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LOGILITY SUPPLY CHAIN SOLUTIONS, INC.: retained earnings or deficit

Retained earnings or deficit for LOGILITY SUPPLY CHAIN SOLUTIONS, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All LOGILITY SUPPLY CHAIN SOLUTIONS, 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 2011-04-30 to 2024-04-30. The SEC response was captured on 2026-09-21.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Retained earnings or deficit in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2024-04-30-26,930,000USD2024-07-0110-K · 0001628280-24-030530
At date2023-04-30-23,479,000USD2024-07-0110-K · 0001628280-24-030530
At date2022-04-30-17,236,000USD2023-07-1310-K · 0001628280-23-024860
At date2021-04-30-15,287,000USD2022-06-2910-K · 0001628280-22-018227
At date2020-04-30-9,013,000USD2021-07-0910-K · 0001628280-21-013701
At date2019-04-30-1,729,000USD2020-07-1010-K · 0001628280-20-010300
At date2018-05-015,119,000USD2019-07-1510-K · 0001628280-19-008742
At date2018-04-303,366,000USD2019-07-1510-K · 0001628280-19-008742
At date2017-04-304,608,000USD2018-07-1310-K · 0001193125-18-217611
At date2016-04-302,897,000USD2017-07-1410-K · 0001193125-17-228535
At date2015-04-304,159,000USD2016-07-1410-K · 0001193125-16-648270
At date2014-04-307,368,000USD2015-07-1010-K · 0001193125-15-250260
At date2013-04-305,398,000USD2014-07-1410-K · 0001193125-14-267720
At date2012-04-308,024,000USD2013-07-1210-K · 0001193125-13-289120
At date2011-04-306,257,000USD2012-07-1210-K · 0001193125-12-300790

Related financial histories

Inspect the source

Entity
LOGILITY SUPPLY CHAIN SOLUTIONS, INC. / CIK 0000713425
Captured
2026-09-21T17:16:53.613Z
SEC response SHA-256
cbb9011744c60aec29f76ed0c4993e95b2e8de92567b87b3e9fbec2881152564

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/0000713425.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"])))