ACUITY INC.: selling, general and administrative expense

What this measure means

Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.

Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. 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 2008-09-01 to 2025-08-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

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

Inspect the source

Entity

ACUITY INC. / CIK 0001144215

Captured

2026-09-20T07:42:15.788Z

SEC response SHA-256

d035f0e80ee740894a85cfe1876ba3aebc1f488ac43282e883002f8c26d6a2f0

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/0001144215.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"])))