Benchmark Returns Research Articles

Estimating Long-Term Expected Returns

Estimating long-term expected returns as accurately as possible is of critical importance. Researchers typically base their estimates on yield and growth, valuation, or a combined yield, growth, and valuation (“three-component”) framework. We run a horse race of the abilities of different frameworks and input proxies within each framework to estimate 10- and 20-year out-of-sample returns. The three-component model based on the TRCAPE valuation proxy outperforms estimates based on historical mean benchmark returns, with mean square error improvements exceeding 30%. Using this approach in asset allocation decisions results in an improvement in Sharpe ratios of more than 50%.

Portfolio Optimization Strategy Based on Four Deep Learning Models

Deep learning techniques have provided a fresh outlook on the evergreen subject of portfolio optimization within the finance domain. This article selects the stocks of Google, Tesla, Tractor Supply Company, Analog Devices, and Duke Energy Corporation and deploys four deep learning models to estimate returns and covariance respectively. The mean-variance model is utilized to generate the target portfolio for each deep learning model, incorporating the predicted outcomes. Ultimately, the returns of each portfolio are compared to the market benchmark (S&P 500) returns. The findings demonstrate that the proposed target model outperforms the market benchmark (S&P 500) across multiple financial metrics. This study highlights the groundbreaking and promising applications of deep learning in the financial sector, providing valuable insights into innovative portfolio allocation strategies for risk-averse investors who aim to achieve stable and positive returns even in turbulent market conditions.

Management of the Pension Fund in Korea: Sharpe Ratio as a Measurement

Purpose: This study criticizes the existing benchmarks of the national equity fund specified by the National Pension Service and proposes alternative benchmarks.
 Design/methodology/approach: First, this study investigates whether the existing benchmarks returns are affected by the value and momentum factors. Second, we examine the effects of different factors on the benchmark returns of internal and outsourcing investments. Third, we propose three benchmarks by including the value factor and/or momentum factor. Finally, the Sharpe ratios of return-to-risk are used to measure these proposed benchmarks compared to the existing benchmarks.
 Findings: First, the existing benchmarks of internal and outsourcing investments are associated with value and momentum factors, which have been observed in many other countries. Second, the Sharpe ratios of the three proposed benchmarks - value oriented, momentum oriented, and value & momentum oriented - are always better than the existing benchmarks. Third, the Sharpe ratio of the value oriented benchmark is better than that of the momentum oriented and value & momentum oriented benchmarks. Finally, the Sharpe ratios are better with increased investment weights of value and/or momentum.
 Research limitations/implications: This study uses the Sharpe ratio to measure the return-to-risk relationship. There could be other measures to capture the relationship.
 Originality/value: This is the first research to analyze the national pension equity fund with proposed benchmarks in the Korean market.

Investor gambling preferences and stock returns: evidence from the Shanghai A-share markets

PurposeThis study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.Design/methodology/approachThis study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.FindingsThe study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.Research limitations/implicationsThis research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.Practical implicationsThis study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.Originality/valueThis study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

HOW CORPORATE PENSIONS AFFECT STOCK RETURNS: THE ROLE OF R&D EXPENDITURES

We examine the stock return implications of corporate-defined benefit pension plans in innovative U.S. firms and in R&D- and patent-sorted portfolio specifications. We find that investors underreact to firms increasing off-balance-sheet liabilities. Pensions represent material off-balance-sheet liabilities: in our extensive and large sample (1985–2017, 2541 firms for 26,522 observations), entities with pension plans are 38% more levered when we integrate pension liabilities and assets into the firms’ capital structure. We find that R&D-intensive firms increasing the size of their pension liability subsequently underperform their benchmark returns. Through six alternative R&D-market capitalization portfolios, we also find that this association is stronger for smaller firms. Finally, the relationship remains persistent over a long horizon. These findings are robust to endogeneity concerns addressed through instrumental variables, propensity score matching, and Heckman correction.

Impact of Financial Benchmarks Upon the Portfolio Distribution of Mutual Funds: The Evidence from Turkish Capital Market

The purpose of the study is to examine how financial benchmark returns impact the portfolio distribution of mutual funds. The scope of paper is limited to Turkish mutual funds market. Method employed in the paper; Granger Causality Test based on the VAR model is used. Findings of the quantitative analysis: As the return on government debt securities (index) inclines, the demand on Government Domestic Debt Securities goes up, and then, weight of government debt securities increases in consolidated portfolio of mutual funds. The paper concludes that for bonds, benchmark returns are effective on portfolio distribution of mutual funds.

A New Portfolio Optimization Model Under Tracking-Error Constraint with Linear Uncertainty Distributions.

