What It Is
Minimum Correlation allocation focuses on reducing the average correlation between assets in your model. The goal is to enhance diversification by combining assets that tend not to move in the same direction, thereby potentially lowering overall portfolio risk.
What It Does in Fincanva
Logic: Allocates more capital to assets with lower correlations to others in the portfolio
Simulation Behavior: At each rebalance, asset relationships are evaluated, and weights are optimized to reduce the average pairwise correlation
Computation: Based on the Minimum Correlation Algorithm (MCA) as proposed by Varadi, Kapler, Rittenhouse, and Bee, implemented through an efficient optimization routine
Constraints: Positive weights only—no short positions are allowed in models
Pros
Promotes diversification by reducing exposure to correlated assets
Can reduce total portfolio volatility without sacrificing return potential
Helps build more stable and resilient investment strategies
Especially useful when combining assets across different sectors or factors
Cons
Asset correlations can shift over time, requiring periodic re-optimization
More computationally intensive than simpler allocation methods
Does not account for individual asset risk or return—focus is purely on relationships
May underweight high-quality assets if they are highly correlated with others
Where You Can Use It
Portfolios: Not available
Models: Yes
When to Use It
Best for diversification-focused strategies
Useful when combining assets from similar categories or asset classes
Ideal for reducing overexposure to thematic or sector-specific risks
Great for building risk-aware models that aim for long-term stability
Example If Asset A is highly correlated with Asset B (correlation = 0.9), but Asset C is only loosely correlated with Asset A (correlation = 0.2), the Minimum Correlation method will prioritize Asset C over Asset B, even if they have similar returns.
Plan Access
Models: Available on Advanced, Ultimate, and Professional plans
Portfolios: Not available
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