All Cap Index & Sectors: Free Cash Flow Yield down through 8/12/22

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While FCF remains above average at lagging levels, the decline in the NC 2000’s FCF yield is alarming given the macroeconomic headwinds companies are currently facing.

This report is an abridged version of All Cap Index & Sectors: Free Cash Flow Yield Falls Through 8/12/22, one of my quarterly reports on fundamental market and industry trends. I calculate these metrics using the S&P Global (SPGI) methodology, which adds up the individual NC 2000 file values ​​for free cash flow and enterprise value before using them to calculate the metrics. I call this the “Aggregate” methodology. This research is based on the latest audited financial data, in most cases the 2Q22 10-Q. Price details are as of 8/12/22.

Falling FCF Yield NC 2000 in 2Q22

The lagging FCF yield for the NC 2000 fell from 1.7% on 6/30/22 to 1.5% on 12/8/22.

Five NC 2000 sectors saw an increase in the lagging FCF return from 30/6/22 to 8/12/22.

Key Details on Selected NC 2000 Sectors

With an FCF return of 10.6%, as of 8/12/22, investors are getting more FCF for their investment dollar in the telecom services sector than any other sector. On the other hand, at -3.8%, the real estate sector currently has the lowest residual FCF yield of all NC 2000 sectors.

The Telecom Services, Energy, Healthcare, Materials and Industrial sectors each saw an increase in lagging FCF returns from 6/30/22 to 8/22/12.

Below I highlight the lagging FCF yield of the energy sector.

The full version provides the same details for each sector as this report for the Energy sector.

Example Sector analysis: Energy

Figure 1 shows that the energy sector lagging FCF yield increased from 4.3% on 6/30/22 to 5.3% on 12/8/22. The energy sector’s FCF rose from $122.8 billion in 1Q22 to $159.3 billion in 2Q22, while enterprise value increased from $2.9 trillion on 6/30/22 to $3.0 trillion on 12/12/ 22.

Figure 1: Energy deficit FCF yield: December 1998 – 22/12/08

The August 12, 2022 measurement period uses price data from that date and includes the financials of 2Q22 10-Qs, as this is the earliest date for which all 2Q22 10-Qs for the NC 2000 components were available.

Figure 2 compares the trends in FCF and enterprise value for the energy sector since 1998. I sum the individual NC 2000/sector stock values ​​for free cash flow and enterprise value. I call this approach the ‘Aggregate’ methodology and it aligns with the S&P Global (SPGI) methodology for these calculations.

Figure 2: Energy FCF and Enterprise Value: December 1998 – 22/12/08

Sources: New Constructs, LLC and corporate filings.

The August 12, 2022 measurement period uses price data from that date and includes the financials of 2Q22 10-Qs, as this is the earliest date for which all 2Q22 10-Qs for the NC 2000 components were available.

The Aggregate methodology provides a clear view of the entire NC 2000/industry, regardless of market cap or index weight, and is consistent with how S&P Global (SPGI) calculates metrics for the S&P 500.

For additional perspective, I compare the Free Cash Flow Aggregate method with two other market-weighted methodologies. Each method has its advantages and disadvantages, which are described in the appendix.

Figure 3 compares these three methods for calculating the trailing FCF returns of the energy sector.

Figure 3: Energy Lagging FCF Yield Methodologies Compared: December 1998 – 12/12/22

The August 12, 2022 measurement period uses price data from that date and includes the financials of 2Q22 10-Qs, as this is the earliest date for which all 2Q22 10-Qs for the NC 2000 components were available.

Disclosure: David Trainer, Kyle Guske II, Matt Shuler, and Brian Pellegrini are not remunerated to write about a specific stock, style, or theme.

Appendix: Analyzing lagging FCF yield with different weighting methods

I derive the above stats by adding the individual NC 2000/sector stock values ​​for free cash flow and enterprise value to calculate the lagging FCF return. I call this approach the “Aggregate” methodology.

The Aggregate methodology provides a clear view of the entire NC 2000/industry, regardless of market cap or index weight, and is consistent with how S&P Global (SPGI) calculates metrics for the S&P 500.

For additional perspective, I compare the Free Cash Flow Aggregate method with two other market-weighted methodologies. These market-weighted methodologies add more value for ratios that do not include market values, e.g. ROIC and its drivers, but I include them here for comparison anyway:

Market Weighted Statistics – calculated by market cap weighting of the lagging FCF returns for the individual companies relative to their industry or the total NC 2000 in each period. Details:

  1. Company weight is equal to the company’s market capitalization divided by the NC 2000/its sector’s market capitalization
  2. I multiply each company’s lagging FCF revenue by its weight
  3. NC 2000/Sector trailing FCF yield is equal to the sum of weighted trailing FCF yields for all companies in NC 2000/sector

Market-weighted drivers – calculated by market cap weighting of free cash flow and enterprise value for the individual companies in each industry in each period. Details:

  1. Company weight is equal to the company’s market capitalization divided by the NC 2000/its sector’s market capitalization
  2. I multiply each company’s free cash flow and enterprise value by its weight
  3. I add up the weighted FCF and the weighted enterprise value for each company in the NC 2000/each industry to determine the weighted FCF and the weighted enterprise value of each industry
  4. NC 2000/Sector trailing FCF yield equals weighted NC 2000/sector FCF divided by weighted NC 2000/sector enterprise value

Each method has its pros and cons, as described below:

Aggregated method:

Advantages:

  • A direct look at the entire NC 2000/industry, regardless of company size or weight
  • Corresponds to how S&P Global calculates statistics for the S&P 500.

cons:

  • Vulnerable to the impact of companies entering/leaving the group of companies, which could have an excessive impact on the total values. Also sensitive to outliers in a certain period.

Market Weighted Statistics method

Advantages:

  • Takes into account a company’s market cap relative to the NC 2000/sector and weights the stats accordingly.

cons:

  • Vulnerable to single firm outliers that have a disproportionate impact on overall lagging FCF revenue.

Market-weighted drivers method

Advantages:

  • Represents a company’s market capitalization relative to the NC 2000/sector and weights its free cash flow and enterprise value accordingly.
  • Mitigates the disproportionate impact of one company’s outlier results on overall results.

cons:

  • More volatile because it emphasizes major changes in FCF and enterprise value for heavily weighted companies.

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