Constructs a portfolio that achieves a specified target return with minimum variance. This optimization finds the point on the efficient frontier corresponding to your desired return level.
Use Cases:
Mathematical Background: Minimizes: w^T Σ w Subject to: w^T μ = target_return, Σw_i = 1, and optional constraints
Where μ is the expected return vector.
Credits: 5 per request
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Expected returns for each asset (annualized)
[0.08, 0.12, 0.1, 0.15]Asset covariance matrix (annualized)
[
[0.04, 0.006, 0.008, 0.01],
[0.006, 0.09, 0.012, 0.015],
[0.008, 0.012, 0.0625, 0.018],
[0.01, 0.015, 0.018, 0.16]
]Desired portfolio return (annualized). Must be achievable given asset returns and constraints.
0.11
Minimum weight constraints for each asset
[0, 0, 0, 0]Maximum weight constraints for each asset
[0.4, 0.4, 0.4, 0.4]