MAD Risk Parity Portfolios

TL;DR

This paper explores the use of Mean Absolute Deviation in Risk Parity portfolios, proposing new formulations and empirically analyzing their performance compared to traditional strategies.

Contribution

It introduces novel MAD-based formulations for Risk Parity portfolios and provides comprehensive empirical evaluation of their effectiveness.

Findings

MAD-RP portfolios perform between minimum risk and equal weight strategies in risk and return.

New computational methods improve accuracy and efficiency of MAD-RP portfolio construction.

Empirical results validate the practical viability of MAD in risk parity asset allocation.

Abstract

In this paper, we investigate the features and the performance of the Risk Parity (RP) portfolios using the Mean Absolute Deviation (MAD) as a risk measure. The RP model is a recent strategy for asset allocation that aims at equally sharing the global portfolio risk among all the assets of an investment universe. We discuss here some existing and new results about the properties of MAD that are useful for the RP approach. We propose several formulations for finding MAD-RP portfolios computationally, and compare them in terms of accuracy and efficiency. Furthermore, we provide extensive empirical analysis based on three real-world datasets, showing that the performances of the RP approaches generally tend to place both in terms of risk and profitability between those obtained from the minimum risk and the Equally Weighted strategies.