Skip to content

HF FOODS GROUP INC.: filings

Every HF FOODS GROUP 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-Q2026-08-10fiscal Q2 2026491400001680873-26-000060
10-Q2026-05-11fiscal Q1 2026491020001680873-26-000027
10-K2026-03-16fiscal FY 2025531070001680873-26-000015
10-Q2025-11-10fiscal Q3 2025481420001680873-25-000074
10-Q2025-08-11fiscal Q2 2025481380001628280-25-039583
10-Q2025-05-12fiscal Q1 2025481000001680873-25-000036
10-K2025-03-17fiscal FY 2024521370001680873-25-000006
10-Q2024-11-12fiscal Q3 2024471400001680873-24-000065
10-Q2024-08-09fiscal Q2 2024471360001680873-24-000058
10-Q2024-05-10fiscal Q1 202447970001680873-24-000029
10-K2024-03-26fiscal FY 2023511360001680873-24-000010
10-Q2023-11-09fiscal Q2 2023481440001628280-23-038280
10-Q2023-08-09fiscal Q2 2023491420001680873-23-000022
10-Q2023-05-10fiscal Q1 2023511060001680873-23-000018
10-K2023-03-31fiscal FY 2022531410001680873-23-000011
10-Q2023-01-31fiscal Q3 2022511480001680873-23-000008
10-Q2023-01-31fiscal Q2 2022511450001680873-23-000007
10-Q2023-01-31fiscal Q1 2022501030001680873-23-000006
10-K2023-01-31fiscal FY 2021524170001680873-23-000004
10-Q2021-11-15fiscal Q3 2021521600001680873-21-000045
10-Q2021-08-09fiscal Q2 2021501430001680873-21-000033
10-Q2021-05-10fiscal Q1 202147990001680873-21-000015
10-K2021-03-16fiscal FY 202047960001680873-21-000006
10-Q2020-11-09fiscal Q3 2020511380001680873-20-000015
10-Q2020-08-10fiscal Q2 2020511340001680873-20-000008
10-Q2020-05-18fiscal Q1 2020511060001437749-20-011101
10-K2020-03-16fiscal FY 201949960001437749-20-005276
10-Q2019-11-14fiscal Q3 2019471290001437749-19-022953
10-Q2019-08-14fiscal Q2 2019471240001437749-19-016813
10-Q2019-05-15fiscal Q1 201946960001437749-19-010083
10-K2019-04-01fiscal FY 201843900001437749-19-006198
10-Q2018-11-14fiscal Q3 2018421090001615774-18-012739
10-Q2018-08-09fiscal Q2 201818430001615774-18-007784
10-Q2018-05-15fiscal Q1 201816310001615774-18-003854
10-K2018-03-29fiscal FY 201717320001615774-18-002196
10-Q2017-11-13fiscal Q3 201717390001615774-17-006582
10-Q2017-09-19fiscal Q2 201713270001615774-17-005205

Inspect the source

Entity
HF FOODS GROUP INC. / CIK 0001680873
Captured
2026-09-21T17:24:57.885Z
SEC response SHA-256
176ecefa58d6ebc55212545acec1a3fbb8601a4a07a8ee70700be3328c3d92a6

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/0001680873.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"])))