Mean-variance-skewness-entropy measures: a multi-objective approach for portfolio selection
type: Item
instance of: scholarly article
title: Mean-variance-skewness-entropy measures: a multi-objective approach for portfolio selection
zbMATH Open document ID: 1229.90287
author: Ilhan Usta
author: Y. Mert Kantar
published in: Entropy
publication date: 2012-01-09T00:00:00Z
review text: Summary: We present a multi-objective approach based on a mean-variance-skewness-entropy portfolio selection model (MVSEM). In this approach, an entropy measure is added to the mean-variance-skewness model (MVSM) to generate a well-diversified portfolio. Through a variety of empirical data sets, we evaluate the performance of the MVSEM in terms of several portfolio performance measures. The obtained results show that the MVSEM performs well out-of sample relative to traditional portfolio selection models.
Mathematics Subject Classification ID: 90C90
Mathematics Subject Classification ID: 91G10
Mathematics Subject Classification ID: 90C29
zbMATH DE Number: 5995923
zbMATH Keywords: portfolio selection
zbMATH Keywords: entropy
zbMATH Keywords: skewness
zbMATH Keywords: portfolio performance measures
zbMATH Keywords: out-of-sample performance
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/e13010117
OpenAlex ID: W1981211029
cites work: The use of mixtures for dealing with non-normal regression errors
cites work: On adaptive estimation
cites work: Measuring the prediction error. A comparison of cross-validation, bootstrap and covariance penalty methods
cites work: A Comparison of Partially Adaptive and Reweighted Least Squares Estimation
cites work: A nonlinear regression model with skew-normal errors
cites work: Q4390474
cites work: Partially adaptive robust estimation of regression models and applications
cites work: Monte Carlo evidence on adaptive maximum likelihood estimation of a regression
cites work: Information Theory and Statistical Mechanics
cites work: Q5615180
cites work: A Skew Extension of the T-Distribution, with Applications
cites work: Estimating classification error rate: repeated cross-validation, repeated hold-out and bootstrap
cites work: Q3859134
cites work: Parametric models for partially adaptive estimation with skewed and leptokurtic residuals
cites work: An efficient algorithm to compute maximum entropy densities
cites work: Maximum entropy autoregressive conditional heteroskedasticity model
cites work: Partially Adaptive Estimation via Quantile Functions
cites work: Model evaluation based on the sampling distribution of estimated absolute prediction error
cites work: Calculation of maximum entropy densities with application to income distribution
cites work: Partially adaptive estimation via the maximum entropy densities
DOI: 10.3390/E13010117
description: scientific article; zbMATH DE number 5995923