At the beginning of 4Q24, the Energy, Consumer Non-cyclicals, and Financials sectors each earn an Attractive-or-better rating. Our sector ratings are based on a normalized aggregation of our ratings for each stock in a given sector. Our stock ratings are based on five criteria that assess a company’s business fundamentals and valuation. See last quarter’s Sector Ratings here.
Investors looking for sector funds that hold quality stocks should focus on the Energy, Consumer Non-cyclicals, and Financials sectors. Figures 4 through 7 provide more details on the ratings of overall sectors, underlying assets, and individual funds. The primary drivers behind an Attractive fund rating is good portfolio management, or good stock-picking, with low total annual costs.
Attractive-or-better ratings do not always correlate with Attractive-or-better total annual costs. This fact underscores that (1) cheap funds can dupe investors and (2) investors should invest only in funds with good stocks and low fees.
More reliable and proprietary fundamental data, proven in The Journal of Financial Economics, drives our research. Our Robo-Analyst technology[1] empowers our unique ETF and mutual fund rating methodology, which leverages our rigorous analysis of each fund’s holdings.[2] Our Core Earnings[3] and Earnings Distortion factor general novel alpha.
See Figures 4 through 13 for a detailed breakdown of ratings distributions by sector. See our ETF & mutual fund screener for rankings, ratings, and reports on 6,300+ mutual funds and 1,000+ ETFs. Our fund rating methodology is detailed here.
All of our reports on the best & worst ETFs and mutual funds in every sector are available here.
Figure 1: Ratings for All Sectors
Source: New Constructs, LLC and company filings
To earn an Attractive-or-better Predictive Rating, an ETF or mutual fund must have high-quality holdings and low costs. Only the top 30% of all ETFs and mutual funds earn our Attractive-or-better ratings.
iShares U.S. Oil & Gas Exploration % Production ETF (IEO) is one of the top rated Energy funds. It gets our Very Attractive rating by allocating over 53% of its value to Attractive-or-better-rated stocks.
Rydex Real Estate Fund (RYREX) is the worst rated Utilities fund. It gets our Very Unattractive rating by allocating over 97% of its value to Unattractive-or-worse-rated stocks. Making matters worse, it charges investors annual costs of 4.23%.
Figure 2 shows the distribution of our Predictive Ratings for all sector ETFs and mutual funds.
Figure 2: Distribution of ETFs & Mutual Funds (Assets and Count) by Predictive Rating
Source: New Constructs, LLC and company filings
Figure 3 offers additional details on the quality of the sector funds. Note that the average total annual cost of Very Unattractive funds is over three times that of Very Attractive funds.
Figure 3: Predictive Rating Distribution Stats
* Avg TAC = Weighted Average Total Annual Costs
Source: New Constructs, LLC and company filings
This table shows that only the best of the best funds get our Very Attractive Rating: they must hold good stocks AND have low costs.
Ratings by Sector
Figure 4 presents a mapping of Very Attractive funds by sector. The chart shows the number of Very Attractive funds in each sector and the percentage of assets in each sector allocated Very Attractive-rated funds.
Figure 4: Very Attractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 5 presents the data charted in Figure 4.
Figure 5: Very Attractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 6 presents a mapping of Attractive funds by sector. The chart shows the number of Attractive funds in each sector and the percentage of assets in each sector allocated to Attractive-rated funds.
Figure 6: Attractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 7 presents the data charted in Figure 6.
Figure 7: Attractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 8 presents a mapping of Neutral funds by sector. The chart shows the number of Neutral funds in each sector and the percentage of assets in each sector allocated to Neutral-rated funds.
Figure 8: Neutral ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 9 presents the data charted in Figure 8.
Figure 9: Neutral ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 10 presents a mapping of Unattractive funds by sector. The chart shows the number of Unattractive funds in each sector and the percentage of assets in each sector allocated to Unattractive-rated funds.
The landscape of sector ETFs and mutual funds is littered with Unattractive funds. Investors in Industrials have put over 24% of their assets in Unattractive-rated funds.
Figure 10: Unattractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 11 presents the data charted in Figure 10.
Figure 11: Unattractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 12 presents a mapping of Very Unattractive funds by sector. The chart shows the number of Very Unattractive funds in each sector and the percentage of assets in each sector allocated to Very Unattractive-rated funds.
Figure 12: Very Unattractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
Figure 13 presents the data charted in Figure 12.
Figure 13: Very Unattractive ETFs & Mutual Funds by Sector
Source: New Constructs, LLC and company filings
This article was originally published on October 11, 2024.
Disclosure: David Trainer, Kyle Guske, and Hakan Salt receive no compensation to write about any specific stock, sector or theme.
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[1] Harvard Business School features our research automation technology in the case Disrupting Fundamental Analysis with Robo-Analysts.
[2] See how our models overcome flaws in Bloomberg and Capital IQ’s (SPGI) analytics in the detailed appendix of this paper.
[3] The Journal of Financial Economics proves that only Core Earnings enable investors to overcome the flaws in legacy fundamental data.