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Measuring Mutual Fund Performance With Characteristic-Based Benchmarks
The Journal of Finance
Abstract
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.
... We use 173 value-weighted portfolios, which are chosen to capture as much of the cross-sectional heterogeneity among individual stocks as possible and are mainly based on Fama & French (2016). For each portfolio, we obtain the Daniel et al. (1997) (DGTW)-adjusted returns, the value-weighted IVOL, and all value-weighted explanatory variables. To structure our analysis, we group the explanations into the categories: (i) information perception, (ii) market frictions, and (iii) lottery preferences. ...
... Data on the risk-free (1-month Treasury Bill) rate, the Fama & French (1993) factors, as well as the definition of 48 industries following Fama & French (1997) are obtained from Kenneth French's data library. 4 Since we need book-to-market value of equity (B/M) data for calculating the adjusted returns based on Daniel et al. (1997) (as described below), our final sample period spans the period from December 1951 to December 2022. This table contains the definitions of the candidate variables. ...
... Unless otherwise noted, we use characteristic-adjusted returns following the methodology of Daniel et al. (1997) ...
... where I JointNews is the joint news indicator that equals one if the JointNews of a firm is above the cross-sectional top tertile, and zero otherwise, and X is a set of control variables that may affect retail investor attention. Following Da, Engelberg, and Gao (2011), we control for log firm size, abnormal turnover, absolute characteristic-adjusted returns (Daniel et al., 1997), log number of analyst coverage, and advertisement expenses/sales ratio. ...
... where I JointNews is the joint news indicator that equals one if the JointNews of a firm is above the cross-sectional top tertile, and zero otherwise. X is a set of control variables that includes the log book-to-market ratio, momentum (MOM, average returns from t − 2 to t − 12), short-term reversal (return in t − 1), idiosyncratic volatility (IVOL), and controls as in Da, Engelberg, and Gao (2011), including log firm size, abnormal turnover, absolute characteristic-adjusted return as in Daniel et al. (1997), advertisement expenses, and log analyst coverage. ...
... Cont'd) Variable Definitions Variables for Cross-Sectional Analysis ASV Abnormal Google search volume. The log of SVI during the month minus the log of average SVI during the previous 12 months, skipping the most recent month New IP Number of new IPs in EDGAR search traffic, defined as the unique IP address that has not searched the focal stock in the past 18 months New IP c Number of new IPs from connected stocks in EDGAR search traffic, defined as the unique IP address that has not searched the focal stock in the past 18 months but searched the connected stocks in the past 18 months New IP o Number of new IPs from other stocks in EDGAR search traffic, defined as New IP net of New IP c Exist IP The number of unique IP addresses that has searched the focal stock in the past 18 months IVOL Idiosyncratic volatility MOM Average returns from t − 2 to t − 12 log(Size) Log market cap log(BM)Log book-to-market ratio Abn Turnover Standardized abnormal turnover as inChordia, Huh, and Subrahmanyam (2007) Abn RetCharacteristic-adjusted return as inDaniel et al. (1997) AdExp/SalesRatio between advertisement expense and sales in the previous fiscal year, where we set advertisement expenditure to zero if it is missing in Compustat log(1+Analyst) Log number of analysts in IBES ...
We analyze over 2.6 million news articles and propose a novel measure of aggregate joint news coverage of firms. The measure strongly and negatively predicts market returns, both in sample and out of sample. The relation is causal, robust to existing predictors, and is especially strong when market uncertainty is high or when market frictions are large. Using data on EDGAR downloads by unique IPs, we provide direct evidence that joint news triggers attention spillover across firms. Our results are consistent with the explanation that joint news generates a contagion in investor attention and causes marketwide overvaluations and subsequent reversals.
... Style drift can be seen as a strategy of active fund management, where portfolio managers adjust the weight of different investment styles in search of higher returns [19]. A large body of literature has found that the investment style of funds often does not match their stated investment objectives [1][2][3], as funds deviate from the investment directions, style characteristics, industry scope, and stock selection criteria defined in their fund contracts [11]. ...
... A large body of literature has found that the investment style of funds often does not match their stated investment objectives [1][2][3], as funds deviate from the investment directions, style characteristics, industry scope, and stock selection criteria defined in their fund contracts [11]. This behavior, where the fund's style characteristics change over time, is referred to as style drift [19]. ...
This study selects the quarterly data of all equity and equity-oriented hybrid open-end funds in China from 2007 to 2022 as the research sample, and examines the impact of fund style drift on fund returns through a two-ways fixed effect model. Our results show that overall style drift tends to improve fund performance. However, after differentiating the type of style drift, we find that fund drift based on stock picking abilities enhanced performance, whereas fund drift based on chasing market trends reduced fund performance. This study presents a new measurement method based on industry allocation, providing an empirical foundation for research on industry-specific theme funds. It also offers fund managers insights for optimizing performance evaluation and incentive systems, while serving as a reference for regulators to develop flexible, effective policies for market stability.
