Are Asset Classes Providing You Diversification?

Diversification is critical to portfolio construction. Using asset classes as the building blocks for diversification, however, can overlook shared risks across asset classes. This post explores how a factor-based approach can help investors uncover overlapping risks in portfolios and improve diversification.

Introduction

Traditional asset class allocation provides investors with a framework for portfolio construction. Investors hope that by allocating across various asset classes, like stocks and bonds, they will achieve portfolio diversification and therefore lower overall portfolio risk.

Venn provides investors with a different lens through which to approach portfolio diversification: risk factors. Risk factors are describable sources of common risk and return across a diverse set of investments and even asset classes. Why use risk factors for portfolio construction? We believe that risk factors, as compared to asset classes, can provide a more granular risk lens and can be constructed to capture independent sources of risk. Therefore, risk factors may help investors achieve more effective portfolio diversification.

Risk Factors Are More Granular Than Asset Classes

Traditional asset class allocation may disregard overlapping risk drivers across asset classes. How might this happen? Take the Bloomberg Barclays Global High Yield Index, for example. From an asset class perspective, the index is made up of a combination of corporate and emerging market bonds.¹ However, from a risk factor perspective, the index is exposed to equity, foreign currency, and credit risks.² Therefore, high yield bonds (as represented by this index) are exposed to more than just downturns in the credit market; we’d expect downturns in the equity market and foreign currency fluctuations to impact the index’s performance, as well.

Exhibit 1: Asset Class Versus Risk Factor Breakdown of the Bloomberg Barclays Global High Yield Index

Thus, a portfolio made up of high yield bonds and stocks may appear diversified, as dollars are spread across two different asset classes (stocks and bonds). However, because both asset classes are exposed to the equity market, the portfolio might not be as diversified from a risk perspective as it would appear to be.

Risk factors can help investors zero in on more granular drivers of portfolio risk and returns. If a portfolio is diversified across many different types of assets, risk factor analysis can help investors understand the elemental exposures of their portfolio once the risks are aggregated across all of the assets.

Risk Factors Are Designed to Be Uncorrelated

As mentioned above, asset classes may have overlapping risk drivers, resulting in positive correlations. In the prior example, high yield bonds and stocks may be positively correlated because of their shared exposure to equity risk.

Further, asset class correlations can be meaningfully high during market disruptions, exactly when diversification is needed the most. The blue bars in Exhibit 2 display correlations among asset classes during the Global Financial Crisis stress period (September 15, 2008 – March 9, 2009). The gray bars demonstrate correlations among risk factors. On average, the asset class pairs exhibited higher, positive correlations over this time relative to the factor pairs. This is by design. The risk factors in the Two Sigma Factor Lens are constructed to capture statistically uncorrelated sources of risk across asset classes by residualizing less liquid macro factors against more liquid ones.³

Exhibit 2: Asset Class Correlations Were Generally Higher Than Factor Correlations During the Global Financial Crisis⁴

Risk Factors Should Be Actionable

The beauty of asset classes is that they are investable. If an investor is underallocated to equities, increasing that exposure is simply a matter of purchasing stocks. We believe that risk factors should be designed to make factor-based analysis interpretable and actionable.

Venn is intended to provide investors with access to a thoughtfully constructed factor lens that can help identify common drivers of risk in portfolios and, ultimately, help investors achieve more effective diversification.

To illustrate the actionability of factors, Exhibit 3 provides the underlying indices used to construct the core macro factors in the Two Sigma Factor Lens. Each of these indices is comprised of a variety of investable, liquid instruments.⁵ Therefore, we believe that investors using the Two Sigma Factor Lens for factor analysis could readily translate their desired changes to factor exposures into asset allocation changes.

Exhibit 3: Core Macro Factors and Indices

Take action: Applying risk factors to portfolio construction

To illustrate the potential benefits of using factors for diversification, let’s analyze Venn’s demo portfolio.⁶ This portfolio contains a mix of asset classes, including a 35% allocation to equity funds, 29% to fixed income funds and 33% to “Other” funds (“Other” combines real estate, liquid alternative, and commodity funds). This portfolio is ostensibly well diversified. Analyzing this portfolio with Venn, however, paints a different picture.

