Skip to content

PPG INDUSTRIES INC: operating income or loss

Operating income or loss for PPG INDUSTRIES INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All PPG INDUSTRIES INC 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 2009-01-01 to 2023-12-31. The SEC response was captured on 2026-09-19.

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

Operating income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2023-01-012023-12-312,675,000,000USD2024-02-1510-K · 0000079879-24-000040
2022-01-012022-12-312,042,000,000USD2024-02-1510-K · 0000079879-24-000040
2021-01-012021-12-312,171,000,000USD2024-02-1510-K · 0000079879-24-000040
2020-01-012020-12-312,109,000,000USD2023-02-1610-K · 0000079879-23-000007
2019-01-012019-12-312,271,000,000USD2022-02-1710-K · 0000079879-22-000009
2018-01-012018-12-312,118,000,000USD2021-02-1810-K · 0000079879-21-000008
2017-01-012017-12-312,292,000,000USD2020-02-2010-K · 0000079879-20-000008
2016-01-012016-12-312,382,000,000USD2019-02-2110-K · 0000079879-19-000008
2015-01-012015-12-312,287,000,000USD2018-06-2810-K/A · 0000079879-18-000039
2014-01-012014-12-312,191,000,000USD2017-02-1610-K · 0000079879-17-000009
2013-01-012013-12-311,923,000,000USD2016-02-1810-K · 0000079879-16-000065
2012-01-012012-12-311,629,000,000USD2015-02-1910-K · 0000079879-15-000009
2011-01-012011-12-311,657,000,000USD2014-02-2010-K · 0000079879-14-000010
2010-01-012010-12-311,722,000,000USD2013-02-2110-K · 0000079879-13-000016
2009-01-012009-12-311,186,000,000USD2012-02-1610-K · 0001193125-12-064763

Related financial histories

Inspect the source

Entity
PPG INDUSTRIES INC / CIK 0000079879
Captured
2026-09-19T14:51:22.035Z
SEC response SHA-256
d2115215c7b5332e873631ef48ba58e08b126192b275c4f6043c31c439948a74

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/0000079879.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"])))