Cryoport (CYRX) Accumulated Expenses (2011 - 2026)
Cryoport's (CYRX) quarterly Accumulated Expenses came in at $12.2 million in Q2 2026, up 29.64% year-over-year from $9.4 million in Q2 2025, and down 28.35% quarter-over-quarter from $17.0 million in Q1 2026.
Cryoport (CYRX) Accumulated Expenses (2011 - 2026) Analysis & Trends
Cryoport (CYRX) has reported Accumulated Expenses for 16 consecutive years, with $12.2 million the latest figure, recorded in Q2 2026.
- On a quarterly basis, Accumulated Expenses rose 29.64% year-over-year to $12.2 million in Q2 2026; TTM through Jun 2026 was $12.2 million, a 29.64% increase from a year earlier, with the FY2025 full-year figure at $13.0 million, up 15.8% from the prior year.
- Accumulated Expenses was $12.2 million for Q2 2026 at Cryoport, down from $17.0 million in the prior quarter.
- Over five years, Accumulated Expenses peaked at $17.0 million in Q1 2026 and troughed at $8.4 million in Q2 2022.
- A 5-year average of $11.2 million and a median of $11.0 million in 2024 frame the typical range for Accumulated Expenses.
- The widest YoY moves for Accumulated Expenses: up 46.92% in 2022, down 14.67% in 2022.
- Over 5 years, Accumulated Expenses stood at $8.5 million in 2022, then soared by 34.89% to $11.4 million in 2023, then retreated by 1.75% to $11.2 million in 2024, then advanced by 15.8% to $13.0 million in 2025, then decreased by 6.12% to $12.2 million in 2026.
- The last three Accumulated Expenses figures came in at $12.2 million (Q2 2026), $17.0 million (Q1 2026), and $13.0 million (Q4 2025), per Business Quant data.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Copart | 26.66 Bn | 23.33 Bn | 732.88 Mn |
| 2 | Expeditors International Of Washington | 24.38 Bn | 23.35 Bn | 1.09 Bn |
| 3 | C. H. Robinson Worldwide | 17.52 Bn | 17.36 Bn | 1.11 Bn |
| 4 | Rb Global | 15.43 Bn | 14.90 Bn | 935.50 Mn |
| 5 | Ryder System | 9.07 Bn | 9.07 Bn | 1.45 Bn |
| 6 | Landstar System | 5.72 Bn | 5.38 Bn | 308.86 Mn |
| 7 | GXO Logistics | 5.25 Bn | 4.52 Bn | 508.00 Mn |
| 8 | Rxo | 3.26 Bn | 3.25 Bn | 302.00 Mn |
| 9 | Hub | 1.94 Bn | 1.85 Bn | 250.84 Mn |
| 10 | Cryoport | 889.89 Mn | 493.20 Mn | 22.82 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.19 Mn |
| Mar 31, 2026 | 17.01 Mn |
| Dec 31, 2025 | 12.98 Mn |
| Sep 30, 2025 | 10.86 Mn |
| Jun 30, 2025 | 9.40 Mn |
| Mar 31, 2025 | 12.68 Mn |
| Dec 31, 2024 | 11.21 Mn |
| Sep 30, 2024 | 11.28 Mn |
| Jun 30, 2024 | 10.69 Mn |
| Mar 31, 2024 | 14.06 Mn |
| Dec 31, 2023 | 11.41 Mn |
| Sep 30, 2023 | 10.43 Mn |
| Jun 30, 2023 | 8.72 Mn |
| Mar 31, 2023 | 10.45 Mn |
| Dec 31, 2022 | 8.46 Mn |
| Sep 30, 2022 | 8.63 Mn |
| Jun 30, 2022 | 8.35 Mn |
| Mar 31, 2022 | 12.10 Mn |
| Dec 31, 2021 | 9.91 Mn |
| Sep 30, 2021 | 8.65 Mn |
Cryoport Accumulated Expenses 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=accumulated-expenses&ticker=CYRX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "CYRX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=CYRX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();