Exhibit 4 | Demo Portfolio Asset Class Allocations⁷

Exhibit 5: Demo Portfolio Risk Factor Analysis⁸

Despite only 35% of the capital in the demo portfolio being allocated to equity funds, the Equity factor has driven over 85% of the risk in this portfolio. And the 29% allocation to fixed income funds doesn’t appear to have meaningfully influenced the risk of the portfolio. The Interest Rates factor is shown as contributing less than 2% to the portfolio’s overall risk.

We believe there are various reasons why Equity overshadows Interest Rates and other factors in this analysis. One is that different levels of risk factor volatility can manifest themselves unequally in a portfolio. Equity volatility can be more than four times as large as bond volatility.⁹ As a result, even in a portfolio diversified by asset classes, Interest Rate risk can be drowned out when other, more volatile risk drivers are present.

Another reason Equity may contribute so much to risk is that investments in non-stock asset classes, such as Real Estate and Commodities, also can provide exposure to the Equity factor.¹⁰

Conclusion

Investors who incorporate a factor view may be able to gain a better understanding of how diversified they actually are. Two Sigma’s paper, “Introducing the Two Sigma Factor Lens,” highlights certain aspects of factor definition and construction in the Two Sigma Factor Lens.¹¹ Notably, it suggests that residualized factors can exhibit lower correlations than asset classes in different market environments and, to that end, serve as a better measure of diversification.

There are many places to start incorporating a factor-based approach. For example, Venn provides the following factor-based analytical tools:

• Manager evaluation: Use factors to estimate an investment’s potential diversification impact
• Portfolio analysis: Use factors to estimate the effect of portfolio modifications to overall risk exposure
• Optimization: Use factors to help align allocation decisions with investment objectives
• Venncast: Use factors to estimate daily portfolio or investment performance
• Drawdown analysis: Use factors to estimate how historical scenarios, if repeated today, might impact a portfolio

To learn more about factors, visit the Venn site. Don't have an account? Sign up for free today.

References

¹ https://data.bloomberglp.com/indices/sites/2/2016/08/Factsheet-Global-High-Yield.pdf

² Venn Tearsheet Analysis, Factor Contributions to Risk, March 2019. Time period: December 6, 2010 – March 1, 2019. We’d like to mention that the index had a positive beta to the Interest Rates factor over this time period, however the Interest Rates factor’s (correlation-adjusted) contribution to risk was near zero. This is because of Interest Rates’ negative correlation with Equity over this time period and the relatively low volatility of the Interest Rates factor versus the index’s other prominent factors: Equity, Credit, and Foreign Currency.

³ The Credit and Commodities factors in the Two Sigma Factor Lens are residualized against both the Equity and Interest Rates factors.

⁴ Rolling 5-day (weekday) data from September 15, 2008 – March 9, 2009. Asset classes are represented by MSCI ACWI (Equity), Bloomberg Barclays Global 7-10 Year Total Return Index Hedged USD (Sovereign Bond), Bloomberg Barclays Global High Yield Total Return Index Value Hedged to USD (High Yield), and Bloomberg Commodity Index (Commodity). Factors are the Equity (Equity), Interest Rates (Sovereign Bond), Credit (High Yield), and Commodities (Commodity) factors from the Two Sigma Factor Lens. Analysis as of April 2019. Average pairwise correlation is the average of the absolute values of the correlations.

⁵ Sources: MSCI, Bloomberg Barclays, and Bloomberg.

⁶ Venn’s USD demo portfolio is a default portfolio that comes pre-populated with every USD account to help demonstrate Venn’s analytics.

⁷ Venn’s USD demo portfolio as of March 2019.

⁸ Venn Analysis, February 2019. Time period: December 19, 2011 – January 11, 2019.

⁹ Venn Factor Insights, February 2019. Time period: January 1, 2003 – February 8, 2019. Annualized volatility for the Equity factor was 14.00%, while annualized volatility for the Interest Rates factor was 2.96%.

¹⁰ Venn USD demo portfolio Pro Forma Analysis, March 2019. Time period: December 19, 2011 – February 28, 2019. The Real Estate sub-strategy in the demo portfolio has a 1.07 beta to Equity. The Commodities sub-strategy has a 0.43 beta to Equity.

¹¹ At the time of the publication of the paper.

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