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SOUTH DAKOTA SOYBEAN PROCESSORS LLC: basic earnings per share

Basic earnings per share for SOUTH DAKOTA SOYBEAN PROCESSORS LLC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All SOUTH DAKOTA SOYBEAN PROCESSORS LLC 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

For 2023–2025, South Dakota Soybean Processors reports earnings per LLC capital unit, not per corporate common share. The source taxonomy’s share concepts represent capital units here. The numerator is income attributable to the Company after noncontrolling interests. The filing states that it has no other capital units or member-equity instruments that are dilutive for this calculation. The reported unit counts and per-unit values are retained without adding basic and diluted denominators. Read the source filing.

Selected filing history

Basic earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-310.58USD/shares2026-03-3110-K · 0001163609-26-000010
2024-01-012024-12-310.67USD/shares2026-03-3110-K · 0001163609-26-000010
2023-01-012023-12-312.32USD/shares2026-03-3110-K · 0001163609-26-000010
2022-01-012022-12-312.22USD/shares2025-03-2810-K · 0001163609-25-000010
2021-01-012021-12-310.92USD/shares2024-03-2210-K · 0001163609-24-000004
2020-01-012020-12-310.51USD/shares2023-03-3010-K · 0001163609-23-000017

Related financial histories

Inspect the source

Entity
SOUTH DAKOTA SOYBEAN PROCESSORS LLC / CIK 0001163609
Captured
2026-09-20T07:43:27.941Z
SEC response SHA-256
d9218bf4ec27955c4ad39b6bf08f993680612291077680c22092b5b68404ac3e

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/0001163609.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"])))