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This paper aims to analyze the portfolio characteristics and the performance measures of sustainability-themed mutual funds, compared to ethical mutual funds that implement different sustainable and responsible investment strategies.

The study refers to a European sample of 106 ethical funds and 51 sustainability-themed funds. The monthly performance of each fund is downloaded from Bloomberg for the period from January 1996 to December 2015. By applying a Fama and French (1993) three-factor model, the authors overcome the limits of a capital asset pricing model (CAPM) based-single index model, to compare the performance of the two categories of funds.

Sustainability-themed funds do not differ significantly from ethical funds in terms of portfolio attributes, except for market capitalization, age and net asset value. Regarding performance measures, the results shows that sustainability-themed funds have a lower underperformance than ethical funds (as measured by Jensen’s alpha), whereas the samples do not differ in terms of market risk (as measured by Beta coefficient). The idiosyncratic risk of sustainability-themed funds is positively influenced by the specific portfolio strategies. The sustainability-themed funds show a higher concentration in the industrial sector and a lower exposure to financial sector than ethical funds; in terms of geographical strategy, they are more global and international oriented; they mainly focus on small caps and value stocks.

The different sustainable and responsible investment strategies can be applied simultaneously and in a growing number of possible combinations. Mutual fund managers can consider thematic approach as an efficient opportunity for reconciling financial performance and economic sustainability. It is demonstrated that sustainability-themed funds adopt a portfolio strategy significantly different from ethical funds and from the environmental, social and governance benchmarks. Mutual fund managers implement a thematic specialization without any negative impact on the funds returns compared to ethical funds; actually, with a proper diversified portfolio, they are able to reduce idiosyncratic risk.

The analysis is extremely innovative, especially for the thematic sample. During the past 15 years, literature about sustainable and responsible investment has been focused especially on the differences in terms of risk and performance between socially responsible and conventional funds. This paper, starting from the methodology applied in these studies, wants to compare two different types of socially responsible strategies, with a specific focus on sustainability-themed mutual funds, given their exponential growth in the past few years.

This paper examines the market timing ability of a sample of 62 Australian International equity funds using the returns‐based approach of Henriksson and Merton (1981) (H&M) and Treynor and Mazuy (1966) (T&M). Specifically, the primary focus is to investigate whether market timing ability bears any relationship to the stated fund allocation policy. Generally, the results indicate that fund managers do not successfully time the market. We also find that there is no relationship between the manager's stated level of activity on allocation and their market timing abilities as calculated using the H&M and T&M models. Managers are not successfully implementing their stated policies. These results are consistent with an irrelevance of perceived management style to fund policies and hence performance. Furthermore, it is indicative that fund managers are not successfully targeting particular classes of risk averse investors.

The purpose of this paper is to present a discrete quantitative trading strategy to directly control a portfolio's maximum percentage of drawdown losses while trying to maximize the portfolio's long‐term growth rate.

The loss control target is defined through a Rolling Economic Drawdown (REDD) with a constant look‐back time window. The authors specify risk aversion in the power‐law portfolio wealth utility function as the complement of maximum percentage loss limit and assume long‐term stable Sharpe ratios for asset class indexes while updating volatility estimation in dynamic asset allocation implementation.

Over a test period of the past 20 years (1992‐2011), a risk‐based out‐of‐sample dynamic asset allocation among three broad based indexes (equity, fixed income and commodities) and a risk free asset, is robust against variations in capital market expectation inputs, and out‐performs the in‐the‐sample calibrated model and traditional asset allocation significantly.

The current proposal can lead to a new mathematical framework for portfolio selection. Besides investors' liquidity and behavioural constraints, macroeconomic and market cycle, and the potential of central bank interventions following a market crash, could be additionally considered for a more rigorous dynamic asset allocation model.

