by Melissa R. Brown, CFA
The macroeconomy has dominated financial news in recent weeks, driven in no small part by the specter of rising inflation. In a fortunate coincidence, Qontigo has just released the new Axioma Macroeconomic Projection Equity Factor Risk Model (WWMP4). Among its many advantages, the new model allows us to dissect the impact of some of these concerns on a particularly hard-hit index, the STOXX® Global 1800 Ax Low Risk index, which has lagged its benchmark, the STOXX® Global 1800, by more than 260 basis points in the first two months of this year (albeit improved since mid-February). The cumulative active return is the dotted line in Figure 1.
Attribution using our standard Axioma Worldwide Fundamental Equity Factor Risk Model (WW4) lays the blame squarely on the index’s negative exposure to Market Sensitivity and Volatility. Both factors have produced unusually positive returns so far this year, and therefore the negative exposure hurt returns. Stock-specific returns also hurt, especially in February. Industry exposures were an initial drag, but the industry contribution turned around in the last few weeks. Country exposures helped returns, offsetting the drag from style factors and specific return by about 50 basis points. While this certainly serves as a reasonable explanation, it may not be the whole story.
Figure 1. Cumulative Active Return, Factor Block and Selected Factor Contributions, Year-to-Date 2021, STOXX Global 1800 Ax Low Risk Index, Worldwide Fundamental Model (WW4)
It’s the economy, silly!1
The Worldwide Macroeconomic Projection Model (WWMP4) tells a quite different story. This model projects macroeconomic factors onto the existing fundamental factors. Returns are first attributed to the portfolio’s active exposures to the macro factors and then to the residual portion of the style, industry and country factors. Currency exposures are treated the same in WW4 and WWMP4.
Compared with the Worldwide Fundamental Model, the Macro Model presents an alternate view. A breakdown of returns shows that much of the underperformance can be attributed to the portfolio’s negative macroeconomic exposures to Commodities, US Inflation expectations and the US Term Spread (Figure 2). Industry exposures were also a drag, as were specific returns, but style factor contributions in aggregate—mainly the same Market Sensitivity and Volatility exposures—were additive to returns, in sharp contrast with what we saw from WW4 (Figure 3).
Medium-Term Momentum, on the other hand, contributed positively according to WW4, but hurt returns according to WWMP4. The large differential in return from Medium-Term Momentum between the two models is also worth noting. Over the long term, Momentum has been less sensitive to the macro environment than other factors such as Market Sensitivity, and its factor returns as defined by WW4 have been close to the residual returns in WWMP4. However, there have been times when the factor has been highly positively or negatively correlated with macro variables, and this is one of those times[2].
Figure 2. Cumulative Active Return, Factor Block and Selected Factor Contributions, Year-to-Date 2021, Macroeconomic Projection Model (WWMP4)
Figure 3. Cumulative Selected Style Factor Contributions, WWMP4 vs. WW4
Conclusion
What does this mean? It has long been assumed that low-risk portfolios are sensitive to the macro economy in general and interest rates in particular. This analysis shows that, in fact, the STOXX Global 1800 Ax Low Risk Index does seem to be impacted by shifts in the macroeconomic outlook, as we can clearly see from the negative contribution from the macro factors. Using the macro model does not change the performance, of course, but provides analysis and insights through a different, and potentially more relevant, lens.
For more thoughts and research from the Applied Research team, please click here.
[1] With apologies to James Carville.
[2] The importance of taking this episodic sensitivity for Momentum in particular into account is highlighted in the paper by SSgA, written jointly with Qontigo, “Quantifying Macroeconomic Risk.”
