FUTUREFUEL CORP.: operating expenses

What this measure means

Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.

Exact concept: us-gaap:OperatingExpenses. 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 2010-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• FUTUREFUEL CORP.: total assets
• FUTUREFUEL CORP.: total liabilities
• FUTUREFUEL CORP.: stockholders equity
• FUTUREFUEL CORP.: cash and cash equivalents
• FUTUREFUEL CORP.: net income or loss
• FUTUREFUEL CORP.: operating cash flow
• FUTUREFUEL CORP.: capital expenditure payments
• FUTUREFUEL CORP.: revenue
• FUTUREFUEL CORP.: contract revenue excluding tax
• FUTUREFUEL CORP.: financing cash flow
• FUTUREFUEL CORP.: investing cash flow
• FUTUREFUEL CORP.: retained earnings or deficit
• FUTUREFUEL CORP.: basic weighted-average shares
• FUTUREFUEL CORP.: diluted weighted-average shares
• FUTUREFUEL CORP.: basic earnings per share
• FUTUREFUEL CORP.: diluted earnings per share
• FUTUREFUEL CORP.: income tax expense or benefit
• FUTUREFUEL CORP.: net property, plant and equipment
• FUTUREFUEL CORP.: share-based compensation expense
• FUTUREFUEL CORP.: operating income or loss
• FUTUREFUEL CORP.: current assets
• FUTUREFUEL CORP.: interest expense
• FUTUREFUEL CORP.: current liabilities
• FUTUREFUEL CORP.: current accounts payable
• FUTUREFUEL CORP.: net current accounts receivable
• FUTUREFUEL CORP.: net inventory
• FUTUREFUEL CORP.: gross profit
• FUTUREFUEL CORP.: selling, general and administrative expense
• FUTUREFUEL CORP.: research and development expense

Inspect the source

Entity

FUTUREFUEL CORP. / CIK 0001337298

Captured

2026-09-20T07:53:56.979Z

SEC response SHA-256

7a4cc846d39d772c15c5a5a76b09ea27b0ab385f721f09e9a503ff6ac4c13b23

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
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001337298.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"])))