Skip to content

Clearfield, Inc.: operating expenses

Clearfield operating expenses: $11.0 million for the year ending 2012-09-30, up 0.6% on the year. 3 values since 2010 from SEC filings. In original units.

All Clearfield, Inc. financial histories

At a glance

Clearfield reported operating expenses of $11.0 million for the year ending 2012-09-30, up 0.6% from $10.9 million a year earlier. Across the last three reported years it ranged from $8.01 million (2010-09-30) to $11.0 million (2012-09-30). That was 29.4% of revenue ($37.5 million) for the same year.

Computed from the values in the table below, in USD; each links to the filing it came from.

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 2009-10-01 to 2012-09-30. The SEC response was captured on 2026-09-19.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Operating expenses in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2011-10-012012-09-3011,010,840USD2012-12-0410-K · 0001171843-12-004374 SEC
2010-10-012011-09-3010,942,149USD2012-12-0410-K · 0001171843-12-004374 SEC
2009-10-012010-09-308,014,121USD2011-11-3010-K · 0001171843-11-003637 SEC

Related CLEARFIELD, INC. histories

All 59 Clearfield histories

Inspect the source

Entity
CLEARFIELD, INC. / CIK 0000796505
Captured
SEC response SHA-256
18b5be317dd546fce0ab0f974ed9eca21788c8d13b4fbd1cad066e27a69d9a47

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.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000796505.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"])))