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BIRKS GROUP INC.: retained earnings or deficit

Retained earnings or deficit for BIRKS GROUP INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All BIRKS GROUP INC. financial histories

What this measure means

Accumulated undistributed earnings or deficit at the reporting date. This balance is not cash available for distribution.

Exact concept: us-gaap:RetainedEarningsAccumulatedDeficit. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2011-03-26 to 2026-03-28. The SEC response was captured on 2026-09-20.

Coverage by original unit

These are separate reported series. A newer period in one unit does not update another unit’s history or establish a currency conversion.

Selected filing history

Retained earnings or deficit in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2026-03-28-141,690,000CAD2026-07-2120-F · 0001193125-26-310554
At date2025-03-29-138,295,000CAD2026-07-2120-F · 0001193125-26-310554
At date2025-03-29-138,295,000USD2025-07-2520-F · 0001193125-25-165500
At date2024-03-30-125,476,000USD2025-07-2520-F · 0001193125-25-165500
At date2023-03-25-120,845,000USD2024-07-1820-F/A · 0001193125-24-181045
At date2022-03-26-113,413,000USD2023-06-2320-F · 0001193125-23-172888
At date2021-03-27-114,700,000USD2022-06-2420-F · 0001193125-22-180536
At date2020-03-28-108,862,000USD2021-06-1720-F · 0001193125-21-193376
At date2019-03-30-98,473,000USD2020-07-0820-F · 0001193125-20-189784
At date2018-03-31-79,787,000USD2019-06-2420-F · 0001193125-19-179036
At date2017-03-25-73,921,000USD2018-07-0320-F · 0001193125-18-212317
At date2016-03-26-78,849,000USD2017-06-2320-F · 0001193125-17-211253
At date2015-03-28-84,287,000USD2016-06-3020-F · 0001193125-16-637910
At date2014-03-29-75,655,000USD2015-06-2620-F · 0001193125-15-237397
At date2013-03-30-69,854,000USD2014-07-2520-F · 0001193125-14-280412
At date2012-03-31-71,367,000USD2013-07-0320-F · 0001193125-13-282552
At date2011-03-26-71,586,000USD2012-07-0320-F · 0001193125-12-293411

Related financial histories

Inspect the source

Entity
BIRKS GROUP INC. / CIK 0001179821
Captured
2026-09-20T07:45:09.505Z
SEC response SHA-256
55974861c39186d8ea6902b14975ff4a8f05a109d5355ae5cf7ed1df065193e9

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

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/0001179821.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"])))