Last data update: 2014.03.03
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R: Markowitz (Mean-Variance) Portfolio Optimization
Markowitz (Mean-Variance) Portfolio Optimization
Description
This function estimates optimal mean-variance portfolio weights from a matrix
of historical or simulated asset returns.
Usage
srisk(x, mu = 0.07, lambda = 1e+08, alpha = 0.1, eps = 1e-04)
Arguments
x |
Matrix of asset returns
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mu |
Required mean rate of return for the portfolio
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lambda |
Lagrange multiplier associated with mean return constraint
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alpha |
Choquet risk parameter, unimplemented
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eps |
tolerance parameter for mean return constraint
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Details
The portfolio weights are estimated by solving a constrained least squares problem.
Value
pihat |
Optimal portfolio weights
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muhat |
Mean return in sample
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sighat |
Standard deviation of returns in sample
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Author(s)
R. Koenker
See Also
qrisk
Results
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