Free Cash Flow Is Up But Prices Are Down

The S&P 500’s free cash flow (FCF) remains high, but it is declining[1]^,[2]. The trailing FCF yield remains high as well, relative to recent quarters, because stock prices are declining more than FCF. I think the market is signaling expectations for further declines in FCF, and I expect prices will continue to fall until FCF bottoms out.

This report is an abridged version of S&P 500 & Sectors: Free Cash Flow Is Up But Prices Are Down, one of my quarterly series on fundamental market and sector trends.

FCF Yield Rises Over the Last Year

2021 was a very profitable year for the S&P 500. The trailing FCF yield for the S&P 500 rose from 1.6% on 6/30/21 to 2.2% as of 5/16/22. The FCF yield for the S&P 500 has been this high only three other times since the beginning of 2015: 6/30/16, 12/31/18, and 3/31/22.

Seven S&P 500 sectors saw an increase in trailing FCF yield from 6/30/21 to 5/16/22.

Key Details on Select S&P 500 Sectors

The Energy Sector has the highest FCF Yield at 5.0% as of 5/16/22. On the flip side, the Real Estate sector, at -4.4%, currently has the lowest trailing FCF yield of all S&P 500 sectors.

The Telecom Services, Energy, Utilities, Financials, Healthcare, Consumer Non-cyclicals, and Consumer Cyclicals sectors each saw an increase in trailing FCF yield from 6/30/21 to 5/16/22.

Below, I highlight the Telecom Services sector, which had the largest YoY improvement in FCF yield.

Sample Sector Analysis: Telecom Services

Figure 1 shows the trailing FCF yield for the Telecom Services sector rose from -5.3% as of 6/30/21 to 2.6% as of 5/16/22. The Telecom Services sector FCF rose from -$86.9 billion in 1Q21 to $37.3 billion in 1Q22, while enterprise value fell from $1.6 trillion as of 6/30/21 to $1.4 trillion as of 5/16/22.

Figure 1: Telecom Services Trailing FCF Yield: Dec 2004 – 5/16/22

The May 16, 2022 measurement period uses price data as of that date and incorporates the financial data from 1Q22 10-Qs, as this is the earliest date for which all the 1Q22 10-Qs for the S&P 500 constituents were available.

Figure 2 compares the trends in FCF and enterprise value for the Telecom Services sector since 2004. I sum the individual S&P 500/sector constituent values for free cash flow and enterprise value. I call this approach the “Aggregate” methodology, and it matches S&P Global’s (SPGI) methodology for these calculations.

Figure 2: Telecom Services FCF & Enterprise Value: Dec 2004 – 5/16/22

The May 16, 2022 measurement period uses price data as of that date and incorporates the financial data from 1Q22 10-Qs, as this is the earliest date for which all the 1Q22 10-Qs for the S&P 500 constituents were available.

The Aggregate methodology provides a straightforward look at the entire S&P 500/sector, regardless of market cap or index weighting, and matches how S&P Global (SPGI) calculates metrics for the S&P 500.

For additional perspective, I compare the Aggregate method for free cash flow with two other market-weighted methodologies: market-weighted metrics and market-weighted drivers. Each method has its pros and cons, which are detailed in the Appendix.

Figure 3 compares these three methods for calculating the Telecom Services sector’s trailing FCF yields.

Figure 3: Telecom Services Trailing FCF Yield Methodologies Compared: Dec 2004 – 5/16/22

The May 16, 2022 measurement period uses price data as of that date and incorporates the financial data from 1Q22 10-Qs, as this is the earliest date for which all the 1Q22 10-Qs for the S&P 500 constituents were available.

Disclosure: David Trainer, Kyle Guske II, and Matt Shuler receive no compensation to write about any specific stock, style, or theme.

Appendix: Analyzing Trailing FCF Yield with Different Weighting Methodologies

I derive the metrics above by summing the individual S&P 500/sector constituent values for free cash flow and enterprise value to calculate trailing FCF yield. I call this approach the “Aggregate” methodology.

The Aggregate methodology provides a straightforward look at the entire S&P 500/sector, regardless of market cap or index weighting, and matches how S&P Global (SPGI) calculates metrics for the S&P 500.

For additional perspective, I compare the Aggregate method for free cash flow 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, nonetheless, for comparison:

Market-weighted metrics – calculated by market-cap-weighting the trailing FCF yield for the individual companies relative to their sector or the overall S&P 500 in each period. Details:

1. Company weight equals the company’s market cap divided by the market cap of the S&P 500/ its sector
2. I multiply each company’s trailing FCF yield by its weight
3. S&P 500/Sector trailing FCF yield equals the sum of the weighted trailing FCF yields for all the companies in the S&P 500/sector

Market-weighted drivers – calculated by market-cap-weighting the FCF and enterprise value for the individual companies in each sector in each period. Details:

1. Company weight equals the company’s market cap divided by the market cap of the S&P 500/ its sector
2. I multiply each company’s free cash flow and enterprise value by its weight
3. I sum the weighted FCF and weighted enterprise value for each company in the S&P 500/each sector to determine each sector’s weighted FCF and weighted enterprise value
4. S&P 500/Sector trailing FCF yield equals weighted S&P 500/sector FCF divided by weighted S&P 500/sector enterprise value

Each methodology has its pros and cons, as outlined below:

Aggregate method

Pros:

• A straightforward look at the entire S&P 500/sector, regardless of company size or weighting.
• Matches how S&P Global calculates metrics for the S&P 500.

Cons:

• Vulnerable to impact of companies entering/exiting the group of companies, which could unduly affect aggregate values. Also susceptible to outliers in any one period.

Market-weighted metrics method

Pros:

• Accounts for a firm’s market cap relative to the S&P 500/sector and weights its metrics accordingly.

Cons:

• Vulnerable to outlier results disproportionately impacting the overall trailing FCF yield.

Market-weighted drivers method

Pros:

• Accounts for a firm’s market cap relative to the S&P 500/sector and weights its free cash flow and enterprise value accordingly.
• Mitigates the disproportionate impact of outlier results from one company on the overall results.

Cons:

• More volatile as it adds emphasis to large changes in FCF and enterprise value for heavily weighted companies.

[1] I calculate these metrics based on S&P Global’s (SPGI) methodology, which sums the individual S&P 500 constituent values for market cap and economic book value before using them to calculate the metrics. I call this the “Aggregate” methodology.

[2] This research is based on the latest audited financial data, which is the 1Q22 10-Q for most companies. Price data is as of 5/16/22.