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Broadstone Net Lease, Inc.: filings

Every Broadstone Net Lease, 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-Q/A2026-07-29fiscal Q2 2026351070001424182-26-000068
10-Q2026-04-30fiscal Q1 202635750001424182-26-000037
10-K2026-02-19fiscal FY 202536990001424182-26-000012
10-Q2025-10-29fiscal Q3 2025361130001424182-25-000037
10-Q2025-07-31fiscal Q2 2025361090001424182-25-000021
10-Q2025-05-01fiscal Q1 202535740000950170-25-061814
10-K2025-02-20fiscal FY 202434940000950170-25-024123
10-Q2024-10-31fiscal Q3 2024341070000950170-24-119514
10-Q2024-07-31fiscal Q2 2024341030000950170-24-088527
10-Q2024-05-02fiscal Q1 202434730000950170-24-052047
10-K2024-02-22fiscal FY 202334930000950170-24-018725
10-Q2023-11-02fiscal Q3 2023331040000950170-23-058155
10-Q2023-08-03fiscal Q2 202333990000950170-23-037932
10-Q2023-05-04fiscal Q1 202333700000950170-23-017821
10-K2023-02-23fiscal FY 202235950000950170-23-004115
10-Q2022-11-03fiscal Q3 2022321040000950170-22-021856
10-Q2022-08-04fiscal Q2 202231950000950170-22-014729
10-Q2022-05-05fiscal Q1 202231670000950170-22-007492
10-K2022-02-23fiscal FY 202136990001193125-22-049969
10-Q2021-11-02fiscal Q3 2021361140000950170-21-002653
10-Q2021-08-04fiscal Q2 2021351070000950170-21-000787
10-Q2021-05-05fiscal Q1 202135750001564590-21-024046
10-K2021-02-25fiscal FY 2020351350001564590-21-008838
10-Q2020-11-05fiscal Q3 2020331000001564590-20-051393
10-Q2020-08-04fiscal Q2 202028800001564590-20-036023
10-Q2020-05-07fiscal Q1 202028590001564590-20-022961
10-K2020-02-27fiscal FY 2019271130001564590-20-007050
10-Q2019-11-12fiscal Q3 201927840001564590-19-042607
10-Q2019-08-07fiscal Q2 201927800001564590-19-029913
10-Q2019-05-07fiscal Q1 201927580001564590-19-016315
10-K2019-03-14fiscal FY 2018251100001564590-19-007675
10-Q2018-11-05fiscal Q3 201826750001564590-18-026666
10-Q2018-08-10fiscal Q2 201826750001564590-18-021208
10-Q2018-05-08fiscal Q1 201823510001564590-18-011584
10-K2018-03-15fiscal FY 2017221080001564590-18-005758
10-Q2017-11-13fiscal Q3 201723690001564590-17-023460
10-Q2017-08-10fiscal Q2 201723690001564590-17-017165

Inspect the source

Entity
Broadstone Net Lease, Inc. / CIK 0001424182
Captured
2026-09-20T08:03:36.691Z
SEC response SHA-256
fb10c234f72afeb0db53f93bbe78582f328a5a0ab631ad59d645d87423095da8

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/0001424182.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"])))