... To investigate these price dynamics, I use the predicted 12-month ahead stock returns from regression 1 as a measure of analysts' outlook. I sort reports into decile groups based on their predictions for each trading day. 4 To calculate buy-and-hold abnormal returns, I follow the characteristics-based benchmark approach proposed by Daniel et al. (1997): ...
This paper documents new investment value in analyst reports. Analyst narratives embedded with large language models strongly forecast future stock returns, generating significant alpha beyond established analyst-based and fundamental-based factors. The return predictability arises primarily from reports that convey negative sentiment but forecast favorable long-term prospects, suggesting systematic market overreaction to near-term negative news. The effect is more pronounced for large, mature firms and for reports authored by skilled, experienced analysts. A Shapley value decomposition reveals that analysts' strategic outlook contributes the most to portfolio performance, especially forward-looking discussions on fundamentals. Beyond demonstrating untapped value in qualitative information, this paper illustrates the broader potential of artificial intelligence to augment, rather than replace, expert human judgment in financial markets.
... Fisher and Statman (2002), as well as Vissing-Jorgensen (2003) [36], examine the first several years of data from the same UBS/Gallup survey of mutual fund investors. According to these researches, respondents frequently expect the continuance of current results [37] Even though the average projections of the wealthier group were consistently lower throughout the examined period, Vissing-Jorgensen shows that their predicted returns follow the same temporal trend as those of the less wealthy. ...
Investors’ are the back bone of every nation. This study examines investor behaviour in order to determine the best investment opportunities accessible in India. The investment strategy is a structured plan that guides an investor in selecting the best suitable investment portfolio for achieving their financial goals over a specified time period. Numerous opportunities for individual investors using a wide range of combination strategies have emerged in the rapidly developing financial services sector of return expectation, risk involves, safety measure, future needs, tax benefits, and time Period. Being aware of the available possibilities is where the question lies. Most people can see that the most popular investment options are stock market, real estate, fixed deposit, gold schemes, mutual fund, and pension schemes though there are a -plenty of other avenues in the market. Data was gathered via a structured questionnaire that was distributed to 225 respondents from various investment categories. Convenience sampling was employed. SmartPLS 3 is utilised to achieve Structure Equation Modelling (SEM), Reliability, Convergent, Discriminate Validity, and model fitness. The findings reveal that return expectation, risk involves, and tax benefits have a significant direct effect on financial system adoption. It also shows the significant effect of return expectation, risk involves, and tax benefits by investments consideration as a mediator for financial system adoption. It's potential that the data gathered may be valuable for both companies and investors interested in entering the Indian financial market.
... There have been precedents in allied financial asset classes for the use of PCA methods to define index constituents (by their common attributes). Daniel et al. [9], for example, argue that its characteristics provide a better ex-ante forecast of the crosssectional returns of futures markets. As such, they argue characteristic identification is a superior way of matching the likely realized returns of an asset class against a benchmark. ...
This paper introduces a novel application of principal component analysis (PCA) in constructing equity indices. While PCA is well-established in other fields, its use in financial index design remains underexplored. The proposed method addresses entropy concerns in nonlinear return time series. PCA is employed to determine equity weights, using factor loadings to guide its construction. This results in a factor model index (FMI) that identifies sub-sectors and assigns data-driven weights. The FMI framework is flexible, allowing adaptation to different asset sub-groups and facilitating synthetic replication of risk factors.
... However, popular factor models hardly explain the cross section of conventional prespecified test assets (e.g., Kozak et al., 2018;Lopez-Lira and Roussanov, 2020), not to mention the ad hoc nature of these test assets hampers the effectiveness of model estimations and evaluations (Lewellen et al., 2010;Ang et al., 2020). For example, characteristics-based test assets are often limited to univariate-and bivariate-sorted portfolios due to the challenges of high-dimensional sorting (Cochrane, 2011), overlooking nonlinearity and asymmetric interactions (that do not uniformly apply to all assets), even with dependent sorting (Daniel et al., 1997). These problems cannot be fully addressed by evaluating different test assets separately for robustness checks (e.g., Fama and French, 1996), selecting test assets (Daniel et al., 2020;Giglio et al., 2023;Bryzgalova et al., 2023), or combining test assets (e.g., Feng et al., 2020). ...
We introduce a new class of tree-based models, P-Trees, for analyzing (unbalanced) panel of individual asset returns, generalizing high-dimensional sorting with economic guidance and interpretability. Under the mean-variance efficient framework, P-Trees construct test assets that significantly advance the efficient frontier compared to commonly used test assets, with alphas unexplained by benchmark pricing models. P-Tree tangency portfolios also constitute traded factors, recovering the pricing kernel and outperforming popular observable and latent factor models for investments and cross-sectional pricing. Finally, P-Trees capture the complexity of asset returns with sparsity, achieving out-of-sample Sharpe ratios close to those attained only by over-parameterized large models.
... The authors found that while some funds exhibited timing skills, these abilities did not persist over time and were not consistently related to superior performance. Daniel, K., Grinblatt, M., Titman, S., & Wermers, R. (1997) The authors proposed a characteristic-based benchmark to evaluate mutual fund performance, which accounts for investment styles and stock characteristics. They found that funds with concentrated portfolios and distinct investment strategies tended to outperform more diversified funds, suggesting a link between investment strategy and performance. ...
