technical-analysis.py

import yfinance as yf
import matplotlib.pyplot as plt
import pandas as pd

# Fetch historical data for AAPL
data = yf.download('AAPL', start='2023-01-01', end='2024-01-01')

# Calculate RSI
def RSI(data, window=14):
    delta = data['Adj Close'].diff(1)
    gain = (delta.where(delta > 0, 0)).rolling(window=window).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean()
    RS = gain / loss
    return 100 - (100 / (1 + RS))

data['RSI'] = RSI(data)

# Calculate MACD
exp1 = data['Adj Close'].ewm(span=12, adjust=False).mean()
exp2 = data['Adj Close'].ewm(span=26, adjust=False).mean()
data['MACD'] = exp1 - exp2
data['Signal Line'] = data['MACD'].ewm(span=9, adjust=False).mean()

# Calculate Bollinger Bands
data['Middle Band'] = data['Adj Close'].rolling(window=20).mean()
data['Upper Band'] = data['Middle Band'] + 2*data['Adj Close'].rolling(window=20).std()
data['Lower Band'] = data['Middle Band'] - 2*data['Adj Close'].rolling(window=20).std()

# Plotting
plt.figure(figsize=(14, 7))

# Plot closing price and Bollinger Bands
plt.subplot(311)
plt.plot(data['Adj Close'], label='Adjusted Close Price', color='blue')
plt.plot(data['Upper Band'], label='Upper Band', color='red')
plt.plot(data['Middle Band'], label='Middle Band', color='black')
plt.plot(data['Lower Band'], label='Lower Band', color='green')
plt.title('AAPL Bollinger Bands')
plt.legend()

# Plot MACD and Signal Line
plt.subplot(312)
plt.plot(data['MACD'], label='MACD', color='blue')
plt.plot(data['Signal Line'], label='Signal Line', color='red')
plt.title('AAPL MACD')
plt.legend()

# Plot RSI
plt.subplot(313)
plt.plot(data['RSI'], label='RSI', color='purple')
plt.title('AAPL RSI')
plt.axhline(70, linestyle='--', alpha=0.5, color='red')
plt.axhline(30, linestyle='--', alpha=0.5, color='green')
plt.legend()

plt.tight_layout()
plt.show()