Enhanced index tracking problem is the issue of selecting a tracking portfolio to outperform the benchmark return with a minimum tracking error. In this paper, we address the enhanced index tracking problem based on uncertainty theory where stock returns are treated as uncertain variables instead of random variables. First, we propose a nonlinear uncertain optimization model, i.e., uncertain mean-absolute downside deviation enhanced index tracking model. Then, we give the analytical solution of the proposed optimization model when stock returns take linear uncertainty distributions. Based on the solution, we find that tracking portfolio frontier is a continuous curve composed of at most n-1 different line segments. Furthermore, we give the condition that tracking portfolio return and risk increase with benchmark return and risk, respectively. Finally, we offer some experiments and show that our proposed model is effective in controlling the tracking error.

기관투자자의 적정 기준수익률 설정 연구

This study aims to reset the effective base return through the analysis of the return on investment by asset group of investment institutions centered on the Fiscal Mutual Aid Association. Since the benchmark return is the basis for the performance evaluation of the asset management results of investment institutions, proper benchmark setting has the effect of maximizing the asset management return. In order to find out whether the benchmark setting of these investment institutions is set to be effective, we can compare the resultsof the benchmark before the change with the results of the standard return analysis after the change. In conclusion, it was analyzed that the pension investment pool MMF was more effective than the MMI operating return as a benchmark for short-term funds, and the weighted average (operating weight) was more effective than the KOSPI and MSCI ACWI weighted average (target ratio).

Understanding leveraged ETFs’ compounding effect

PurposePrior literature has shown that, theoretically, holding-period returns of a leveraged exchange-traded fund (LETF) are generally negatively affected by the volatility of the underlying benchmark’s daily returns, particularly for long holding periods. However, recent empirical studies simulate LETFs’ returns using historical benchmark returns and report results that are not entirely consistent with the theoretical predictions, leading to the possibility that the distribution of real-world returns may have certain characteristics that influence the outcomes. In this paper, the authors examine how asymmetric volatility affects LETFs’ performance and provide detailed explanations for the behavior of the performance of LETFs under different market conditions.Design/methodology/approachThe authors conduct simulation analyses on a +3x LETF and a −3x LETF based on historical S&P 500 stock index returns, with asymmetric volatility incorporated into the model.FindingsBy incorporating the asymmetric volatility effect, the simulation results suggest that, contrary to the theoretical predictions, higher volatility does not always lead to more negative impact on LETFs’ performance. Rather, the performance depends on the market conditions under which high volatility occurs. The findings therefore help reconcile prior theoretical predictions with reported empirical findings.Originality/valueThe analysis adds to the literature by incorporating the asymmetric volatility effect of stock returns in studying LETFs’ performance. The authors also provide detailed explanations for the behavior of LETFs’ returns and compounding effect under different market conditions, thus providing contexts to prior empirical results.

A STUDY OF MUTUAL FUND ACCOUNTING IN PERSPECTIVE OF BUILDING NATION

Mutual Fund is a fund establishment in the form of a trust to raise money through the sale of units to the public or a section of the public under one or more schemes for investing in securities, including money market instrument. The investors want to know about the present and past performance of the selected mutual funds. This information must be supported by certied documents. The system of accounting for Mutual Fund is different from conventional system of accounting which is followed in industrial sectors. Hence, only proper accounting for mutual funds can show the real picture of risk and return of a specic mutual fund. An investor may compare accounting information relating to a mutual fund with its benchmark return. He can do the comparison with condence on the basis of audited report of a particular fund. Moreover proper system of mutual fund accounting leads the fund manager to minimize cost

HEDGE FUND STRATEGIES: PERFORMANCE, RISK AND DIVERSIFICATION OPPORTUNITIES / Hedge Fon Stratejileri: Performans, Risk Ve Çeşitlendirme Fırsatları

This study aimed at comparing the performances of distinct hedge fund strategies and assessing the diversification opportunities using hedge funds. This paper analyses the overall performance of distinct hedge fund strategies (as indices) for the period of 2001-2020. Hedge fund performances are compared using alternative risk adjusted performance metrics; first, alpha based on four asset-pricing models (CAPM, Fama-French 3 factor, Carhart and Fama-French 5 factor models); then, the Sharpe ratio. The findings of the study revealed that almost all hedge fund strategies outperform the benchmark return (MSCI World Index) and are superior in terms of risk/return measures. The alternative risk metrics used in the calculation of risk-adjusted performances did not cause a dramatic change in the rank ordering of the hedge fund strategies.