Purpose/Aim:-The aim of the present research is to investigate the mediating role of investment strategy on the relationship between market timing ability and mutual fund performance in the contemporary context. The market timing ability include, economic indicators: Interest rates, inflation rates and GDP growth rate followed by technical analysis tools include: moving averages, relative strength index, fund manager expertise, investor confidence level and news and media influence, geopolitical development and natural disasters and pandemics. The mediating factor is the type of the investment strategy includes, the risk tolerance ability, time horizon, the main goals and objectives of investment strategy, market conditions and economic conditions and asset allocation and diversification. The mutual fund performance metrics are absolute returns, risk-adjusted returns, alpha value, beta value, net asset value (NAV), expense ratio and turnover ratio. Outcome:-The outcome of the research witnessed that, the impact of the market timing ability on mutual fund performance majorly dependents on the type of the investment strategy selected by the investor to invest in mutual funds. The strategic investment for enhance performance and risk assessment. Research Methodology/Approach/Design:-Designed closed ended structured questionnaire to collect the opinion of mutual fund investors with respect to three different constructs like: Market Timing Ability, Investment strategies and mutual fund investment performance. Limitations/Implications:-There are certain factors only considered under market timing ability, still there are other factor which enhances the performance of mutual funds. Sampling Technique:-Google Survey sheet being developed and applied simple random sampling technique to collect the opinion from various investors. Statistical Tools:-Applied both descriptive and inferential statistics which include Mean, SD, Correlation, Regression and Structural Equation Modeling Algorithm (SEM) and all the values of the model assessment model include, GFI, AGFI, NFI, TLI and CFI >.90 and RMSEA <.08 and Ch-Square value (P<.000). The measurement model witnesses the accuracy. Generalizability:-The outcome of the research and the model constructs can be used where need arises the mutual fund performance based on the market timing ability, the objective of investment strategy and mutual fund performance. Introduction:-The market timing ability factors are essential especially the economic indicators are the interest rates changes are the primary driver of market movement followed by the inflation rates and GDP growth of the nation and the technical analysis tool include the moving averages and the relative strength index (RSI) and the fund manager expertise and market sentiment analysis and global events include, geopolitical development and natural disasters and pandemic conditions in various countries are the essential concepts must be studies under the market timing ability. The investment strategies include the risk tolerance ability of the investor which include, high risk-ability and low-risk ability and the time horizon of the investment include, short term investment and long-term investment and investors goals and objectives include: retirement savings, capital preservation, income generation and wealth creation, the fund diversification across different fields and other strategies are essential under investment category. The present research model include three different constructs namely: market timing ability, investment strategy and mutual fund performance. The researcher is trying to test the model with respect to direct and indirect effect. The direct effect draws the
... Grinblatt and Titman (1994) show that the choice of benchmarks matters much more for performance inferences than the choice of measures. On the other hand, if fund holding data are available, holdings-based measures (e.g., Grinblatt and Titman, 1989;Daniel, Grinblatt, Titman, and Wermers, 1997) are more robust to benchmark error. This paper does not consider holdings-based measures. ...
Alpha-based performance evaluation may fail to capture correlated residuals due to model errors. This paper proposes using the Generalized Information Ratio (GIR) to measure performance under misspecified benchmarks. Motivated by the theoretical link between abnormal returns and residual covariance matrix, GIR is derived as alphas scaled by the inverse square root of residual covariance matrix. GIR nests alphas and Information Ratio as special cases, depending on the amount of information used in the residual covariance matrix. We show that GIR is robust to various degrees of model misspecification and produces stable out-of-sample returns. Incorporating residual correlations leads to substantial gains that alleviate model error concerns of active management.
... The results achieved by Henrikson and Merton were confirmed for the same market in the period 1971-1979 by Chang and Lewellen (1984). For the period 1975-1994, Daniel et al. (1997) examined over 2,500 funds, mainly aggressive growth funds, finding selectivity in many cases with a lack of market timing. Research for the US market also moved to other markets. ...
Research background
Investment funds are an important part of the capital market. Household savings in this type of asset are increasing every year. From an investor’s point of view, the performance of funds is important. These, along with the risks, are what most often determine the choice of fund type and finally the specific fund. The performance of a fund is often determined by both the size of the fund and the application of the managers’ selectivity and market sense.
Purpose
The aim of this research is to investigate the impact of fund size on performance through the use of selectivity and market sense by managers. Dividing funds into size groups will allow the search for patterns in terms of managers’ use of market timing.
Research methodology
The research used a Treynor-Mazuy model as a market timing model and Ward’s method as the cluster analysis methods. The performance of the funds was determined using an investment performance indicator, i.e., Omega.
Results
The obtained results indicate that the funds are similar within the groups. However, there were differences in the results between the groups. During periods of high volatility, it is recommended to invest in units of funds with an average size below the median.
