Sentiment is Bottoming, the Pain Trade Will Be Higher Equity Prices

Three months ago (https://wp.me/p9vaFZ-81) I recommended reducing allocations to equities based upon risks that were growing in the market. While my fundamental view hasn’t changed, sentiment is beginning to bottom. Based upon history, when a change in sentiment occurs after a period of significant stress, there is a high probability for a strong counter-trend move to take place regardless of fundamentals.

In this post I will discuss:

  • Quick Significant Declines in Market Multiples
  • US Recession? Short Answer… No
  • Measuring Sentiment with Volume and Volatility

A change in sentiment can quickly gather steam as investors rapidly change from fear to a fear of missing out (FOMO). When comparing the current development to similar periods, the probability for a 15% move (+/- 5%) is high enough that I’m increasing my recommended allocation to Equities and reducing the strong USD exposure.

Quick Significant Declines in Market Multiples

In the market, there are two items that determine price: fundamentals and the multiple. I look at the multiple as a way to view the market’s opinion, or sentiment. Currently, most market bears have been focused on the multiples being high. However, just because multiples are high doesn’t mean that the market is destine to decline. Said differently, the level of the multiple is never a catalyst for the market to increase or decrease.

Specifically looking at Enterprise Value to the last 12 months of EBITDA (EV/TTM EBITDA), which has not been impacted by the lower corporate tax rate, we see that it is near 30 year highs. This simply means that the market believes that each dollar of revenue, gross profit, operating income, etc is more valuable than it was previously. Investors have to decide whether they want to fight the market, which is a losing battle, or embrace the valuation being applied by the market.

EV/TTM EBITDA

Source: Bloomberg

Since I’ve already said that valuation is never a catalyst for the market to move, what I look for are sharp sudden moves in valuation. Historically, when moves of about 10% or greater occur to the downside, the market has been higher three months later unless we’re in a recession, which is a key point. These moves have been noted in the next three charts.

1990 – 2001: EV/TTM EBITDA (black), S&P 500 (red)

Source: Bloomberg

2003 – 2008: EV/TTM EBITDA (black), S&P 500 (red)

Source: Bloomberg

2010 – 2018: EV/TTM EBITDA (black), S&P 500 (red)

Source: Bloomberg

The current move of 11-12% is a rather significant decline compared to the last 30 years. Additionally, it’s worth noting that Emerging Markets have seen a multiple decline typically only seen during a US Recession.

EV/TTM EBITDA (black), S&P 500 (red), US Recession (blue outline)

Source: Bloomberg

US Recession? Short Answer… No

In the eyes of the market there is a big difference between being in a recession and the economy readjusting to a lower growth rate, which is what I believe we are seeing. In September (https://wp.me/p9vaFZ-81) I discussed how the fiscal stimulus would end that month and detailed how the market was showing signs of adjusting and pricing this in.  Furthermore, in October (https://wp.me/p9vaFZ-8w) I detailed how the economic data continued to peak and decline. 

Looking at a very broad view of the US economy, ISM Manufacturing and Employment are not showing signs of the US being in a recession.

Starting with the leading indicator of ISM Manufacturing, New Orders, while the trend is lower the readings are far too high to think that we’re in a recession.

ISM Manufacturing New Orders

Source: Bloomberg

The same is true when looking only at the headline number as well. 

1990 – Now: ISM Manufacturing (green), S&P 500 (red), US Recession (blue)

Source: Bloomberg

1960 – 1990: ISM Manufacturing (green), S&P 500 (red), US Recession (blue)

Source: Bloomberg

Turning to the employment data, we see the unemployment rate (U-3) is very low relative to the past 60 years. Applying a similar thinking to the multiples on the S&P, just because it’s low doesn’t mean that it has to turn higher. 

1960 – Now: Unemployment Rate, U-3 (red), Recession (blue)

Source: Bloomberg

Also, we always see Continuous Jobless Claims Y/Y turn higher well before U-3. Currently, CJC isn’t turning higher so the probability of U-3 sustainably turning higher very low.