Besides the benefit of a clear mandate to construct suitable client portfolios, the portfolio approach can be applied to design invest‐able securities, such as principal‐guaranteed investment products, target risk asset allocation ETFs, and target‐date mutual funds with a glide path, etc. The formulation can also be implemented as a managed futures hedge fund portfolio.

The paper introduces the Rolling Economic Drawdown (REDD) concept and specifies risk aversion as the floor of maximum percentage loss tolerance. Dynamic asset allocation is implemented through updating estimation of asset class volatilities.

Prior research has documented inconclusive and/or mixed empirical evidence on the timing performance of hybrid funds. Their performance inferences generally do not efficiently control for fixed-income exposure, conditioning information, and cross-correlations in fund returns. This study examines the stock and bond timing performances of hybrid funds while controlling and accounting for these important issues. It also discusses the inferential implications of using alternative bootstrap resampling approaches.

We examine the stock and bond timing performances of hybrid funds using (un)conditional multi-factor benchmark models with robust estimation inferences. We also rely on the block bootstrap method to account for cross-correlations in fund returns and to separate the effects of luck or sampling variation from manager skill.

We find that the timing performance of portfolios of funds is neutral and sensitive to controlling for fixed-income exposures and choice of the timing measurement model. The block-bootstrap analyses of funds in the tails of the distributions of stock timing performances suggest that sampling variation explains the underperformance of extreme left tail funds and confirms the good and bad luck in the bond timing management of tail funds. We report inference changes based on whether the Kosowski et al. or the Fama and French bootstrap approach is used.

This study provides extensive and robust evidence on the stock and bond timing performances of hybrid funds and their sensitivity based on (un)conditional linear multi-factor benchmark models. It examines the timing performances in the extreme tails funds using the block bootstrap method to efficiently identify (un)skilled fund managers. It also highlights the sensitivity of inferences to the choice of testing methodology.

Wrap fee programs are an increasingly popular product offered by broker‐dealers and investment managers to their clients. Wrap fee programs present unique issues under both the Investment Company Act of 1940 (“Investment Company Act”) and the Investment Advisers Act of 1940 (“Advisers Act”), the two primary bodies of law that govern the product and those who offer and manage it. The regulations and rules under those Acts applicable to wrap fee programs and related interpretive statements made by the SEC staff, however, are wide ranging and have not been provided in a single format. This article attempts to present a comprehensive discussion on the regulation of wrap fee programs, as well as the many compliance issues associated with these programs. The article is delivered in two parts. Part I, presented in this issue, addresses the regulation of wrap fee programs under the Investment Company Act. Part I also begins a review of unique issues arising under the Advisers Act, including registration requirements for wrap fee sponsors and other persons who manage or offer the product to their clients, as well as required contents for wrap fee brochures and related disclosure issues. Part II, which will be presented in the next issue, will discuss additional Advisers Act issues such as suitability, fees and advertising. It also will briefly review issues arising under the Securities Exchange Act of 1934 (“Exchange Act”) and the Employee Retirement Income Security Act of 1974 (“ERISA”).

Part I of this series appeared in the Summer 2002 issue of The Journal of Investment Compliance. It addressed the regulation of wrap fee programs under the Investment Company Act of 1940 (“Investment Company Act”) and the requirements of Rule 3a‐4 thereunder, which must be met so that a wrap fee program is not deemed to be an investment company. Part I also discussed certain issues arising under the Investment Advisers Act of 1940 (“Advisers Act”), including how program sponsors and any third‐party portfolio managers generally are viewed as investment advisers and are subject to the Advisers Act. Part II discusses additional Advisers Act issues such as suitability, fees, and advertising. It also briefly reviews issues arising under the Securities Exchange Act of 1934 (“Exchange Act”) and the Employee Retirement Income Security Act of 1974 (“ERISA”). The information provided in Part II assumes that readers have some basic familiarity with Part I.

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 purpose of this paper is to study the scope for country diversification in international portfolios of mutual funds for the “core” EMU countries. The author uses a sample of daily returns for country indices of French, German and Italian funds to investigate the quest for international diversification. The author focuses on fixed-income mutual funds during the period of the financial market turmoil since 2007.

