Past Fund Performance Research Articles

A Study on Environmental, Social and Governance Fund Performance and Fund Flow: Evidence From Korea Stock Exchange.

This study analyzed the sensitivity between fund flow and fund performance with Korean funds, whether there would be a difference in the sensitivity between environmental, social and governance (ESG) funds and non-ESG funds, and whether there was a difference in sensitivity according to the type of past fund performance (positive and negative). The main results of the analysis are as follows. First, the analysis of the fund flow–performance correlation of Korean funds revealed that they had a negative (−) correlation and the ESG did not affect fund flow. Analysis of the difference in sensitivity between fund flow and performance volatility revealed that there was a negative (−) correlation regardless of the performance measuring method and ESG. Finally, the comparison of fund flow and performance sensitivity according to the type of past fund performance revealed that despite consistent asymmetry, there was little difference in sensitivity asymmetry between ESG funds and non-ESG funds. The results reveal that, unlike the expectation that investors in Korean ESG funds would focus more on non-financial properties like the purpose of investment than on profit, they attach the same importance to fund performance.

Investor learning and mutual fund flows

AbstractThis paper investigates how volatility of performance affects the sensitivity of mutual fund flows to past performance, and examines how investor learning may contribute to this effect. We illustrate theoretically that when sophisticated investors learn from past fund performance to form their posterior expectations of managerial ability, the flow‐performance sensitivity should be weaker for funds with more volatile past performance. Moreover, the dampening effect of performance volatility on the flow‐performance sensitivity should be stronger for funds attracting more sophisticated investors. We provide supporting evidence for this investor learning hypothesis using mutual fund flows and demonstrate variations in the volatility dampening effect across funds with differing levels of sophistication among investors, such as load versus no‐load, high‐expense versus low‐expense, retail versus institutional, and star versus nonstar funds.

On the Valuation Skills of Corporate Bond Mutual Funds

We introduce a novel measure to assess the valuation skills of investment-grade corporate bond funds. Our measure recognizes funds ex-ante holding a higher fraction of underpriced bonds as having better valuation skills. The measure predicts future fund performance, is stable over time, and is unrelated to other sources of skill. Fund investors recognize such skills by responding more to the past performance of funds with better valuation skills. Consistent with the equilibrium model of Gârleanu and Pedersen (2018), our evidence suggests that as growing capital gets allocated to skilled bond funds, the investment-grade corporate bond market is becoming more efficient.

Factors Affecting Small Investors Behavior: Empirical Evidence from Mutual Fund Investors of a District of Uttarakhand

Purpose: This study is meant to analyze investment behavior of the small investors towards mutual funds at district level of a state and to determine various factors which prompt the small investors to invest in mutual funds. Design/Methodology/Approach: This study is descriptive in nature and used factor analysis on the data collected from 108 respondents out of 120 to whom questionnaire was distributed. For research, primary data is collected and used and secondary data is used for literature review. In this study authors have taken the principal component analysis approach to determine the variables affecting the behavior of small investors towards the mutual fund investments. Findings: The study revealed that mainly males between 34-41 age group in middle class income range had been investing in mutual funds. This study concludes that the fund manager experience, fund performance, scheme risk and the low risk and high returns are the main factors appraised by the small investors while investing in mutual funds. Research Implications: This study can be used by the mutual fund companies in creating their strategies for attracting the small investors. Deploying their best fund managers, introducing diversified schemes, with high growth and liquidity, and showcasing tax benefits, past fund performance, low risk and time horizon may prove success strategies for attracting small investors towards mutual funds.

Importance of Costs in Target Date Fund Selection Using Three Morningstar Ratings