Source: St Louis Federal Reserve, FRED

To summarize, yes, the economy is slowing but we are definitely not in a recession and not going into one in the next three months. Just a reminder, the US is not a boom bust economy like it was in the 60s and 70s so a recession takes much longer to develop in a consumer driven and more stable economy.

Measuring Sentiment with Volume and Volatility

In the next three charts, I’m seeing the market price in and adjust to the uncertainties in the economy. In August (https://wp.me/p9vaFZ-7t) I detailed how I use Volume and Volatility so I’ll refrain from repeating it.

With Volume, history shows that volume tends to slowly rise with growing uncertainty and decline once the uncertainty is behind it or less of a concern. An important point to keep in mind, Volume doesn’t gradually move higher once we’ve seen a significant spike like we did in October. Currently, we are seeing less volume in the market than in October. Similar to 2010 and 2011, it hasn’t declined much but we are seeing lower highs.

Total Market Volume

Source: Bloomberg

When we look at similar periods of declining Volume on a chart of the 2ndmonth futures contract of Volatility, we see it stabilizing once more at an elevated level. During periods of high uncertainty, we tend to see this pattern until the uncertainty has been priced in.

Volatility – Continuous 2ndMonth Futures Contract

Source: Bloomberg

Additionally, after the large increase in market stress in early October, the Volatility Spread has been putting in higher lows. While still negative, and therefore showing signs of high stress, the signal is that the Spread is becoming less negative as the uncertainty is becoming less of a concern for the market.

Current Chart: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

Comparing this to similar economic periods when growth (i.e. ISM Manufacturing) was peaking or slowing, Volume was declining after a large increase, and 2ndMonth Volatility was stabilizing, we see similar patterns in the Volatility Spread.

Early 2018: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

2014-2015: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

Mid – 2010: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

Early 2007: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

Mid – 2006: Generic 2-1 (blue, right), S&P 500 (red, left)

Source: Trading View

Finally, an indicator that is used commonly is the VIX/VIX3M (i.e. Spot VIX divided by the 3 Month Implied Volatility). As you can see on the next chart, the level the ratio reached on Thursday morning has only been exceeded five times since 2005. This is a very good example of the high levels of pessimism currently in the market.

VIX/VIX3M (white), Thursday AM reading of 1.18 (red line)

Source: Bloomberg

Since the market is still seeing uncertainty, the market has remained under high stress. However, the uncertainty and stress is waning.

Summary

There are three risks to my overall view of sentiment bottoming. 

First, I’m too early, which very well could be the case. There is plenty of headline risk at the moment with the UK vote and ECB meeting this week, the Fed meeting next week, Mueller-Trump, etc. The way that I’m handling this is by gradually reducing my shorts and adding to my longs on days of weakness. As I start to see the market become less stressed then I’ll continue to make the transition with the remaining segments of the portfolio.

Another risk is that this bounce is similar to the bounce in 2014-2015, which was less than 10% and only lasted three months. Since I’m not seeing a driver for fundamentals to change its longer term trend, the probability of this occurring is higher than I would like. However, the market multiple has declined much more now than in 2014-2015.

The third is that I’m reading the market wrong and the bears have every right to be excited. Since the probability of being in a recession now or in the next three months is low, then the probability of the market behaving like we’re in a recession is low.

All together, my view on sentiment leads me to change my recommended allocation. Since the USD has been strong for the past 8 months, a pullback should be expected in a strong counter-trend rally. Without a change in the fundamentals, I’m only changing to Neutral. Since I’m changing my view on the USD, then I am also changing my recommended exposure for Emerging Market Bonds and Equities to Neutral.

