Understanding correlation is fundamental to building a well-diversified portfolio. When you know how your investments move relative to each other, you can make smarter decisions about risk management and asset allocation. This guide explains correlation in simple terms and shows you how to use it effectively.
What is Correlation?
Correlation measures how two investments move in relation to each other. It is expressed as a number between -1 and +1, known as the correlation coefficient. This single number tells you a lot about how your portfolio will behave in different market conditions.
The correlation spectrum:
- +1.0: Perfect positive correlation - assets move exactly together
- 0: No correlation - assets move independently
- -1.0: Perfect negative correlation - assets move in opposite directions
Why Correlation Matters for Diversification
The primary benefit of diversification comes from combining assets with low or negative correlations. When one investment falls, another may rise or stay stable, reducing your overall portfolio volatility.
Example: Correlation Impact on Risk
Consider two portfolios with the same expected return of 8%:
- Portfolio A: Two stocks with +0.9 correlation - Portfolio volatility: 18%
- Portfolio B: Two stocks with +0.2 correlation - Portfolio volatility: 12%
Portfolio B has 33% less risk simply because of lower correlation between holdings.
Common Asset Class Correlations
Understanding typical correlations helps you build better portfolios. Here are some general relationships:
Typically Positive Correlations
- US Large Cap and US Small Cap stocks: +0.7 to +0.9
- US Stocks and International Developed stocks: +0.7 to +0.85
- Corporate bonds and stocks: +0.3 to +0.5
- Emerging market stocks and commodities: +0.4 to +0.6
Typically Low or Negative Correlations
- US Treasury bonds and stocks: -0.2 to +0.2
- Gold and stocks: -0.1 to +0.2
- Real estate and bonds: +0.1 to +0.3
- Managed futures and stocks: -0.2 to +0.1
How to Calculate Correlation
The correlation coefficient is calculated using the covariance between two assets divided by the product of their standard deviations:
Correlation Formula
Correlation (A,B) = Covariance(A,B) / (Standard Deviation A x Standard Deviation B)
In practice, you will use spreadsheet software or investment tools to calculate this automatically from historical returns data.
Building a Correlation Matrix
A correlation matrix shows the correlations between all pairs of assets in your portfolio. This powerful tool helps you identify which positions provide true diversification benefits.
Example: Simple Correlation Matrix
| **Stocks** | **Bonds** | **Gold** | |
| **Stocks** | 1.00 | 0.10 | 0.05 |
| **Bonds** | 0.10 | 1.00 | 0.25 |
| **Gold** | 0.05 | 0.25 | 1.00 |
This matrix shows gold has almost no correlation with stocks, making it an effective diversifier.
Correlation Changes Over Time
One of the most important things to understand is that correlations are not static. They change based on market conditions, especially during crises.
- During market crashes: Correlations between risk assets tend to spike toward +1
- In calm markets: Correlations are more stable and closer to historical averages
- Over long periods: Average correlations can shift due to structural economic changes
Crisis correlation: During the 2008 financial crisis and March 2020, many "uncorrelated" assets moved down together. This phenomenon, called correlation breakdown, is why diversification alone cannot fully protect your portfolio during extreme events.
Practical Applications of Correlation Analysis
1. Portfolio Construction
Use correlation to select assets that provide genuine diversification. Aim for a mix of high-quality assets with varying correlations rather than simply owning many assets.
2. Risk Assessment
If your portfolio has many highly correlated positions, your true diversification is lower than it appears. Calculate portfolio correlation to understand your real risk exposure.
3. Pair Selection for Hedging
Find negatively correlated assets to hedge specific risks. For example, utilities stocks often have lower correlation to the overall market and can provide stability during downturns.
4. Sector Rotation
Different sectors have varying correlations with the market. Understanding these relationships can help you position your portfolio for different economic cycles.
Limitations of Correlation Analysis
While correlation is valuable, it has important limitations:
- Historical data: Past correlations may not predict future relationships
- Linear relationships only: Correlation does not capture non-linear dependencies
- Time period sensitivity: Results vary based on the time period analyzed
- Correlation is not causation: Two assets moving together does not mean one causes the other
Tips for Using Correlation Effectively
- Look at multiple time periods: Calculate correlations over 1, 3, 5, and 10 years
- Monitor for changes: Review correlations periodically, especially after market stress
- Consider rolling correlations: Track how correlations evolve over time
- Combine with other metrics: Use correlation alongside volatility, beta, and returns
- Do not over-optimize: Small differences in correlation are not meaningful
Analyze Your Portfolio Correlation
Pro Trader Dashboard automatically calculates the correlation matrix for your holdings, helping you identify concentration risks and optimize diversification.
Summary
Correlation is a powerful tool for understanding how your investments interact with each other. By combining assets with low correlations, you can reduce portfolio risk without sacrificing expected returns. Remember that correlations change over time, especially during market stress, so regular monitoring is essential. Use correlation analysis as one component of a comprehensive portfolio management approach.
Continue learning about portfolio analysis with our guides on portfolio beta and the efficient frontier.