HIGH SIERRA TECHNOLOGIES, INC.: financial reference
Explore HIGH SIERRA TECHNOLOGIES, INC. financial histories from SEC filings, with original units, reporting periods, filing dates and downloadable source data.
Reported financial histories
Choose a measure to inspect its definition, complete selected history and filing provenance. Each row shows the latest period available for that selected concept and original unit. Separate currencies and reporting intervals remain separate rows. Coverage dates can differ between concepts. A recent capture does not imply recent accounting coverage; these amounts are not prices.
| Measure | Period start | Period end | Value | Unit | Filed |
|---|---|---|---|---|---|
| Total assets | At date | 2022-12-31 | 101,502 | USD | 2023-04-17 |
| Total liabilities | At date | 2022-12-31 | 611,785 | USD | 2023-04-17 |
| Stockholders equity | At date | 2022-12-31 | -510,283 | USD | 2023-04-17 |
| Cash and cash equivalents | At date | 2021-12-31 | 55,351 | USD | 2022-03-21 |
| Net income or loss | 2022-01-01 | 2022-12-31 | -323,952 | USD | 2023-04-17 |
| Operating cash flow | 2022-01-01 | 2022-12-31 | -219,659 | USD | 2023-04-17 |
| Capital expenditure payments | 2022-01-01 | 2022-12-31 | 43,435 | USD | 2023-04-17 |
| Revenue | 2020-01-01 | 2020-12-31 | 0 | USD | 2021-04-14 |
| Financing cash flow | 2022-01-01 | 2022-12-31 | 220,000 | USD | 2023-04-17 |
| Investing cash flow | 2022-01-01 | 2022-12-31 | -43,435 | USD | 2023-04-17 |
| Retained earnings or deficit | At date | 2022-12-31 | -1,464,666 | USD | 2023-04-17 |
| Basic weighted-average shares | 2022-01-01 | 2022-12-31 | 20,512,033 | shares | 2023-04-17 |
| Net property, plant and equipment | At date | 2022-12-31 | 77,386 | USD | 2023-04-17 |
| Operating income or loss | 2022-01-01 | 2022-12-31 | -238,364 | USD | 2023-04-17 |
| Current assets | At date | 2022-12-31 | 24,116 | USD | 2023-04-17 |
| Interest expense | 2022-01-01 | 2022-12-31 | 66,473 | USD | 2023-04-17 |
| Current liabilities | At date | 2022-12-31 | 561,785 | USD | 2023-04-17 |
| Current accounts payable | At date | 2020-12-31 | 58,373 | USD | 2021-04-14 |
| Operating expenses | 2022-01-01 | 2022-12-31 | 238,364 | USD | 2023-04-17 |
Inspect the source
- Entity
- HIGH SIERRA TECHNOLOGIES, INC. / CIK 0001365388
- Captured
- 2026-09-20T07:56:33.024Z
- SEC response SHA-256
cfc7e16e3065398f8b13963f1f5f17884edc7e4ec95812cf1092d52aac40e273
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001365388.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))