Public Company Earnings Reading Assistant

Before you begin

Who this is for

Individual investors, stock research beginners, quantitative learners, AI tool users and information researchers.

Use cases

Understand financial data and business changes. For building a research framework, not instructions to buy or sell individual stocks.

Data to prepare

Full official financial report, reporting period, at least two historical reporting periods, currency and accounting standards.

When parameters are filled in on the right, the text updates automatically. Complete any remaining placeholders before use.

<p>Welcome. Get the prompt to verify.</p>

Example input and output structure

Example input (parameter format only)

Research subject: Example Company A (fictional)
Time period: The actual reporting period of your materials
Source materials: Original files, public links and collection times

This example contains no real news, market prices or company financial data.

Expected output structure

Revenue changes | Net profit changes | Gross margin and expense ratios | Cash flow | Debt | Business segments | Management statements | Causes of change | Historical comparison | Industry context | Risks | Data to verify

Example output excerpt (placeholder only)

Facts / data: Awaiting original materials from the user
Sources and dates: To be provided and verified
Inferences / opinions: Insufficient evidence; no inference made
Verification questions: Original sources, definitions and validity period
Uncertainty: Live data unavailable; no investment conclusion

How to use

1. Define your research question and time period, and prepare lawfully obtained original materials.
2. Click “Get the prompt” or use the bottom-right button, then fill in parameters and paste into your AI tool.
3. Upload or paste original materials and confirm whether the model has web access.
4. Ask AI to list missing data and unverifiable information separately.
5. Verify results against original sources, keep your own research notes and judge independently.

Verification checklist

• Does each fact include its original source, publication date and collection time?
• Are units, currencies, time zones and calculation definitions consistent?
• Are facts, data, inferences and opinions clearly distinguished?
• Are unverified claims, missing items and alternative explanations marked?
• Are guaranteed returns and trading instructions avoided?

Common mistakes and limitations

• Asking a model without web access for the “latest” information without supplying original materials.
• Treating secondhand claims as facts or a single indicator as an investment signal.
• Ignoring differences in accounting definitions, statistical scope and timing.
• AI may misinterpret data, fabricate sources or omit risks. Templates cannot eliminate these risks.
• Social samples and historical data do not guarantee representativeness or future results.

Data timeliness reminder

The update date refers to template maintenance, not live data from that period. Check source dates every time. Model knowledge cutoffs and web access depend on the tool version.

Original sources and references

A research framework curated by this site. The sources above are suggested verification resources, not evidence of partnership, authorization or institutional endorsement.