Blog Posts — March 2, 2021

When Macro Factors Speak, Investors Should Listen

The new Axioma Worldwide Macroeconomic Projection Equity Factor Risk Model offers a unique way to identify a portfolio’s exposures to macroeconomic factors, such as interest rates and inflation, while maintaining the structure and benefits of a more traditional fundamental equity factor risk model. With macroeconomic factors projected onto fundamental factors, the risk forecasts do not change; only the distribution of the risk varies.

The benefit of this approach is that the user sees a consistent risk forecast, while at the same time gaining a better understanding of how economic changes may impact returns. While macroeconomic exposures do not always account for substantial risk, and may not impact all types of portfolios, at times they can be quite significant. The risk model user should be aware of this and may want to mitigate the exposure, or at least understand how the macro economy has impacted portfolio returns. That is where this model comes in.

Macro Factor Exposures Hurt the Global 1800 Index

An attribution of the drivers of the 8.52% annualized return from 2004 through 2020 for the STOXX Global 1800 index from the standard Worldwide medium-horizon model (WW4) shows, as expected, that the major driver of return for the index was its exposure to the market. Using the macroeconomic model (WWMP4), however, shows that the market “would have” produced higher returns had the index’s macroeconomic exposures not generated a significant drag (Figure 1).

Unlike traditional fundamental style factors, which are standardized and generally close to zero when aggregated for a broad collection of stocks, the macroeconomic factors in this model are calculated as a beta times the original exposure to the fundamental factor. Therefore, even a broad benchmark like the STOXX Global 1800 may have significant macro exposures.


A detailed accounting of the return drag from the macro factors (Figure 2) shows that the exposure to non-Energy Commodities was one of the few that boosted returns, whereas Oil, and GB and US term and credit spreads, hurt. Other macro factors had little or no impact on the index return.

Figure 1. Annualized Return and Factor Contribution to STOXX Global 1800 Return, Worldwide vs. Macroeconomic Model, 2004 – 2020

Source: Qontigo

Figure 2. Breakdown of Macro Factor Contribution, Annualized

Source: Qontigo

Drilling down for a deeper look at the time series, we note that Non-Energy Commodities exposure, which was positive throughout the 17-year period, had a large and consistent positive impact (almost 2% per year), but a number of other factors were significant negative contributors (Figure 3).  Of those, the generally negative GBP BBB Corporate Spread exposure (Figure 4) produced a consistently adverse return contribution, culminating in a huge stumble as the market fell in early 2020, despite a relatively small negative exposure at the time.  (Remember that spreads widened substantially in March at the same time the market tanked.) USD BBB spreads also clobbered returns but had had almost no impact before then.

The sensitivity2 of the index to macroeconomic variables in the model has fluctuated substantially over time. In some cases, the sign of the sensitivity rarely changes, but the magnitude does (for example, the US Term Spread, Oil and Commodities). This means that we would expect the index to rise as the commodity price goes up or the term spread widens. For other factors, the sensitivity fluctuates between negative and positive, and may therefore be even more important to track. In late 2006, the STOXX Global 1800 had a negative exposure to the US BBB Spread, so we would have expected the index to fall as the spread widened. By 2013 the exposure reached its peak positive level, suggesting that after four years of economic recovery widening spreads would actually be good for equities. That reversed quickly, though.

Exposures may not always be significant, but when they are, investors should take notice

Much of the time exposures are close to zero (for example, for the GB Term Spread). This suggests they are unlikely to have a major impact on the index. But when they do dip or soar, the effects may be significant. As the GB Term Spread sensitivity dipped at the height of the global financial crisis, it also detracted almost 20% from the index return over the next year. Imagine if you could have hedged that macro exposure!

Figure 3. Cumulative Return Contribution of Highest Contributing Macro Factors

Source: Qontigo

Figure 4. Exposures to Highest Contributing Macroeconomic Factors

Source: Qontigo

Conclusion

Your results may differ, of course, especially in an active portfolio. This simple example was based on a broad index. In future articles, we will look at the macro exposures and their impact on the return of various types of portfolios. The model is designed to recognize these exposures and their contributions to portfolio risk and return. It can also be used in portfolio construction to mitigate the types of risks we have noted here, or to allow users to bet more efficiently on the factors on which they have views, while maintaining the same overall total and active risk level as the standard fundamental model on which these factors have been projected. It may not be necessary for every risk review or portfolio rebalancing, but when the macro factors speak, investors should listen.


1 Note that the style and industry exposures for the macro model are residual to the macroeconomic factors, so the interpretation of the exposures is different

2 Note that we use “exposure” and “sensitivity” interchangeably here. One could also use the term beta.