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The article seeks to outline the requirements under the Investment Company Act of 1940 (the “Investment Company Act”), the Investment Advisers Act of 1940 (the “Advisers Act”) and related US Securities and Exchange Commission (the “SEC”) rules and interpretive guidance for structuring performance‐based fees for investment advisers and sub‐advisers to registered investment companies (or mutual funds).

The article discusses the appropriate structure and timing for performance fees and describes in detail how SEC standards for structuring performance fees have evolved over time. The article explains recent SEC enforcement actions against investment advisers for improperly structured performance fees, and notes that the use of performance fees has once again become a focus of SEC scrutiny.

The article concludes that, despite a common perception that performance fees create an effective incentive to improve fund performance by more closely aligning the interests of the adviser and fund shareholders than traditional fee arrangements, there is minimal empirical evidence proving that the use of performance fees translates into superior fund performance. Investment advisers who charge performance fees to mutual fund clients should consider reevaluating the structure and payment process for the performance fees in light of recent SEC scrutiny and enforcement actions, adviser compliance obligations under Rule 206(4)‐7 of the Advisers Act, and fund compliance obligations under Rule 38a‐1 of the Investment Company Act.

The article provides a concise overview of the regulatory requirements for structuring performance fees charged by mutual fund advisers.

Prior research has demonstrated that investment management performance fees have the characteristic of a call option. It is important to examine whether these performance fees are consistent with traditional fee structures used by investment managers. It is also worth examining whether clients or managers benefit significantly more than the other party under performance fee structures. The paper aims to discuss these issues.

The authors use Black-Scholes options pricing methodology to examine three cases of performance fee structures. The Absolute Hurdle case examines the fee structure where the manager receives a portion of the return over a pre-defined absolute rate of return. The Benchmark Relative Hurdle case shows a fee structure based on performance in excess of the return of a benchmark portfolio. The Breakeven Relative Hurdle case illustrates the fee structure where there is revenue neutrality with the classic management fees when portfolio performance matches the benchmark.

The findings of this paper illustrate that a particular performance fee structure can be designed to have the same revenue as a traditional investment management fee structure. Such a structure is equally beneficial to both the investment manager and to the client and should have salutary motivational effects to improve investment results, while simultaneously rewarding the manager for value added at a fair price for both the manager and the investor.

This study is unique in that it examines three cases of performance fees and provides a comparison between performance fee structures and traditional investment management fee structures. The findings will assist investment portfolio managers in better setting management fees they charge clients. In addition, this study help with clients who feel they are being charged excessive management fees by their investment manager.

The paper aims to investigate the performance determinants of European non-listed private equity real estate funds between 2001 and 2014.

Using a sample of 363 funds collected from the Inrev database, the analysis evaluated the impact of fees and other intrinsic characteristics of these funds, such as leverage, size and duration, on the funds’ performance, intending to enhance the understanding underlying their relationship.

The findings show a negative relationship between the return of the funds and redemption fee, performance fee and management fee. Conversely, marketing fees have a positive effect on performance. When analyzing the investment style, the results reveal inhomogeneous behaviors of leverage on funds’ performance. This variable has a positive impact on the return in core funds, while there is a negative relationship in value-added investments. Finally, the emphasis on the global financial crisis shows that the effects of the independent variables on the performance do not significantly change in different economic cycles.

The practical implication of the research is to understand whether an investor can direct its resources in a fund, leveraging on certain intrinsic characteristics that can be observed a priori.

Even if there is a considerable body of literature on determinants of performance in European non-listed real estate funds, little research has analyzed the role of fees in driving their results. Besides, this paper takes advantage of observations from different investment styles to emphasize the impact of higher or lower risk profiles and from the full economic cycle to understand the effects of the crisis period.

