S&P 500 Valuation Starting In 2020

Jan. 02, 2020 10:13 PM ETVanguard S&P 500 ETF (VOO)IVV, SPY, XLB, XLC, XLE, XLF, XLI, XLK, XLP, XLRE, XLU, XLV, XLY3 Comments10 Likes

Summary

  • A score in value and quality for every sector.
  • Evolution since last month.
  • The best and the worst sectors for these metrics.
  • This idea was discussed in more depth with members of my private investing community, Quantitative Risk & Value. Get started today »

This monthly series gives fundamental scores by sector for companies in the S&P 500 index (NYSEARCA:VOO, SPY, IVV). I follow chosen fundamental factors for every sector and compare them to a historical baseline, so as to create a synthetic dashboard with a value score (V-score) and a quality score (Q-score). You can find here data that may be useful in a top-down approach.

Methodology

  • The median value of 4 valuation ratios is calculated for S&P 500 companies in each sector: Price/Earnings (P/E), Forward Price Earnings for the current year (Fwd P/E), Price-to-Sales (P/S), Price to-Free Cash Flow (P/FCF).
  • It is compared in percentage to its own historical average. For example, a difference of 10% means that the current median ratio is 10% over- or underpriced relative to its historical average in the sector.
  • The V-score of a sector is the average of differences in percentage for the 4 factors, multiplied by -1. The higher is the better.
  • The Q-score is the difference between the current median ROE (return on equity) and its historical average. The higher is the better.
  • GICS sectors had major changes in 2016 (real estate) and in 2018 (communication). Historical averages have been calculated using the current sub-industry structure in the past when possible, so as to compare things that are comparable.

The choice of the valuation and quality ratios has been justified in previous articles. Among the simple, publicly available fundamental factors, they are the best predictors of future returns according to 17-year backtests. Median values are better reference data than averages for stock-picking. Each median is the middle point of a sector, which can be used to separate good and bad elements. A median is also less sensitive to outliers.

Sector valuation metrics on 1/2/2020

The next table reports the 4 valuation factors. There are 3 columns for each factor: the current median value, the historical average (“Avg”) between January 1999 and October 2015 taken as an arbitrary reference of fair valuation, and the difference in percentage (“%Hist”). The first column “V-score” shows the value score as defined above.

V-score

P/E

Avg

%Hist

Fwd P/E

Avg

%Hist

P/S

Avg

%Hist

P/FCF

Avg

%Hist

All

-36.68

23.27

19.18

21.35

18.11

14.83

22.13

2.76

1.58

74.84

31.71

24.7

28.38

Cs. Discretionary

-21.90

20.72

18.15

14.18

16.83

14.11

19.26

1.48

1.01

46.07

26.35

24.38

8.07

Cs. Staples

-39.81

25.50

20.48

24.49

20.66

16.27

27.00

2.58

1.54

67.72

55.00

39.28

40.02

Energy

-4.10

16.23

17.8

-8.81

19.24

14.38

33.79

1.81

1.94

-6.64

30.00

30.59

-1.94

Financials

-22.10

14.15

15.02

-5.79

12.35

11.55

6.92

2.54

1.89

34.28

15.34

10.03

52.99

Healthcare

-22.09

28.77

23.76

21.11

19.01

16.85

12.79

4.17

2.93

42.37

33.67

30.04

12.10

Industrials

-32.60

21.91

18.75

16.85

17.84

14.52

22.89

1.89

1.24

52.80

35.38

25.66

37.87

Technology

-27.43

28.41

28.14

0.95

21.16

19.29

9.69

5.01

2.84

76.56

30.77

25.11

22.54

Communication

10.97

17.09

21.28

-19.69

16.88

17.09

-1.24

2.06

2.01

2.38

19.64

26.31

-25.34

Materials

-29.40

22.41

19.74

13.52

16.82

14.36

17.14

1.91

1.15

65.73

33.37

27.53

21.20

Utilities

-65.60

22.63

15.21

48.81

20.14

13.15

53.17

2.89

1.11

160.42

N/A

43.5

N/A

Real Estate

-19.48

38.09

40.71

-6.45

46.94

36

30.40

9.04

6.67

35.49

61.37

51.8

18.48

Energy: P/FCF Avg starts in 2000 - Utilities: P/FCF too volatile to be relevant - Real Estate: Avg start in 2006

V-score chart:

Sector quality metrics

The next table gives a score for each sector relative to its own historical average. Here, only one factor is accounted.

Q-score (Diff)

Median ROE

Avg

All

0.36

15.29

14.93

Cs. Discretionary

4.15

22.03

17.88

Cs. Staples

-3.97

20.09

24.06

Energy

-7.38

7.51

14.89

Financials

-0.55

11.98

12.53

Healthcare

-0.69

16.91

17.6

Industrials

6.79

23.74

16.95

Technology

12.41

26.16

13.75

Communication

4.92

16.89

11.97

Materials

1.83

15.72

13.89

Utilities

-1.12

10.23

11.35

Real Estate

1.15

7.98

6.83

Q-score chart:

Momentum

The next table and chart show the return in 1 month and 1 year for all sectors, represented by their respective SPDR ETFs (including dividends).

Sector

ETF

1-month return

1-year return

All

SPY

2.91%

31.22%

Cs. Discretionary

XLY

2.76%

28.39%

Cs. Staples

XLP

2.41%

27.43%

Energy

XLE

6.03%

11.74%

Financials

XLF

2.61%

31.88%

Healthcare

XLV

3.47%

20.45%

Industrials

XLI

-0.20%

29.08%

Technology

XLK

4.32%

49.86%

Communication

XLC

2.26%

31.05%

Materials

XLB

2.86%

24.13%

Utilities

XLU

3.29%

25.93%

Real Estate

XLRE

1.14%

28.68%

Monthly Momentum:

Annual Momentum:

Interpretation

For median-based metrics, S&P 500 companies look overpriced by about 37%, with an ROE close to the historical average. The highest overvaluation since I started this series in 2015 was 39% just before the correction of February 2018.

Since last month:

  • The S&P 500 went up by 2.9%.
  • The V-score has deteriorated by 6.7 percentage points.
  • The Q-score is on a slow downtrend for a few months. It is close to our historical baseline.
  • Looking only at the median P/E, S&P 500 companies are overpriced by 21% relative to the average from 2000 to 2015.
  • All sectors except industrials have gained more than 1%. Healthcare is leading with +6%.
  • All sectors went up last 12 months. Technology is leading with +50%, energy is lagging with +12%.
  • V-Score has deteriorated in all sectors.
  • Q-score has not changed significantly in any sector.

According to these metrics, communication is underpriced by about 10%. Energy is close to fair price. Financials, technology, healthcare, real estate, consumer discretionary and materials are overpriced by 20-30%; consumer staples and industrials by 30-40%; utilities by 65%. Communication, technology, industrials and consumer discretionary are significantly above their historical averages in quality metric, which may partly justify overpricing. Energy and consumer staples are below the quality baseline. Combining these metrics, communication is the most attractive sector and utilities the worst one.

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This article was written by

Fred Piard profile picture
14.34K Followers
Data-driven model portfolios and market 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.

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Disclosure: I am/we are long SPY. 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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