Portfolio Management Services in India: Returns and Incentives

On the back of booming equity markets and falling interest rates, Indian high net worth investors have flocked to Portfolio Management Services (PMS) funds in India with substantial assets under management of INR 18,07,939 crores. However, there is scant academic literature on the performance of PMS funds in India which charge high fees compared to passive index funds. The purpose of this study is twofold. First, describe the performance of PMS funds in India as compared to their respective benchmark. Secondly, review the incentives fees structure of PMS funds and recommend regulatory changes needed to address the shortcomings. The principal results indicate that majority of PMS funds have failed to outperform the benchmark in the short-term and medium-term periods. In the long-term period, however, largely PMS funds have beaten the benchmark returns. The implications of this study are two-fold in the Indian market context. First, high net worth individuals in India must invest via PMS funds only if their investment time horizon is at least ten years. For the short to medium-term, it will be better to invest in index funds due to their meager expense ratio and returns, which are like the benchmark indices. Second, Indian policymakers must increase the minimum hurdle rate based on which the variable performance fee is charged to ensure portfolio managers are rewarded if they generate abnormal risk-adjusted returns. This study contributes to academic literature by focusing on the performance and incentives of PMS funds market in India, which is largely unexplored till now.

Predicting the Global Minimum Variance Portfolio

We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP) for the conditional covariance matrix of asset returns. The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss function from which we can infer the GMVP weights without imposing any distributional assumptions on the returns. In order to capture time variation in the returns’ conditional covariance structure, we model the portfolio weights through a recursive least squares (RLS) scheme as well as by generalized autoregressive score (GAS) type dynamics. Sparse parameterizations and targeting toward the weights of the equally weighted portfolio ensure scalability with respect to the number of assets. We apply these models to daily stock returns, and find that they perform well compared to existing static and dynamic approaches in terms of both the expected loss and unconditional portfolio variance.

Operational risk, market risk and value of the asset managers

Asset management has been one of the fastest-growing industries in the financial industry for a long time (Bigelli & Manuzzi, 2019). Moreover, after the eruption of the financial turmoil in 2008, financial intermediation has been characterized by a rapid increase in the role of the asset management industry. This paper aims to analyse the determinants of asset manager value and, in particular, it is focused on the value implicit in the assets under management. Starting from the works by Huberman (2005) and Joenväärä and Scherer (2017) the paper proposes a model for determining the enterprise value (EV) of asset managers by assessing the role of the contribution margin and the degree of risk (operational and market risk). As noted by Scherer (2008), following the financial crisis, asset management companies suffered a decline in profits, also due to the exposure of their revenues to the market risk. Although, as it’s known, the asset management firms are not directly subject to the market (and credit) risk, their revenues are exposed to the market risk, not only to the operational risk that had been thought of as the main risk factor (Hull, 2007). Management companies, in fact, operate in a cyclical context closely linked to the performance of the financial markets, which contributes to determining the size and volatility of the assets under management (AuM). Starting from a discounted cash flow (DCF) asset side model, a simple stochastic Monte Carlo simulation is provided in order to capture the relevance of the asset under management return and volatility and, therefore, the volatility of the benchmark return and management style. In this theoretical framework, the key point is that the enterprise value depends on the specific asset class the firm is involved with. Given the asset class, the enterprise value depends on the management style also.

Mutual fund manager turnover: an empirical investigation of performance

PurposeWhen a fund manager leaves, the investment strategy of the fund changes or remains the same. The departing fund manager's resignation is either forced or voluntary. The study investigates the relationship between the portfolio manager's transition and the fund's investment strategy and how the change affects the mutual fund returns in the subsequent period.Design/methodology/approachThe authors examine 148 fund manager changes in India between April 2005–March 2018 using three performance measures: abnormal return (fund return minus benchmark return), Jensen's alpha and Carhart four-factor alpha. The analysis includes an event study methodology, followed by a two-step Fama–MacBeth regression approach.FindingsContrary to the previous studies conducted in the developed markets, the authors find that fund performance improves irrespective of whether the fund manager change is forced or voluntary. The outperformance after the fund manager's exit is significant for funds belonging to the larger fund families.Originality/valueIn the context of investment management, the authors provide a conceptual framework to understand the effect of fund manager exit on mutual fund performance. The authors substantiate their arguments with empirical evidence. To the best of the authors' understanding, this is the first research to examine the effect of changing mutual fund managers in an emerging market setting.

