Skip to content

GENERAL MOTORS COMPANY: operating income or loss

Operating income or loss for GENERAL MOTORS COMPANY. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All GENERAL MOTORS COMPANY financial histories

What this measure means

Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.

Exact concept: us-gaap:OperatingIncomeLoss. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Operating income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-312,909,000,000USD2026-01-2710-K · 0001467858-26-000013
2024-01-012024-12-3112,784,000,000USD2026-01-2710-K · 0001467858-26-000013
2023-01-012023-12-319,298,000,000USD2026-01-2710-K · 0001467858-26-000013
2022-01-012022-12-3110,315,000,000USD2025-01-2810-K · 0001467858-25-000032
2021-01-012021-12-319,324,000,000USD2024-01-3010-K · 0001467858-24-000031
2020-01-012020-12-316,634,000,000USD2023-01-3110-K · 0001467858-23-000029
2019-01-012019-12-315,481,000,000USD2022-02-0210-K · 0001467858-22-000034
2018-01-012018-12-314,445,000,000USD2021-02-1010-K · 0001467858-21-000037
2017-01-012017-12-318,661,000,000USD2020-02-0510-K · 0001467858-20-000028
2016-01-012016-12-318,686,000,000USD2019-02-0610-K · 0001467858-19-000033
2015-01-012015-12-315,538,000,000USD2018-02-0610-K · 0001467858-18-000022
2014-01-012014-12-311,530,000,000USD2017-02-0710-K · 0001467858-17-000028
2013-01-012013-12-315,131,000,000USD2016-02-0310-K · 0001467858-16-000255
2012-01-012012-12-31-30,363,000,000USD2015-02-0410-K · 0001467858-15-000036
2011-01-012011-12-315,656,000,000USD2014-02-0610-K · 0001467858-14-000043
2010-01-012010-12-315,108,000,000USD2013-02-1510-K · 0001467858-13-000025

Related financial histories

Inspect the source

Entity
GENERAL MOTORS COMPANY / CIK 0001467858
Captured
2026-09-20T09:07:00.875Z
SEC response SHA-256
0aadbfd12c0d97ba9743acec6b3ad5b0b6082fab7fbc8f1edbbb7d38fe050e38

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/0001467858.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"])))