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Zebra Technologies Corporation: other nonoperating income or expense

Other nonoperating income or expense for Zebra Technologies Corporation. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Zebra Technologies Corporation financial histories

What this measure means

Other income or expense outside operations under this concept. The composition is filer-specific and can include one-time items.

Exact concept: us-gaap:OtherNonoperatingIncomeExpense. 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 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Other nonoperating income or expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-14,000,000USD2026-02-1210-K · 0001628280-26-007668
2024-01-012024-12-31-14,000,000USD2026-02-1210-K · 0001628280-26-007668
2023-01-012023-12-31-12,000,000USD2026-02-1210-K · 0001628280-26-007668
2022-01-012022-12-31-5,000,000USD2025-02-1310-K · 0000877212-25-000027
2021-01-012021-12-31-1,000,000USD2024-02-1510-K · 0000877212-24-000029
2020-01-012020-12-313,000,000USD2023-02-1610-K · 0000877212-23-000025
2019-01-012019-12-311,000,000USD2022-02-1010-K · 0000877212-22-000026
2018-01-012018-12-3110,000,000USD2021-02-1110-K · 0000877212-21-000008
2017-01-012017-12-31-6,000,000USD2020-02-1310-K · 0000877212-20-000006
2016-01-012016-12-31-11,000,000USD2019-02-1410-K · 0000877212-19-000011
2015-01-012015-12-31-1,000,000USD2018-02-2210-K · 0000877212-18-000011
2014-01-012014-12-31-1,000,000USD2017-02-2710-K · 0000877212-17-000009
2013-01-012013-12-315,000,000USD2016-11-1410-K/A · 0000877212-16-000023
2012-01-012012-12-31-1,514,000USD2015-03-1710-K · 0001193125-15-095560
2011-01-012011-12-31-2,255,000USD2014-02-2010-K · 0001193125-14-060748
2010-01-012010-12-31-1,117,000USD2013-02-2110-K · 0001193125-13-069145
2009-01-012009-12-31-787,000USD2012-02-2310-K · 0001193125-12-075320
2008-01-012008-12-31-1,366,000USD2011-02-2410-K · 0001193125-11-045274

Related financial histories

Inspect the source

Entity
Zebra Technologies Corporation / CIK 0000877212
Captured
2026-09-20T05:01:16.309Z
SEC response SHA-256
088b7ddd8e1833b9c11a792460a164736754bd47928fbabf9917ae20d8ae064c

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/0000877212.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"])))