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It was early 2015 and executives in iShares' Factor Strategies Group were considering the launch of a new class of exchange-traded funds (ETFs) called smart beta funds. Specifically, the group was considering smart beta multifactor ETFs that would provide investors with simultaneous exposure to four fundamental factors that had shown themselves historically to be significant in driving stock returns: the stock market value of a firm, the relative value of a firm's financial position, the quality of a firm's financial position, and the momentum of a firm's stock price. The executives at iShares were unsure whether there would be demand in the marketplace for such multifactor ETFs, since their value added from an investor's portfolio perspective was unknown. Students will act as researchers for iShares' Factor Strategies Group and conduct detailed analysis of Fama and French's five-factor model and the momentum effect, smart beta ETFs including multifactor ETFs, and factor investing with smart beta ETFs to help iShares make its decision.

The portfolio of low-risk stocks outperforms the portfolio of high-risk stocks and market portfolios on a risk-adjusted basis. This phenomenon is called the low-risk effect. There are several economic and behavioral explanations for the existence and persistence of such an effect. However, it is still unclear whether specific sector orientation drives the low-risk effect. The study seeks to answer the following important questions in Indian equity markets: (a) Whether sector bets or stock bets mainly drive the low-risk effect? (b) Is it a mere proxy for the well-known value effect? (c) Does the low-risk effect prevail in long-only portfolios?

The study is based on all the listed stocks on the National Stock Exchange (NSE) of India from December 1994 to September 2018. It classifies them into 11 Global Industry Classification Standard (GICS) sectors to construct stock-level and sector-level BAB (Betting Against Beta) and long-only low-risk portfolios. It follows the study of Asness et al. (2014) to construct various BAB portfolios. It applies Fama–French (FF) three-factor and Fama–French–Carhart (FFC) four-factor asset pricing models in addition to Capital Asset Pricing Model (CAPM) to examine the strength of BAB, sector-level BAB, stock-level BAB and long-only low-beta portfolios.

Both sector- and stock-level bets contribute to the return of the low-risk investing strategy, but the stock-level effect is dominant. Only betting on safe sectors or industries will not earn economically significant alpha. The low-risk effect is unique and not a value effect in disguise. Both long-short and long-only portfolios within sectors and industry groups deliver positive excess returns. Consumer staples, financial, materials and healthcare sectors mainly contribute to the returns of the low-risk effect in India. This study offers empirical evidence against the Samuelson (1998) micro-efficient market given the strong performance of the stock-level low-risk effect.

The superior performance of the low-risk investment strategies at both stock and sector levels offers investors an opportunity to strategically invest in stocks from the right sectors and earn high risk-adjusted returns with lower drawdowns over an entire market cycle. Besides, it paves the way for stock exchanges and index manufacturers to launch sector-specific low-volatility indices for relevant sectors. Passive funds can launch index funds and exchange-traded funds by tracking these indices. Active fund managers can espouse sector-specific low-risk investment strategies based on the results of this and similar other studies.

The study is the first of its kind. It offers insights into the portfolio characteristics and performance of the long-short and the long-only variant of low-risk portfolios within sectors and industry groups. It decomposes the low-risk effect into sector-level and stock-level effects.

The purpose of this paper is to examine the relative effects of rational and quasi-rational sentiments of individual and institutional investors on a set of smart beta fund returns. The magnitudes of the impacts of institutional investor sentiments are greater than those of individual investor sentiments. In addition, both rational and quasi-rational sentiments of individual and institutional investors have significant impacts on smart beta fund returns. The magnitudes of the impacts of quasi-rational sentiments are greater than those of the rational sentiments for both types of investors (quasi-rational sentiments of institutional investors have the maximum impact). These results are consistent with the arguments that professional investors consider the sentiments of individual investors as contrarian leading indicators which are mainly driven by noise while conform the sentiments of institutional investors which are driven by more rational factors. A majority of smart beta funds in the sample outperform the S&P500 returns in the short term but fail to consistently beat the market. The authors find evidence that smart beta funds with consistently high returns are relatively less (more) driven by individual (institutional) investor sentiments. Overall, the authors argue that smart beta funds appear to follow quasi-rational sentiments of both individual and institutional investors that are not rooted in economic fundamentals.

The results of the impulse functions generated from a multivariate model suggest that the smart beta fund returns are negatively (positively) impacted by individual (institutional) investor sentiments.

The magnitudes of the impacts of institutional investor sentiments are greater than those of individual investor sentiments. In addition, both rational and quasi-rational sentiments of individual and institutional investors have significant impacts on smart beta fund returns. The magnitudes of the impacts of quasi-rational sentiments are greater than those of the rational sentiments for both types of investors (quasi-rational sentiments of institutional investors have the maximum impact).

These results are consistent with the arguments that professional investors consider the sentiments of individual investors as contrarian leading indicators which are mainly driven by noise while conform the sentiments of institutional investors which are driven by more rational factors. A majority of smart beta funds in the sample outperform the S&P500 returns in the short term but fail to consistently beat the market. The authors find evidence that smart beta funds with consistently high returns are relatively less (more) driven by individual (institutional) investor sentiments. Overall, the authors argue that smart beta funds appear to follow quasi-rational sentiments of both individual and institutional investors that are not rooted in economic fundamentals.

