What's the question?
There are two ways to make money from a warehouse. Sell each item at a wide markup and accept that it sits for months, or take a narrow markup and move the stock quickly. Both models survive.
Retail buyers formalise that tradeoff with gross margin return on inventory, usually shortened to GMROI: gross profit divided by the inventory carried to produce it. A GMROI of 3 means every dollar tied up in stock threw off three dollars of gross profit. It decomposes into gross margin and inventory turnover, the latter being cost of revenue divided by inventory. Inventory days also enter the cash conversion cycle, alongside receivable and payable days.
The question is whether the two parts cancel. Competition says they should: if rapid turnover were free money, capital would move into the fast businesses until their margins fell far enough to equalise the return on stock. Exact cancellation would leave GMROI constant across companies and velocity worth nothing. Partial cancellation would mean the fast businesses keep something real, more gross profit from the same dollar of working capital.
The approach
The test measures both components for one fiscal year and asks how completely one offsets the other across the index.
- Universe: companies in the S&P 500 today. Financials, utilities and real estate drop out, since their balance sheets carry no product inventory cycle.
- Filings: the latest annual report per company with a fiscal year ending on or after 1 June 2025, so January and May year ends sit alongside December filers.
- Cross-check: the reported gross profit line and revenue minus cost of revenue must agree within 2 percent of revenue. Revenue stated gross of excise taxes against a cost line stated net of them, which is how tobacco companies report, inflates the margin, and companies where the two disagree drop from the sample.
- Inventory floor: inventory of at least 2 percent of revenue, about a week of sales, so the ratios describe a real stock cycle rather than a rounding item.
That leaves 206 companies. Fitting the relationship in logs makes the slope an elasticity: -1 means margin falls in exact proportion to the rise in turnover and GMROI is constant, while anything shallower means velocity pays.
Code
import numpy as np
import pandas as pd
import xfinlink as xfl
from scipy import stats
xfl.set_api_key("YOUR_API_KEY") # free at https://xfinlink.com/signup
FIELDS = ["revenue", "cost_of_revenue", "gross_profit", "inventory"]
uni = xfl.index("sp500")
tickers = sorted(uni.loc[uni["removed_date"].isna(), "ticker"].dropna().unique())
f = xfl.fundamentals(tickers, period_type="annual", start="2025-06-01",
version="restated", fields=FIELDS)
latest = f.sort_values("period_end").groupby("ticker").tail(1)
s = latest[~latest["gics_sector"].isin({"Financials", "Utilities", "Real Estate"})]
s = s.dropna(subset=FIELDS)
s = s[(s[FIELDS] > 0).all(axis=1)].copy()
s["gross_profit_calc"] = s["revenue"] - s["cost_of_revenue"]
gap = (s["gross_profit"] - s["gross_profit_calc"]).abs() / s["revenue"]
s = s[(gap <= 0.02) & (s["inventory"] >= 0.02 * s["revenue"])]
s["gross_margin"] = s["gross_profit_calc"] / s["revenue"]
s["turns"] = s["cost_of_revenue"] / s["inventory"]
s["days_inventory"] = 365 / s["turns"]
s["gmroi"] = s["gross_profit_calc"] / s["inventory"]
fit = stats.linregress(np.log(s["turns"]), np.log(s["gross_margin"]))
s["quintile"] = pd.qcut(s["turns"], 5, labels=["Q1 slowest", "Q2", "Q3", "Q4", "Q5 fastest"])
print(f"slope {fit.slope:+.3f} R2 {fit.rvalue ** 2:.3f} p {fit.pvalue:.2g}")
print(s.groupby("quintile", observed=True)[["days_inventory", "gross_margin", "gmroi"]].median())Full script with formatting and visualisation: inventory-turns-gross-margin-tradeoff-python.py
Output
Sample: 206 current S&P 500 members, latest annual filing (2025-06-27 to 2026-05-31)
log gross margin on log turns: slope -0.512 R2 0.296 p 3.1e-17
Spearman turns vs gross margin: -0.545 (p 2.4e-17)
Spearman turns vs GMROI: +0.139 (p 0.046)
Turnover quintile n days of inventory gross margin GMROI
Q1 slowest 42 193 63% 2.76
Q2 41 118 41% 2.22
Q3 41 86 39% 2.67
Q4 41 64 31% 2.61
Q5 fastest 41 32 26% 4.15
Highest gross profit per dollar of inventory
FFIV F 5 INC 49 days 81% 32.55
KMI KINDER MORGAN INC 38 days 67% 19.87
COP CONOCOPHILLIPS 31 days 62% 19.55
AVGO BROADCOM INC 40 days 68% 19.07
TRGP TARGA RESOURCES CORP 15 days 38% 15.19
Lowest gross profit per dollar of inventory
BG BUNGE GLOBAL S A 72 days 5% 0.26
DOW DOW INC 64 days 6% 0.38
CAH CARDINAL HEALTH INC 29 days 4% 0.49
ADM ARCHER DANIELS MIDLAND CO 50 days 6% 0.49
SMCI SUPER MICRO COMPUTER INC 87 days 11% 0.52
Sector medians (sectors with at least 5 names)
Materials 26 67 days 28% 1.89
Consumer Discretionary 25 103 days 37% 2.22
Information Technology 40 109 days 48% 2.54
Industrials 37 91 days 38% 2.67
Consumer Staples 30 67 days 34% 2.93
Health Care 39 123 days 64% 3.97
Energy 8 27 days 34% 9.33What this tells us
The tradeoff is real. Rank correlation between turnover and gross margin is -0.545 across 206 companies, and the quintile medians fall from 63 percent at 193 days of inventory to 26 percent at 32 days. The slowest quintile carries six times the stock of the fastest and prices its goods at more than twice the markup.
The tradeoff is also incomplete. The fitted elasticity is -0.512, so doubling inventory turnover comes with a gross margin about 30 percent lower, not 50 percent lower. Full compensation requires -1. At roughly half that, faster companies retain part of the benefit of velocity: 4.15 dollars of gross profit per dollar of stock in the fastest quintile against 2.61 in the fourth.
The advantage is concentrated rather than gradual. Quintiles two through four cluster between 2.22 and 2.67, and the rank correlation between turnover and GMROI is only +0.139, marginal at p = 0.046. Turning stock faster does not order companies by return on inventory; it separates the extremes.
What drives GMROI is business model, not operating quality. The spread runs from 0.26 at Bunge, an agricultural processor whose 5 percent margin leaves almost nothing per dollar of grain in silos, to 32.55 at F5, which sells software-heavy networking gear at an 81 percent margin on seven weeks of hardware. Sector medians span 1.89 in materials to 9.33 in energy, where midstream operators hold under a month of stock.
So what?
Gross margin on its own does not travel between velocity regimes. Cardinal Health at 4 percent and Vertex Pharmaceuticals at 86 percent are not on the same scale, and a screen that ranks on margin alone ranks industries rather than companies. Dividing gross profit by inventory puts both on one axis; the benchmark that keeps the comparison honest is the sector median, not the market median.
The measure earns its keep inside a single company over time. A GMROI that falls while margin holds steady means stock is accumulating faster than sales, which is the standard prelude to a write-down. A GMROI that falls while turnover holds steady means the goods are moving only because they are being discounted. Both look identical in a headline revenue number.
For a working screen: rank on GMROI within sector, then split the year-on-year change into the margin term and the turnover term. The direction of the change matters more than the level, which the industry mostly sets.
Built with xfinlink — free financial data API for Python.