Currencies

  • Neutral (or 50% exposure) USD
  • Neutral (or 50% exposure) Emerging Market currencies

Bonds

  • Overweight (or long) US debt 
  • Neutral (or 50% exposure) Emerging Market debt 

Equities

  • Neutral (or 50% exposure) S&P 500 
  • Neutral (or 50% exposure) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries 

The China Trepidation… A Lack of Demand for its Goods

Most China Bears tend to mention China’s debt without giving details on how it’ll become an issue in the future. Like any highly leveraged company, when growth (or revenue) is increasing, it makes servicing the debt on its balance sheet an easier task. However, once growth slows, the cash flow created decreases and the ability to service even the interest payments can become a serious issue. In the case of China, they have a mounting concern because demand is slowing for its products, globally and domestically, which could lead to numerous problems if this trend continues.

In this post I will discuss:

  • A slowing of demand, globally and domestically, for China’s products
  • The message being told by China’s credit and loan data
  • The impact on equities, commodities, and currency

If the demand for China’s goods continues to decrease, globally and domestically, their government will be forced to change from “managing” the economic slowdown to full on stimulus. As China’s Premier Li Keqiang mentioned recently, they have no plans for “massive stimulus” despite the economic slowdown. Therefore, there is further room to the downside, in regards to demand, before the Chinese government changes course.

A Slowing of Demand, Globally and Domestically, for China’s Products

In last month’s post (https://wp.me/p9vaFZ-8w), I detailed how consumer demand is slowing in US. Therefore, I won’t spend time rehashing it. One item I will mention is that the US is seeing a sudden increase in imports coming from China. As discussed by the WSJ:

Imports into U.S. seaports are surging over usual seasonal patterns in an apparent push by retailers and manufacturers to pull orders forward ahead of a new round of tariffs set to hit U.S.-China trade in January.

Ports in Southern California, Georgia and Virginia reported double-digit growth in import volume from September to October, setting monthly records as furniture, apparel, auto parts and other goods streamed in.

https://www.wsj.com/articles/imports-surge-at-u-s-ports-as-companies-brace-for-new-tariffs-1542310733?mod=e2twe

In other words, the potential tariff increase is pulling forward the demand of goods from China. Whether the tariffs occur or not, we should expect to see less demand of Chinese goods in 1Q19 relative to 1Q18 because of demand being pulled forward. After this adjustment period, the demand of Chinese goods will depend upon the strength and demand of the US consumer rather than policies coming out of DC.

US Imports from China

Source: Bloomberg

Turning to China’s other large trading partner, we see that demand from Europe began to slow in 1H18. Europe accounts for ~20% of China’s total exports. Unlike the US, there are no tariffs being threatened by Europe so this narrative can not be used as an excuse.

Europe Imports from China

Source: Bloomberg

Before moving to the Chinese consumer, just a reminder that I don’t trust the data published by China. This is why I use other data points to confirm my view whenever possible. Keeping this in mind, when it comes to the Chinese consumer, the economic data published by China is telling a concerning story.

When looking at consumer sales, there are two types of data points: headline and enterprise. The headline number (or total) is discussed by the media and, in my view, is adjusted to show a more positive outlook. The enterprise number is based off retail businesses with 5 million CNY (~$750,000 USD) and hotel and catering with 2 million CNY (~$300,000 USD). Meaning, it doesn’t take a lot to be considered an enterprise in China.

Starting with retail sales, we see that Total Retail Sales have gradually declined in 2018 and over the years. However, since the start of the year, Enterprise Retail Sales has dropped substantially from ~9% to 3.6%, which is less than the current growth rate in the US.

Retail Sales Y/Y: Total (white), Enterprise (yellow)

Source: Bloomberg

e-Commerce sales have seen a similar decline and helps explain the YTD declines in JD.com and Alibaba.

e-Commerce Sales Y/Y (white), JD.com (JD, green), Alibaba (BABA, yellow)

Source: Bloomberg

Auto sales on a 6 month average Y/Y is back to the levels last seen in 3Q15.

Auto Sales (All Models)

Source: Bloomberg

Just in case the Chinese have changed their spending preferences from goods to experiences, we turn to hotels and catering. Unfortunately, we see a similar story being told here, a gradual decline in Total Sales and a larger decline by Enterprise since the start of the year.

