Hello Group Inc.: diluted weighted-average shares

What this measure means

Weighted-average shares used for diluted earnings per share. Potential shares are included under the applicable dilution rules, not simply added to outstanding shares.

Exact concept: us-gaap:WeightedAverageNumberOfDilutedSharesOutstanding. 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 2012-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

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

Inspect the source

Entity

Hello Group Inc. / CIK 0001610601

Captured

2026-09-20T09:26:43.282Z

SEC response SHA-256

b31bcd78033a56b1f5a03a8835b428d201f543288880ce6538697e5dd2f193d7

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/0001610601.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"])))