity, and regulation. This study contributes to the scarce literature on these types of funds and provides a comprehensive performance assessment against various benchmarks during a period that encompasses significant bear and bull markets across the world.

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.

This paper aims to explain the fundraising and valuation processes of startups and discuss the conflicts of interest between entrepreneurs, venture capital (VC) firms and stakeholders in the context of startup corporate governance. Further, this paper uses the examples of WeWork and Zenefits to explain how a failure of stakeholders to demand an external audit from an independent accounting firm in early stages of funding led to an opportunity for fraud.

The methodology used is a literature review and analysis of startup valuation combined with the Fraud Triangle Theory. This paper also provides a discussion of WeWork and Zenefits, both highly visible examples of startup fraud, and explores an increased role for independent external auditors in fraud risk mitigation on behalf of stakeholders prior to an initial public offering (IPO).

This paper documents a number of fraud risks posed by the “fake it till you make it” ethos and investor behavior and pricing in the world of entrepreneurial finance and VC, which could be mitigated by a greater awareness of startup stakeholders of the value of an external audit performed by an independent accounting firm prior to an IPO.

An implication of this paper is that regulators should consider greater oversight of the startup financing process and potentially take steps to facilitate greater independence of participants in the IPO process.

Given the potential conflicts of interest between VC firms, investment banks and startup founders, the investors at the time of an IPO may be exposed to the risk that the shares of the IPO firms are overvalued at offering.

This study demonstrates how startup practices can be extended to the Fraud Triangle and issue a call to action for the accounting profession to take a greater role in protecting the public from startup fraud. This study then offers recommendations for regulators and standards entities.

There are few academic papers in the financial crime literature that link the valuation and culture of startup firms with fraud risk. This study provides a concise explanation of the process of valuation for startups and highlights the considerations for stakeholders in assessing fraud risk. In addition, this study documents an emerging role for auditors as stewards of proper valuation for pre-IPO firms.

The study assess the selection ability and market timing skills of mutual fund and unit trust managers in Ghana.

The study uses an improved survivorship bias-free dataset of yearly after-fee returns of all mutual funds and unit trusts operating in Ghana from January 2011 to December 2019, cumulating in nine years of quantitative fund data. The authors assess Mutual funds and Unit trusts that ever existed, “alive” or “dead,” over the sample period in the study. The authors construct factor loadings to enable the application of multifactor models in the analysis. The authors apply the unconditional versions of the Jensen alpha, Fama-French three-factor, and Carhart four-factor models to determine the selection ability and market timing skills of 32 mutual funds and 17 unit trusts. The authors deploy HAC-consistent robust standard errors to the OLS estimations to subdue the effect of heterogeneity and autocorrelation.

The results indicate that, on average, mutual funds and unit trust managers possess market timing skills but no selection ability. When the results are decomposed into fund types, fixed-income and balanced mutual fund managers possess selection ability and market timing skills.

To the authors' best knowledge, this study is the earliest to examine the selection ability and market timing skills of both mutual fund and unit trust managers in Sub-Saharan Africa (SSA). It is also the earliest to construct factor loadings for the Ghana stock market.

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。.

Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study.

Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022.

The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions.

In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered.

While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.