Financial Report Tracker

Automatically track tech company financial reports and generate investment summaries. Suitable for investors tracking portfolio companies' earnings calendars and automatically summarizing earnings highlights and risks.

Use Cases

When users mention earnings reports, financial reports, EPS, revenue expectations, earnings interpretation, tracking a company's financials, and similar scenarios.

Prerequisites

Install Python dependencies before first use:

pip install yfinance requests pandas

Core Capabilities

1. Earnings Calendar Tracking — Automatically retrieve target company earnings release dates
2. Market Expectation Comparison — EPS/Revenue expectations vs. actual data
3. Earnings Interpretation — Key metric changes and management guidance summary

Command List

Usage Workflow

Scenario 1: Track Earnings Date

Track Apple's next earnings release date and market expectations

python scripts/earnings_tracker.py track AAPL

Scenario 2: Earnings Preview Analysis

Pre-earnings expectation analysis

python scripts/earnings_tracker.py preview AAPL

Scenario 3: Earnings Review

Interpret key data from the latest earnings report

python scripts/earnings_tracker.py review AAPL --quarter Q1

Output Format

All commands output a standard Markdown format report:

# 📊 Financial Report Tracker Report

**Generated on**: YYYY-MM-DD HH:MM

## Key Findings
1. [Key finding 1]
2. [Key finding 2]
3. [Key finding 3]

## Data Overview
| Metric | Value | Trend | Rating |
|--------|-------|-------|--------|
| Metric A | XXX | ↑ | ⭐⭐⭐⭐ |
| Metric B | YYY | → | ⭐⭐⭐ |

## Detailed Analysis
[Multi-dimensional analysis based on actual data]

## Actionable Recommendations
| Priority | Recommendation | Expected Outcome |
|----------|----------------|------------------|
| 🔴 High | [Specific recommendation] | [Quantified expectation] |
| 🟡 Medium | [Specific recommendation] | [Quantified expectation] |
| 🟢 Low | [Specific recommendation] | [Quantified expectation] |

References

• yfinance Library — Earnings calendar and earnings data
• Financial Modeling Prep API — Financial report data

Notes

• All analysis is based on data retrieved by the script; data is not fabricated
• Missing data fields are marked "Data Unavailable" rather than guessed
• It is recommended to combine with human judgment; AI analysis is for reference only