Verisk Analytics, Inc.: diluted earnings per share

What this measure means

Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.

Exact concept: us-gaap:EarningsPerShareDiluted. 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 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

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

Inspect the source

Entity

Verisk Analytics, Inc. / CIK 0001442145

Captured

2026-09-20T09:04:08.932Z

SEC response SHA-256

7ff151fb537fe40bd72f3e304b894f10371a6edefbbb18e8ab97766dc9fa9e4a

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/0001442145.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"])))