Novelty
The added value is the study of market timing in groups of funds similar in size. In each group, the results of the Treynor-Mazuy model estimation, and the Omega investment efficiency index were determined, and the differences in the obtained results between the groups were examined. Finally, all funds were clustered using the Ward method.
... For example, Osinga et al. (2020), found that hedge fund managers are better suited for incorporating factor timing as a strategy, which is the main contributor to positive factor timing returns. Daniel et al. (1997) analyzed returns from 125 passive portfolios in comparison to their respective benchmarks and found that factor timing was unsuccessful and it might not be a strategy that could be applied successfully to reach optimal results for passive funds, noting that the manager skill would be the main contributing factor if funds produce desired results. Aiken and Kang (2023) used a holdings-based approach to assess the impact a manager's skill might have on the performance of a fund. ...
The pursuit of higher returns has led to a growing interest in factor timing as a strategy to enhance portfolio returns. Momentum is a popular factor, which involves buying securities that have shown consistent price appreciation over the past 3 to 12 months or past few years, with the expectation that the trend will continue and reducing exposure to those that consistently declined. An important part of a factor timing strategy is in the portfolio optimization process. This article aimed to first construct a large capitalization pure momentum portfolio, which included a dynamic stringent portfolio construction process criteria for selecting stocks estimated from historical data. Second, as a part of the portfolio's risk management strategy, the Kalman filter was applied to the historical performance of this portfolio. Lastly, the ARIMA forecast was used to estimate expected performance and the confidence intervals. The empirical results showed that this pure equity momentum factor timing framework with the Kalman filter together with the ARIMA (autoregressive integrated moving average) forecasting methodology was iterative and incorporated new information as it became available and further enhanced the monitoring and rebalancing process. This adaptive approach enabled the portfolio to capitalize on time-varying return anomalies as they occured.
We find return comovement in stocks that conduct a similar extent of environmental, social, and corporate governance (ESG) activities. The return comovement is stronger among firms with lower ESG scores than among firms with higher ESG scores. Consistent with the affordable fund view, high-growth companies may be more likely to allocate funds toward achieving profitability rather than conducting ESG, resulting in higher return comovement among their stocks. Therefore, ESG return comovement likely arises from fundamentals, particularly asset growth. In addition, we find weak evidence that ESG return comovement is related to investor recognition or information diffusion in excess of the fundamentals.
Prior research has shown that the adoption of SFAS 142 resulted in inflated goodwill levels and untimely impairments by managers. One possible cause is that directors are simply too busy to properly monitor the managers, and accordingly, we explore whether busy directors impact managers’ decisions to impair goodwill. We find that firms with busy directors, with less time to perform monitoring duties, recognize fewer and smaller goodwill impairment losses. For instance, the likelihood of recognizing goodwill impairment losses is around 10% lower in firms with busy directors. Our results are confirmed using an exogenous shock to director busyness from the termination of board seats in merged firms. We also find that managers with busy directors tend to recognize goodwill impairment losses in a less timely manner. Finally, these effects are more evident in firms with weaker internal and external monitoring mechanisms and are driven by busy directors who are independent or members of the audit committee. Overall, our results suggest that effective monitoring by less busy directors, especially independent and audit committee members, can restrict management's discretion afforded by SFAS 142 in recognizing goodwill impairments.
Using a unique data set of firms listed on China’s Shenzhen Stock Exchange, we show that investors’ corporate site visits convey information about future stock returns. Firms with abnormally frequent investor visits predictably outperform firms with abnormally infrequent investor visits by approximately 70-to-100 basis points per month. This return predictability concentrates on neglected firms with low trading volumes and when investors incur higher travel costs. Abnormally frequent investor visits accompany increased holdings among visiting institutions and predict improvements in firms’ fundamental performance, consistent with institutions using visits to gain an information advantage regarding underpriced firms.
The significance of conducting site visits and in-depth research by fund companies is to consistently deliver stable and substantial returns to clients through professional expertise. (Lei Jing, CEO of Harvest Fund Management Co., Ltd., China)
This study introduces a new metric to evaluate a firm's intangible asset intensity, focusing on its ability to generate revenue from nonphysical assets. It finds a strong positive correlation between firm performance and both internally generated and externally acquired intangible assets. Firms with high intangible intensity outperform peers by 3% annually. The oversight of intangible assets is identified as a factor in value stocks' underperformance. Rigorous tests, including endogeneity checks, confirm these firms exhibit superior accounting quality, labour investment efficiency and acquisition returns. A framework highlights how managerial attributes enhance firm value through decision‐making.