Although target date mutual funds (TDFs) have only been around since the mid-1990s, they are now common vehicles for retirement investing. Sixty percent of US companies now automatically funnel employees’ non-directed retirement funds into TDFs, which account for nearly one-quarter of all savings US workers have in 401(k)s. Helping investors pick among TDFs, Morningstar rates past risk-adjusted performance using a star system and provides forward-looking evaluations of more than 2,500 TDFs using either Analyst Ratings or a newly implemented machine-learning-based Quantitative Ratings. Morningstar assigns Analyst Ratings to a smaller subset of TDFs that tend to have been in existence the longest and have the largest size. We find that TDFs with lower fees have significantly higher star ratings than their higher expense counterparts. No-load TDFs have significantly higher star ratings than their load-charging counterparts. In assessing future fund prospects, TDFs with low expense ratios are favored by both analysts and artificial intelligence. TDFs without load charges have significantly better Quantitative Ratings than their load charging counterparts. TDFs with Quantitative Ratings tend to be smaller, younger, and have poorer prior performance than TDFs with Analyst Ratings. <b>TOPICS:</b>Long-term/retirement investing, mutual funds/passive investing/indexing, information providers/credit ratings <b>Key Findings</b> ▪ Target date funds (TDFs) with low expenses and without load charges have significantly higher Morningstar star ratings of past risk-adjusted performance. These same low-cost funds have higher Morningstar Analyst ratings and Quantitative ratings, which estimate future fund prospects of performance. ▪ Regression results suggest Morningstar’s two forward-looking fund ratings are not perfect substitutes. Analyst ratings weight fund expense and fund age more heavily (both negatively) while the computer-generated Quantitative ratings are more positively influenced by past fund performance. ▪ Morningstar’s star ratings, Analyst ratings, and Quantitative ratings all suggest that retirement investing will result in a larger nest egg when attention is restricted to no-load, low-expense TDFs. Additionally, the ratings suggest investors should favor larger but relatively younger funds.

Mutual Fund Flows and the Information Channel of the Risk-free Rate

This study brings to light the new empirical fact that flows into US domestic equity mutual funds are less sensitive to past fund returns when the risk-free rate declines. In particular, a one-percentage-point drop in interest rates is associated with a decrease in the slope of the flow-performance relationship of around 18%. I demonstrate through a model of portfolio allocation with endogenous information choice that this novel finding is consistent with more privately informed fund investors when rates fall. Specifically, a lower riskless rate diminishes the opportunity cost of acquiring costly private information about a mutual fund, which leads to flows that are less dependent on publicly-available information (i.e., past fund performance). I provide empirical evidence for the model's mechanism by exploiting the cross-sectional implication that the weakening of the link between flows and past performance is more pronounced when information barriers are higher. With a fund class' retail clientele as proxy for information costs, I obtain ample support for this prediction. I also find that, in line with more intense information acquisition, flows are more positively related to future changes in fund performance when rates are low, with this effect similarly being stronger for retail fund classes.

Performance persistence of mutual funds: evidence from Bangladesh

Purpose: Since 1990s, the discussion on whether mutual funds can perform better and persistently as compare to market has become an ongoing issue. Current research investigates the performance persistence of equity mutual funds’, particularly in the financial market of Bangladesh.Theoretical Framework: Different researchers have strived to examine the performance of mutual funds by using numerous performance indicators and risk adjustment techniques.Design/Methodology/Approach: The equity mutual funds data for this study are obtained from DSE (Dhaka Stock Exchange) database. The sample set includes all open-end mutual funds from 2010 to 2015. There is no mutual fund that has ceased trade or merged with other mutual funds during the study period.Originality/Value: Broad literature have been directed on the performance and persistence of mutual funds in the American markets, while some of the studies also centered on Australia, China, Hong Kong and U.K. financial markets. However, in the context of Bangladesh’s financial market, no identical research has been carried on the performance persistence of mutual funds.Findings: The results reveal that the managers of equity mutual funds have selective ability to obtain higher returns in Bangladesh. Moreover, the past performance of mutual funds has an impact on their future performance. The size of mutual funds doesn’t have any impact on their performance. The parametric and non-parametric models demonstrate that as compare to long run, equity mutual funds in Bangladesh could perform persistently in the short-run.

Sentimental Mutual Fund Flows

We show that many stylized empirical patterns for mutual fund flows are driven by investor sentiment. Specifically, when sentiment is high, investors exhibit a stronger tendency of chasing past fund performance; fund flows are less sensitive to fund expenses; and investors are attracted more to funds with sheer visibility. Moreover, the well-documented positive relation between fund flows and future fund performance is significant only during high sentiment periods and is mainly driven by expected component of fund flows. Finally, we show that mutual fund investors exhibit a significantly negative timing ability at the individual fund level when sentiment is high.

