Journal of the Operations Research Society of Japan
Online ISSN : 2188-8299
Print ISSN : 0453-4514
ISSN-L : 0453-4514
ASSET ALLOCATION WITH ASSET-CLASS-BASED AND FACTOR-BASED RISK PARITY APPROACHES
Hirotaka KatoNorio Hibiki
Author information
JOURNAL FREE ACCESS

2020 Volume 63 Issue 4 Pages 93-113

Details
Abstract

The asset allocation strategy is important to manage assets effectively. In recent years, the risk parity strategy has become attractive to academics and practitioners. The risk parity strategy determines the allocation for asset classes in order to equalize their contributions to overall portfolio risk. Roncalli and Weisang (2016) propose the use of “risk factors” instead of asset classes. This approach achieves the portfolio diversification based on the decomposition of portfolio risk into risk factor contribution. The factor-based risk parity approach can diversify across the true sources of risk whereas the asset-class-based approach may lead to solutions with hidden risk concentration. However, it has some shortcomings. In our paper, we propose a methodology of constructing the well-balanced portfolio by the mixture of asset-class-based and factor-based risk parity approaches. We also propose the method of determining the weight of two approaches using the diversification index. We can construct the portfolio dynamically controlled with the weight which is adjusted in response to market environment. We examine the characteristics of the model through the numerical tests with seven global financial indices and three factors. We find it gives the well-balanced portfolio between asset and factor diversifications. We also implement the backtest from 2005 to 2018, and the performances are measured on a USD basis. We find our method decreases standard deviation of return and downside risk, and it has a higher Sharpe ratio than other portfolio strategies. These results show our new method has practical advantages.

Content from these authors
© 2020 The Operations Research Society of Japan
Next article
feedback
Top