Skip to content

cbdMD, Inc.: filings

Every cbdMD, 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-Q2026-08-13fiscal Q3 2026421050001437749-26-027665
10-Q2026-05-14fiscal Q2 2026411040001437749-26-017042
10-Q2026-02-17fiscal Q1 202539780001437749-26-004343
10-K2025-12-19fiscal FY 202548940001437749-25-038435
10-Q2025-08-14fiscal Q3 2025431170001437749-25-026930
10-Q2025-05-15fiscal Q2 2025431130001437749-25-017178
10-Q2025-02-13fiscal Q1 202541810001437749-25-003752
10-K2024-12-18fiscal FY 2024481070001437749-24-037840
10-Q2024-08-14fiscal Q3 2024461250001437749-24-026784
10-Q2024-05-15fiscal Q2 2024481260001437749-24-017042
10-Q2024-02-13fiscal Q1 202442830001437749-24-003902
10-K2023-12-22fiscal FY 2023481080001437749-23-035228
10-Q2023-08-10fiscal Q3 2023461280001437749-23-023130
10-Q2023-05-15fiscal Q2 2023451220001437749-23-014599
10-Q2023-02-13fiscal Q1 202345900001437749-23-003144
10-K2022-12-15fiscal FY 2022471060001437749-22-029136
10-Q2022-08-11fiscal Q3 2022451320001437749-22-020140
10-Q2022-05-13fiscal Q2 2022421220001654954-22-006755
10-Q2022-02-10fiscal Q1 202242880001654954-22-001424
10-K2021-12-17fiscal FY 2021441050001654954-21-013292
10-Q2021-08-12fiscal Q3 2021421280001654954-21-008840
10-Q2021-05-12fiscal Q2 2021431230001654954-21-005506
10-Q2021-02-09fiscal Q1 202142870001654954-21-001364
10-K2020-12-22fiscal FY 2020451020001654954-20-013835
10-Q2020-08-12fiscal Q3 2020431240001654954-20-008894
10-Q2020-05-15fiscal Q2 2020431210001654954-20-005675
10-Q2020-02-13fiscal Q1 202044900001654954-20-001499
10-K2019-12-18fiscal FY 2019451040001654954-19-014052
10-Q2019-08-14fiscal Q3 2019441300001654954-19-009562
10-Q2019-05-15fiscal Q2 2019441260001654954-19-006099
10-Q/A2019-04-26fiscal Q1 201939810001654954-19-004888
10-Q2019-02-14fiscal Q1 201939810001654954-19-001576
10-K2018-12-12fiscal FY 201840820001654954-18-013865
10-Q2018-08-14fiscal Q3 2018421170001654954-18-009006
10-Q2018-05-15fiscal Q2 2018411150001654954-18-005463
10-Q2018-02-14fiscal Q1 201836750001654954-18-001547
10-K2017-12-26fiscal FY 201736740001654954-17-011858

Inspect the source

Entity
cbdMD, Inc. / CIK 0001644903
Captured
2026-09-19T11:19:57.378Z
SEC response SHA-256
e7b0402fb6302b7af9c050b7b76ee0c0c4c399de3a53926613f2aba30916cbe3

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/0001644903.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"])))