In prior work, GAO found that contractors were paid billions of dollars in award fees regardless of acquisition outcomes. In December 2007, the Office of Management and Budget (OMB) issued guidance aimed at improving the use of award fee contracts. GAO was asked to (1) identify agencies’ actions to revise or develop award fee policies and guidance to reflect OMB guidance, (2) assess the consistency of current practices with the new guidance, and (3) determine the extent agencies are collecting, analyzing, and sharing information on award fees. GAO reviewed the Departments of defense (DOD), Energy (DOE), Health and Human Services (HHS), and Homeland Security (DHS) and the National Aeronautics and Space Administration (NASA)-agencies that constituted over 95 percent of the dollars spent on award fee contracts in fiscal year 2008.

This paper aims to examine the performance and benchmark asset allocation policy of 70 KiwiSaver funds catergorised as growth, balanced or conservative over the period October 2007-June 2016. The study focuses on the sources for returns variability across time and returns variation among funds.

Each fund is benchmarked against a portfolio of eight indices representing eight invested asset classes. Three measures were used to examine the after-fee benchmark-adjusted performance of each fund: excess return, cumulative abnormal return and holding period returns difference. Tracking error and active share were used to capture manager’s benchmark deviation.

On average, funds underperform their respective benchmarks, with the mean quarterly excess return (after management fees) of −0.15 per cent (growth), −0.63 per cent (balanced) and −0.83 per cent (conservative). Benchmark returns variability, on average, explains 43-78 per cent of fund’s across-time returns variability, and this is primarily driven by fund’s exposures to global capital markets. Differences in benchmark policies, on average, account for 18.8-39.3 per cent of among-fund returns variation, while differences in fees and security selection may explain the rest. About 61 per cent of balanced and 47 per cent of Growth funds’ managers make selection bets against their benchmarks. There is no consistent evidence that more actively managed funds deliver higher after-fee risk-adjusted performance. Superior performance is often due to randomness.

This study makes use of a unique data set gathered directly from KiwiSaver managers and captures the long-term strategic asset allocation target which underlines the investment management process in reality. The study represents the first attempt to examine the impact of benchmark asset allocation policy on KiwiSaver fund’s returns variability across time and returns variation among funds.

The purpose of this paper is probe the early data emerging from the KiwiSaver market and to draw insights on KiwiSaver investor behaviour, particularly in respect of the unique default provider feature of the scheme.

The primary source of data for this study is a purpose-built database compiled using data from KiwiSaver providers’ annual reports for the period 2009-2011.

The study finds that KiwiSaver members, like other investors, are chasing performance and seeking to avoid fees. However, an unexpected negative relation is found for bank ownership.

The key limitations of this data source include the low frequency, differing formats and levels of detail disclosed in various annual reports.

Chasing past performance indicates a need for investor education for KiwiSaver members.

The study provides an initial empirical examination of the KiwiSaver market, and the determinants of the flow of funds and members. The results can be used to guide policymakers and providers in their future decision-making around the scheme and individual offerings.

Since the mid‐1990s, in a generally strongly performing property market, there has been huge growth in the aggregate size and number of global property funds in both listed and unlisted formats. Managers have been able to raise significant capital, which potentially rewards them with performance fees without necessarily being able to provide clear evidence of out‐performance against defined market benchmarks or performance targets. In a more challenging, mature and increasingly transparent market this is unlikely to continue to be the case as it will be increasingly possible to assemble performance records. The purpose of this paper is to describe the sources of risk and return within property funds and set out a more holistic performance attribution framework encompassing the concepts of alpha (out‐performance) and beta (risk), which traditional attribution frameworks in property fund management do not.

A four component risk and return attribution framework is put forward. The first two components are portfolio structure which measures the impact of allocations to more or less risky markets, and stock selection which considers more or less risky assets. Fund structure, measures the impact of financial leverage and fees and finally the return impact of timing is attributed to the movement of capital into and out of the fund.

A case study of a single unlisted fund has been used to compare traditional attribution results with an examination of alpha and beta return attribution. In this instance fund structure, which is largely the financial leverage impact, is found to be significant. This simply reflects extra risk taking and there is no clear evidence of manager out‐performance, yet significant performance fees are paid to the manager.