Hotel and Catering Sales Y/Y: Total (white), Enterprise (yellow)

Source: Bloomberg

Finally, if we assume the Total Retail Sales and Total Hotel & Catering Sales are correct, that would mean that small and medium sized businesses would have stronger cash flow generation than enterprise businesses. Meaning, banks would find them more attractive to lend to. However, there are numerous articles, like discussed in the link below, which suggesting this is not occurring.

https://www.scmp.com/business/china-business/article/2161759/brother-can-you-spare-dime-chinas-small-firms-cant-get-loans

The Message Being Told By China’s Credit and Loan Data

As discussed in previous posts, China is a credit driven economy. When China’s money supply and loan growth is slowing, demand slows. By itself, declines in interest rates have never been enough to generate an increase for the demand of goods and services in China. Historically, loan growth and the money supply haven’t increased until the PBOC embarked on stimulus to generate growth.

In May I discussed Shadow Banking vs traditional lending from banks (https://wp.me/p9vaFZ-5f). Since then, Shadow Financing has continued to decline and is now negative for the first time ever.

Shadow Financing

Source: Bloomberg

However, bank loans (CNY Loans) have continued to grow steadily at 13%.

CNY Loans

Source: Bloomberg

The good news, in regards to the stability of China’s financial system, is that the more risky loans (Shadow Financing) are shrinking while the more stable loans (CNY Loans) are increasing. However, CNY Loans are not increasing at a fast enough pace to outweigh the decline in Shadow Financing, which leads to a headwind for demand of goods and services.

Source: Bloomberg

Turning to the money supply in China, we continue to see M1 decline. Just a reminder, inflection points on the 12ma Y/Y has historically led turning points in manufacturing data by ~6 months.

China M1

Source: Bloomberg

For the last 15 years, M1 has done a great job leading the export data of its major trading partners by ~6 months. Since China is the largest consumer of raw materials and manufacturers more goods than the US and Europe, M1 should continue to lead the export data. Unfortunately, this means that M1 is forecasting that the small deviation that we’re currently seeing (similar to 2011 and 2014) isn’t sustainable.

China M1 (black), Exports 6ma, Y/Y lagged 6 months: Australia (blue), Brazil (green), South Korea (red)

Source: Bloomberg

Turning to interest rates, we tend to see interest rates in China decline after M1 has rolled over. As stated earlier, lower interest rates by themselves don’t increase demand in China, stimulus provided by the PBOC increases demand.

China M1 (blue), China 1yr yield (red)

Source: Bloomberg

Looking at the three interest rates I follow closely in China, we see that after a brief pause in 3Q18, the 1yr and 5yr have begun to decline once more.

5yr Yield (green), 1yr Yield (yellow), SHIBOR (green)

Source: Bloomberg

In January (https://wp.me/p9vaFZ-2w), I went into more detail about how the difference in the interest rate spreads can show signs of stress. For me, the initial signal comes from the 5s – 1s spread and the SHIBOR – 1s spread confirms that signal.

Currently, 5s – 1s is above 0.50 but is not accelerating higher. Therefore, I continue to think the stress building in China’s financial system is manageable at this time. If the 5s – 1s spread would suddenly move towards 1.00, SHIBOR – 1s is also increasing, and interest rates are declining, then I would get very concerned about the stability of China’s financial system.

Top Panel: CNY (green), SHIBOR – 1yr Yield (white); Bottom Panel: 5yr Yield – 1yr Yield (yellow)

Source: Bloomberg

Similar to previous periods of stress, the PBOC has indicated that it may begin to manage the CNY to prevent it from depreciating further. If this is occurring, than the implied volatility of the CNH should begin to significantly decline from its current level.

https://www.bloomberg.com/news/articles/2018-11-12/china-signals-tougher-yuan-management-at-expense-of-market-role

CNH (white), CNY (yellow), Implied Volatility of CNH (purple)

Source: Bloomberg

The Impact on Equities, Commodities, and Currency

Considering the issues discussed in the previous two segments, this doesn’t give the best outlook for the cyclical components of the market and reinforces why I’ve been negative on them since I started this blog in January.