An Analysis of the Performance of Target Date Funds

This article presents a thorough evaluation of target date funds (TDFs) for the period 2010–2020. TDFs have grown enormously in assets, reaching $1.4 trillion at the end of 2019, and account for approximately 24% of all assets in 401(k) accounts. We report on the results of a style analysis evaluation of TDFs that determines their effective asset allocation. It examines both the constant in the style analysis regressions and resulting Sharpe ratios, which reflect the over- or under-performance of the funds relative to a passive benchmark with the same asset allocation. Lower cost TDFs tend to match the benchmark returns, while higher cost TDFs deviate from them considerably. We examine how TDFs performed in the stock market crash between February 19 and March 23, 2020, during which five-week period broad market averages fell by about one-third. We find that the value of long-dated TDFs (those with a target date of 2045 and beyond) fell by between 30% and 35%, while the 2025 funds, designed for people roughly 60 years old, lost between 20% and 25% of their value. We find that past performance only weakly influences future expected performance. As with equity funds in general in this period, TDFs with actively managed ingredient funds, on average, trailed the performance of their cheaper passively managed counterparts. <b>TOPICS:</b>Pension funds, portfolio theory, risk management, performance measurement <b>Key Findings</b> ▪ Even near term target date funds (TDFs) have considerable equity exposure. For instance, 2025 TDFs lost between 20 and 25% of their value in the five weeks between February 19 and March 23, 2020. Many longer horizon TDFs did no better than pure equity funds in this period. ▪ 75% of actively managed TDFs failed to do as well as the best fitting set of reference ETFs. ▪ Past performance is only a weak predictor of future performance for TDFs. An extra 1% per year return in 2010–14 period only increases the expected return in 2015–19 by 9 basis points per year.

The Best and Worst Stock Pickers' Markets: Ranked by Year, 2000-2020

I construct a measure for how good a time period was for stock pickers selecting from a benchmark index. A market is better for skilled stock pickers when it is difficult for random selection to do well, in particular, in years where more stocks underperform than outperform the benchmark return. I apply the measure to the S&P500 index for 2000 through 2020. The best five years for skilled stock pickers were 2020, 2007, 2018, 2017, and 2015, in that order, while the worst five years for skilled stock pickers were 2001, 2000, 2002, 2004, and 2010, respectively. Large cap equity manager underperformance has been especially bad in years that would have been good for skilled stock pickers, further emphasizing the well-known lack of stock-picking skill among most large cap U.S. equity managers.

PORTFOLIO AND BENCHMARK RETURNS OF PRIVATE PENSION FUNDS: A COMPARATIVE ANALYSIS FOR TURKEY

The purpose of this study is to ascertain whether pension fund returns are in line with benchmark returns taking into account the regulatory structure in Turkey. The methodology of the study is the cumulative portfolio returns. Data is retrieved from TEFAS Platform and official web site of Capital Market Board of Turkey. Portfolio and benchmark of pension funds are compared. Only standard pension funds are covered within the scope of voluntary pension funds of Turkey. Findings are as follows; Portfolio returns and benchmark returns are in line significantly. The results are partly attributable to the regulations about pension fund management and portfolio structure. The paper also shows that in the long term, the volatility of returns decreases and returns prove to conform with the primary purpose of the private pension system.

Benchmarking the Performance of Private Equity Portfolios of the World’s Largest Institutional Investors: A View from CEM Benchmarking

The CEM database contains private equity true-time weighted portfolio returns net of investment costs, along with self-reported benchmark returns for some of the largest institutional investors in the world. To quantify performance, the article uses a consistent benchmarking methodology, employing geographic blends of small-cap equity indexes and showing that the method yields a better benchmark. From 1996–2018, private equity slightly underperforms the benchmark, indicating that the returns for private equity are comparable to those of listed equity. <b>TOPICS:</b>Private equity, performance measurement, equity portfolio management, statistical methods, style investing, pension funds <b>Key Findings</b> • Of the private equity benchmarks currently used by investors, most are flawed. A benchmarking method using listed small-cap equity, with a lag of between three and five months, is sufficient to benchmark most private equity portfolios. • The average private equity portfolio historically underperforms this simple investible benchmark. The average net value added from 1996–2018 is −0.67%. • Costs strongly affect relative performance; low-cost internal direct or co-investment private equity outperforms high-cost fund-of-funds private equity.

A sharing mechanism of investment outcome for interest-sensitive life insurance products

As growing sales of insurance contracts with a saving feature, an issue of sharing investment outcome gets the attention of insurers and policyholders. This paper focuses on a systematic way of finding the sharing mechanism for an optimal contract design in such a way that a policyholder and an insurer maximize their expected utilities. We adopt the policyholder and the insurer as a principal and an agent, respectively, and regard a share of the investment performance as an incentive for the insurer to elicit efforts. As a result of this setting, the moral hazard issue generated from the insurer is unavoidable. For the purpose, the Holmström (1979)’s principal-agent model with limited observability of the insurer’s action plays a leading role in resolving a pie-cutting problem. Under our model assumption, the sharing mechanism states that a portion of the outcome belonging to the insurer is a nondecreasing function of the excess of the portfolio return over a benchmark return when the two parties are risk-averse. In particular, the sensitivity of the sharing portion has an S-shape curve which is consistent with the insurer’s risk propensity.An empirical study based on companies’ portfolio attributes and crediting rates verifies that our theoretical findings are consistent with statistically significant results. In particular, we confirm that the bargaining power of the insurer has a considerable impact on the sharing mechanism as it is theoretically important.