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Published in: Review of Quantitative Finance and Accounting 4/2023

07-02-2023 | Original Research

Mutual funds and stock fundamentals

Authors: Qiyuan Peng, Sheri Tice, Ling Zhou

Published in: Review of Quantitative Finance and Accounting | Issue 4/2023

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Abstract

This paper studies abnormal returns to mutual funds from using a firm fundamental trading strategy. We find that the abnormal returns and the Sharpe Ratio are higher for actively managed mutual funds holding fundamentally strong stocks. These results are driven by the lower risk of stocks with strong fundamentals rather than higher returns. Compared to benchmark index funds, actively managed mutual funds do not slant their portfolios towards fundamentally strong stocks. The lack of trading on firm fundamentals appears to be related to manager incentives as fund inflows are uncorrelated with changes in the fundamentals of their holding stocks.

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Appendix
Available only for authorised users
Footnotes
1
Examples of papers that link fundamental trading strategies to abnormal stock returns in the accounting literature are Ou and Penman (1989), Holthausen and Larcker (1992), Abarbanell and Bushee (1998), Piotroski (2000), Beneish, Lee and Tarpley (2001), Mohanram (2005), Soliman (2008), and Asness, Frazzini and Pedersen (2019). For more information on accounting studies that examine the link between firm fundamentals and future stock returns see a literature survey by Richardson et al (2010). Examples of papers that link fundamental trading strategies to abnormal stock returns in the finance literature are Piotroski and So (2012), Yan and Zheng (2017), Bartram and Grinblatt (2018), Jiang and Zheng (2018) and Avramov et al (2022).
 
2
During our sample period, mutual funds have been required to report their positions to the SEC either quarterly (before 1985 or after May 2004) or semiannually (between 1985 and May 2004), although many funds voluntarily file their holdings quarterly even when not required. Since we only observe long equity positions of mutual funds in our database, our tests will not reflect profits or losses on short positions. This is not much of a concern for two reasons. First, stock shorting by mutual funds does not appear to be very prevalent. For example, Chen, Hong, and Stein (2002a, b), state “We are probably on safe ground in assuming that mutual funds rarely, if ever, take short positions.” Almazon et al (2004) report that only 30% of mutual funds are allowed to short. Of the 30% who are allowed to short, less than 10% of them report that they take short positions and this is only 3% of the mutual fund universe. Second, even if mutual funds cannot short, they can slant their long positions towards stocks with strong fundamentals and away from stocks with weak fundamentals to exploit the anomaly.
 
3
The F_SCORE screen consists of nine binary signals where a score of one on a signal indicates a fundamental strength and the score of zero on a signal indicates a fundamental weakness. These nine signals cover profitability, leverage, and operating efficiency. Hence a stock’s F_SCORE can range from zero to nine. Further details regarding how the F_SCORE is calculated are in Appendix Table 9.
 
4
Another comprehensive screen of fundamental signals is the G-SCORE developed by Mohanram (2005) which is tailored for growth firms. We find evidence that mutual funds holding firms with higher G-SCOREs earn risk-adjusted returns, but the results are weaker than those with F-SCORE (available upon requests) probably because most of the returns of the G-SCORE strategy come from the short side (Mohanram 2005) , and most mutual funds do not short stocks and hence cannot benefit fully from the G-SCORE strategy.
 
5
Like Piotroski and So (2012), we use F_SCORE to assess the firm fundamentals of the entire stock market (both value and growth stocks). Our one year buy-and-hold abnormal returns are similar in magnitude and significance to theirs.
 
6
McLean and Pontiff (2016) find that results of some anomalies weaken after academic studies are published. To address this concern, we examine if there are similar results using a sample after Piotroski (2000) was published. The actively managed mutual fund results using gross and net returns are both similar to the results in the full sample period.
 
7
Several papers have examined whether anomalies survive after controlling for costs. Examples include Chen, Stanzl, and Watanabe (2002), Bushee and Raedy (2005), and Frazzini, Israel, and Moskowitz (2012). In particular, a recent study by Novy-Marx and Velikov (2016) shows that trading on one comprehensive fundamental strategy, the F_SCORE strategy, is profitable after controlling for transaction costs. However, they only control for transaction costs (based on the bid-ask spread) and ignore other costs, fees, and price pressure effects.
 
8
We use the index fund in each style category instead of the entire market as the benchmark because mutual funds are restrained in the stocks they can hold by their investment styles. For example, mutual funds in the Small-Cap/Value category hold stocks of small value firms. To determine whether these funds trade on firm fundamentals, we will compare the average fundamental strength of stocks they hold with that of stocks in the Vanguard Small-Cap Value Index Fund.
 
