Skip to content

ARGO GROUP INTERNATIONAL HOLDINGS, INC.: depreciation expense

Depreciation expense for ARGO GROUP INTERNATIONAL HOLDINGS, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All ARGO GROUP INTERNATIONAL HOLDINGS, INC. financial histories

What this measure means

Depreciation recognized for the period under this concept. It is a noncash allocation of asset cost and may exclude amortization and depletion reported elsewhere.

Exact concept: us-gaap:Depreciation. 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 2024-12-31. The SEC response was captured on 2026-09-21.

Selected filing history

Depreciation expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-01-012024-12-3111,400,000USD2025-03-2510-K · 0001628280-25-014609
2023-01-012023-11-159,100,000USD2025-03-2510-K · 0001628280-25-014609
2022-01-012022-12-3122,300,000USD2025-03-2510-K · 0001628280-25-014609
2021-01-012021-12-3123,900,000USD2024-03-1910-K · 0001628280-24-011791
2020-01-012020-12-3124,100,000USD2023-03-0610-K · 0001628280-23-006451
2019-01-012019-12-3124,400,000USD2022-03-1610-K · 0001628280-22-006331
2018-01-012018-12-3124,500,000USD2021-03-1510-K · 0001628280-21-004668
2017-01-012017-12-3124,100,000USD2020-02-2810-K · 0001628280-20-002567
2016-01-012016-12-3120,900,000USD2019-02-2610-K · 0001628280-19-001883
2015-01-012015-12-3117,500,000USD2018-02-2710-K · 0001564590-18-003547
2014-01-012014-12-3115,100,000USD2017-02-2410-K · 0001564590-17-002394
2013-01-012013-12-3115,500,000USD2016-02-2610-K · 0001564590-16-013542
2012-01-012012-12-3112,600,000USD2015-02-2710-K · 0001564590-15-001103
2011-01-012011-12-3110,100,000USD2014-02-2810-K · 0001193125-14-077302
2010-12-312011-12-3110,100,000USD2013-02-2810-K · 0001193125-13-084723
2010-01-012010-12-318,500,000USD2012-02-2910-K · 0001193125-12-089089
2009-12-312010-12-318,500,000USD2013-02-2810-K · 0001193125-13-084723
2009-01-012009-12-317,600,000USD2012-02-2910-K · 0001193125-12-089089

Related financial histories

Inspect the source

Entity
ARGO GROUP INTERNATIONAL HOLDINGS, INC. / CIK 0001091748
Captured
2026-09-21T17:18:15.282Z
SEC response SHA-256
8f4e3573212e327b0a95896286e8dc9e80f214b51ffe68cd439f5ba09a58c0af

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/0001091748.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"])))