Watch the Tails - Expanding our Macro Detection Palette

‍Last week, we delved into ‘when’ macro matters by using the Axioma Macro Projection Model to identify historical periods when macro factors drove US equity volatility. This approach highlighted the Sovereign Debt Crisis in 2012 and the COVID market downturn as periods when macro factors became the leading contributors to volatility in the Russell 1000 Index. We also observed evidence of macro influence on performance during the COVID recovery period and uncovered Inflation as a critical rebound driver of equities in the past year.

This week we take a closer look into the role that inflation is playing in the market.

Now on to this week’s topic. As noted by CNBC, following a disappointing jobs report on Friday that saw just 266,000 jobs added relative to an expected 1,000,000, all eyes will be on this Wednesday’s CPI news. Despite the Fed’s recent announcement that it does not plan to intervene in the near term, increased inflationary pressures may force the Fed’s hand to act much sooner than they had planned.

We can again turn to Axioma’s Macro Projection model to uncover the role inflation plays in the current market. This time, we’re going to look a little further back to get a sense of how today’s environment stacks up historically. We will take a different approach this week to focus on factor exposures rather than contributions to risk.

‍Macro Insights via Exposures

‍In the Axioma Worldwide Fundamental Model, we know that style factor exposures are represented by z-scores to illustrate a universe mean-relative tilt for each stock in the model. In the Axioma Macro Projection model, however, macro factor exposures are expressed in terms of a stock’s beta sensitivity to each factor. Because of this, exposures across the market can change dramatically over time both in terms of direction and dispersion.

Let’s take a look at the Inflation factor, for example. Below, we show the distribution of exposures for stocks in the Russell 1000 through the 5th, 25th, 50th, 75th, and 95th percentiles. The median will tell us when stocks generally become more or less sensitive to each factor and the outer percentile bounds will shed insight into the dispersion across the index. Dispersion tells us how different exposures can be across a single index at any given point in time.

It’s clear that Mar 2020-present has been a period of historic inflationary pressure in the large cap US market. The median exposure to the Inflation factor reached 10.17 in May and September, higher than any time since pre-2008 including its peak of 9.02 in May 2016. The 95th percentile reached 23.44 in that same time frame, while the 5th percentile was at just 3.26, illustrating a wide dispersion in the distribution of exposures.

‍What do These Exposures Mean Practically?

‍The predicted annualized volatility of the Inflation factor was 0.63% as of April 30th, well above its 0.55% 10-year average. This may seem insignificant but the 95th percentile stock in the Russell 1000 had an exposure of 18.21 on April 30th, meaning a 0.63% move in the Inflation factor would result in a performance impact of approximately 11.5% for that name.

‍What about Commodity Factors?

‍The Inflation factor in this model is represented by the changes in the 5-Year breakeven inflation rate which generally measures the difference in yield between nominal and inflation-protected bonds of the same maturity. To get a more holistic picture of the inflationary landscape, we will also want to explore non-oil commodities which are represented in the Axioma model by the Gold factor and Commodity factor as commodities tend to feel increased impacts from dramatic movements in inflation.

From the beginning of the COVID pandemic to today, the Gold and Commodity factors show a similar trend both in direction and dispersion. Stocks in the Russell 1000, in general, have seen a large increase in sensitivity to commodity prices, particularly at the high end of the spectrum. Although the units are much smaller for these factors than what we saw in Inflation, the commodity factors themselves are much more volatile. Because these factors are based on market-traded indices with much larger magnitudes of daily price changes, equity betas to these factors will be smaller than those of the Inflation factor.

Gold factor predicted annualized standard deviation as of April 30th: 14.94%
Commodity factor predicted annualized standard deviation as of April 30th: 12.23%

Now that we’ve confirmed the unique nature of the current inflation-driven market environment we are in, there are two follow-up questions we need to ask:

1. What is driving the spikes and dispersion?
2. What can we do about inflation-related risk?

To answer the first question, we quartiled the stocks in the Russell 1000 by a multi-factor exposure to the Inflation, Gold, and Commodity factors. We can see below the number of stocks that fall into the top and bottom quartiles by sector along with the percent that number represents relative to the total number of stocks in the index.

