TYSON FOODS, INC.: investing cash flow

What this measure means

Net cash from investing activities, including asset purchases, disposals and investment transactions. This differs from capital expenditure payments alone.

Exact concept: us-gaap:NetCashProvidedByUsedInInvestingActivities. 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 2007-10-01 to 2025-09-27. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

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

Inspect the source

Entity

TYSON FOODS, INC. / CIK 0000100493

Captured

2026-09-19T14:53:40.007Z

SEC response SHA-256

24a6a5c4789b2f7a7b07b229d2158838c030e4cccd2ff08f8158ec56c35b96b1

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/0000100493.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"])))