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George Risk Industries, Inc.: net inventory

George Risk Industries net inventory: $11.8 million at 2026-04-30, up 10.1% on the year. 12 values since 2015 from SEC filings, each linked to its filing.

All George Risk Industries, Inc. financial histories

At a glance

George Risk Industries reported net inventory of $11.8 million at 2026-04-30, up 10.1% from $10.7 million a year earlier. From 2015 to 2026 it grew at a compound 16.2% a year, from $2.27 million to $11.8 million. Across the last five reported years it ranged from $7.94 million (2022-04-30) to $11.8 million (2026-04-30). That was 16.6% of total assets ($71.4 million) at the same date.

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

What this measure means

Inventory carrying amount after applicable valuation and LIFO reserves. It does not establish realizable selling proceeds or inventory turnover without other inputs.

Exact concept: us-gaap:InventoryNet. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2015-04-30 to 2026-04-30. The SEC response was captured on 2026-09-19.

Selected filing history

Net inventory in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
-2026-04-3011,822,000USD2026-08-0710-K · 0001493152-26-036522 SEC
-2025-04-3010,740,000USD2026-08-0710-K · 0001493152-26-036522 SEC
-2024-04-3011,558,000USD2025-08-1210-K · 0001641172-25-023170 SEC
-2023-04-3011,443,000USD2024-07-3110-K · 0001493152-24-029743 SEC
-2022-04-307,940,000USD2023-07-3110-K · 0001493152-23-026094 SEC
-2021-04-305,622,000USD2022-08-1510-K · 0001493152-22-022508 SEC
-2020-04-305,103,000USD2021-08-1210-K · 0001493152-21-019424 SEC
-2019-04-304,583,000USD2020-08-1310-K · 0001493152-20-015508 SEC
-2018-04-303,267,000USD2020-05-2610-K/A · 0001493152-20-009782 SEC
-2017-04-302,304,000USD2018-08-1310-K · 0001493152-18-011555 SEC
-2016-04-302,964,000USD2017-08-1410-K · 0001493152-17-009263 SEC
-2015-04-302,275,000USD2016-08-1010-K · 0001387131-16-006450 SEC

Related GEORGE RISK INDUSTRIES, INC. histories

All 51 George Risk Industries histories

Inspect the source

Entity
GEORGE RISK INDUSTRIES, INC. / CIK 0000084112
Captured
SEC response SHA-256
bffe28108ba1ced6e8efa057783de0b778afbfa8a992c4ee1e8f99c12c6f68ad

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/0000084112.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"])))