The percentages highlighted in green within the “Top Quartile % of Stocks” column tell us what sectors tend to have particularly high exposure to inflation and commodity factors. The ones highlighted in green within the “Bottom Quartile & of Stocks” column tell us what sectors tend to have particularly low exposure to inflation and commodity factors.

Sectors like Energy and Utilities, for example, pass the intuition test. However, it’s important to note that many sectors, highlighted in yellow, show a significant dispersion. For example, about 25% of Communication Services stocks are highly exposed to these factors on aggregate while 25% of the stocks are underexposed relative to the rest of the index.

For fundamental managers, there is value not only in sector allocation to mitigate inflation risk, but also in stock selection within key sectors. Being deliberate in these two areas can help managers better understand and dictate inflationary risks in their portfolios.

‍Concluding Thoughts

‍Macro matters today because more subjective intuitions around macro influences almost always tend to fall short. Leveraging macro models alongside fundamental models will quantify the true intended and unintended exposures and risks across a portfolio. Now that we have our research compiled we will use next week’s Factor Spotlight to address our second question: “What can we do about to mitigate macro-related risks?”.

US & Global Market Summary

US Market: 05/03/21 - 05/07/21

• The S&P 500 and DJIA both hit record highs on Friday after a weak jobs print allayed concerns over the Fed tamping down its stimulus efforts in the near term.
• Value outperformed growth on the week as the Nasdaq ended lower for the third straight week despite a nearly +1% move on Friday.
• In April, the US added 266,000 jobs vs. consensus expectations close to 1 million - one of the biggest misses in decades. Job gains in March were also revised lower. Unemployment rose from 6% in March to 6.1% in April, possibly due to a shortage of workers and raw materials.
• The US dollar fell towards its lowest level since February relative to a basket of major currencies on the expectation of continued liquidity from the Fed and that interest rates will remain suppressed.
• About 88% of S&P 500 companies have reported 1Q21 results thus far, with 86% of them beating consensus EPS.

‍Normalized Factor Returns: Axioma US Equity Risk Model (AXUS4-MH)

• Momentum saw positive normalized gains for the 6th straight week, and is now in Overbought territory at +1 standard deviation above the mean.
• Value appears to have hit a nadir of -1.76 SD below the mean on 5/4, and saw a slight uptick on a normalized basis towards the end of the week.
• Market Sensitivity saw a decline as it headed deeper into negative normalized space at -1.62 SD below the mean.
• Size continued to slip from its 4/20 peak of +2.08 SD above the mean while remaining an Overbought factor at +1.49 SD above the mean.
• Growth was the week’s biggest loser, as it fell away from its recent peak of +1.78 SD above the mean on 4/30.
• US Total Risk (using the Russell 3000 as proxy) declined by 24 basis points.

‍Normalized Factor Returns: Axioma Worldwide Equity Risk Model (AXWW4-MH)

• Exchange Rate Sensitivity saw the biggest positive move this week, as it headed back towards the mean with a +0.35 standard deviation move.
• Value ticked up after hitting a trough of -1.8 SD below the mean on 4/30 and appears to be reverting towards the mean while remaining an Oversold factor.
• Momentum headed higher into Overbought space at +1.21 SD above the mean.
• Profitability has seen some interesting movement as of late, peaking at +2.41 SD above the mean on 4/21, then drifting down to +1.94 SD above the mean on 5/3, and now back on the rise at +2.07 SD above the mean.
• Earnings Yield saw a significant decline, moving from positive to negative normalized space during the course of the week.
• Global Risk (using the ACWI as proxy) fell by 15 basis points.

Regards,
Kevin