Python is the industry standard for financial engineering due to its robust library ecosystem.
Financial data distribution changes over time. Retrain weekly or use online learning (River library).
# Create Features df['SMA_50'] = df['Close'].rolling(window=50).mean() df['SMA_200'] = df['Close'].rolling(window=200).mean() df['Return'] = df['Close'].pct_change() df['Volatility'] = df['Return'].rolling(window=20).std()