iShares IUSV: A Decent Value ETF, But It Could Be Better

IUSV strategy and portfolio

The iShares Core S&P U.S. Value ETF (IUSV) has been tracking the S&P 900 Value Index since July 2000. It has a large portfolio of 750 holdings, a distribution yield of 1.93% and an expense ratio of 0.04% (cheaper than SPY).

As described by S&P Global, S&P 900 constituents are classified in two “Value” and “Growth” styles using a systematic process based on three valuation ratios and three growth metrics. The valuation ratios are book value to price, earnings to price and sales to price. By construction, 33% of S&P 900 constituents exclusively belongs to each style, and 34% belong to both styles. The “Value” style subset serves as S&P 900 Value Index and is rebalanced annually. It is capital-weighted, with a “style strength” adjustment for constituents belonging to both styles.

IUSV invests mostly in U.S. based companies (98.7% of asset value). Large companies represent 72.1% of the portfolio, mid-caps 23.3% and small caps 4.6%.

As expected, IUSV is significantly cheaper than the benchmark Russell 1000 (IWB) regarding usual valuation ratios, reported in the table below.

The top 10 holdings, listed in the next table with valuation ratios, represent 16.6% of asset value. The heaviest one weighs about 3%, so the risk related to individual stocks is low.

The top five sectors are financials (16.2%), healthcare (15.4%), industrials (13%), technology (11.5%) and consumer staples (10.6%). Other sectors are below 8%. Compared to the Russell 1000, the fund overweights the top 5 sectors except technology, and also energy, utilities and materials. It underweights technology, consumer discretionary and communication.

Performance

Since inception (7/24/2000), IUSV has slightly outperformed IWB in return and it has a similar volatility (standard deviation of monthly returns).

Data calculated with Portfolio123

The next chart plots the equity value of $100 invested in IUSV and IWB since July 2000.

IUSV has alternatively beaten and lagged the broader index, outperforming it by a short margin of 40 bps annualized.

Comparing IUSV with my Dashboard List model

The Dashboard List is a list of 80 stocks in the S&P 1500 index (occasionally less), updated every month based on a simple quantitative methodology. All stocks in the Dashboard List are cheaper than their respective industry median in Price/Earnings, Price/Sales and Price/Free Cash Flow. An exception in Utilities: the Price/Free Cash Flow is not taken into account to avoid some inconsistencies. After this filter, the 10 companies with the highest Return on Equity in every sector are kept in the list. Some sectors are grouped together: Energy with Materials, Telecom with Technology. Real Estate is excluded because these valuation metrics don’t work well in this sector. I have been updating the Dashboard List every month on Seeking Alpha since December 2015, first in free-access articles, then in Quantitative Risk & Value.

The next table compares IUSV performance since inception with the Dashboard List model, with a tweak: here the Dashboard List is reconstituted only once a year to make it comparable with a passive index.

Past performance is not a guarantee of future returns. Data Source: Portfolio123

The Dashboard List beats IUSV by a wide margin in return and risk-adjusted performance (Sharpe ratio). However, the ETF performance is real, whereas the model performance is hypothetical.

IUSV fundamental shortcomings

The two models are similar in complexity, so why is the difference so big? The S&P 900 Value Index has two shortcomings in my opinion. The first and largest one is to classify all stocks on the same criteria. It means the valuation ratios are considered comparable across sectors. Obviously they are not: you can read my monthly dashboard here to go a bit deeper into this topic. A consequence is to privilege sectors where valuation ratios are naturally cheaper, for example financials and energy. Some other sectors are disadvantaged: those with large intangible assets like technology, consumer discretionary and communication. To make things simple, companies with large intangible assets are those with a business model based on massive R&D, or a strong branding, or large user databases, or operating in a field where competition is limited by an expensive entry ticket. All these elements are not correctly reflected by valuation ratios. The value discrepancy between sectors results in a significant difference in sector weights as seen in a previous chart.

The second flaw is using the price/book ratio (P/B), which first amplifies the intangible asset issue, and second adds some risk in the strategy. Intuitively, we can guess a large group of companies with low P/B contains a higher percentage of value traps than a same-size group with low price/earnings, price/sales or price/free cash flow. Statistically, such a group will also have a higher volatility and deeper drawdowns in price. The next table shows the return and risk metrics of the cheapest quarter of the S&P 500 (i.e.125 stocks) measured in price/book, price/earnings, price/sales and price/free cash flow. The sets are reconstituted annually between 1/1/1999 and 1/1/2022 with elements in equal weight.

Data calculated with Portfolio123

This explains my choice of using P/FCF and not P/B in the Dashboard List model.

Takeaway

IUSV follows a systematic strategy based on a ranking system using three valuation metrics. It has slightly outperformed the benchmark since its inception two decades ago and it is cheap in management fees. However, there are two points I don’t like in its strategy: it ranks stocks regardless of their sectors, and one of the three metrics is the worst of value ratios. An efficient value model should compare stocks in comparable sets (sector, industry), like I have been doing in the Dashboard List since 2015. This model also uses three valuation metrics, but prefers price/free cash flow to price/book. Moreover, a basic profitability rule helps filter out some value traps and normalize the number of components.