Lucas GC Limited: operating cash flow

What this measure means

Cash generated or used by operating activities. Working-capital timing can make this differ substantially from reported income.

Exact concept: us-gaap:NetCashProvidedByUsedInOperatingActivities. 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 2021-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.

Coverage by original unit

• CNY: 2021-01-01 to 2025-12-31.
• USD: 2023-01-01 to 2025-12-31.

These are separate reported series. A newer period in one unit does not update another unit’s history or establish a currency conversion.

Selected filing history

Related financial histories

• Lucas GC Limited: total assets
• Lucas GC Limited: total liabilities
• Lucas GC Limited: stockholders equity
• Lucas GC Limited: cash and cash equivalents
• Lucas GC Limited: net income or loss
• Lucas GC Limited: revenue
• Lucas GC Limited: financing cash flow
• Lucas GC Limited: investing cash flow
• Lucas GC Limited: retained earnings or deficit
• Lucas GC Limited: basic weighted-average shares
• Lucas GC Limited: diluted weighted-average shares
• Lucas GC Limited: basic earnings per share
• Lucas GC Limited: diluted earnings per share
• Lucas GC Limited: income tax expense or benefit
• Lucas GC Limited: net property, plant and equipment
• Lucas GC Limited: operating income or loss
• Lucas GC Limited: current assets
• Lucas GC Limited: interest expense
• Lucas GC Limited: current liabilities
• Lucas GC Limited: current accounts payable
• Lucas GC Limited: net current accounts receivable
• Lucas GC Limited: operating expenses
• Lucas GC Limited: gross profit
• Lucas GC Limited: cost of revenue
• Lucas GC Limited: research and development expense

Inspect the source

Entity

Lucas GC Limited / CIK 0001954694

Captured

2026-09-21T17:38:05.624Z

SEC response SHA-256

09ac3192b4542ffb9d40392d5c3fad3433ae1fd99b8f406c6a49987c34fbdcb1

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/0001954694.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"])))