Waldencast (WALD) Other Working Capital Changes (2021 - 2022)
Waldencast's Other Working Capital Changes was $318,000 in the year ended Dec 31, 2025, compared with -$2.24 million a year earlier.
Analysis
Waldencast (WALD) Other Working Capital Changes (2021 - 2022) Analysis & Trends
From the year ended Dec 31, 2020 onward, Waldencast has reported Other Working Capital Changes for 6 years.
- Annual Other Working Capital Changes has moved between -$2.24 million (the year ended Dec 31, 2024) and $996,000 (the year ended Dec 31, 2023) over five years.
- Per Business Quant data, Other Working Capital Changes in earlier years was -$2.24 million in the year ended Dec 31, 2024, $996,000 in the year ended Dec 31, 2023, -$724,000 in the year ended Dec 31, 2022 and -$1.1 million in the year ended Dec 31, 2021.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Procter & Gamble | 346.43 Bn | 302.42 Bn | 10.28 Bn |
| 2 | Colgate Palmolive | 69.04 Bn | 64.10 Bn | 3.30 Bn |
| 3 | Estee Lauder Companies | 34.63 Bn | 22.70 Bn | 2.74 Bn |
| 4 | Kenvue | 34.35 Bn | 29.97 Bn | 2.30 Bn |
| 5 | Kimberly Clark | 32.85 Bn | 30.17 Bn | 1.60 Bn |
| 6 | Church & Dwight | 22.69 Bn | 21.21 Bn | 693.90 Mn |
| 7 | Clorox | 9.84 Bn | 8.28 Bn | 804.00 Mn |
| 8 | e.l.f. Beauty | 6.00 Bn | 4.97 Bn | 398.84 Mn |
| 9 | Reynolds Consumer Products | 4.65 Bn | 4.32 Bn | 245.00 Mn |
| 10 | Waldencast | 120.91 Mn | 83.49 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2022 | -790,000.00 |
| Mar 31, 2022 | 648,000.00 |
| Dec 31, 2021 | -1.43 Mn |
| Sep 30, 2021 | 3.90 Mn |
| Jun 30, 2021 | -1.69 Mn |
| Mar 31, 2021 | -1.88 Mn |
API Access
Waldencast Other Working Capital Changes 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=other-working-capital-changes&ticker=WALD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-working-capital-changes", "ticker": "WALD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-working-capital-changes&ticker=WALD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();