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AGENUS INC: diluted weighted-average shares

Diluted weighted-average shares for AGENUS INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AGENUS INC financial histories

What this measure means

Weighted-average shares used for diluted earnings per share. Potential shares are included under the applicable dilution rules, not simply added to outstanding shares.

Exact concept: us-gaap:WeightedAverageNumberOfDilutedSharesOutstanding. 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 2020-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Reading these values

This selected numerical history matches Basic weighted-average shares for the same reporting intervals and original units. The accounting definitions remain distinct. Equal values do not establish that the concepts are interchangeable or explain why they match; filing dates and accessions may differ. Compare the definitions and source filings before combining them.

Context from the filing

For 2023–2025, Agenus includes common shares issuable under its directors’ deferred-compensation plan in basic EPS. Other potential dilution is excluded because the common-stockholder result is a loss. The numerator reflects preferred dividends and noncontrolling interests. Reported 2025 EPS rounds to zero despite a common-stockholder loss; zero EPS does not mean break-even. The share counts are presented in thousands and tagged with scale three. The filing already adjusts applicable share and per-share information for the 2024 one-for-twenty reverse split; no second adjustment is applied. Read the source filing.

Selected filing history

Diluted weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3129,734,000shares2026-03-1610-K · 0001193125-26-108632
2024-01-012024-12-3121,473,000shares2026-03-1610-K · 0001193125-26-108632
2023-01-012023-12-3117,894,000shares2026-03-1610-K · 0001193125-26-108632
2022-01-012022-12-3114,087,000shares2025-03-1710-K · 0000950170-25-040289
2021-01-012021-12-31228,919shares2024-03-1410-K · 0000950170-24-031620
2020-01-012020-12-31172,504shares2023-03-1610-K · 0000950170-23-008517

Related financial histories

Inspect the source

Entity
AGENUS INC / CIK 0001098972
Captured
2026-09-20T05:22:49.565Z
SEC response SHA-256
0bb04cf709e54fd580c9e80c09e73789126e777d686ac12276d26072bab81d40

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/0001098972.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"])))