Stock Analysis

Stock Analysis

Comprehensive stock and company analysis using Python yfinance library.

Dependencies

pip install yfinance pandas openpyxl

Quick Start

import yfinance as yf

# Company info
ticker = yf.Ticker("AAPL")
info = ticker.info  # Full profile
hist = ticker.history(period="1y")  # Price history
recs = ticker.recommendations  # Analyst recommendations

Available Data via yfinance

Script

Run analysis via: python ~/.claude/skills/stock-analysis/scripts/stock_analysis.py

# Company overview
python stock_analysis.py profile AAPL

# Price chart data
python stock_analysis.py chart AAPL --period 1y --interval 1d

# Analyst recommendations
python stock_analysis.py recommendations AAPL

# Insider transactions
python stock_analysis.py insiders AAPL

# Full analysis (all data)
python stock_analysis.py full AAPL

# Compare multiple stocks
python stock_analysis.py compare AAPL,MSFT,GOOGL --period 6mo

# Export to Excel
python stock_analysis.py full AAPL --excel output.xlsx

Common Workflows

Company Overview

User: "Tell me about AAPL"
-> profile (business summary, industry, employees)
-> recommendations (analyst outlook)
-> chart (recent performance)

Investment Analysis

User: "Is TSLA a good buy?"
-> chart (price trends, 52-week range)
-> recommendations (analyst consensus, target price)
-> profile (business fundamentals)
-> insider_transactions (insider sentiment)

Multi-Stock Comparison

User: "Compare AAPL vs MSFT vs GOOGL"
-> chart for each (relative performance)
-> profile for each (market cap, P/E, sector)
-> recommendations for each (ratings comparison)
-> Export side-by-side to Excel

Key Data Points

Profile: ticker.info

• marketCap, sector, industry, fullTimeEmployees
• forwardPE, trailingPE, dividendYield
• fiftyTwoWeekHigh, fiftyTwoWeekLow
• targetMeanPrice, recommendationKey

History: ticker.history(period, interval)

• Periods: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
• Intervals: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo
• Returns DataFrame with Open, High, Low, Close, Volume

Recommendations: ticker.recommendations

• Columns: period, strongBuy, buy, hold, sell, strongSell

When to Use

Trigger words: "stock", "share price", "AAPL", "TSLA", "$MSFT", "analyze company", "compare stocks", "insider trading", "SEC filing", "analyst rating", "акции", "курс", "биржа"

Excel Export Integration

Use with skill xlsx for professional reports:

import yfinance as yf
import pandas as pd

ticker = yf.Ticker("AAPL")
hist = ticker.history(period="1y")
hist.to_excel("aapl_history.xlsx", sheet_name="Price History")