Sentimental mutual fund flows

AbstractWe show that many stylized empirical patterns for mutual fund flows are driven by investor sentiment. Specifically, when sentiment is high, investors exhibit a stronger tendency of chasing past fund performance; fund flows are less sensitive to fund expenses; and investors are attracted more to funds with sheer visibility. Moreover, the well‐documented positive relation between fund flows and future fund performance is significant only during high sentiment periods and is mainly driven by expected component of fund flows. Finally, we show that mutual fund investors exhibit a significantly negative timing ability at the individual fund level when sentiment is high.

Private equity characteristics and performance: An analysis of North American venture capital and buyout funds

AbstractThe paper investigates the relationship between fund performance and fund characteristics of North American private equity (PE) funds, by analyzing the interactions of fund size, fund sequence, and past fund performance on traditional fund return measures. The empirical evidence is based on both linear and polynomial regressions, on a sample of 345 venture capital (VC) and 411 buyout (BO) funds with vintage year over the period 1995–2010. We document a concave relationship between fund size and performance, persistence in PE performance, as well as a convex relationship between fund sequence and performance. We suggest both the optimal fund size and the optimal fund sequence number. Economic implications for investors and general partners are discussed as well.

Practical Applications of Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance

<h3>Practical Applications Summary</h3> Quantitative investing, which deploys machine learning and other algorithms, now more or less dominates financial markets. In this environment, it9s useful to step back and compare the performance and risk exposures of discretionary and systematic hedge fund managers. Many allocators to hedge funds, large and small alike, avoid allocating to systematic funds, either partially or entirely, believing them to be difficult to understand, to offer less transparency, and to deliver worse performance due to the use of data from the past. These reasons seem to be consistent with “algorithm aversion”—a distrust of systems. In their article Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance, published in the Summer 2017 issue of <b><i>The Journal of Portfolio Management</i></b>, Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto van Hemert compare the past performance of systematic funds with their discretionary counterparts. They show that, after adjusting for volatility and factor exposures, the lack of confidence in systematic funds is not justified. <b>TOPICS:</b>Real assets/alternative investments/private equity, statistical methods, performance measurement, manager selection

Detecting Repeatable Performance

Past fund performance does a poor job of predicting future outcomes. The reason is noise. Using a random effects framework, we reduce the noise by pooling information from the cross-sectional alpha distribution to make density forecasts for each individual fund’s alpha. In simulations, we show that our method generates parameter estimates that outperform alternative methods, both at the population and at the individual fund level. An out-of-sample forecasting exercise also shows that our method generates improved alpha forecasts. Received November 23, 2016; editorial decision November 1, 2017 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web Site next to the link to the final published paper online.

Costly Information Production, Information Intensity, and Mutual Fund Performance

This study examines the concentration of active mutual fund managers' research efforts toward information-intense stocks and the degree to which they are successful in such efforts. Using the contribution of jumps to stock return variance as a proxy for information intensity, we find that both skilled and unskilled fund managers are attracted to high information-intensity stocks. Moreover, performance persistence is only observed among funds investing in high information-intensity stocks. We show that our results are robust to controlling for characteristics of fund stock holdings and measures of fund activeness. Finally, we find a higher flow sensitivity to past performance of funds with higher information intensity. These findings suggest that investing in high information-intensity stocks is an important strategy by fund managers and has significant impact on investor fund selection decisions.

Do Investors Chase Performance or Skill? Evidence from Mutual Fund Flows

When evaluating a manager, investors should attempt to separate luck from skill. We find a mutual fund manager’s demonstrated skill better predicts future performance than past fund performance. Despite that fact, investors tend to buy the funds with the best past performance, not the funds whose managers have demonstrated the most skill. Further, investors react strongly to fund performance even when it contains no information about manager skill. By failing to separate luck from skill, investors make inferior capital allocations.