The paper provides a complete framework for the performance measurement and attribution of property funds, which enables investors to gain a fuller understanding of these increasingly used investment conduits.

The purpose of this paper is to examine the ability of well known fund characteristics such as the recent past performance, fund size, management fees, fund age, net asset value and fund growth so as to explain Tunisian equity mutual fund performance.

The sample was split according to investment objectives, and the advanced dynamic panel data approach was used over the period 1999‐2006.

The authors find that past performance and fund size have a positive and significant influence on future performance for all fund categories, irrespective of what performance measure was used. This may indicate the existence of scale economies in the Tunisian equity mutual fund industry. The author also find that the other fund characteristics play an important role in explaining performance, but their impact varies among the fund categories. In all, regression results support the dynamic links between fund characteristics and future performance.

The findings do not take into account the behaviour of fund managers and their ability to extend the investment opportunities set. It seems that there are more complex factors related to the strategic behaviour of the manager and driving differences in performance across funds than previous studies have indicated.

The authors confirm the empirical evidence that historical performance contains some information about future performance and such information may be important to mutual fund investors. It was also found that fund size is positively related to future performance of small fund category as well as of large fund category. This may indicate the existence of scale economies in the Tunisian equity mutual fund industry. In addition, the influence of the other control variables varies among the fund categories, but often is the same as in earlier studies.

The paper provides information to foreign investors for investing in Tunisian capital market.

In this regard, the study of literature revealed that the explanation of performance, based on quantitative factors, is often limited to a static approach that involves making estimates resting on multiple regression, regression in cross section and principal component analysis for short periods. However, several empirical studies highlight the impact of past performance on future performance. It seemed essential to enrich the analysis by using a dynamic approach.

The purpose of this paper is to analyze the effects of individual manager characteristics on real estate mutual fund (REMF) performance. Human capital theory predicts that factors like education, experience and professional certifications improve skill sets and thus performance. Conversely, capital markets theory suggests that these things may be irrelevant in the management of mutual funds.

A total of 63 REMFs were sampled over the period 2001‐2003 and equations were estimate regressing, alternatively, risk‐adjusted return, market risk and management fees on a series of fund variables and manager characteristics including the manager's tenure, whether the fund manager holds a professional certification, whether the manager has specific real estate experience, and whether the fund is team‐managed.

Modest evidence is found that team‐managed funds have lower risk‐adjusted returns than solo‐managed funds. Managers with longer tenure tend to pursue higher market risk levels, and there is no relation between manager characteristics and management fees.

This study considers only one cross‐sectional time period. Future research might use longitudinal data.

Despite real estate being a specialized field of finance, there is little if any support for the predictions of human capital theory that experience, education and training result in greater performance among managers of REMFs.

This paper extends prior work in mutual fund management characteristics and fund performance to real estate funds.

COVID-19 induced uncertainty in the firms’ business transactions, financial markets and product-market competition, causing a severe organizational legitimacy crisis. Using the organizational legitimacy perspective and agency theory, this paper aims to study the relationship between prior corporate social responsibility (CSR) activities, monitoring cost (MC) and firm performance.

This study uses a quarterly panel (16,924 firm-quarter observations from 61 countries for CSR and 53,345 firm-quarter observations from 55 countries for MC) for 14 quarters from January 2018 to June 2021. This study uses panel fixed-effect regression models to estimate the effect of CSR activities and MC (measured as audit fees) on firm performance during the COVID-19 period.

This study finds a U-shaped relationship between CSR and firm performance. This relationship is strengthened during COVID-19. In contrast, this study finds an inverted U-shaped relationship between firm MC and firm performance. However, this relationship is weakened during the pandemic.

This study contributes to theory and practice on maintaining organizational legitimacy and reducing agency costs during the pandemic. This study shows that firms’ prior legitimacy-gaining practices, such as CSR activities and MC, provide an opportunity to increase firm value. To balance agency costs and legitimacy benefits, firm managers also need to identify the optimal level of CSR activities and MC.