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GRAN TIERRA ENERGY INC.: basic weighted-average shares

Basic weighted-average shares for GRAN TIERRA ENERGY INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All GRAN TIERRA ENERGY INC. financial histories

What this measure means

Time-weighted shares used for basic earnings per share. This denominator differs from shares outstanding at a single reporting date.

Exact concept: us-gaap:WeightedAverageNumberOfSharesOutstandingBasic. 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

Basic weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3135,435,782shares2026-03-0410-K · 0001273441-26-000010
2024-01-012024-12-3132,042,897shares2026-03-0410-K · 0001273441-26-000010
2023-01-012023-12-3133,469,828shares2026-03-0410-K · 0001273441-26-000010
2022-01-012022-12-3136,445,546shares2025-02-2410-K · 0001273441-25-000002
2021-01-012021-12-3136,702,290shares2024-02-2010-K · 0001273441-24-000006
2020-01-012020-12-31366,981,556shares2023-02-2210-K · 0001273441-23-000005
2019-01-012019-12-31376,495,306shares2022-02-2310-K · 0001273441-22-000007
2018-01-012018-12-31390,930,453shares2020-02-2710-K · 0001273441-20-000007
2017-01-012017-12-31396,683,593shares2020-02-2710-K · 0001273441-20-000007
2016-01-012016-12-31320,851,538shares2019-04-1610-K · 0001144204-19-019750
2015-01-012015-12-31285,333,869shares2016-02-2910-K · 0001273441-16-000052
2014-01-012014-12-31284,715,785shares2016-02-2910-K · 0001273441-16-000052
2013-01-012013-12-31282,808,497shares2016-02-2910-K · 0001273441-16-000052
2012-01-012012-12-31280,741,255shares2015-03-0210-K · 0001273441-15-000011
2011-01-012011-12-31273,491,564shares2014-02-2610-K · 0001273441-14-000008
2010-01-012010-12-31253,697,076shares2013-02-2610-K · 0001273441-13-000012
2009-01-012009-12-31241,258,568shares2012-02-2710-K · 0001140361-12-010944
2008-01-012008-12-31123,421,898shares2011-02-2510-K · 0001144204-11-010891

Related financial histories

Inspect the source

Entity
GRAN TIERRA ENERGY INC. / CIK 0001273441
Captured
2026-09-20T07:47:52.316Z
SEC response SHA-256
9eeddc412ff5a790fb95d17efbbfda08b0c75ed46811f18dc0dc4f2dcb85fe0b

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/0001273441.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"])))