EMERSON RADIO CORP: 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 2010-04-01 to 2026-03-31. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

• EMERSON RADIO CORP: total assets
• EMERSON RADIO CORP: total liabilities
• EMERSON RADIO CORP: stockholders equity
• EMERSON RADIO CORP: cash and cash equivalents
• EMERSON RADIO CORP: net income or loss
• EMERSON RADIO CORP: operating cash flow
• EMERSON RADIO CORP: capital expenditure payments
• EMERSON RADIO CORP: contract revenue excluding tax
• EMERSON RADIO CORP: financing cash flow
• EMERSON RADIO CORP: investing cash flow
• EMERSON RADIO CORP: retained earnings or deficit
• EMERSON RADIO CORP: basic weighted-average shares
• EMERSON RADIO CORP: diluted weighted-average shares
• EMERSON RADIO CORP: basic earnings per share
• EMERSON RADIO CORP: diluted earnings per share
• EMERSON RADIO CORP: income tax expense or benefit
• EMERSON RADIO CORP: net property, plant and equipment
• EMERSON RADIO CORP: operating income or loss
• EMERSON RADIO CORP: current assets
• EMERSON RADIO CORP: interest expense
• EMERSON RADIO CORP: current liabilities
• EMERSON RADIO CORP: net current accounts receivable
• EMERSON RADIO CORP: common-stock repurchase payments
• EMERSON RADIO CORP: net inventory

Inspect the source

Entity

EMERSON RADIO CORP / CIK 0000032621

Captured

2026-09-19T14:46:27.062Z

SEC response SHA-256

1d6283e2a0a26d0064cc9de5093d303f6e5a17f747fe99c3e1ac4f7c91673739

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/0000032621.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"])))