There is causal evidence that mortgage credit expansions increase house prices. Does an expansion of margin lending increase stock prices? Because unconstrained arbitrageurs are more important for pricing stocks than homes, the impact is not obvious. Tests are limited because sizable shocks to margin lending are rare. We examine a major Chinese margin-lending expansion between 2010 and 2015. Institutional holding, regression discontinuity, and event study evidence—exploiting the rollout of margin lending across stocks—shows that arbitrageurs anticipated and bought in advance of a significant causal effect of credit. We develop a model to rationalize our findings. Our estimates suggest that margin debt contributes to stock market fluctuations.
p>The study investigated the impact of corporate governance (CG), investment strategy (IS) and macroeconomic variables on the financial performance of pension schemes in Kenya, thereby addressing the key research question: What is the effect of CG, IS and macroeconomic variables on the financial performance of pension funds in Kenya? Qualitative, quantitative and correlational research designs were used to assess the effect of these factors on the financial performance of pension funds. Quantitative data on the annual return of pension funds and macroeconomic variables from 2012 to 2020, as well as qualitative data on CG indicators and IS, were used in the study. Return on investments proxied pension fund performance. Primary data was collected using survey questionnaires from the pension schemes from both the CG and IS indicators to develop both CG and IS indices. The findings show that CG, as well as IS and macroeconomic variables, impact pension funding differently. The effect of CG indicators on pension performance was positive and significant. The intervening effect of IS on the link between CG and pension performance was significant, while the moderating effect of macroeconomic variables was significant. The individual contribution of both CG indicators and macroeconomic factors on pension performance, nonetheless, varied. The main conclusion of the study is that pension fund financial performance is influenced by CG, IS and macroeconomic factors implying that there is a need to take into account the impact of these factors in the execution of investment plans of pension funds to ensure the generation of adequate funds for retirement benefits.
JEL: G23, G32, G34, E44, O55
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Purpose
This study aims to examine whether rising air pollution impacts cryptocurrency returns across different categories.
Design/methodology/approach
This study uses panel regression to investigate the impact of air pollution on cryptocurrencies between January 2014 and June 2023. Cryptocurrency prices are sourced from www.coinmarketcap.com . Air quality is measured using the air quality index (AQI) values provided by the World Air Quality Index Project. Generalized method of moments (GMM) estimators for dynamic panel regression have also been used to control for endogeneity concerns.
Findings
High AQI levels are observed to negatively affect cryptocurrency returns. This impact remains absent during good air quality and for cryptocurrencies with lower energy consumption like stablecoins, clean energy and health cryptocurrencies, supporting the argument that rising air pollution leads to lower returns for cryptocurrencies more prone to damaging the environment.
Practical implications
The findings of this study could offer investors valuable insights in formulating more efficient cryptocurrency trading strategies. It also demonstrates how environmental variables influence the performance of volatile assets like cryptocurrencies. The presence of lower returns for currencies perceived as damaging to the environment could put the focus on promoting sustainability in the production of such digital currencies.
Originality/value
No prior study has investigated the influence of AQI on cryptocurrency returns. This study aims to focus on the behavioral aspect of financial decision-making. As cryptocurrency adoption rates rise across the globe, the findings of this study can provide useful insights to cryptocurrency traders.
Assessing market efficiency and investment performance often relies on a simultaneous test for zero intercepts in a factor model, and such a test is asymptotically valid under some cross-sectional dependence (CSD) assumptions such as sparsity or sufficiently weak CSD. Because these assumptions are imposed from theoretical needs, a direct validation is almost infeasible. This paper introduces a novel approach to indirectly validating the CSD assumptions by adapting existing tests to factor model residuals. Theoretically, the adapted tests can be shown to exhibit a normal limit under the same conditions as the original tests. Empirically, the adapted tests indicate that some prominent factor models fail to capture CSD, confounding the intended interpretation of the original tests. While CSD is always a problematic feature in returns, we identify various stock characteristics as promising for constructing factors explaining CSD.
We investigate whether bank loan financing from 1994 to 2018 conveys valuable private information using a sample of over 10,000 bank loan announcements identified from 8-K filings. We show that the positive announcement effect is persistent and closely related to the information revealed in loan characteristics: The effect is stronger when deals have higher materiality, more favorable pricing, larger lead bank shares, and higher syndicate concentration. The effect is also stronger when lenders have higher credit quality and when credit market conditions are worse. The insignificant wealth effect documented in several early studies is potentially driven by small sample size.
Newborn funds disproportionately hold popular stocks, representing long‐lived strategic choices. This suggests that when choosing strategies in which to launch new funds, families do not consider only expectations for their own performance but also consider investor sentiment toward those strategies. The two motives for entry result in an interaction effect between competitive entry and strategy popularity, which affects performance and flows for both existing and newborn funds. Newborn funds' expectations for performance are partly driven by fund manager skill in those strategies, but this is not the only factor, leaving a role for time‐varying investment opportunities.
We present the first evidence of investor‐trading‐based disagreement's influence on cross‐sectional cryptocurrency daily returns. We interpret abnormal trading volume as investor disagreement and find evidence in support of Miller's disagreement model: when short‐sale constraints are binding, high abnormal volume (high disagreement) assets experience lower future returns. Further supporting Miller, these same conditions associate with higher contemporaneous order imbalance, and ex post decreases in both buying and selling activities, with the former exceeding the latter in magnitude. By contrast, the effect of high disagreement disappears after a coin's margin trading is activated. We conclude that price‐optimism models explain the disagreement‐returns relationship when opinion divergence is likely the dominant determinant of returns.
