by Olivier d'Assier
As Mark Twain reputedly said, “History doesn’t repeat itself, but it often rhymes.” If the last three months of market volatility seem eerily familiar, it is because they are. In fact, looking at the volatility of the Russell 1000 as predicted by Axioma’s four US equity risk model variants since 1990, time spent at or near new volatility lows has rarely been followed by “happily-ever-after.”
Also note that the risk level after the latest volatility spike barely makes the cut in the top-10 list since 1990 (although the increase from the low has been substantial). The tech-bubble (1998) and subsequent bursting thereof (2000-2001), the GFC (2008), the European debt crisis (2011), and the China Crash (2015), all handsomely beat the recent highs of near 20% predicted volatility by any of our risk models.
Another forward-looking indicator that we often cite in our quarterly Axioma InsightTM webinars[1] is the risk spread between our Short-Horizon and Middle Horizon fundamental risk models. Figure 2 shows that since the start of 2019, this strongly positive risk spread[2] has seen a steep decline. While it remains in positive territory, the current spread of 0.2% is a far cry from the recent highs of 3.3%, reached on January 18, 2019.
But what if the fundamental model is, well, wrong? Not so much “wrong” as perhaps missing a non-recurring and transient factor that is temporarily affecting investor behavior and contributing to the current volatility of markets. Figure 3 shows the risk spread between the statistical and the fundamental short-horizon model forecast for the Russell 1000 index during the same period. This risk spread has surged at the same time that the spread between the two fundamental models in Figure 2 has declined, suggesting there may be more to the current market volatility than our fundamental eye might perceive—and that, in the short-term at least, there might be another factor at play[3].
This contradiction between the two risk spreads is not unfamiliar. The last time we experienced this was in Q4 of 2015, and we all know how Q1 2016 started out. Between the start of September 2015 to the end December, the SH-MH risk spread declined from a high of +4.5% following the China Crash, to a low of -1.6%. At the same time, the spread between the statistical and fundamental variants of the short-horizon model jumped from -2.8% to +1.0%. The latter spread remained positive for all of 2016, save for a short period in September that year. The driving force for 2016 was, of course, the US presidential election. The statistical model was able to capture this risk contributor, while the fundamental models reflected longer-term econometric concerns—which were all fairly good at the time.
The difference now is that the geopolitical headwinds are global. In the US, the openly partisan relationship between Congress and the White House is now deeply confrontational. And just when Europeans thought nothing could rival their regional bickering over Brexit, the intricacies of both British and German politics, and the self-destructive budgeting of a populist Italian government, President Donald Trump, freshly bruised from his previous shutdown fight with Congress, has opted to add a second summit with the North Korean leader in order to defuse the denuclearization grenade he unpinned during their first meeting in Singapore last June. Simultaneously, the British government and the EU seem to be playing a game of chicken, hurtling towards the March Brexit wall ‘sans’ brakes. All of this is taking place amid a sharply slowing Chinese economy, a looming trade war, and a dividend yield for S&P500 companies at 2.01% (2.0% one year ago) versus a 1-year Treasury yield of 2.56% (1.95% one year ago).
Given all of the above, the statistical model seems to be paraphrasing the Kingsman in telling us that this is not the end. Nor is it the beginning. It is not even the beginning of the end. But perhaps, it is the end of the beginning.
[1] Sign-up for the Axioma InsightTM webinars here: https://www.axioma.com/events/
[2] Positive means that volatility predicted by the short-horizon model is higher than that predicted by the medium horizon one, indicating that risk is still trending upwards in the short term.
[3] “Another” refers to the fundamental factors in the AXUS4-SH model. Possible transient factors include the US Shutdown Round 2, Brexit, North Korea, [insert your favorite geopolitical crisis du jour here].