The purpose of this paper is to study if actively managed exchange-traded funds (AMETFs) and actively managed mutual funds (AMMFs) are complements or substitutes. It also tests if there are tax or liquidity clientele effects.

The study investigates the relation between individual AMMF flows and aggregate AMETF flows as well as individual AMETF flows and aggregate AMMF flows. A 2013 tax change is used to analyze if a tax clientele effect exists between the AMETF and AMMF markets. The authors use differences in investor groups for institutional vs retail fund share classes to test for liquidity clientele effects.

The authors find that equity and mixed AMETFs and AMMFs are substitutes, although not perfect substitutes. Taxation-related differences between the two products create a clientele effect for fixed income and mixed funds where tax-sensitive investors are more likely to substitute AMETFs for AMMFs surrounding tax increases. There is weak evidence that institutional investors may prefer AMETFs more than retail investors because of their enhanced liquidity.

This is the first study to investigate the flow relation between AMETFs and AMMFs. The fast-paced growth of the AMETF area coupled with the substitutability between the two products and tax advantages of AMETFs has the capability to gain significant market share from AMMFs in the future.

This paper aims to examine the impact of the return differential between the domestic and foreign markets on the risk exposure of country mutual funds (CMFs). It is argued that when US market returns are higher than the foreign market returns, the returns chasing investors will tilt their portfolio toward the US market assets, increasing the co-movement between the US market and CMF return.

The sample includes 19 exchange traded funds (ETFs) and 18 closed-end mutual funds (CEFs) over the period between 2001 and 2011. A static two-factor model is used to get the benchmark results. On the other hand, a conditional specification is used, with the return differential as the information variable, to capture the variation in the exposure of the country funds to their underlying risks.

Empirically, the authors find results that partially support their argument. The results of the static two-factor model indicate that the CMFs are exposed to the foreign market risks, whereas the local (US) market risk is not generally priced. The results obtained from the conditional specification, however, shows that the estimated US betas are significant for a number of CMFs.

A possible interpretation of this finding is that the return differential encourages return chasing behavior of the US investors documented in the international investment literature. This, in turn, may contribute to the time-varying exposure of the CMF return to their underlying risk factors. The findings of the paper have important implications for the investors as the time variation in risk exposure of CMFs causes fluctuation in diversification benefits over time.

To the best of the authors’ knowledge, this is the first paper that uses return differential as the information variable in a conditional factor model.

The purpose of this paper is to outline the problems encountered by a student-managed investment program (SMIP) when the pool of qualified finance majors is limited in number. Restructuring the program to a single-semester course and opening the class to motivated/intelligent non-finance majors increased the number of applicants, but resulted in alternative difficulties, particularly time constraints and inadequate student preparedness. A prerequisite exam and regimented classroom structure were the solutions.

The paper discusses the problems encountered and solutions devised to address the early year difficulties experienced by a newly developed SMIP at a relatively small university. The core of the paper chronicles the classroom approach to solving the main problem of a single-semester portfolio management course, the handling of an investment learning curve in a short period of time.

Though empirically limited due to the program’s infancy, portfolio performance has been encouraging and student feedback exceptional. Regarding the former, stocks purchased by the fund have created greater wealth in total than that of equal dollar investments in an S&P500 index fund.

Universities interested in running a student-managed fund should feel secure in a one-semester approach, regardless of talent pool size, as measured by the number of motivated, intelligent finance majors.

Aside from the uniqueness of requiring a mastery of entrance exam investing materials prior to the first class, this paper’s outline of core portfolio management activities includes several strategies and methods meant to streamline the process within a groupthink design.

This study aims to examine style-deviation practices in the socially responsible mutual funds (SMRF) industry i.e. how mutual funds game their stated financial objectives to earn a higher relative performance ranking. In addition, the consequences of such practices on sustainable scores and money flows are studied.

A sample of 454 US equity SRMFs is studied. This paper uses panel regressions controlling for time and style fixed-effects.

This study finds that 17.60% of SRMF managers in the sample are engaged in style deviation practices. These practices positively impact the sustainable performance of SRMFs and negatively impact their financial performance. One effect offsets the other and they consequently do not affect money flows. Another finding is that only investors with lower portfolio sustainability scores do show return-chaser behaviour.

This paper reveals that SRMF managers deviating from their stated financial style face a dilemma that is non-existent for their conventional peers that is style deviation practices affect financial and sustainable performance in opposing ways, whereas SRMF investor utility depends positively on both dimensions. The findings are not conclusive about the effectiveness of style deviation practices in attracting SRMF money flows.

SRMF industry has experienced tremendous growth in the past decade. The increased competition in this industry has led managers to strive to attract investors, sometimes by relying on irregular practices that enhance their portfolio results. Regulators should consider how to avoid such perverse behaviour with a view to improving mutual funds transparency.

This is the first research that analyses style deviation practices and their consequences for the SRMF industry.