I show that memory-induced attention can distort prices in financial markets. I exploit rigid earnings announcement schedules to identify which firms are associated in investors’ memory. Firms with randomly overlapping earnings announcements are associated in memory because many investors experience them in the same context. Months later, when only one of the two firms announces earnings, this context is cued, and triggers the recall of the other, associated firm. On such days, I find that memory-induced attention leads to buying pressure in the associated firm’s stock. The strength of this effect varies as predicted by associative memory theory.
This study examines the relationship between fund flows and subsequent performance, testing the smart money and price pressure hypotheses within the context of passive and active exchange‐traded funds (ETFs). By differentiating between managerial skill and non‐fundamental demand shocks, we uncover a significant positive flow‐performance relationship, challenging traditional attributions solely to investor skill in identifying superior fund management. We further develop a measure of flow shocks to individual stocks by aggregating daily changes in ETF ownership of 5600 stocks. An event study on ETF constituents further disentangles the effects of price pressure from smart money. Through robust analyses, including Fama–French industry portfolios and propensity score matching, our findings suggest a nuanced interaction between investor behaviour and market dynamics, contributing to the discourse on fund flows' impact on performance. This research highlights the complexity of the flow‐performance relationship and its implications for fund management and investment strategies, offering new insights into the mechanisms driving fund performance in the ETF landscape.
We examine the informativeness of analyst stock recommendations in the presence of aggregate uncertainty. Our results suggest that a one standard deviation increase in aggregate uncertainty decreases the likelihood of influential recommendation revisions by 5.26%. Increased aggregate uncertainty leads to a small stock price impact for upgrade and downgrade recommendations. Our findings reveal consistent search for information by investors, which, support a post‐recommendation price drift amidst high aggregate uncertainty. We further find that investors of firms with fewer distracted shareholders, less readable financial statements, and more informed trading seek more information when aggregate uncertainty is high. Our study highlights that investors become more cautious while responding to analysts' stock recommendations during high aggregate uncertainty.
Artykuł koncentruje się na dokonaniu wstępnej oceny efektów gospodarowania funduszy inwestycyjnych działających w Polsce w latach 2000–2015. Wykorzystując dużą próbę badawczą, składającą się z 221 krajowych funduszy, dokonano analizy wyników osiąganych w trzech segmentach: akcji, mieszanych oraz obligacji. Przy użyciu zarówno tradycyjnych miar wyników, jak i popularnych miar ryzyka możliwe było ustalenie, czy polskie fundusze posiadają zdolność osiągania ponadprzeciętnych rezultatów. W wyniku przeprowadzonej analizy zaobserwowano, że fundusze uzyskiwały generalnie gorsze średnie stopy zwrotu niż wzorzec odniesienia. Jednak ostatecznie rezultaty w większości przypadków nie były statystycznie istotne. Zwiększenie poziomu ryzyka funduszy odpowiada- ło zwiększeniu zaangażowania inwestycji w papiery właścicielskie.
We examine long-run firm performance following open market share repurchase announcements, 1980–1990. We find that the average abnormal four-year buy-and-hold return measured after the initial announcement is 12.1%. For ‘value’ stocks, companies more likely to be repurchasing shares because of undervaluation, the average abnormal return is 45.3%. For repurchases announced by ‘glamour’ stocks, where undervaluation is less likely to be an important motive, no positive drift in abnormal returns is observed. Thus, at least with respect to value stocks, the market errs in its initial response and appears to ignore much of the information conveyed through repurchase announcements.
We show that the persistent use of momentum investment strategies by mutual funds has important implications for the performance persistence and survivorship bias controversies. Using mutual fund portfolio holdings from a database free of survivorship bias, we ¯nd that the best performing funds during one year are the best performers during the following year, with the exception of 1981, 1983, 1988, and 1989. This pattern corresponds exactly to the pattern exhibited by the momentum e®ect in stock returns, ¯rst documented by Jegadeesh and Titman (1993) and recently studied by Chan, Jegadeesh, and Lakonishok (1996). Our evidence points not only to the momentum e®ect in stock returns, but to the persistent, active use of momentum strategies by mutual funds as the reasons for performance persistence. Moreover, essentially no persistence remains after controlling for the one-year momentum e®ect in stock returns. We also explain why most recent studies have found that survivorship bias is a relatively small concern. Funds that were the best performers during one year are the worst performers during the following year whenever the momentum e®ect in stock returns is absent, and these funds tend to disappear with a frequency not appreciably lower than that of consistently poor performers. Therefore, the pool of non-surviving funds is more representative of the cross-section of all funds than previously thought. Speci¯cally, we ¯nd a di®erence of only 20 basis points per year in risk-adjusted pre-expense returns between the average fund and the average surviving fund.