Using interest rates as a very broad overlay, it supports why it will be best to avoid cyclicals until interest rates, at a minimum, stabilize. There will be counter-trend rallies along the way but the longer term trend will be lower for the forseeable future .

This means, avoiding Emerging Markets…

Emerging Markets ETF (EEM, white), 1yr Yield (yellow), SHIBOR (green)

Source: Bloomberg

…avoiding industrial metals…

LME Metals Index (white), 1yr Yield (yellow), SHIBOR (green)

Source: Bloomberg

…avoiding oil (or energy)…

WTI (white), 1yr Yield (yellow), SHIBOR (green)

Source: Bloomberg

…while being long assets that benefit from a stronger US Dollar.

US Trade Weighted Dollar (inversed, white), 1yr Yield (yellow), SHIBOR (green)

Source: Bloomberg

Finally, here’s a breakdown showing the cyclicality of various global indices when looking at the weights of Financials, Industrials, Energy, and Materials.

As shown by the Nasdaq this week, it does not mean that the indices with low cyclical weightings will be safe. It ultimately means that you need to know what’s in the index and understand the drivers behind it.

Source: Cornerstone Macro

Summary

While this post leaned more to the negative side than normal, I don’t see the concerns highlight by China Bears escalating in the immediate future.

In my opinion, the key to China’s ability to “manage” the economy will come down to the US consumer. There might be declines in demand, like we’re seeing currently, but as long as the US employment data remains strong, then the PBOC can continue as is.

No changes in recommended asset allocation this month.

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Neutral (or 50% exposure) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

US Demand Slowing = Issues for Global Equities

After seeing a decent decline in the market, the natural thought is to take advantage of the decline and allocate additional resources to equities. This strategy works well when the global economy is growing but when it begins to slow, this strategy should be avoided and is why I recommended decreasing exposure to US equities last month.

In this post I will discuss:

  • An updated view of US demand overlaid with equities
  • How US demand affects the profitability and performance of the S&P 500
  • How US demand affects global trade and ex-US equities

In some areas of the market, we’ve already seen multiples decline significantly, giving off the elusion that equities are cheap. However, based upon my analysis, the market is seeing a slowdown develop, which is why “buying the dip” should be avoided at this time.

An Updated View of US Demand Overlaid with Equities

In July (https://wp.me/p9vaFZ-6N) I did a detailed breakdown of how I track US demand with various economic data points and confirming those data points with the relative performance of equities. Three months later, we see the rate of change has continued to decline.

Demand tends to be driven by a change in credit. Therefore, when we see commercial & industrial loans (corporate loans) and consumer credit card debt growth rate decreasing Y/Y, the probability of demand increasing from the current is slim. Additionally, it shouldn’t be a surprise that banks (large cap and regional) are underperforming the S&P when this occurs.

Commercial and Industrial Loans: Absolute (blue), Y/Y (red)


Source: St Louis Federal Reserve (FRED)

Consumer Loans- Credit Cards and Other Revolving Plans: Absolute (red), Y/Y (blue)


Source: St Louis Federal Reserve (FRED)

Banks Index vs S&P 500 (white), Regional Banks Index vs S&P 500 (yellow)

Source: Bloomberg

Next, we see that ISM New Orders continues to decline from the January 2018 peak along with the relative performance of the Machinery Industry. As seen in the last economic cycle, the relative performance of Machinery tends to be more driven by global growth instead of only US growth.

ISM New Orders

Source: Bloomberg

Machinery Index vs S&P 500

Source: Bloomberg

Turning to the volume of containers at the five major US ports, we see that they are barely above 0% growth on a 6 month average Y/Y through August.  When looking at the container companies, they continue to move lower against the market.


Source: Various Port Websites

CAI vs S&P 500 (white), TGH vs S&P 500 (yellow)

Source: Bloomberg

Turning to intermodal rail volume, it looks like we saw the peak in July. However, rail stocks continue to do well. Historically, rails are the last cyclical industry to outperform relative to the S&P.

