Upbound Group, Inc.: operating income or loss

What this measure means

Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.

Exact concept: us-gaap:OperatingIncomeLoss. 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 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• Upbound Group, Inc.: total assets
• Upbound Group, Inc.: total liabilities
• Upbound Group, Inc.: stockholders equity
• Upbound Group, Inc.: cash and cash equivalents
• Upbound Group, Inc.: net income or loss
• Upbound Group, Inc.: operating cash flow
• Upbound Group, Inc.: capital expenditure payments
• Upbound Group, Inc.: revenue
• Upbound Group, Inc.: financing cash flow
• Upbound Group, Inc.: investing cash flow
• Upbound Group, Inc.: retained earnings or deficit
• Upbound Group, Inc.: basic weighted-average shares
• Upbound Group, Inc.: diluted weighted-average shares
• Upbound Group, Inc.: basic earnings per share
• Upbound Group, Inc.: diluted earnings per share
• Upbound Group, Inc.: income tax expense or benefit
• Upbound Group, Inc.: net property, plant and equipment
• Upbound Group, Inc.: share-based compensation expense
• Upbound Group, Inc.: interest expense
• Upbound Group, Inc.: goodwill carrying amount
• Upbound Group, Inc.: net finite-lived intangible assets
• Upbound Group, Inc.: common-stock repurchase payments
• Upbound Group, Inc.: operating expenses
• Upbound Group, Inc.: gross profit
• Upbound Group, Inc.: cost of revenue

Inspect the source

Entity

Upbound Group, Inc. / CIK 0000933036

Captured

2026-09-20T05:09:33.057Z

SEC response SHA-256

a7cbe68c1a5b4da2cc0142a7464b1ba23aec88db8fd6ae48221c52266258aad3

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/0000933036.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"])))