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Calculate technical analysis indicators for stock market analysis
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| name | technical-indicators |
| description | Calculate technical analysis indicators for stock market analysis |
Quick guide for calculating technical indicators using Python and pandas-ta.
import yfinance as yf
import pandas_ta as ta
df = yf.download('AAPL', period='1y')
df['RSI'] = ta.rsi(df['Close'], length=14)
print(df[['Close', 'RSI']].tail())
df['RSI'] = ta.rsi(df['Close'], length=14)
# RSI > 70: overbought | RSI < 30: oversold
df['SMA_50'] = ta.sma(df['Close'], length=50)
# Golden Cross: SMA_50 > SMA_200
# Death Cross: SMA_50 < SMA_200
df['EMA_12'] = ta.ema(df['Close'], length=12)
macd = ta.macd(df['Close'])
# MACD > Signal: bullish | MACD < Signal: bearish
bbands = ta.bbands(df['Close'], length=20)
# Price > Upper: overbought | Price < Lower: oversold
adx = ta.adx(df['High'], df['Low'], df['Close'], length=14)
# ADX > 25: strong trend | ADX < 20: weak trend
df['ATR'] = ta.atr(df['High'], df['Low'], df['Close'], length=14)
stoch = ta.stoch(df['High'], df['Low'], df['Close'], length=14)
df['OBV'] = ta.obv(df['Close'], df['Volume'])
import yfinance as yf
import pandas as pd
import pandas_ta as ta
# Fetch data
ticker = 'AAPL'
df = yf.download(ticker, period='2y')
# Calculate multiple indicators
df['RSI'] = ta.rsi(df['Close'], length=14)
df['SMA_20'] = ta.sma(df['Close'], length=20)
df['SMA_50'] = ta.sma(df['Close'], length=50)
df['EMA_12'] = ta.ema(df['Close'], length=12)
# MACD
macd = ta.macd(df['Close'])
df = pd.concat([df, macd], axis=1)
# Bollinger Bands
bbands = ta.bbands(df['Close'], length=20)
df = pd.concat([df, bbands], axis=1)
# ATR
df['ATR'] = ta.atr(df['High'], df['Low'], df['Close'], length=14)
print(df[['Close', 'RSI', 'SMA_20', 'SMA_50', 'ATR']].tail())
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