The Mutual Fund Investor

This chapter for an upcoming handbook on mutual funds (by Edward Elgar Publishing) offers an overview of the mutual fund market and the investors who inhabit it. On the supply side, mutual funds hold $16 trillion in financial assets and have become the largest component of our private retirement system. On the demand side, mutual fund ownership has become widespread, with 90 million fund-owning households composed mostly of middle-class, educated, and older investors.The portrait of mutual fund investors, painted by a large and consistent body of academic and government studies over the past few decades, is disturbing. Fund investors are mostly ignorant of fund characteristics, inattentive to risks (and opportunities) of different asset classes, and often insensitive to fund fees. Instead, fund investors tend to chase past returns and attempt to time the market. As a result, the average returns for fund investors (both in stock and bond funds) have significantly trailed benchmark market returns – according to some studies, by several percentage points.The role of financial intermediaries in the mutual fund market is also disconcerting. Often, financial advisers give fund investors conflicted advice, leading them to choose high-cost, under-performing funds on which the advisers garner commissions. Although some employers are shifting employees to low-cost, risk-appropriate balanced funds, many 401(k) plans remain less than optimal. Moreover, fund companies tout higher-cost actively managed funds, despite growing evidence that most, if not all, fund managers are unable to beat the market – particularly after fees.There are, however, glimmers of hope. Recently, many fund investors have moved to lower-cost index funds – reflecting a new sensitivity both to the importance of low costs and to the empty promise of active fund management. Target date funds have also established a beachhead in the 401(k) market. The recent clarion calls of the financial press reinforces these trends, as a growing drumbeat of stories emphasizes the importance of fund fees, the counter-productivity of trying to beat or time the market, and the emptiness of chasing past fund performance.

Information and investment under uncertainty

In a model of mutual fund investor learning about managerial ability, we investigate how investment decisions depend on both past returns and non-return information. We show that non-return information affects investors’ reliance on past returns as well as their decision to participate. Our results have important consequences for the relationship between flows of money and past fund performance.

Information and Investment Under Uncertainty

In a model of mutual fund investor learning about managerial ability, we investigate how investment decisions depend on both past returns and non-return information. We show that non-return information affects investors' reliance on past returns as well as their decision to participate. Our results have important consequences for the relationship between flows of money and past fund performance.

Performance persistence in real estate private equity

This study investigates performance persistence across real estate private equity funds. We apply a combination of non-parametric and parametric tests to assess the relationship between past fund performance and subsequent fund performance of non-listed real estate funds. Based on a large global sample of value-added and opportunistic real estate private equity funds raised between 1990 and 2009, we use contingency tables, cross-product ratios, rank correlation statistics and regression analyses to investigate whether there is persistence in the performance across consecutive funds. We find strong evidence for performance persistence across directly consecutive funds. However, we find little support for a relationship between the performance of other prior funds and the focal fund, suggesting that performance persistence is a short-term phenomenon.

DOES THE RIGHT TO CHOOSE MATTER FOR DEFINED CONTRIBUTION PLANS?

We find that sensitivity of fund flows and fund performance are both related to participants' right to choose their investments in defined contribution plans. Under the Mandatory Provident Fund system of Hong Kong, both employers and employees are required to contribute to a retirement account. Originally, employees' investment choices were restricted to a subset of funds chosen by their employers. The system was later modified so that employees are allowed to invest in any fund within the system. We present evidence that flows of fund have become more sensitive to past fund performance after this policy change, and that average fund performance in the system has also improved. Based on the improvement in fund performance, we estimate the accumulated cost of the lack of choice to be around 10% of the current total asset value of the system. (JEL G14, G18)

Performance persistence in institutional investment management: The case of Chinese equity funds

This paper investigates the performance and persistence in performance of equity funds in China. We apply the capital asset pricing model (CAPM) and the Carhart four-factor model to examine 520 equity funds for an eleven-year period with 39,449 observations. To investigate persistence, the entire sample is divided into ten portfolios (deciles) on the basis of lagged one-year performance and then observed over the next 12 months. We find that equity funds in China outperform their benchmark market but do not find any evidence of persistence in the performance of equity funds. Top-performing (worst-performing) funds do not continue to perform well (worse) in the following year. Top-performing funds are younger and have lower expense ratios than the worst-performing funds. However, the size of the top-performing funds and the worst-performing funds show no significant difference. Our results suggest that past performance of equity funds is not predictive of future fund performance.