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OLD Dominion Freight Line, Inc.: share-based compensation expense

OLD Dominion Freight Line share-based compensation expense: $12.9 million for the year ending 2025-12-31, up 13.3% on the year. 12 values since 2014.

All OLD Dominion Freight Line, Inc. financial histories

At a glance

OLD Dominion Freight Line reported share-based compensation expense of $12.9 million for the year ending 2025-12-31, up 13.3% from $11.3 million a year earlier. Across the last five reported years it ranged from $11.1 million (2023-12-31) to $15.9 million (2022-12-31).

Computed from the values in the table below, in USD; each links to the filing it came from.

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 2014-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Share-based compensation expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3112,854,000USD2026-02-2410-K · 0001193125-26-067161 SEC
2024-01-012024-12-3111,349,000USD2026-02-2410-K · 0001193125-26-067161 SEC
2023-01-012023-12-3111,080,000USD2026-02-2410-K · 0001193125-26-067161 SEC
2022-01-012022-12-3115,893,000USD2025-02-2510-K · 0000950170-25-026661 SEC
2021-01-012021-12-3115,039,000USD2024-02-2610-K · 0000950170-24-020176 SEC
2020-01-012020-12-3111,337,000USD2023-02-2210-K · 0000950170-23-003783 SEC
2019-01-012019-12-3116,717,000USD2022-02-2310-K · 0001564590-22-006303 SEC
2018-01-012018-12-314,894,000USD2021-02-2410-K · 0001564590-21-008056 SEC
2017-01-012017-12-313,242,000USD2020-02-2610-K · 0001564590-20-006626 SEC
2016-01-012016-12-311,410,000USD2019-02-2710-K · 0001564590-19-004755 SEC
2015-01-012015-12-310USD2018-02-2710-K · 0000878927-18-000005 SEC
2014-01-012014-12-310USD2017-02-2710-K · 0000878927-17-000005 SEC

Related OLD DOMINION FREIGHT LINE, INC. histories

All 48 OLD Dominion Freight Line histories

Inspect the source

Entity
OLD DOMINION FREIGHT LINE, INC. / CIK 0000878927
Captured
SEC response SHA-256
cfe7fd09a23eb4d6d7bb463f37abe15444151e095b394a457b7e41b69d6f3046

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.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000878927.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"])))