Design of High-Order Portfolios Including Skewness and Kurtosis
Design high-order portfolio based on weighted linear combination of fi...
Design MVSK portfolio without shorting based on the parameters of gene...
Design high-order portfolio by tilting a given portfolio to the MVSK e...
Estimate first four moment parameters of multivariate observations
Estimate the parameters of skew-t distribution from multivariate obser...
Evaluate first four moments of a given portfolio
highOrderPortfolios: Design of High-Order Portfolios via Mean, Varianc...
The classical Markowitz's mean-variance portfolio formulation ignores heavy tails and skewness. High-order portfolios use higher order moments to better characterize the return distribution. Different formulations and fast algorithms are proposed for high-order portfolios based on the mean, variance, skewness, and kurtosis. The package is based on the papers: R. Zhou and D. P. Palomar (2021). "Solving High-Order Portfolios via Successive Convex Approximation Algorithms." <arXiv:2008.00863>. X. Wang, R. Zhou, J. Ying, and D. P. Palomar (2022). "Efficient and Scalable High-Order Portfolios Design via Parametric Skew-t Distribution." <arXiv:2206.02412>.
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