Portfolio Correlation Matrix Calculator

Calculate portfolio diversification benefits by analyzing correlation between assets. See how combining assets with different correlations affects overall portfolio risk.

Portfolio Risk = √[w₁²σ₁² + w₂²σ₂² + 2w₁w₂σ₁σ₂ρ]. Diversification Benefit = Weighted Volatility - Portfolio Volatility
Asset 1: Stocks (10% return, 15% vol, 60% weight) Asset 2: Bonds (5% return, 4% vol, 40% weight) Correlation: 0.2 Portfolio Return = (0.6×10) + (0.4×5) = 8% Portfolio Risk = ~9.5% (vs 11.2% if fully correlated) Diversification benefit = ~15% risk reduction

What is portfolio correlation and why does it matter?

Correlation measures how two assets move relative to each other (-1 to +1). Perfect positive (+1) means they move together, perfect negative (-1) means they move opposite, zero means no relationship. Low correlation improves diversification - when one asset drops, another may rise, reducing overall portfolio risk. The lower the correlation between assets, the better the diversification benefit.

What correlation values should I look for in a portfolio?

For optimal diversification: Look for correlations below 0.3 between portfolio assets. 0.4-0.7 = moderate correlation (some diversification). Above 0.7 = high correlation (limited diversification benefit). Negative correlations (below 0) provide the best hedge - when one asset falls, the other tends to rise. Many investors aim for a portfolio correlation between 0.2-0.4 for balanced risk reduction.

How does correlation affect portfolio risk?

Correlation directly impacts portfolio volatility through diversification. With perfect positive correlation (+1), no diversification benefit exists - portfolio risk is simply the weighted average. With zero correlation, risk decreases significantly. With perfect negative correlation (-1), you can theoretically eliminate all risk. In practice, most asset correlations are 0.2-0.6, providing moderate but meaningful risk reduction.

How do I calculate portfolio correlation?

Correlation is calculated using historical price data: r = Σ(x-x̄)(y-ȳ) / √[Σ(x-x̄)² × Σ(y-ȳ)²]. For common assets: US stocks vs Bonds ≈ 0.2, US stocks vs Intl stocks ≈ 0.7-0.8, Stocks vs Real Estate ≈ 0.3-0.5, Stocks vs Commodities ≈ 0.2. Use historical data or refer to correlation matrices from financial databases to estimate correlation between assets.