Dixie (DXYN) Change in Accured Expenses (2010 - 2026)
Dixie's Change in Accured Expenses was -$921,000 in Q2 2026, compared with $438,000 a year earlier.
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Analysis
Dixie (DXYN) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Dixie's Change in Accured Expenses was $801,000 through Jun 27, 2026, down 86.6% year-over-year; for FY2025, it came in at $9.34 million.
- Change in Accured Expenses shows a five-year compound annual growth rate of 17.6% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was -$618,000 in FY2024, -$506,000 in FY2023, -$9.65 million in FY2022 and $7.31 million in FY2021 (+76.0%).
- Quarterly Change in Accured Expenses has moved between -$8.43 million (Q4 2022) and $11.51 million (Q1 2025) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last four quarters, with growth averaging 133.1%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q3 2025 (growth of 506.0%); the worst was Q2 2022 (a decline of 89.2%).
- Per Business Quant data, DXYN's Change in Accured Expenses in the three quarters before Q2 2026 was $4.33 million (Q1 2026), -$5.34 million (Q4 2025) and $2.73 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | SharkNinja | 26.80 Bn | 24.47 Bn | 860.34 Mn | 311.96 Mn |
| 2 | Somnigroup International | 13.22 Bn | 12.76 Bn | 817.20 Mn | - |
| 3 | Hni | 3.33 Bn | 2.90 Bn | 647.20 Mn | 100.30 Mn |
| 4 | Newell Brands | 2.36 Bn | 1.52 Bn | 812.00 Mn | - |
| 5 | Sonos | 2.01 Bn | 912.92 Mn | 189.31 Mn | 43.63 Mn |
| 6 | Whirlpool | 1.72 Bn | -1.75 Bn | 442.00 Mn | -21.00 Mn |
| 7 | Millerknoll | 1.45 Bn | 747.53 Mn | 385.30 Mn | -31.60 Mn |
| 8 | Arhaus | 1.44 Bn | 521.74 Mn | 172.07 Mn | 24.17 Mn |
| 9 | Corsair Gaming | 1.40 Bn | 928.63 Mn | 104.29 Mn | 2.72 Mn |
| 10 | Dixie | 5.36 Mn | 3.26 Mn | 20.23 Mn | -921,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | -921,000.00 |
| Mar 28, 2026 | 4.33 Mn |
| Dec 27, 2025 | -5.34 Mn |
| Sep 27, 2025 | 2.73 Mn |
| Jun 28, 2025 | 438,000.00 |
| Mar 29, 2025 | 11.51 Mn |
| Dec 28, 2024 | -6.44 Mn |
| Sep 28, 2024 | 450,000.00 |
| Jun 29, 2024 | -554,000.00 |
| Mar 30, 2024 | 5.92 Mn |
| Dec 30, 2023 | -6.64 Mn |
| Sep 30, 2023 | 476,000.00 |
| Jul 1, 2023 | 2.62 Mn |
| Apr 1, 2023 | 3.03 Mn |
| Dec 31, 2022 | -8.43 Mn |
| Sep 24, 2022 | 265,000.00 |
| Jun 25, 2022 | 469,000.00 |
| Mar 26, 2022 | -1.95 Mn |
| Dec 25, 2021 | -5.14 Mn |
| Sep 25, 2021 | -57,000.00 |
API Access
Dixie Change in Accured 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=change-in-accured-expenses&ticker=DXYN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "DXYN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=DXYN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();