If competitive equilibrium is defined as a situation in which prices are such that all arbitrage profits are eliminated, is it possible that a competitive economy always be in equilibrium? Clearly not, for then those who arbitrage make no (private) return from their (privately) costly activity. Hence the assumptions that all markets, including that for information, are always in equilibrium and always perfectly arbitraged are inconsistent when arbitrage is costly. We propose here a model in which there is an equilibrium degree of disequilibrium: prices reflect the information of informed individuals (arbitrageurs) but only partially, so that those who expend resources to obtain information do receive compensation. How informative the price system is depends on the number of individuals who are informed; but the number of individuals who are informed is itself an endogenous variable in the model. The model is the simplest one in which prices perform a well-articulated role in conveying information from the informed to the uninformed. When informed individuals observe information that the return to a security is going to be high, they bid its price up, and conversely when they observe information that the return is going to be low. Thus the price system makes publicly available the information obtained by informed individuals to the uninformed. In general, however, it does this imperfectly; this is perhaps lucky, for were it to do it perfectly , an equilibrium would not exist. In the introduction, we shall discuss the general methodology and present some conjectures concerning certain properties of the equilibrium. The remaining analytic sections of the paper are devoted to analyzing in detail an important example of our general model, in which our conjectures concerning the nature of the equilibrium can be shown to be correct. We conclude with a discussion of the implications of our approach and results, with particular emphasis on the relationship of our results to the literature on "efficient capital markets."
Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between
volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance
of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength
of the evidence favoring return predictability.
This paper documents that strategies that buy stocks that have performed well in the past and sell stocks that hav e performed poorly in the past generate significant positive returns o ver three- to twelve-month holding periods. The authors find that the profitability of these strategies are not due to their systematic risk or to delay ed stock price reactions to common factors. However, part of the abnorm al returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented. Copyright 1993 by American Finance Association.
This paper presents new empirical evidence of predictability of individual stock returns. The negative first-order serial correlation in monthly stock returns is highly significant. Furthermore, significant positive serial correlation is found at longer lags, and the twelve-month serial correlation is particularly strong. Using the observed systematic behavior of stock return, one-step-ahead return forecasts are made and ten portfolios are formed from the forecasts. The difference between the abnormal returns on the extreme decile portfolios over the period 1934-87 is 2.49 percent per month. Copyright 1990 by American Finance Association.
This study analyzes the extent to which mutual funds purchase stocks based on their past returns as well as their tendency to exhibit 'herding' behavior (i.e., buying and selling the same stocks at the same time). The authors find that 77 percent of the mutual funds were 'momentum investors,' buying stocks that were past winners; however, most did not systematically sell past losers. On average, funds that invested on momentum realized significantly better performance than other funds. The authors also find relatively weak evidence that funds tended to buy and sell the same stocks at the same time. Copyright 1995 by American Economic Association.
This paper seeks to better describe the characteristics that explain the cross section of average stock returns. Fama and French (FF) (1993) argue that book-to-market ratio (BE/ME) proxies for risk which investors require a premium for assuming. An alternative hypothesis proposed by Daniel and Titman (1996) (DT) suggests that BE/ME may price stocks because investors irrationally focus on firm characteristics rather than on risk factor loadings.A firm's BE/ME depends on accounting standards and other elements which vary across industries. Therefore BE/ME may be a noisy proxy either for risk factor sensitivity or for sources of potential investor irrationality. We attempt to reduce this noise by creating "industry-relative" factor- mimicking portfolios using both inter- and intra-industry BE/ME information.We first document that our portfolios generate significant pricing errors in FF three-factor regressions and may price the FF test assets better than FF's (1993) HML factor. We then use these new factor-mimicking portfolios to explore a hypothesis of Kenneth French, which attempts to reconcile the results of DT with rational asset-pricing. Using our intra-industry factor, we perform asset-pricing tests which may distinguish between the French and DT stories. These tests find no support for the French hypothesis.
In this paper I derive a risk-adjusted measure of portfolio performance (now known as Jensen's Alpha) that estimates how much a manager's forecasting ability contributes to the fund's returns. The measure is based on the theory of the pricing of capital assets by Sharpe (1964), Lintner (1965a) and Treynor (Undated). I apply the measure to estimate the predictive ability of 115 mutual fund managers in the period 1945-1964 - that is their ability to earn returns which are higher than those we would expect given the level of risk of each of the portfolios. The foundations of the model and the properties of the performance measure suggested here are discussed in Section II. The evidence on mutual fund performance indicates not only that these 115 mutual funds were on average not able to predict security prices well enough to outperform a buy-the-market-and-hold policy, but also that there is very little evidence that any individual fund was able to do significantly better than that which we expected from mere random chance. It is also important to note that these conclusions hold even when we measure the fund returns gross of management expenses (that is assume their bookkeeping, research, and other expenses except brokerage commissions were obtained free). Thus on average the funds apparently were not quite successful enough in their trading activities to recoup even their brokerage expenses.
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 introduces a new measure of portfolio performance and applies it to study the performance of a large sample of mutual funds. In contrast to previous studies of mutual fund performance, the measure used in this study employs portfolio holdings and does not require the use of a benchmark portfolio. It finds that the portfolio choices of mutual fund managers, particularly those that managed aggressive growth funds, earned significantly positive risk-adjusted returns in the 1976-85 period. Copyright 1993 by University of Chicago Press.
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.