9
See for example, Piotroski (2000) and Mohanram (2005).
 
10
Ali et al. (2008) exclude balanced funds from actively managed mutual funds. Our results are robust to the exclusion of balanced funds.
 
11
Many funds have multiple share classes, which mainly differ in fee structures. We calculate the monthly fund return as the TNA (total net assets)-weighted average monthly return across all the share classes and the expense ratio as the TNA-weighted average expense ratio across all share classes.
 
12
See Table 9 in the Appendix for the definition of each F_SCORE component.
 
13
ACCRUAL and ΔLEVER are assigned a score of one when they are negative. Other signals are assigned a score of one when they are positive.
 
14
For high book-to-market firms, the profitability of the F_SCORE strategy is mostly driven by the long position. In contrast, the profitability of the F_SCORE strategy for low book-to-market firms is primarily driven by the short position. Even if mutual fund managers cannot take short positions, growth style mutual funds managers can outperform their peers by slanting their long positions away from (towards) low (high) F_SCORE stocks.
 
15
Data for RF, MRP, SMB, HML and UMD are obtained from Ken French’s website: http://​mba.​tuck.​dartmouth.​edu/​pages/​faculty/​ken.​french/​.
 
16
We conduct the test in Table 2 at the portfolio-year level, i.e., each F-score category stands as one observation. Thus, the number of observations in each F_SCORE category is 36 (the number of years in our sample periods), which is much smaller than that used in Table 1, making it difficult to obtain statistically significant differences.
 
17
We could also use the Morningstar investment style categories to control for the size-value styles as in Sect. 5. However, our sample will then be restricted to mutual funds that are covered by Morningstar after 1994, when the Morningstar categories became available.
 
18
Results are available upon request.
 
19
Morningstar uses the equity style grid to help investors determine the style category of a fund based on its stockholdings. The Morningstar equity style grid is a 3X3 box which classifies equities by size (small-cap/mid-cap/large cap) along the vertical axis and a measure of relative value (value/blend/growth) along the horizontal axis. The nine categories in the equity style grid are large cap/blend, large cap/growth, large cap/value, mid-cap/blend, mid-cap/growth, mid-cap/value, small-cap/blend, small-cap/growth, and small cap/value.
 
20
We use the following nine index funds (ETFs) as benchmark funds for each of the nine Morningstar style categories: (1) Small-Cap/Value category: Vanguard Small-Cap Value Index Fund; (2) Small-Cap/Growth category: Vanguard Small-Cap Growth Index Fund; (3) Small-Cap/Blend category: Vanguard Small-Cap Index Fund; (4) Mid-Cap/Value category: iShares S&P Mid-Cap 400 Value ETF; (5) Mid-Cap/Growth category: iShares S&P Mid-Cap 400 Growth ETF; (6) Mid-Cap/Blend category: Vanguard Mid-Cap Index Fund; (7) Large Cap/Value category: Vanguard Large-Cap Value Index Fund; (8) Large Cap/Growth category: Vanguard Large-Cap Growth Index Fund; (9) Large-Cap/Blend category: Vanguard Large-Cap Index Fund.
 
21
Compared with previous tables we lose some observations because of the data requirement on the availability of Morningstar style categories.
 
22
We hesitate to conclude that mutual funds trade against the firm fundamental anomaly based on the results in Table 6 because funds might hold fundamentally weaker stocks than the index funds for other reasons, i.e., they do not have to be deliberately picking fundamentally weak firms to end up with such firms. For example, they might be picking illiquid stocks for reduced competition (Ali et al 2020), and while doing so, they happen to end up with fundamentally weak stocks.
 
23
Following Kacperczyk, Sialm, and Zheng (2005), we define Δw j,t,t+1, the active change in stock j’s weight in a fund due to fund trading during period t + 1 as w j,t+1w_hat j,t. Here, w j,t +1 is stock j’s weight in a given fund at the end of period t + 1, and w_hat,j,t = $$\frac{{w}_{j,t} (1+{R}_{j, t+1})}{{\sum }_{i} {w}_{j,t} (1+ {R}_{j,t+1})}$$, where R j,t +1 is the return of stock j from the end of period t to the end of period t + 1. The purpose is to control for the effect of stock price changes on the calculation of weights: if a fund does not change the number of shares of stock j it holds, Δw j,t,t+1 = 0 by the above definition, regardless of the stock price change.
 
24
Table VIII shows weak evidence that the correlation between changes in FIM and fund flows is positive for funds with low FIM, and negative for funds with high FIM. It seems that investors prefer funds that move their FIM towards the middle.
 
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Metadata
Title
Mutual funds and stock fundamentals
Authors
Qiyuan Peng
Sheri Tice
Ling Zhou
Publication date
07-02-2023
Publisher
Springer US
Published in
Review of Quantitative Finance and Accounting / Issue 4/2023
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-023-01131-w

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