I have updated the free cash flow (FCF) yield for the S&P 500 and all sectors through 8/15/24.
Over the last several quarters, we are seeing a clear trend in the S&P 500’s FCF yield. At the sector level, there is no clear trend, just mixed signals. Four sectors saw FCF yields go up while seven saw them decline – and to varying degrees.
I calculate these metrics based on S&P Global’s (SPGI) methodology, which sums the individual S&P 500 constituent values for free cash flow and enterprise value before using them to calculate the metrics. I call this the “Aggregate” methodology.
This report is based on the latest audited financial data available, which is the 2Q24 10-Q in most cases. Price data is as of 8/15/24. QoQ analysis is based on the change since last quarter.
This report leverages my firm’s cutting-edge Robo-Analyst technology to deliver proven-superior fundamental research and support more cost-effective fulfillment of the fiduciary duty of care.
Sneak Peak on Select S&P 500 Sectors
Investors are getting the highest FCF for their investment dollar in the Telecom Services sector as of 8/15/24. On the flip side, the Real Estate sector has the lowest trailing FCF yield of all S&P 500 sectors.
To give you a sense of what I show in the full report, I provide a snippet on the Real Estate sector, below.
The full report provides these details and charts on the S&P 500 and all sectors.
Sample Sector Analysis: Real Estate
Figure 1 shows the trailing FCF yield for the Real Estate sector rose from 5/16/24 to 8/15/24.
Figure 1: Real Estate Trailing FCF Yield: Dec 2004 – 8/15/24
The August 15, 2024 measurement period uses price data as of that date and incorporates the financial data from 2Q24 10-Qs, as this is the earliest date for which all the 2Q24 10-Qs for the S&P 500 constituents were available.
Figure 2 compares the trends in FCF and enterprise value for the Real Estate sector since 2004. I arrive at these numbers by adding up the individual S&P 500/sector constituents’ 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: Real Estate FCF & Enterprise Value: Dec 2004 – 8/15/24
The August 15, 2024 measurement period uses price data as of that date and incorporates the financial data from 2Q24 10-Qs, as this is the earliest date for which all the 2Q24 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 Real Estate sector’s trailing FCF yields.
Figure 3: Real Estate Trailing FCF Yield Methodologies Compared: Dec 2004 – 8/15/24
The August 15, 2024 measurement period uses price data as of that date and incorporates the financial data from 2Q24 10-Qs, as this is the earliest date for which all the 2Q24 10-Qs for the S&P 500 constituents were available.
Disclosure: David Trainer, Kyle Guske II, and Hakan Salt 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:
- Company weight equals the company’s market cap divided by the market cap of the S&P 500/ its sector
- I multiply each company’s trailing FCF yield by its weight
- 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:
- Company weight equals the company’s market cap divided by the market cap of the S&P 500/ its sector
- I multiply each company’s free cash flow and enterprise value by its weight
- 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
- 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.