Skip to content

THE LOVESAC COMPANY: filings

Every THE LOVESAC COMPANY 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-Q2026-09-10fiscal Q2 2027441240001628280-26-061220
10-Q2026-06-11fiscal Q1 202744920001628280-26-042366
10-K2026-04-02fiscal FY 2026511340001628280-26-022929
10-Q2025-12-11fiscal Q3 2026441240001628280-25-056423
10-Q2025-09-11fiscal Q2 2026441240001701758-25-000016
10-Q2025-06-12fiscal Q1 202644920001628280-25-030861
10-K2025-04-10fiscal FY 2025501310001628280-25-017241
10-Q2024-12-12fiscal Q3 2025421160001628280-24-050870
10-Q2024-09-12fiscal Q2 2025411140001628280-24-040192
10-Q2024-06-13fiscal Q1 202541860001628280-24-028040
10-K2024-04-11fiscal FY 2024471220001628280-24-015804
10-Q2023-12-06fiscal Q3 2024431230001628280-23-040881
10-Q/A2023-11-30fiscal Q1 202443890001628280-23-040368
10-K/A2023-11-30fiscal FY 2023492790001628280-23-040367
10-Q2023-11-03fiscal Q2 2024431190001628280-23-036551
10-Q/A2023-11-02fiscal Q1 202443890001628280-23-036441
10-K/A2023-11-02fiscal FY 2023462730001628280-23-036432
10-Q2023-06-09fiscal Q1 202443890001628280-23-021678
10-K2023-03-29fiscal FY 2023491250001628280-23-009725
10-Q2022-12-08fiscal Q3 2023441270001628280-22-031559
10-Q2022-09-09fiscal Q2 2023441230001628280-22-024650
10-Q2022-06-08fiscal Q1 202344910001628280-22-016567
10-K2022-03-30fiscal FY 2022521350001628280-22-007882
10-Q2021-12-09fiscal Q3 2022451280001628280-21-024765
10-Q2021-09-09fiscal Q2 2022441170001213900-21-047197
10-Q2021-06-11fiscal Q1 202242850001213900-21-032094
10-K2021-04-14fiscal FY 202147940001213900-21-021548
10-Q2020-12-09fiscal Q3 2021441220001213900-20-041810
10-Q2020-09-10fiscal Q2 2021391010001213900-20-026027
10-Q2020-06-09fiscal Q1 202138780001213900-20-014515
10-K2020-04-29fiscal FY 202039800001213900-20-010439
10-Q2019-12-18fiscal Q3 2020391060001213900-19-026458
10-Q2019-09-13fiscal Q2 2020381020001213900-19-018036
10-Q2019-06-18fiscal Q1 202036740001213900-19-010970
10-K2019-05-03fiscal FY 201939790001213900-19-007792
10-Q2018-12-19fiscal Q3 201933830001213900-18-017555
10-Q2018-09-14fiscal Q2 201935880001213900-18-012589

Inspect the source

Entity
THE LOVESAC COMPANY / CIK 0001701758
Captured
2026-09-21T17:25:53.868Z
SEC response SHA-256
720078157ddba25e81b1a4b2a0ba9b54270dd750640c18b98eee5f001ecb2b84

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/0001701758.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"])))