Genpact Limited: 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 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

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

Inspect the source

Entity

Genpact Limited / CIK 0001398659

Captured

2026-09-20T08:00:24.889Z

SEC response SHA-256

426f3b0c113b3e6a44e4a2b4a5a18a65e3f473c85b103301854da3c7cc76c6e9

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/0001398659.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"])))