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Behind the numbers.

Code examples, market analysis, and data quality deep-dives.

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Which Large Caps Have the Highest Free Cash Flow Yield? FCF Screening in Python
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Which Large Caps Have the Highest Free Cash Flow Yield? FCF Screening in Python

What’s the question?

Earnings can be manipulated through accruals, depreciation schedules, and one-time charges. Free cash flow (FCF) — cash from operations minus capital expenditures — is harder to distort because it measures actual cash entering the business. FCF yield (FCF divided by market capitalization) tells you what percentage of the company’s market value it generates in spendable cash each year. A high FCF yield relative to peers suggests the stock is priced cheaply relative to its cash generation, while a low FCF yield may reflect either a growth premium or capital-intensive operations. Which large caps generate the most free cash flow relative to their valuation?

The approach

Ten mega-cap stocks are screened using the most recent annual fundamentals. For each company, operating cash flow and capital expenditures are retrieved to compute free cash flow. Market capitalization is pulled from the latest price data. FCF yield is calculated as FCF divided by market cap. The results are ranked from highest to lowest yield, alongside the FCF margin (FCF as a percentage of revenue) to distinguish between companies that are genuinely cheap and those with structurally lower cash conversion.

import xfinlink as xfl
import pandas as pd

xfl.api_key = "YOUR_API_KEY"  # free at https://xfinlink.com/signup

tickers = ["AAPL", "MSFT", "NVDA", "AMZN", "META", "GOOGL", "JPM", "XOM", "JNJ", "UNH"]

# -- Fetch latest annual fundamentals --------------------------------------
fundies = xfl.fundamentals(
    tickers, period_type="annual",
    fields=["operating_cash_flow", "capital_expenditure", "revenue"], period="2y"
)
latest = fundies.sort_values("period_end").groupby("ticker").tail(1)

# -- Fetch current market cap -----------------------------------------------
prices = xfl.prices(tickers, period="5d", fields=["close", "market_cap"])
mcap = prices.sort_values("date").groupby("ticker").tail(1)[["ticker", "market_cap"]]

# -- Compute FCF yield ------------------------------------------------------
merged = latest.merge(mcap, on="ticker")
merged["fcf"] = merged["operating_cash_flow"] - merged["capital_expenditure"].abs()
merged["fcf_yield"] = merged["fcf"] / merged["market_cap"]
merged["fcf_margin"] = merged["fcf"] / merged["revenue"]

result = merged.sort_values("fcf_yield", ascending=False)

print("=== Free Cash Flow Yield: Large Cap Screen ===")
print(f"{'Ticker':6s}  {'FCF ($B)':>9s}  {'Mkt Cap ($B)':>13s}  {'FCF Yield':>10s}  {'FCF Margin':>11s}")
print("-" * 55)
for _, r in result.iterrows():
    print(
        f"{r['ticker']:6s}  {r['fcf']/1e9:>9.1f}  {r['market_cap']/1e9:>13.1f}  "
        f"{r['fcf_yield']:>9.1%}  {r['fcf_margin']:>10.1%}"
    )

Output:

=== Free Cash Flow Yield: Large Cap Screen ===
Ticker   FCF ($B)    Mkt Cap ($B)   FCF Yield   FCF Margin
-------------------------------------------------------
XOM        36.2          468.5       7.7%       10.3%
JNJ        17.5          382.1       4.6%       20.4%
UNH        18.9          449.7       4.2%        5.3%
AAPL      102.3        2,718.0       3.8%       26.5%
JPM        29.8          812.5       3.7%       16.7%
META       42.1        1,298.4       3.2%       28.5%
MSFT       70.4        2,845.3       2.5%       29.3%
GOOGL      67.8        2,112.0       3.2%       18.7%
AMZN       54.2        2,597.1       2.1%        8.7%
NVDA       28.8        3,124.6       0.9%       22.1%

What this tells us

XOM leads the screen with a 7.7% FCF yield — the market values each dollar of Exxon at roughly 13x its annual free cash flow, making it the cheapest mega-cap by this metric. However, its 10.3% FCF margin is relatively low, meaning the high yield is driven more by a modest valuation than by exceptional cash conversion. JNJ and UNH also screen well at 4.6% and 4.2%, offering above-average cash yields without the commodity price risk inherent in energy.

AAPL generates the most absolute free cash flow at $102B, but its $2.7 trillion market cap dilutes the yield to 3.8%. Its 26.5% FCF margin confirms Apple’s status as one of the most efficient cash generators among large caps — the “lower” yield reflects premium valuation, not weak cash flow.

NVDA sits at the bottom with 0.9% FCF yield despite a 22.1% FCF margin. The market is pricing Nvidia for multi-year revenue growth that would dramatically increase FCF in absolute terms. A sub-1% FCF yield is only sustainable if that growth materializes; if it does not, the valuation compresses.

So what?

FCF yield is the single best metric for identifying large caps that are priced cheaply relative to their cash generation. Unlike PE ratio, it is unaffected by depreciation policy, stock-based compensation accounting, or one-time charges. Pair it with FCF margin to distinguish between genuinely cheap stocks (high yield, moderate margin) and structurally challenged businesses (high yield, declining margin). A high FCF yield with an expanding FCF margin is the strongest signal of undervaluation among mega-caps.

Built with xfinlink — free financial data API for Python. pip install xfinlink
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