Lean
$LEAN_TAG$
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Provides an implementation of a minimum variance portfolio optimizer that calculate the optimal weights with the weight range from -1 to 1 and minimize the portfolio variance with a target return of 2% More...
Public Member Functions | |
MinimumVariancePortfolioOptimizer (double lower=-1, double upper=1, double targetReturn=0.02) | |
Initialize a new instance of MinimumVariancePortfolioOptimizer More... | |
double[] | Optimize (double[,] historicalReturns, double[] expectedReturns=null, double[,] covariance=null) |
Perform portfolio optimization for a provided matrix of historical returns and an array of expected returns More... | |
Protected Member Functions | |
LinearConstraint | GetBudgetConstraint (int size) |
Sum of all weight is one: 1^T w = 1 / Σw = 1 More... | |
IEnumerable< LinearConstraint > | GetBoundaryConditions (int size) |
Boundary constraints on weights: lw ≤ w ≤ up More... | |
Provides an implementation of a minimum variance portfolio optimizer that calculate the optimal weights with the weight range from -1 to 1 and minimize the portfolio variance with a target return of 2%
The budged constrain is scaled down/up to ensure that the sum of the absolute value of the weights is 1.
Definition at line 29 of file MinimumVariancePortfolioOptimizer.cs.
QuantConnect.Algorithm.Framework.Portfolio.MinimumVariancePortfolioOptimizer.MinimumVariancePortfolioOptimizer | ( | double | lower = -1 , |
double | upper = 1 , |
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double | targetReturn = 0.02 |
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Initialize a new instance of MinimumVariancePortfolioOptimizer
lower | Lower bound |
upper | Upper bound |
targetReturn | Target return |
Definition at line 41 of file MinimumVariancePortfolioOptimizer.cs.
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protected |
Sum of all weight is one: 1^T w = 1 / Σw = 1
size | number of variables |
Definition at line 53 of file MinimumVariancePortfolioOptimizer.cs.
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protected |
Boundary constraints on weights: lw ≤ w ≤ up
size | number of variables |
Definition at line 68 of file MinimumVariancePortfolioOptimizer.cs.
double [] QuantConnect.Algorithm.Framework.Portfolio.MinimumVariancePortfolioOptimizer.Optimize | ( | double | historicalReturns[,], |
double[] | expectedReturns = null , |
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double | covariance[,] = null |
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Perform portfolio optimization for a provided matrix of historical returns and an array of expected returns
historicalReturns | Matrix of annualized historical returns where each column represents a security and each row returns for the given date/time (size: K x N). |
expectedReturns | Array of double with the portfolio annualized expected returns (size: K x 1). |
covariance | Multi-dimensional array of double with the portfolio covariance of annualized returns (size: K x K). |
Implements QuantConnect.Algorithm.Framework.Portfolio.IPortfolioOptimizer.
Definition at line 94 of file MinimumVariancePortfolioOptimizer.cs.