Alpha Cluster Analysis

The Alpha Cluster Analysis uses machine learning to group stocks with similar risk-return characteristics. This helps identify different investment styles and opportunities:

• Alpha: Excess return over the benchmark (annualized %). Higher alpha indicates better performance relative to the market.
• Beta: Sensitivity to market movements. Beta > 1 means more volatile than market, Beta < 1 means less volatile.
• Sharpe Ratio: Risk-adjusted return. Higher values indicate better return per unit of risk.
• Volatility: Standard deviation of returns (annualized). Measures price fluctuation.
• Momentum: Performance over different time periods (1m, 3m, 6m, 12m). Identifies trending stocks.
• Max Drawdown: Largest peak-to-trough decline. Indicates worst-case historical loss.
• Cluster Groups:
  • ⭐ Alpha Leaders - Highest alpha generators
  • ● Momentum Runners - Strong recent performance
  • ● Compounders - Consistent steady growth
  • ● Mixed - Balanced characteristics
  • ● Volatile - High risk, high potential
  • ▼ Lagging - Underperformers