NMF SLF I, Inc.: basic earnings per share
Basic earnings per share for NMF SLF I, Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All NMF SLF I, 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 2021-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.
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.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2025-01-01 | 2025-12-31 | 0.89 | USD/shares | 2026-03-04 | 10-K · 0001766037-26-000004 |
| 2024-01-01 | 2024-12-31 | 1.24 | USD/shares | 2026-03-04 | 10-K · 0001766037-26-000004 |
| 2023-01-01 | 2023-12-31 | 1.53 | USD/shares | 2026-03-04 | 10-K · 0001766037-26-000004 |
| 2022-01-01 | 2022-12-31 | 0.66 | USD/shares | 2025-03-06 | 10-K · 0001766037-25-000003 |
| 2021-01-01 | 2021-12-31 | 0.97 | USD/shares | 2024-03-06 | 10-K · 0001766037-24-000005 |
Related financial histories
- NMF SLF I, Inc.: total assets
- NMF SLF I, Inc.: total liabilities
- NMF SLF I, Inc.: stockholders equity
- NMF SLF I, Inc.: cash and cash equivalents
- NMF SLF I, Inc.: net income or loss
- NMF SLF I, Inc.: operating cash flow
- NMF SLF I, Inc.: financing cash flow
- NMF SLF I, Inc.: retained earnings or deficit
- NMF SLF I, Inc.: basic weighted-average shares
- NMF SLF I, Inc.: diluted weighted-average shares
- NMF SLF I, Inc.: diluted earnings per share
- NMF SLF I, Inc.: interest expense
Inspect the source
- Entity
- NMF SLF I, Inc. / CIK 0001766037
- Captured
- 2026-09-21T17:19:44.646Z
- SEC response SHA-256
5eb494aea83e3323d58dc16e321de58810ae46010b03f4d06cf457464a0ea744
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.
- Get an API key and run your first validation
- Connect the MCP server to your coding assistant
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- Read the MCP server source and integration examples
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001766037.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"])))