Skip to content

EXAGEN INC.: basic earnings per share

Basic earnings per share for EXAGEN INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All EXAGEN INC. financial histories

What this measure means

Reported earnings or loss per basic common share or unit. Inspect attribution, share classes and restatements before comparing periods. This is not a market return.

Exact concept: us-gaap:EarningsPerShareBasic. 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 Diluted earnings per share 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

Exagen's 2024 and 2025 basic and diluted denominators already include shares issuable under nominal-price pre-funded warrants. Other potentially dilutive warrants, options, restricted stock units and employee stock-purchase shares are excluded as anti-dilutive during losses; they must not be added to the reported denominator. Dollar losses are displayed in thousands, while shares and per-share amounts are unscaled. Read the source filing.

Selected filing history

Basic earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-0.93USD/shares2026-03-1010-K · 0001274737-26-000009
2024-01-012024-12-31-0.83USD/shares2026-03-1010-K · 0001274737-26-000009
2023-01-012023-12-31-1.34USD/shares2025-03-1110-K · 0001274737-25-000019
2022-01-012022-12-31-2.77USD/shares2024-03-1810-K · 0001274737-24-000022
2021-01-012021-12-31-1.68USD/shares2023-03-2010-K · 0001274737-23-000019
2020-01-012020-12-31-1.32USD/shares2022-03-2210-K · 0001628280-22-006926

Related financial histories

Inspect the source

Entity
EXAGEN INC. / CIK 0001274737
Captured
2026-09-20T07:47:58.165Z
SEC response SHA-256
e5dec18c6ce30b9c5996c9552c3038c60c5a4f2ddd0b66db38cf430134585544

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/0001274737.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"])))