RCI Hospitality Holdings, Inc.: net current accounts receivable

At a glance

RCI Hospitality Holdings reported net current accounts receivable of $9.85 million at 2023-09-30, up 15.7% from $8.51 million a year earlier. From 2010 to 2023 it grew at a compound 23.1% a year, from $662.0 thousand to $9.85 million. Across the last five reported years it ranged from $6.65 million (2020-06-30) to $9.85 million (2023-09-30). That was 1.6% of total assets ($610.9 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

Current customer receivables after the allowance for credit loss. The balance is not cash collected or a guarantee of collection.

Exact concept: us-gaap:AccountsReceivableNetCurrent. 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 2010-09-30 to 2023-09-30. The SEC response was captured on 2026-09-20.

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

Related RCI HOSPITALITY HOLDINGS, INC. histories

• Total assets
• Current assets
• Cash and cash equivalents
• Net inventory
• Prepaid expenses and other current assets
• Net property, plant and equipment
• Total liabilities
• Stockholders equity

All 62 RCI Hospitality Holdings histories

Inspect the source

Entity

RCI HOSPITALITY HOLDINGS, INC. / CIK 0000935419

Captured

2026-09-20 05:09 UTC

SEC response SHA-256

c9cd950d1a46a466493e149fe94721cbadbfbdba5e9e0f456451a4b8d6c0f521

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
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• Read the MCP server source and integration examples

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.

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000935419.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"])))