Risk Factors As Building Blocks For Portfolio Diversification: The Chemistry Of Asset Allocation by Eugene L. Podkaminer, CFA, CFA Institute
Asset classes can be broken down into factors that explain risk, return, and correlation characteristics better than traditional approaches. Because seemingly diverse asset classes may have high correlations as a result of overlapping risk factor exposures, factor analysis can improve portfolio diversification. Creating risk factor–based portfolios is theoretically possible, but practically challenging. Nevertheless, factor-based methodologies can be used to enhance portfolio construction and management.
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- Asset classes can be broken down into building blocks, or factors, that explain the majority of the assets’ risk and return characteristics. A factor-based investment approach enables the investor theoretically to remix the factors into portfolios that are better diversified and more efficient than traditional portfolios.
- Seemingly diverse asset classes can have unexpectedly high correlations—a result of the significant overlap in their underlying common risk factor exposures. These high correlations caused many portfolios to exhibit poor diversification in the recent market downturn, and investors can use risk factors to view their portfolios and assess risk.
- Although constructing ex ante optimized portfolios using risk factor inputs is possible, there are significant challenges to overcome, including the need for active, frequent rebalancing; creation of forward-looking assumptions; and the use of derivatives and short positions. However, key elements of factor-based methodologies can be integrated in multiple ways into traditional asset allocation structures to enhance portfolio construction, illuminate sources of risk, and inform manager structure.
Risk Factors As Building Blocks For Portfolio Diversification: The Chemistry Of Asset Allocation – Introduction
In search of higher returns at current risk levels, institutional investors have expressed intense interest in further diversifying seemingly staid, “traditional” asset allocations constructed using asset class inputs with mean-variance-optimization (MVO) tools. During the past decade, institutional investors have augmented public fixed income and equity allocations with a wide range of strategies—including full and partial long/short, riskparity, and low-volatility strategies—and have enlarged allocations to alternative strategies. However, comparatively little has been accomplished at the overall policy level; for most investors, asset classes remain the primary portfolio building blocks.
In this article, I explore portfolio construction by using risk factors, also referred to as “risk premia,” as the basic elements. Theoretically, this approach may result in lower correlations between various portfolio components and may lead to more efficient and diversified allocations than traditional methods. However, the practical limitations of policy portfolios constructed with risk factors are significant enough that few investors are embracing full-scale implementation. Yet, much of the intuition of risk factor portfolios can be used to refine and augment traditional allocations and offers a holistic and succinct manner to diversify portfolio risk.
Why Look At Risk Factors?
Recent periods of market stress and dislocation have created considerable interest in credible alternatives to MVO asset allocation methodologies. A multitude of alternative approaches question the quality of the inputs rather than the tools, such as optimizers, that assist in generating asset allocations. From an attribution perspective, many vendors of risk analytics systems use factors to provide a clearer perspective on common exposures across an entire portfolio, rather than simply reporting on siloed asset classes measured with incompatible tools. Practitioners seek inputs that capture essential trade-offs, with logical relationships among components that result in reasonable portfolios. This spawns an interest in a risk factor approach.
Many traditional asset class and sub-asset-class correlations have trended upward over the past decade. These correlations rose to uncomfortable levels during the 2008–09 crisis, driving a desire to find a way to construct portfolios with lower correlations between the various components. High correlations caused many investors to question basic assumptions about traditional models. Seemingly disparate asset classes moved in lockstep during the depths of the crisis, and the distinction in returns between U.S. equity and non-U.S. equity, for instance, was largely immaterial. Because many asset classes, such as equity, fixed income and real estate, have become increasingly correlated, some investors have sought out less correlated, alternative investments, such as hedge funds, commodities, and infrastructure.
Ideally, investors could create portfolios using many components with independent risks that are individually rewarded by the market for their level of risk. Asset classes could be broken down into building blocks, or factors, that explain the majority of their return and risk characteristics. These asset classes would provide an indirect way to invest in factors, but it is also possible to invest in some factors directly. The advantage to a factor-based approach is that factors can, theoretically, be remixed into portfolios that are better diversified and more efficient than traditional methods allow.
Prior to fully defining factors and explaining how they are derived, I review some of the basic tenets of asset class–based portfolio construction, including tools and required inputs, in order to understand how a risk factor–based approach diverges from the traditional asset class approach. The use of risk factors is the next step in the evolution of the policy portfolio.
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