Combination Portfolio: A Cocktail Therapy for Training Portfolio Selection

48 Pages Posted: 14 Sep 2019 Last revised: 27 Dec 2019

See all articles by Tsung-Wu Ho

Tsung-Wu Ho

National Taiwan Normal University, College of Management

Date Written: October 25, 2019

Abstract

The quantitative practice of portfolio selection aims to select the in-sample optimal portfolio that is robust out of sample. However, at each estimation period, the conventional method is selection by solving a given objective function, without a learning mechanism, or training.

This paper designs a method to train portfolio selection. Each optimal portfolio is a combination of three basic elements: strategy, covariance matrix, and risk type; therefore, like the cocktail therapy, we propose a selection method by first augmenting the combination to 250 optimal portfolios at each estimation period, and then we propose a score to select the best portfolio to hold in the next period. In the machine learning literature, combining multiple models together in some way has proven to be useful. Such combinations of models are sometimes called committees. We show that the combination portfolio exhibits superior performance and robustness, and the alternative way to train portfolio selection is useful.

Keywords: portfolio selection, combination portfolio, mean-variance, risk diversification, risk optimal

JEL Classification: C13, C51, G11

Suggested Citation

Ho, Tsung-Wu, Combination Portfolio: A Cocktail Therapy for Training Portfolio Selection (October 25, 2019). Available at SSRN: https://ssrn.com/abstract=3448896 or http://dx.doi.org/10.2139/ssrn.3448896

Tsung-Wu Ho (Contact Author)

National Taiwan Normal University, College of Management ( email )

No. 31, Shi-Da Road
Taipei, 10610
Taiwan
+886(2)7734-5624 (Phone)

HOME PAGE: http://web.ntnu.edu.tw/~tsungwu/

Register to save articles to
your library

Register

Paper statistics

Downloads
163
Abstract Views
559
rank
188,046
PlumX Metrics