The author compute optimal portfolio allocations from both unconstrained and constrained mean-variance frameworks that take as input the out-of-sample forecasts for the conditional mean, volatility and correlation of country-level indices for funds returns. The author also applies a portfolio allocation model based on utility maximization with learning about the time-varying conditional moments. The author compares the out-of-sample forecasting performance of 12 multivariate volatility models.

The author finds that there is a “core” EMU country also for the mutual fund industry: optimal portfolios allocate the largest portfolio weight to German funds, with Italian funds assigned a lower weight in comparison to French funds. This result is remarkably robust across competing forecasting models and optimal allocation strategies. It is also consistent with the findings from a utility-maximization model that incorporates learning about time-varying conditional moments.

This is the first study on optimal country-level diversification for a mutual fund investor focused on European countries in the fixed-income space for the turmoil period. The author uses a large array of econometric models that captures the salient features of a period characterized by large changes in volatility and correlation, and compare the performance of different optimal asset allocation models.

The purpose of this paper is to examine the value of active fund management using a sample of hybrid mutual funds.

Instead of using traditional risk‐adjusted measures, the paper employs an alternative attribution return methodology where the actual monthly fund return is compared to the return that would have been earned by the indexing strategy that best reflects the fund's prior month allocation. Value is measured by defining a fund's attribution return as the difference between a fund's actual month t return and the return that would have been generated in month t by the indexing strategy that most closely approximates the fund's month t−1 portfolio allocation.

It is found that hybrid funds as a group do not add value and that this underperformance does not appear to be driven by the poor performance of non‐surviving funds. However, these funds perform significantly better than the style benchmark under weak vs strong stock market conditions. This performance difference between bull and bear market conditions suggests some hedge fund‐like downside protection that may offer a reason why investors choose these funds despite the funds’ average underperformance and despite their higher costs relative to index funds.

The contribution of this paper is twofold. First, it concentrates on hybrid mutual funds, which despite a surge in their interest over the last five years have attracted very little academic study. Second, in the implementation of its non‐traditional performance measure, it employed daily fund returns, stock market indices and bond market indices as opposed to the monthly or quarterly data used in other related studies.

The purpose of this study is to measure mutual funds' manager performance by attributing it to their abilities to choose better securities (selectivity effect) and to allocate these securities better than their benchmarks (allocation effect). The study enables the authors to examine the relative contributions of the commonly known asset-pricing factors in mutual funds' performance.

To examine managers' ability to steer funds' returns, the authors conduct a two-dimensional holdings-based analysis using factor-specific decomposition of funds' excess returns into their ability to select and allocate securities better than their benchmarks. Subsequently, the authors conduct an analysis of the covariance (ANCOVA) due to these factors in explaining funds' excess returns over time.

While managers' ability to choose better securities than the benchmarks (the selectivity effect) appears modest, some funds (especially the winners) allocate securities in their portfolios better than their benchmarks (the allocation effect) based on their exposures to certain factors (e.g. the momentum factor for the winner funds). However, although funds consistently gain through their ability to predict the size and value factors well, they do not consistently possess the skills to predict the momentum factor.

Although the paper analyzes all the available diversified funds, the sample excludes several other categories, such as thematic and international funds. Further, the analysis is based on equity-oriented Indian funds. Broader studies of changes in factor exposures and the inclusion of more factors apart from those conventionally used may shed more light on the managers' ability to maneuver these factors.

The results show that mutual fund managers lack persistence in their performance, even though some of them could predict specific factors well. Since the activity in active mutual funds could not lead to superior performance over time, investors could be better off by selecting cheaper passive funds for their long-term investments.

The paper presents a novel approach to studying funds' performance by conducting a two-dimensional holdings-based analysis to capture the relative contributions of common asset-pricing factors in the cross-section as well as over time.