XLY: Consumer Discretionary Dashboard For February (NYSEARCA:XLY)

This monthly article series shows a dashboard with aggregate subsector metrics in Consumer Discretionary. It is also a top-down analysis of sector ETFs like the Consumer Discretionary Select Sector SPDR ETF (XLY), the Fidelity MSCI Consumer Discretionary Index ETF (FDIS) and the Vanguard Consumer Discretionary ETF (VCR), whose largest holdings are used to calculate these metrics.

Shortcut

The next two paragraphs in italic describe the dashboard methodology. They are necessary for new readers to understand the metrics. If you are used to this series or if you are short of time, you can skip them and go to the charts.

Base Metrics

I calculate the median value of five fundamental ratios for each subsector: Earnings Yield (“EY”), Sales Yield (“SY”), Free Cash Flow Yield (“FY”), Return on Equity (“ROE”), Gross Margin (“GM”). The reference universe includes large companies in the U.S. stock market. The five base metrics are calculated on trailing 12 months. For all of them, higher is better. EY, SY and FY are medians of the inverse of Price/Earnings, Price/Sales and Price/Free Cash Flow. They are better for statistical studies than price-to-something ratios, which are unusable or non available when the “something” is close to zero or negative (for example, companies with negative earnings). I also look at two momentum metrics for each group: the median monthly return (RetM) and the median annual return (RetY).

I prefer medians to averages because a median splits a set in a good half and a bad half. A capital-weighted average is skewed by extreme values and the largest companies. My metrics are designed for stock-picking rather than index investing.

Value and Quality Scores

I calculate historical baselines for all metrics. They are noted respectively EYh, SYh, FYh, ROEh, GMh, and they are calculated as the averages on a look-back period of 11 years. For example, the value of EYh for retailing in the table below is the 11-year average of the median Earnings Yield in retail companies.

The Value Score (“VS”) is defined as the average difference in % between the three valuation ratios (EY, SY, FY) and their baselines (EYh, SYh, FYh). The same way, the Quality Score (“QS”) is the average difference between the two quality ratios (ROE, GM) and their baselines (ROEh, GMh).

The scores are in percentage points. VS may be interpreted as the percentage of undervaluation or overvaluation relative to the baseline (positive is good, negative is bad). This interpretation must be taken with caution: the baseline is an arbitrary reference, not a supposed fair value. The formula assumes that the three valuation metrics are of equal importance.A floor of -100 is set for VS and QS when the calculation goes below this value. It may happen when metrics in a subsector are very bad.

Current data

The next table shows the metrics and scores as of last week’s closing. Columns stand for all the data named and defined above.

Value and Quality chart

The next chart plots the Value and Quality Scores by subsector (higher is better).

Chart: author; data: Portfolio123

Evolution since last month

The value score has improved the most in auto/components and durables/apparel during the current market correction. Quality keeps improving in services.

Momentum

The next chart plots momentum data. Services are the best performing subsector in one month and 12 months.

Chart: author; data: Portfolio123

Interpretation

Durables and apparel are by far the most attractive subsector in consumer cyclicals regarding my metrics. Both value and quality scores are above the baseline based on 11-year averages. Retail and automobiles/components are slightly overvalued (by about 12% and 16% relative to the baseline, respectively). Good quality scores may justify it. The services subsector, which includes hotels, restaurants, leisure and diversified services, has improved a lot in the last few months, but value and quality scores are still very bad. The median ROE is negative, which means most customer services companies are unprofitable regarding this metric on a trailing twelve months basis. The recovery is in progress, but many companies hit by lockdowns and travel bans have increased their debt burdens in the last two years. Moreover, some consumer habits may have changed in a lasting way.

Focus on XLY

The Consumer Discretionary Select Sector SPDR Fund (XLY) has been tracking the Consumer Discretionary Select Sector Index since 12/16/1998. It has 64 holdings and a total expense ratio of 0.12%, which is a bit more expensive than VCR (0.10%) and FDIS (0.08%).

The next table shows the top 10 holdings with basic ratios and dividend yields. Their aggregate weight is 69%, with over 40% in the top two names. Amazon and Tesla respectively represent 23.15% and 17.08% of the fund’s asset value.

Ratios by Portfolio123

XLY has beaten the S&P 500 (SPY) by 2.5 percentage points in annualized return since January 1999. Drawdown and standard deviation of monthly returns (volatility) point to a higher risk (see next table).

Data calculated with Portfolio123

In summary, XLY is a good fund with cheap management fees for investors seeking capital-weighted exposure in consumer cyclicals. Vanguard’s and Fidelity’s funds are even cheaper, but the difference is not very significant. XLY is more liquid: it a better instrument for trading and tactical allocation. Investors who are concerned by the high exposure to Amazon and Tesla may prefer the Invesco S&P 500 Equal Weight Consumer Discretionary ETF (RCD).

Dashboard List

I use the first table to calculate value and quality scores. It may also be used in a stock-picking process to check how companies stand among their peers. For example, the EY column tells us that a retail company with an Earnings Yield above 0.0509 (or price/earnings below 19.65) is in the better half of the industry regarding this metric. A Dashboard List is sent every month to Quantitative Risk & Value subscribers with the most profitable companies standing in the better half among their peers regarding the three valuation metrics at the same time. The list below was sent to subscribers several weeks ago based on data available at this time.

It is a rotating list with a statistical bias toward excess returns on the long-term, not the result of an analysis of each stock.