This article presents a model that provides insights about various measures of portfolio performance. The model explores several
criticisms of these measures. These include the problem of identifying an appropriate benchmark portfolio, the possibility
of overestimating risk because of market-timing ability, and the failure of informed investors to earn positive risk-adjusted
returns because of increasing risk aversion. The article argues that these need not be serious impediments to performance
evaluation.
Several recent studies suggest that equity mutual fund managers achieve superior returns and that considerable persistence in performance exists. This study utilizes a unique data set including returns from all equity mutual funds existing each year. These data enables the author to more precisely examine performance and the extent of survivorship bias. In the aggregate, funds have underperformed benchmark portfolios both after management expenses and even gross of expenses. Survivorship bias appears to be more important than other studies have estimated. Moreover, while considerable performance persistence existed during the 1970s, there was no consistency in fund returns during the 1980s. Copyright 1995 by American Finance Association.
The relative performance of no-load, growth-oriented mutual funds persists in the near term, with the strongest evidence for a one-year evaluation horizon. Portfolios of recent poor performers do significantly worse than standard benchmarks; those of recent top performers do better, though not significantly so. The difference in risk-adjusted performance between the top and bottom octile portfoli os is six to eight percent per year. These results are not attributable to known anomalies or survivorship bias. Investigations with a differen t (previously used) data set and with some post-1988 data confirm the finding of persistence. Copyright 1993 by American Finance Association.
Firm sizes and book-to-market ratios are both highly correlated with the average returns of common stocks. Eugene F. Fama and Kenneth R. French (1993) argue that the association between these characteristics and returns arise because the characteristics are proxies for nondiversifiable factor risk. In contrast, the evidence in this article indicates that the return premia on small capitalization and high book-to-market stocks does not arise because of the comovements of these stocks with pervasive factors. It is the characteristics rather than the covariance structure of returns that appear to explain the cross-sectional variation in stock returns. Copyright 1997 by American Finance Association.
Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the capital asset pricing model, (CAPM), they are called anomalies. The authors find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Their results are consistent with rational intertemporal CAPM or arbitrage pricing theory asset pricing but the authors also consider irrational pricing and data problems as possible explanations. Copyright 1996 by American Finance Association.
Using a sample free of survivor bias, the author demonstrates that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual funds' mean and risk-adjusted returns. Darryll Hendricks, Jayendu Patel, and Richard Zeckhauser's (1993) 'hot hands' result is mostly driven by the one-year momentum effect of Narasimham Jegadeesh and Sheridan Titman (1993), but individual funds do not earn higher returns from following the momentum strategy in stocks. The only significant persistence not explained is concentrated in strong underperformance by the worst-return mutual funds. The results do not support the existence of skilled or informed mutual fund portfolio managers. Copyright 1997 by American Finance Association.
Mutual funds represent one of the fastest growing type of financial intermediary in the American economy. The question remains as to why mutual funds and in particular actively managed mutual funds have grown so fast, when their performance on average has been inferior to that of index funds. One possible explanation of why investors buy actively managed open end funds lies in the fact that they are bought and sold at net asset value, and thus management ability may not be priced. If management ability exists and it is not included in the price of open end funds, then performance should be predictable. If performance is predictable and at least some investors are aware of this, then cash flows into and out of funds should be predictable by the very same metrics that predict performance. Finally, if predictors exist and at least some investors act on these predictors in investing in mutual funds, the return on new cash flows should be better than the average return for all investors in these funds. This article presents empirical evidence on all of these issues and shows that investors in actively managed mutual funds may have been more rational than we have assumed.
The use of predetermined variables to represent public information and time-variation has produced new insights about asset pricing models but the literature on mutual fund performance has not exploited these insights. This paper advocates conditional performance evaluation in which the relevant expectations are conditioned on public information variables. The authors modify several classical performance measures to this end and find that the predetermined variables are both statistically and economically significant. Conditioning on public information controls for biases in traditional market timing models and makes the average performance of the mutual funds in the authors' sample look better. Copyright 1996 by American Finance Association.
This paper analyzes how mutual fund performance relates to past performance. These tests are based on a multiple portfolio benchmark that was formed on the basis of securities characteristics. The authors find evidence that differences in performance between funds persist over time and that this persistence is consistent with the ability of fund managers to earn abnormal returns. Copyright 1992 by American Finance Association.
Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market "beta", size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in "beta" that is unrelated to size, t he relation between market "beta" and average return is flat, even when "beta" is the only explanatory variable. Copyright 1992 by American Finance Association.
An uninformed observer using the tools of mean variance and security market line analysis to measure the performance of a portfolio manager who has superior information is unlikely to be able to make any reliable inferences. While some positive results of a very limited nature are possible, e.g., when there is a riskless asset or when information is restricted to be “security specific,” in general anything is possible. In particular, a manager with superior information can appear to the observer to be below or above the security market line and inside or outside of the mean‐variance efficient frontier, and any combination of these is possible.
Industry costs of equity Working paper
- Eugene F Fama
- R Kenneth
- French
An investigation of the impact of industry factors in asset-pricing tests
- Cohen Randolph
- B Andchristopherk Polk