FACTSET RESEARCH SYSTEMS INC.: retained earnings or deficit

What this measure means

Accumulated undistributed earnings or deficit at the reporting date. This balance is not cash available for distribution.

Exact concept: us-gaap:RetainedEarningsAccumulatedDeficit. 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 2010-08-31 to 2025-08-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• FACTSET RESEARCH SYSTEMS INC.: total assets
• FACTSET RESEARCH SYSTEMS INC.: total liabilities
• FACTSET RESEARCH SYSTEMS INC.: stockholders equity
• FACTSET RESEARCH SYSTEMS INC.: cash and cash equivalents
• FACTSET RESEARCH SYSTEMS INC.: net income or loss
• FACTSET RESEARCH SYSTEMS INC.: operating cash flow
• FACTSET RESEARCH SYSTEMS INC.: capital expenditure payments
• FACTSET RESEARCH SYSTEMS INC.: revenue
• FACTSET RESEARCH SYSTEMS INC.: contract revenue excluding tax
• FACTSET RESEARCH SYSTEMS INC.: financing cash flow
• FACTSET RESEARCH SYSTEMS INC.: investing cash flow
• FACTSET RESEARCH SYSTEMS INC.: basic weighted-average shares
• FACTSET RESEARCH SYSTEMS INC.: diluted weighted-average shares
• FACTSET RESEARCH SYSTEMS INC.: basic earnings per share
• FACTSET RESEARCH SYSTEMS INC.: diluted earnings per share
• FACTSET RESEARCH SYSTEMS INC.: income tax expense or benefit
• FACTSET RESEARCH SYSTEMS INC.: net property, plant and equipment
• FACTSET RESEARCH SYSTEMS INC.: share-based compensation expense
• FACTSET RESEARCH SYSTEMS INC.: operating income or loss
• FACTSET RESEARCH SYSTEMS INC.: current assets
• FACTSET RESEARCH SYSTEMS INC.: current liabilities
• FACTSET RESEARCH SYSTEMS INC.: goodwill carrying amount
• FACTSET RESEARCH SYSTEMS INC.: net finite-lived intangible assets
• FACTSET RESEARCH SYSTEMS INC.: net current accounts receivable
• FACTSET RESEARCH SYSTEMS INC.: common-stock repurchase payments
• FACTSET RESEARCH SYSTEMS INC.: operating expenses
• FACTSET RESEARCH SYSTEMS INC.: cost of revenue
• FACTSET RESEARCH SYSTEMS INC.: selling, general and administrative expense
• FACTSET RESEARCH SYSTEMS INC.: research and development expense

Inspect the source

Entity

FACTSET RESEARCH SYSTEMS INC. / CIK 0001013237

Captured

2026-09-20T05:12:29.125Z

SEC response SHA-256

a82da656084a714535a6e3d662af63d1c45b7560e9d9cdb4c1d7a8419bf410d1

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/0001013237.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"])))