Ridgetech, Inc.: filings
Every Ridgetech, Inc. annual and quarterly report in the SEC record with the published financial measures it tagged, 5 filings, each linked to its SEC index.
Filings with published measures
Each page shows what one filing reported, as tagged in that filing, with the periods it covered. Later filings can restate a value; the company overview shows the latest-filed value per period.
| Form | Filed | Fiscal period | Measures | Facts | SEC accession |
|---|---|---|---|---|---|
| 20-F | 2026-07-31 | fiscal FY 2026 | 52 | 133 | 0001213900-26-083638 |
| 20-F | 2025-07-28 | fiscal FY 2025 | 52 | 130 | 0001213900-25-067924 |
| 20-F | 2024-07-30 | fiscal FY 2024 | 52 | 130 | 0001013762-24-002657 |
| 20-F | 2023-06-15 | fiscal FY 2023 | 49 | 127 | 0001213900-23-049280 |
| 20-F | 2022-07-28 | fiscal FY 2022 | 50 | 128 | 0001213900-22-042481 |
Inspect the source
- Entity
- Ridgetech, Inc. / CIK 0001856084
- Captured
- 2026-09-21T17:38:56.773Z
- SEC response SHA-256
159ec0aa9d2b12b66ca905bf04c2b57fb117cb9c400d49dfb65d8126e48e60bf
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.
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.
- Get an API key and run your first validation
- Connect the MCP server to your coding assistant
- Inspect the ALPHAC engine on GitHub
- Read the MCP server source and integration examples
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001856084.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"])))