BIMERGEN ENERGY CORPORATION: retained earnings or deficit

Name: BIMERGEN ENERGY CORPORATION: retained earnings or deficit
Creator: BIMERGEN ENERGY CORPORATION

Retained earnings or deficit for BIMERGEN ENERGY CORPORATION. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All BIMERGEN ENERGY CORPORATION 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 2009-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Retained earnings or deficit in original reported units, latest-filed observation per period
Period start	Period end	Value	Unit	Filed	Source filing
At date	2025-12-31	-9,748,121	USD	2026-03-31	10-K · 0001493152-26-014356
At date	2024-12-31	-4,774,699	USD	2026-03-31	10-K · 0001493152-26-014356
At date	2023-12-31	-2,017,012	USD	2025-05-30	10-K · 0001641172-25-013018
At date	2022-12-31	-1,096,594	USD	2024-04-01	10-K · 0001493152-24-012444
At date	2021-12-31	-284,959	USD	2023-03-31	10-K · 0001493152-23-010282
At date	2020-12-31	-20,138,182	USD	2022-03-16	10-K · 0001185185-22-000287
At date	2019-12-31	-19,840,788	USD	2021-03-26	10-K · 0001185185-21-000395
At date	2018-12-31	-18,228,219	USD	2020-03-30	10-K · 0001185185-20-000382
At date	2017-12-31	-17,556,564	USD	2019-04-01	10-K · 0001185185-19-000482
At date	2016-12-31	-17,150,640	USD	2018-03-29	10-K · 0001185185-18-000544
At date	2015-12-31	-16,394,695	USD	2017-03-28	10-K · 0001185185-17-000672
At date	2014-12-31	-15,337,091	USD	2016-03-29	10-K · 0001185185-16-004041
At date	2013-12-31	-13,644,433	USD	2015-03-31	10-K · 0001185185-15-000736
At date	2012-12-31	-13,018,362	USD	2014-03-31	10-K · 0001185185-14-000759
At date	2011-12-31	-12,588,144	USD	2013-04-01	10-K · 0001144204-13-019134
At date	2010-12-31	-13,903,148	USD	2012-03-30	10-K · 0001144204-12-018919
At date	2009-12-31	-20,278,547	USD	2022-03-16	10-K · 0001185185-22-000287

Related financial histories

Inspect the source

Entity: BIMERGEN ENERGY CORPORATION / CIK 0001066764
Captured: 2026-09-20T05:18:58.951Z
SEC response SHA-256: b354e8f4668bf8295ed5a4d88d442cf5ec7325705a5aa07140cba56e5eebe32d

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/0001066764.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"])))