A Cost-effective Approach to Portfolio Construction with Range-based Risk Measures

34 Pages Posted: 12 Dec 2019

See all articles by Chi Seng Pun

Chi Seng Pun

Nanyang Technological University (NTU) - School of Physical and Mathematical Sciences

Lei Wang

Nanyang Technological University (NTU) - School of Physical and Mathematical Sciences

Date Written: November 25, 2019

Abstract

In this paper, we introduce a new class of risk measures and the corresponding risk minimizing portfolio optimization problem. Instead of measuring the expected deviation of a daily return from a single target value, we propose to measure its deviation from a range of values centered on the single target value. By relaxing the definition of deviation, the proposed risk measure is robust to the variation of data input and thus the resulting risk-minimizing portfolio has a lower turnover rate and is resilient to outliers. To construct a practical portfolio, we propose to impose an ℓ2-norm constraint on the portfolio weights to stabilize the portfolio's out-of-sample performance. We show that for some cases of our proposed range-based risk measures, the corresponding portfolio optimization can be recast as a support vector regression problem. This allows us to tap into the machine learning literature on support vector regression and effectively solve the portfolio optimization problem even in high dimensions. Moreover, we present theoretical results on the robustness of our range-based risk minimizing portfolios. Simulation and empirical studies are conducted to examine the out-of-sample performance of the proposed portfolios.

Keywords: Portfolio selection, Range-based risk measure, ℓ2-regularized portfolios, Machine learning, Support vector regression, Robustness

JEL Classification: G11, C32

Suggested Citation

Pun, Chi Seng and Wang, Lei, A Cost-effective Approach to Portfolio Construction with Range-based Risk Measures (November 25, 2019). Available at SSRN: https://ssrn.com/abstract=3493493 or http://dx.doi.org/10.2139/ssrn.3493493

Chi Seng Pun (Contact Author)

Nanyang Technological University (NTU) - School of Physical and Mathematical Sciences ( email )

SPMS-MAS-05-22
21 Nanyang Link
Singapore, 637371
Singapore
(+65) 6513 7468 (Phone)

HOME PAGE: http://www.ntu.edu.sg/home/cspun/

Lei Wang

Nanyang Technological University (NTU) - School of Physical and Mathematical Sciences ( email )

S3 B2-A28 Nanyang Avenue
Singapore, 639798
Singapore

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
20
Abstract Views
126
PlumX Metrics