BayCom (BCML) Cash & Equivalents (2016 - 2026)
BayCom's Cash & Equivalents was $203.72 million in the quarter ended Jun 30, 2020, down 42.1% from $351.59 million a year earlier and down 25.7% from the prior quarter.
BayCom (BCML) Cash & Equivalents (2016 - 2026) Analysis & Trends
As of Dec 31, 2019, Cash & Equivalents at BayCom came in at $295.38 million, down 8.7% from the prior year.
- Cash & Equivalents shows a three-year compound annual growth rate of 31.9% (years ended Dec 2016 to Dec 2019).
- In earlier years, Cash & Equivalents was $323.58 million in the year ended Dec 31, 2018 (+29.5%), $249.85 million in the year ended Dec 31, 2017 (+94.2%) and $128.68 million in the year ended Dec 31, 2016.
- The figure for the quarter ended Jun 30, 2020 marks the lowest quarterly Cash & Equivalents since the quarter ended Jun 30, 2017.
- Compared with a year earlier, Cash & Equivalents has declined for three straight quarters, with growth averaging 4.8% over the last eight quarters.
- The best year-over-year quarter for Cash & Equivalents over five years was the quarter ended Mar 31, 2018 (growth of 103.6%); the worst was the quarter ended Jun 30, 2020 (a decline of 42.1%).
- Per Business Quant data, BCML's Cash & Equivalents in the three quarters before the quarter ended Jun 30, 2020 was $274.31 million (quarter ended Mar 31, 2020), $295.38 million (quarter ended Dec 31, 2019) and $337.08 million (quarter ended Sep 30, 2019).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | - |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | 2.20 Bn |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 249.64 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 222.46 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 138.67 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 45.78 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 176.77 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | - |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | - |
| 10 | BayCom | 341.69 Mn | -606.12 Mn | - | 218.48 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 218.48 Mn |
| Jun 30, 2026 | 177.38 Mn |
| Mar 31, 2026 | 305.90 Mn |
| Dec 31, 2025 | 206.51 Mn |
| Sep 30, 2025 | 228.45 Mn |
| Jun 30, 2025 | 291.62 Mn |
| Mar 31, 2025 | 256.55 Mn |
| Dec 31, 2024 | 364.03 Mn |
| Sep 30, 2024 | 301.28 Mn |
| Jun 30, 2024 | 391.21 Mn |
| Mar 31, 2024 | 348.33 Mn |
| Dec 31, 2023 | 307.54 Mn |
| Sep 30, 2023 | 301.93 Mn |
| Jun 30, 2023 | 250.20 Mn |
| Mar 31, 2023 | 197.54 Mn |
| Dec 31, 2022 | 176.82 Mn |
| Sep 30, 2022 | 224.68 Mn |
| Jun 30, 2022 | 354.51 Mn |
| Mar 31, 2022 | 427.20 Mn |
| Dec 31, 2021 | 379.69 Mn |
BayCom Cash & Equivalents 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=cash-and-equivalents&ticker=BCML&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "BCML", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=BCML&period=max&api_key=YOUR_API_KEY");
const data = await res.json();