Digging Deeper Into Macro Factors - which companies are most sensitive to China & US economies

Last week, we introduced Wolfe Research’s Macroeconomic Factor Overlay by highlighting some interesting macro factors that the S&P 500 is exposed to. One of the chief follow-up questions that we’ve heard is “How do I determine the potential impact on my portfolio if these macro indicators change?”

Today, we’ll dig a little deeper into the Wolfe macro factor library to better understand how it works, and to show how it can specifically be leveraged by investment managers to make better decisions. As usual we will also provide our weekly factor market update.

Understanding the Wolfe Macro Factors

To begin, let’s get an intuition for these macro factors by looking at two of the common factors in the library: US PMI and China PMI. PMI measures the activity level of purchasing managers in the manufacturing sector and is typically considered to be a leading economic indicator.

Wolfe Research measures each company’s excess stock price return sensitivity to these PMI indicators. The excess return is calculated by removing the component of the stock price return that is explained by the market. For example, if the market returned 1%, and security ABC has a beta of 1.5, but shows a total return of 2%, we’d remove the 1.5%, and then correlate the movement of the PMI indicator with the 50bps in excess return.

Searching for companies with high excess stock price return sensitivity to changes in US and China PMI can help us learn which companies investors believe will be the first to move with a positive or negative reading in these indicators.

For US-focused investors, the top 5 most sensitive securities in the S&P500 to the US PMI are the retailers Macy’s & Kohls, and financial institutions Goldman Sachs, Ameriprise, and Regions. For Macy’s and Kohls, a 1% movement in the US PMI translates roughly to a 1.88% and 1.83% excess returns.

For international investors, the top 5 most sensitive securities in the MSCI ACWI to China PMI are from Brazil, Greece, and Indonesia:

• As many of us are aware, China is Brazil’s largest trading partner. In 2017 Brazil exported $47.4B to China and imported $27.3B from China.

• ELET3 BR: Eletrobras - the largest power company in Latin America, serves many of the commodity exporters to China manufacturers. A 1% move in China PMI translates in a 2.04% excess return in Electrobras.
• MGLU3 BR: Magazine Luiza, or Magalu, is one of the largest Brazilian retail companies, and likely one of the largest importers of Chinese-made goods. A 1% move in China PMI translates in a 2.02% excess return in Magalu.

• However, Greece’s intensifying links to China is more recent news. Earlier this year, Greece already became a member of China’s 17+1 initiative, which aims to deepen cooperation between Beijing and 17 states in central and eastern Europe and the Balkans. Furthermore, China has recently invested in Greek shipping, education, and agriculture.

• ETE GR: National Bank of Greece - likely stands to gain the most from general China investment in Greece. A 1% move in China PMI translates in a 1.61% excess return in National Bank of Greece.
• EUROB GR: Eurobank Ergasias is a commercial and retail bank serving Greek consumers and businesses.

• Finally, Indah Kiat Pulp & Paper (INKP ID) is one of the largest manufacturers of pulp & paper in the world, especially to China. Recently, the company’s growth has been buoyed by China’s slowdown in domestic paper production, thus tightening supply and supporting higher prices.

Creating Macro Factor Portfolios

Suppose that as an investor you really liked Macy’s for company-specific reasons (improving margins, better management team, etc...) but were concerned that by buying Macy’s you were making an inherent call on the US economy. How can you remove this risk from your portfolio?

Or suppose that your economist believed that US PMI was going to show a positive reading while China was going to show a negative reading in the next month’s report (or vice versa)? Is there a way you can capture this effect in an investable security?

By constructing a factor portfolio, you can isolate the US or China PMI sensitivity to address either case above.

A US or China PMI factor portfolio is like a special ETF, where the sum of all securities betas to US PMI is equal to 1, and all other betas are close to 0. Thus, by buying or selling this portfolio you can create a pure 1:1 price return to the changes in the US or China PMI.

Let’s take a look at how these portfolios look versus the S&P500 and MSCI ACWI.

‍Performance YTD 2019

‍From a returns perspective, the US PMI factor portfolio (on the left) is 0% correlated to the China PMI factor portfolio (2nd from the left), 7% correlated to the S&P500 (2nd from the right), and 9% correlated to the MSCI ACWI index (right).

Risk YTD 2019
From a risk perspective, the US PMI factor portfolio (on the left) is 99% idiosyncratic, which means that the market or any other factor explains only 1% of this factor’s performance, while the S&P500 (2nd from the right) is only 1% idiosyncratic (meaning, 99% of its performance can be explained by the market or other factors). The China PMI factor portfolio (2nd from left) is a bit less idiosyncratic (88%), while the MSCI ACWI index (right) is 0.55% idiosyncratic.

Because most of the return and risk in these factors is idiosyncratic, this tells us that these macro factors can truly explain facets of your portfolio that are completely independent of a traditional risk model.

If we put this all together, you can see how by using our framework, we can take any factor, gauge the idiosyncratic component, and then see how the returns correlation might pan out in your own portfolio.

This ultimately gives you a more holistic view, allowing you to understand your portfolio’s sensitivity to global economic factors, and allowing you to prepare for scenarios like, “What happens if Chinese PMI turns negative?”

You can now buy Macy's and hedge with the US PMI factor portfolios or create a long/short pair of US PMI vs China PMI. Essentially, by building these factor portfolios we can fulfill a dual purpose, ultimately helping you to fortify your portfolio and prepare it for any type or scale of storm.‍

US & Global Market Summary

US Market

• The market ticked slightly down over the week, as we saw some positive economic data while investors hung on to every word related to the US / China trade morass.
• Comments out of DC and Beijing continued to suggest potential for a trade deal, while the FCC voted on Friday to label Huawei and ZTE as national security risks, causing more noise.
• Speaking of PMI, the US flash manufacturing sector PMI went from 51.3 in Oct to 52.2 in Nov, while the US flash services sector PMI rose from 50.6 in Oct to 51.6 in Nov.
• The U Michigan consumer sentiment index also showed improvement, up to 96.8 in Nov vs. 95.7 the prior month.

‍Factor Update - US Model

• We saw a significant rotation out of Value and into Growth, which continued to see strong tailwinds as it now approaches Overbought territory. Meanwhile, Value was the biggest loser, falling almost a full standard deviation over the past week and crossing into negative normalized return space.
• Momentum saw more strength, popping up +0.51 SD after a +0.41 SD move last week.
• Market Sensitivity and Volatility both continued their downward trend, with the former still labeled as an Overbought factor.
• The decline in Earnings Yield carried on, after it had hit a peak of +1.35 SD on 10/30.
• Profitability was another big loser, as it plunged more than half of a standard deviation in one week, now sitting firmly in negative territory.
• US Total Risk (using the Russell 3000 as proxy) saw a decrease of 24 bps.

Factor Update - Worldwide Model

• Momentum was again the biggest winner, lifting itself out of negative normalized return territory.
• Similar to the US, Growth was also bid up on a normalized basis worldwide.
• Volatility and Market Sensitivity both started to decline after being labeled as Overbought factors.
• Exchange Rate Sensitivity appears to have hit a trough and has started to tick up from a trough of -2.33 SD below the mean on 11/18.
• Global Risk (using the ACWI as proxy) saw a sizable decline of 62bps.

Regards,
Omer