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Are Enhanced Index Funds Enhanced?
Abstract
One of the major trends in the mutual fund industry is the rising importance of passive investing. One of the responses of the investment community to this challenge has been the creation of enhanced return index funds. In this paper, we examine the performance of enhanced index funds and find that they outperform index funds when we analyze both pre-expense performance (management ability) and post-expense performance (investor returns). However, when we use any of several criteria that have been proposed for picking the best fund from among those following some index, index funds outperform enhanced index funds.
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The global mutual fund industry is growing and is expected to reach $100 trillion by 2027. However, the performance of actively managed mutual funds has remained lacklustre, resulting in a flow toward passive funds over the past one-and-a-half decades. Against this backdrop, the mutual fund performance debate has taken centre stage. This study combines bibliometric and content analyses of 708 Scopus-indexed journal articles published in A or A* category journals according to the Australian Business Deans Council (ABDC) classification between 2014 and mid-2024. This study consolidates contemporary knowledge, identifies and analyses significant research clusters, elicits trends, and establishes a future agenda for research on mutual fund performance. This study identifies four research clusters: (a) Socially Responsible Investments (SRI), Environmental, Social and Governance (ESG) and contemporary studies; (b) Fund flows and institutional ownership; (c) Active vs passive and fund managers’ skills; (d) Investors’ preferences, behavioural dimensions and institutional settings. The impact of fund flows, portfolio churn, portfolio concentration, expense ratio, active share, investment style, fund managers’ skills on fund performance alongside SRI and ESG funds’ performance and active vs passive fund management remain the focus areas of research and need further examination. Asset pricing, market efficiency, human capital efficiency, social trust, performance-chasing behaviour and overconfidence are the dominant theories that explain mutual fund performance. The study benefits portfolio managers, investors, policymakers, regulators, and scholars by helping them understand mutual funds’ performance nuances.
The rise of index funds presents a challenge for the corporate governance of listed companies. Based on a comprehensive data analysis, the thesis documents the growing importance of passive asset managers in listed firms' ownership structures. It then explains why the incentives of these managers to engage in the corporate governance of their portfolio companies are not socially optimal, relying, among other things, on recent results from the empirical corporate finance literature. Finally, the thesis critically reviews the instruments employed by the legal system to respond to the problems identified, with a focus on the "stewardship" provisions of the revised Shareholder Rights Directive and the shortcomings of their specific design.
We review the major models of mutual fund performance: (1) using return data to evaluate equity funds—from single to multi-index models, (2) measuring passive portfolio performance, (3) using holdings-based performance measures, (4) measuring timing ability, and (5) measuring bond fund performance. We conclude with a discussion of issues affecting performance measurement: data sources and bias, missing factors, and improvements to benchmarks.
There is a vast literature which shows that investors don’t make rational decisions in allocating resources among both different types of investments and different individual investments. Target risk funds and target date funds are two types of mutual funds that make the asset allocation decision for an investor Target risk funds have not been studied before: this article is the first comprehensive study of their characteristics and performance and how they compare to target date funds as an investment vehicle.
S&P 500 index funds represent one of the simplest vehicles for examining rational behavior. They hold virtually the same securities, yet their returns differ by more than 2 percent per year. Although the relative returns of alternative S&P 500 funds are easily predictable, the relationship between cash flows and performance is weaker than rational behavior would lead us to expect. We show that selecting funds based on low expenses or high past returns outperforms the portfolio of index funds selected by investors. Our results exemplify the fact that, in a market where arbitrage is not possible, dominated products can prosper. © 2011 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
There is a vast literature which shows that investors don't make rational decisions in allocating resources among different investments. Target risk funds and target date funds are two types of mutual funds primarily organised as fund of funds that make the asset allocation decision for an investor. Both are used as options in 401(k) plans and Individual Retirement Accounts. However they control for risk in very different ways. Target risk funds have not been studied. This article is the first comprehensive study of their characteristics and performance and how they compare to target date funds as an investment.
We apply parametric and non-parametric estimates to test market and style timing ability of individual German equity and bond mutual funds using a sample of over 500 equity and 350 bond funds, over the period 1990–2009. For equity funds, both approaches indicate no successful market timers in the 1990–1999 or 2000–2009 periods, but in 2000–2009 the non-parametric approach gives fewer unsuccessful market timers than the parametric approach. There is evidence of successful style timing using the parametric approach, and unsuccessful style timing, particularly in the 2000–2009 period. There is evidence of positive and negative bond timing in the 2000–2009 period.
A five-factor model directed at capturing the size, value, profitability, and investment patterns in average stock returns performs better than the three-factor model of Fama and French (FF, 1993). The five-factor model's main problem is its failure to capture the low average returns on small stocks whose returns behave like those of firms that invest a lot despite low profitability. The model's performance is not sensitive to the way its factors are defined. With the addition of profitability and investment factors, the value factor of the FF three-factor model becomes redundant for describing average returns in the sample we examine.
This article develops and applies new measures of portfolio performance which use benchmarks based on the characteristics of stocks held by the portfolios that are evaluated. Specifically, the benchmarks are constructed from the returns of 125 passive portfolios that are matched with stocks held in the evaluated portfolio on the basis of the market capitalization, book‐to‐market, and prior‐year return characteristics of those stocks. Based on these benchmarks, “Characteristic Timing” and “Characteristic Selectivity” measures are developed that detect, respectively, whether portfolio managers successfully time their portfolio weightings on these characteristics and whether managers can select stocks that outperform the average stock having the same characteristics. We apply these measures to a new database of mutual fund holdings covering over 2500 equity funds from 1975 to 1994. Our results show that mutual funds, particularly aggressive‐growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability.
This paper identifies five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors, related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates, the bond-market factors capture the common variation in bond returns. Most important, the five factors seem to explain average returns on stocks and bonds.
This article employs the 1975-84 quarterly holdings of a sample of mutual funds to construct an estimate of their gross returns. This sample, which is not subject to survivorship bias, is used in conjunction with a sample that contains the actual (net) returns of the mutual funds. In addition to allowing the authors to estimate the bias in measured performance that is due to the survival requirement and to estimate total transaction costs, the sample is used to test for the existence of abnormal performance. The tests indicate that the risk-adjusted gross returns of some funds were significantly positive. Copyright 1989 by the University of Chicago.
We examine the performance of "enhanced index" and "quantitative equity funds". Both types of funds use quantitative models in investment selection. Enhanced index funds set an explicit objective to outperform a benchmark index. Proponents of quantitative funds argue that their management style takes human emotions out of the investment decision-making process and leads to more objective stock selection. We find evidence of outperformance by quantitatively managed growth funds, especially those investing in small cap stocks. Copyright 2005 by the Eastern Finance Association.
Do enhanced index funds live up to their name?
- Chang E.
Enhanced index funds and tracking error optimization. University of California
- P Jorion
Market and style timing: German equity and bond funds
- K. Cuthbertson
- S. Hayley
- D. Nitzeche