RHS: Consumer Staples Dashboard For July

Summary

  • Tobacco and household products are undervalued relative to 11-year averages.
  • Staple retail is the most overvalued subsector.
  • RHS, a balanced alternative to XLP.
  • Looking for a helping hand in the market? Members of Quantitative Risk & Value get exclusive ideas and guidance to navigate any climate. Learn More »

Flat lay view at kitchen table full with non-perishable foods. Spase for text

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This monthly article series shows a dashboard with aggregate industry metrics in consumer staples. It is also a review of sector ETFs like the Consumer Staples Select Sector SPDR ETF (XLP) and the Invesco S&P 500® Equal Weight Consumer Staples ETF (NYSEARCA:RHS), 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 industry: 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 food in the table below is the 11-year average of the median Earnings Yield in food 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.

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.

VS

QS

EY

SY

FY

ROE

GM

EYh

SYh

FYh

ROEh

GMh

RetM

RetY

Staple/Food Retail

-33.50

12.89

0.0312

1.8445

0.0106

22.13

20.53

0.0436

1.9348

0.0325

16.47

22.47

6.88%

13.19%

Food

-1.03

-6.47

0.0598

0.5756

0.0205

15.32

29.18

0.0461

0.6836

0.0247

15.29

33.58

6.35%

-0.69%

Beverage

-14.17

-14.95

0.0337

0.2485

0.0135

22.74

41.38

0.0371

0.2687

0.0182

24.60

53.26

8.40%

8.88%

Household prod.

6.41

1.28

0.0659

1.3567

0.0059

18.35

38.88

0.0442

0.8740

0.0396

17.08

40.86

-2.95%

-31.21%

Personal care

-13.92

17.51

0.0375

0.4062

0.0148

25.93

63.20

0.0386

0.4588

0.0204

21.56

55.08

5.42%

-8.80%

Tobacco

53.37

100*

0.0635

0.7889

0.0261

263.29

51.30

0.0591

0.4602

0.0144

29.94

52.73

-7.72%

-5.21%

*Capped to 100 for convenience

Value And Quality chart

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

Value and quality in consumer staples

Value and quality in consumer staples (Chart: author; data: Portfolio123)

Evolution since last month

The most notable move is an improvement of the quality score in the tobacco industry.

Value and quality variation

Value and quality variation (Chart: author; data: Portfolio123)

Momentum

The next chart plots momentum data.

Momentum in consumer staples

Momentum in consumer staples (Chart: author; data: Portfolio123)

Interpretation

The tobacco industry is the most attractive subsector relative to 11-year averages in value and quality metrics. It is far above the baseline in both value and quality scores. A note of caution about statistics: only five tobacco companies are in my reference universe, this is a small sample size. Household products are slightly undervalued relative to the historical baseline and quality is close to the baseline. Food is close to historical averages in both value and quality. Personal care products and beverage are moderately overvalued (by about 14%). Only personal care may justify it by a good quality score. The beverage industry is below the quality baseline. Staple/food retail is overvalued by more than 30% and quality doesn’t justify it.

Fast facts on RHS

Invesco S&P 500 Equal Weight Consumer Staples ETF (RHS) has been tracking the S&P 500 Equal Weight Consumer Staples Index since 11/01/2006. It has a total expense ratio of 0.40%, which is significantly more expensive than the consumer staples benchmark XLP (0.12%). It has slightly outperformed XLP since inception. The difference is 80 bps in annualized return. However, RHS is a bit more volatile and both funds are almost tie in risk-adjusted performance (Sharpe ratio).

Total Return

Annual Return

Max Drawdown

Sharpe

Std. Dev.

RHS

384.39%

10.58%

-35.78%

0.8

12.50%

XLP

331.93%

9.78%

-33.45%

0.79

11.65%

The fund holds 33 stocks, which means its target individual weight on rebalancing is 3.03%. As of writing, the largest holding is General Mills Inc (GIS) with 3.31%. The top 10 holdings have an aggregate weight about 32%. As a consequence, exposure to risk related to individual companies is low. This contrasts with the capital-weighted ETF XLP, whose top 10 holdings weigh 70% of asset value, the top 4 representing 46%.

RHS is cheaper than XLP regarding the usual valuation ratios reported in the next table.

RHS

XLP

Price / Earnings TTM

20.25

22.95

Price / Book

3.45

5.3

Price / Sales

1.34

1.64

Price / Cash Flow

15.07

17.35

Data: Fidelity

In summary, RHS is a good instrument for investors seeking exposure to consumer staples and avoid concentration in the largest companies. It is a better value play than the capital-weighted index, but past performance since inception is very close to it. Liquidity makes XLP a better choice for tactical allocation and trading.

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 food company with an earnings yield above 0.0598 (or price/earnings below 16.72) 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.

USNA

USANA Health Sciences, Inc.

SAFM

Sanderson Farms, Inc.

EPC

Edgewell Personal Care Company

BJ

BJ's Wholesale Club Holdings Inc.

POST

Post Holdings, Inc.

TSN

Tyson Foods, Inc.

TAP

Molson Coors Beverage Company

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.

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This article was written by

Fred Piard profile picture
14.42K Followers
Data-driven portfolios and risk indicators.
Author of Quantitative Risk & Value and three books, I have been investing in systematic strategies since 2010. I have a PhD in computer science, an MSc in software engineering, an MSc in civil engineering and 30 years of professional experience in various sectors. My aim is making simple and efficient quantitative investing techniques available to my followers. Quantitative models can make investment decisions faster, reproducible and emotionless by focusing on relevant information in the middle of market noise. Moreover, models can be refined to meet specific risk tolerance and objectives. 

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I am an individual investor and an IT professional, not a finance professional. My writings are data analysis and opinions, not investment advice. They may contain inaccurate information, despite all the effort I put in them. Readers are responsible for all consequences of using information included in my work, and are encouraged to do their own research from various sources.

Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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