Factor investing using risk parity optimization
1University of Oulu, Oulu Business School, Department of Finance, Finance
|Online Access:||PDF Full Text (PDF, )|
|Persistent link:|| http://urn.fi/URN:NBN:fi:oulu-201811283113
|Publish Date:|| 2018-11-28
|Thesis type:||Master's thesis
Investor’s dilemma is: “How to earn the highest possible return with the lowest possible risk.” Yet, if we understood better what is driving the returns and risks, our portfolios could become better performing and diversified. We would also potentially encounter less unpleasant surprises during economic downturns. This seemingly easy question has become a challenging one since investors have failed to diversify portfolios well enough especially during bad times. Factors are currently a popular topic in the financial industry. Yet, majority of the literature focuses on the significance of certain factors and less on how to apply factors in practice. Risk parity optimization serves an attractive alternative for optimizing portfolio weights. The aim of this study is to analyze whether our attention should be directed from asset classes to factors and what benefits such drift could possibly entail. Therefore, the research questions are organized as follows: 1. How chosen factors perform during different periods? 2. What factors seems to be the most persistent out of the six chosen factors? 3. How optimized portfolios perform with respect to the control portfolios? 4. How the chosen portfolio optimization methods work in terms of returns and risks? 5. What is the risk distribution of each constructed portfolio? 6. What do factors reveal from the MSCI World index? We focus on the practical part of portfolio management and aim at outperforming a global equity fund. We use index performance data from the Morgan Stanley Capital International (MSCI) and our broad sample period is 30th Nov 1998 – 31st May 2018. The study is conducted by using long only factor exposures and static weights. As we do not need constant rebalancing and also because currently there are existing low cost ETFs to all used indices, trading costs are not included. This study shows how an attractive risk return based portfolio is constructed using Value, Momentum, Size, Quality, Low Volatility and Dividend factors. We optimize six static portfolios using different risk parity optimized methods and compare their performance to two benchmark portfolios; Equal Weighted (EW) or often called 1/N along with Restricted Minimum Variance. First contribution of this study is that by combing the factors together investors ensure that they are exposing portfolio to the best performing factors. In addition to that, this study verifies that risk optimized portfolios lead win the horse race with EW. Yet, Restricted Minimum Variance portfolio is able to achieve the most attractive risk return tradeoff and wins the competition, but Beta Risk Parity offers better solution from the diversification point of view. Unlike than MVR that chooses only two factors; BRP uses all the six of them. Furthermore, this study confirms that it is generally advisable to shift attention from an asset class-based allocation towards the risk-based allocation. This is due to the fact that the performance of each sample portfolio seems to beat the performance of MSCI World. Such portfolio offers a more favorable return and risk reward relation that should be the simple goal of each rational investor.
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