NANO NUCLEAR ENERGY INC.: diluted earnings per share
Diluted earnings per share for NANO NUCLEAR ENERGY INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All NANO NUCLEAR ENERGY INC. financial histories
What this measure means
Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.
Exact concept: us-gaap:EarningsPerShareDiluted. 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 2022-10-01 to 2025-09-30. The SEC response was captured on 2026-09-21.
Reading these values
This selected numerical history matches Basic 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.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2024-10-01 | 2025-09-30 | -1.06 | USD/shares | 2025-12-18 | 10-K · 0001493152-25-028285 |
| 2023-10-01 | 2024-09-30 | -0.39 | USD/shares | 2025-12-18 | 10-K · 0001493152-25-028285 |
| 2022-10-01 | 2023-09-30 | -0.28 | USD/shares | 2024-12-30 | 10-K · 0001493152-24-052393 |
Related financial histories
- NANO NUCLEAR ENERGY INC.: total assets
- NANO NUCLEAR ENERGY INC.: total liabilities
- NANO NUCLEAR ENERGY INC.: stockholders equity
- NANO NUCLEAR ENERGY INC.: net income or loss
- NANO NUCLEAR ENERGY INC.: operating cash flow
- NANO NUCLEAR ENERGY INC.: financing cash flow
- NANO NUCLEAR ENERGY INC.: retained earnings or deficit
- NANO NUCLEAR ENERGY INC.: basic weighted-average shares
- NANO NUCLEAR ENERGY INC.: diluted weighted-average shares
- NANO NUCLEAR ENERGY INC.: basic earnings per share
- NANO NUCLEAR ENERGY INC.: share-based compensation expense
- NANO NUCLEAR ENERGY INC.: current assets
- NANO NUCLEAR ENERGY INC.: current liabilities
- NANO NUCLEAR ENERGY INC.: operating expenses
- NANO NUCLEAR ENERGY INC.: research and development expense
Inspect the source
- Entity
- NANO NUCLEAR ENERGY INC. / CIK 0001923891
- Captured
- 2026-09-21T17:36:41.601Z
- SEC response SHA-256
d17454f45f10b968cff0e86cf779cf52b93a14a310df63367c6371777c01aa95
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.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001923891.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"])))