Design of High-Order Portfolios Including Skewness and Kurtosis
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Documentation for package ‘highOrderPortfolios’ version 0.1.1
Help Pages
| highOrderPortfolios-package | highOrderPortfolios: Design of High-Order Portfolios via Mean, Variance, Skewness, and Kurtosis |
| design_MVSKtilting_portfolio_via_sample_moments | Design high-order portfolio by tilting a given portfolio to the MVSK efficient frontier |
| design_MVSK_portfolio_via_sample_moments | Design high-order portfolio based on weighted linear combination of first four moments |
| design_MVSK_portfolio_via_skew_t | Design MVSK portfolio without shorting based on the parameters of generalized hyperbolic skew-t distribution |
| estimate_sample_moments | Estimate first four moment parameters of multivariate observations |
| estimate_skew_t | Estimate the parameters of skew-t distribution from multivariate observations |
| eval_portfolio_moments | Evaluate first four moments of a given portfolio |
| X100 | Synthetic 500x100 matrix dataset |
| X200 | Synthetic 1000x200 matrix dataset |
| X50 | Synthetic 250x50 matrix dataset |