Original scientific paper
https://doi.org/10.1080/1331677X.2021.1981963
Improving the volatility of the optimal weights of the Markowitz model
Roberto Ortiz
Mauricio Contreras
Cristhian Mellado
Abstract
The main practical problems that are faced by portfolio optimisation under the Markowitz model are (i) its lower out-of-sample
performance than the naive 1=n rule, (ii) the resulting asset
weights with extreme values, and (iii) the high sensitivity of those
asset weights to small changes in the data. In this study, we aim
to overcome these problems by using a computation method
that shifts the smaller eigenvalues of the covariance matrix to the
space that houses the eigenvalue spectrum of a random matrix.
We evaluate this new method using a rolling sample approach.
We obtain portfolios that show both more stable asset weights
and better performance than the 1=n rule. We expect that this
new computation method will be extended to several problems
in portfolio management, thereby improving their consistency
and performance.
Keywords
Portfolio selection; risk estimation; investment performance; random matrix theory; eigenvalue spectrum
Hrčak ID:
302486
URI
Publication date:
31.3.2023.
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