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TERADYNE, INC.: share-based compensation expense

Share-based compensation expense for TERADYNE, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All TERADYNE, INC. financial histories

What this measure means

Reported noncash expense for share-based payment arrangements. Noncash treatment does not mean the awards have no economic cost to shareholders.

Exact concept: us-gaap:ShareBasedCompensation. 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 2026-09-19.

Selected filing history

Share-based compensation expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3163,999,000USD2026-02-1910-K · 0001193125-26-059002
2024-01-012024-12-3160,122,000USD2026-02-1910-K · 0001193125-26-059002
2023-01-012023-12-3157,682,000USD2026-02-1910-K · 0001193125-26-059002
2022-01-012022-12-3148,228,000USD2025-02-2010-K · 0000950170-25-023784
2021-01-012021-12-3145,643,000USD2024-02-2210-K · 0000950170-24-018701
2020-01-012020-12-3144,906,000USD2023-02-2210-K · 0001193125-23-044711
2019-01-012019-12-3137,897,000USD2022-02-2310-K · 0001193125-22-049828
2018-01-012018-12-3133,577,000USD2021-02-2210-K · 0001193125-21-050735
2017-01-012017-12-3134,097,000USD2020-03-0210-K · 0001193125-20-058676
2016-01-012016-12-3130,750,000USD2019-03-0110-K · 0001193125-19-059974
2015-01-012015-12-3130,451,000USD2018-03-0110-K · 0001193125-18-066579
2014-01-012014-12-3140,307,000USD2017-03-0110-K · 0001193125-17-064638
2013-01-012013-12-3136,612,000USD2016-02-2910-K · 0001193125-16-484381
2012-01-012012-12-3139,920,000USD2015-02-2710-K · 0001193125-15-067671
2011-01-012011-12-3132,337,000USD2014-02-2810-K · 0001193125-14-077218
2010-01-012010-12-3129,777,000USD2013-03-0110-K · 0001193125-13-087821
2009-01-012009-12-3124,354,000USD2012-02-2910-K · 0001193125-12-087457
2008-01-012008-12-3122,250,000USD2011-03-0110-K · 0001193125-11-051703

Related financial histories

Inspect the source

Entity
TERADYNE, INC. / CIK 0000097210
Captured
2026-09-19T14:53:19.894Z
SEC response SHA-256
e63938f59166b737c6c5aec9f42095752ee968c24e9c7f8c2fd4053f51572e41

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/0000097210.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"])))