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Hawkeye Digital, Inc.: filings

Every Hawkeye Digital, Inc. annual and quarterly report in the SEC record with the published financial measures it tagged, 37 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.

FormFiledFiscal periodMeasuresFactsSEC accession
10-K2026-09-11fiscal FY 202632660001683168-26-007087
10-Q2026-05-13fiscal Q3 202628960001683168-26-003821
10-Q2026-02-23fiscal Q2 202622700001477932-26-000977
10-Q2025-12-05fiscal Q1 202622480001477932-25-008814
10-K2025-10-15fiscal FY 202524490001477932-25-007562
10-Q2025-05-13fiscal Q3 202522760001477932-25-003614
10-Q2025-01-28fiscal Q2 202522700001477932-25-000487
10-Q/A2024-11-20fiscal Q1 202521460001477932-24-007498
10-K2024-09-30fiscal FY 202426540001477932-24-006059
10-Q2024-04-29fiscal Q3 202423730001477932-24-002373
10-Q2024-02-08fiscal Q2 202421660001477932-24-000592
10-Q2023-11-17fiscal Q1 202321460001477932-23-008599
10-K2023-10-17fiscal FY 202323470001477932-23-007680
10-Q2023-05-22fiscal Q3 202324750001477932-23-003816
10-Q2023-01-31fiscal Q2 202320650001477932-23-000629
10-Q2022-12-15fiscal Q1 202320490001477932-22-009317
10-K2022-12-14fiscal FY 202230620001477932-22-009275
10-Q2022-05-19fiscal Q3 202225780001477932-22-003660
10-Q2022-04-14fiscal Q2 202225740001477932-22-002291
10-Q2021-11-15fiscal Q1 202224510001477932-21-008275
10-K2021-10-13fiscal FY 202132650001477932-21-007236
10-K/A2021-07-01fiscal FY 202032650001477932-21-004400
10-Q/A2021-07-01fiscal Q2 202133900001477932-21-004399
10-Q/A2021-07-01fiscal Q1 202129610001477932-21-004398
10-Q2021-05-13fiscal Q3 202130900001477932-21-003103
10-Q/A2021-04-14fiscal Q2 202133900001477932-21-002286
10-Q/A2021-04-14fiscal Q1 202129610001477932-21-002285
10-K/A2021-04-14fiscal FY 202032650001477932-21-002284
10-Q2021-03-09fiscal Q2 202133900001477932-21-001326
10-Q2021-02-26fiscal Q1 202129610001477932-21-001115
10-K2021-02-01fiscal FY 202032650001477932-21-000520
10-Q2020-06-29fiscal Q3 202024750001477932-20-003601
10-Q2020-04-27fiscal Q2 201918470001477932-20-002210
10-Q2020-01-17fiscal Q1 202018390001477932-20-000286
10-K2019-12-09fiscal FY 201922410001477932-19-007005
10-Q2019-05-16fiscal Q2 201924410001674796-19-000077
10-Q2019-02-13fiscal Q2 201920340001674796-19-000013

Inspect the source

Entity
Hawkeye Digital, Inc. / CIK 0001750777
Captured
2026-09-21T17:29:03.469Z
SEC response SHA-256
0624035ab7cb66008429c675c54722a3c9e40427c33dd76729af5bd355497a62

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001750777.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"])))