Analyzing Financial Statements

Input Format

Financial data can be provided as:

• CSV with financial line items
• JSON with structured financial statements
• Text description of key financial figures
• Excel files with financial statements

Output Format

Results include:

• Calculated ratios with values
• Industry benchmark comparisons (when available)
• Trend analysis (if multiple periods provided)
• Interpretation and insights
• Excel report with formatted results

Example Usage

"Calculate key financial ratios for this company based on the attached financial statements"

"What's the P/E ratio if the stock price is $50 and annual earnings are $2.50 per share?"

"Analyze the liquidity position using the balance sheet data"

Scripts

• calculate_ratios.py: Main calculation engine for all financial ratios
• interpret_ratios.py: Provides interpretation and benchmarking

Best Practices

1. Always validate data completeness before calculations
2. Handle missing values appropriately (use industry averages or exclude)
3. Consider industry context when interpreting ratios
4. Include period comparisons for trend analysis
5. Flag unusual or concerning ratios

Limitations

• Requires accurate financial data
• Industry benchmarks are general guidelines
• Some ratios may not apply to all industries
• Historical data doesn't guarantee future performance