First Merchants (FRME) Return on Sales [ROS] (2010 - 2026)
First Merchants (FRME) reported Return on Sales [ROS] of 564.45% for Q2 2026, down 122.44 percentage points from 686.90% a year earlier but up 71.71 percentage points from the prior quarter.
First Merchants (FRME) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, First Merchants' Return on Sales [ROS] came in at 600.97%, down 114.15 percentage points year-over-year; for FY2025, it was 685.78%, down 39.83 percentage points from FY2024.
- Return on Sales [ROS] has a five-year change of +360.77 percentage points (FY2020 to FY2025).
- By year, Return on Sales [ROS] came in at 725.62% in FY2024 (+17.35 pp), 708.26% in FY2023 (+300.94 pp), 407.32% in FY2022 (+32.80 pp) and 374.52% in FY2021 (+49.51 pp).
- Five-year quarterly Return on Sales [ROS] spans a low of 244.88% in Q2 2022 and a high of 768.20% in Q1 2024.
- Year over year, Return on Sales [ROS] has now declined in each of the last four quarters, with an average year-over-year change of -63.17 percentage points over the last eight quarters.
- The high point for year-over-year Return on Sales [ROS] in five years was Q2 2023 (a gain of 488.03 percentage points); the low point was Q1 2026 (a drop of 211.96 percentage points).
- Per Business Quant data, the three quarters before Q2 2026 came in at 492.74% (Q1 2026), 666.93% (Q4 2025) and 686.59% (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 883.45 Bn | 912.92 Bn | - | 91.77% |
| 2 | Banco Santander Chile | 401.52 Bn | 521.46 Bn | - | - |
| 3 | Bank Of America | 377.43 Bn | -1,998.64 Bn | - | 93.16% |
| 4 | Hsbc Holdings | 330.31 Bn | 330.37 Bn | - | - |
| 5 | Morgan Stanley | 299.17 Bn | -209.92 Bn | - | 95.89% |
| 6 | Royal Bank Of Canada | 274.08 Bn | 124.82 Bn | - | 138.04% |
| 7 | Mitsubishi Ufj Financial | 270.70 Bn | -1,317.79 Bn | 10.89 Bn | - |
| 8 | Goldman Sachs | 263.13 Bn | -3,293.98 Bn | - | 131.07% |
| 9 | Wells Fargo & Company | 243.64 Bn | 245.78 Bn | - | 84.05% |
| 10 | First Merchants | 2.50 Bn | 2.50 Bn | - | 564.45% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 564.45% |
| Mar 31, 2026 | 492.74% |
| Dec 31, 2025 | 666.93% |
| Sep 30, 2025 | 686.59% |
| Jun 30, 2025 | 686.90% |
| Mar 31, 2025 | 704.70% |
| Dec 31, 2024 | 747.78% |
| Sep 30, 2024 | 720.41% |
| Jun 30, 2024 | 667.94% |
| Mar 31, 2024 | 768.20% |
| Dec 31, 2023 | 712.18% |
| Sep 30, 2023 | 767.79% |
| Jun 30, 2023 | 732.91% |
| Mar 31, 2023 | 624.15% |
| Dec 31, 2022 | 632.89% |
| Sep 30, 2022 | 474.28% |
| Jun 30, 2022 | 244.88% |
| Mar 31, 2022 | 303.39% |
| Dec 31, 2021 | 326.82% |
| Sep 30, 2021 | 368.47% |
First Merchants Return on Sales [ROS] API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=FRME&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "FRME", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=FRME&period=max&api_key=YOUR_API_KEY");
const data = await res.json();