Intermodal Rail Volume

Source: Bloomberg

Rail Industry vs S&P 500

Source: Bloomberg

With loan growth, new orders for manufacturing, and the transportation of goods all declining, we now turn to end demand.

With the 30 year fixed rate continuing to increase, we see New Home Sales and Existing Homes Sales disappoint on a 6 month average Y/Y. Therefore, seeing LEN and MHK underperform should be expected.

New Home Sales 6ma Y/Y (red), Existing Home Sales 6ma Y/Y (green), National 30 yr Fixed Rate (blue, inversed)

Source: Bloomberg

National 30yr Fixed Rate (white), LEN vs S&P 500 (yellow), MHK vs S&P 500 (red)

Source: Bloomberg

Auto Sales continue to see a slowing growth rate, which makes the Auto related stocks undesirable to own compared to the S&P 500.

US Auto Sales

Source: Bloomberg

Autos and Components Index vs S&P 500

Source: Bloomberg

Finally, when we look at Retail Sales ex Autos and Gasoline, we see that they might have peaked last month on a 6ma Y/Y. Until the 3ma Y/Y is less than the 6ma Y/Y, there is a possibility of it rebounding. Nonetheless, based upon the way the Specialty Retailers have recently performed vs the S&P 500, the market might be telling us that we’ve seen the peak.

Retail Sales ex Autos and Gasoline

Source: Bloomberg

Specialty Retailers vs S&P 500

Source: Bloomberg

To summarize, the probability that the demand of goods in the US has peaked continues to increase, which leads us to the next part in regards to how this affects the broad index.

How Demand Affects the Profitability and Performance of the S&P 500

In April (https://wp.me/p9vaFZ-4J) I showed how the market rewards equities based upon relative financial performance. When thinking about the S&P 500, you can go through the same process but on an absolute level.

Starting with Revenue Growth Y/Y, we see that it is still increasing but the pace of the increase is beginning to slow.


Source: Yardini.com, October 15, 2018 S&P 500 Quarterly Sector Fundamentals

Surprisingly, when we look to profitability (i.e. Operating Margin), instead of seeing it expand with Revenue Growth, we actually see that it has stagnated since the 1H17. This is not something you would expect to see when all we hear is how strong the market is fundamentally.

S&P 500 Operating Margin (Semi-Annual Basis)

Source: Bloomberg

Digging into the drivers the same way you would analyze a company, we start with the leading indicators of inflation, which is going to impact the cost of goods sold (COGS). We know the leading indicators of inflation (PPI, Import & Export Prices, and ISM Prices Paid) started rising in early 2016. It wasn’t until they began to make five year highs in 2017 did we begin to hear companies discuss rising costs.

Two items to note. First, Core CPI (light blue) & Core PCE (dark blue) are lagged 18 months because they trail the leading indicators of inflation. Two, the leading indicators have recently begun to decline so there is the potential for this headwind to dissipate in the next few months.

Inflation Data: 3 month average, Y/Y

Source: Bloomberg

Next, we know that companies have increased Capital Expenditures substantially since 2010 and even more so since the tax cuts were past.

S&P 500 Capital Expenditures –Semiannual Basis

Source: Bloomberg

However, these newer projects have yet to increase in efficiency, as shown by the utilization rate in the US still being below where it was in 2014.

Finally, we know that the pace of hiring has increased, which has resulted in the initial jobless claims and continuous jobless claims reaching levels not seen since the late 1960s.


Source: St Louis Federal Reserve (FRED)

Going forward, we should expect revenue growth Y/Y to begin to decline from the 2Q18 levels as demand continues to slow. Therefore, management teams will need to determine how to reduce the pace of spending to help support profitability. If they can’t reduce the pace fast enough, that’s when they will start to make larger cuts to their expenses by reducing the labor force or delaying planned projects.

Regardless of how management teams decide to deal with a reduction in revenues, it seems that the market has already determined that we have reached peak profitability.

S&P 500: Price (white), Operating Margin (red)

Source: Bloomberg

How US Demand Affects Global Trade and ex-US Equities

Due to all of the political headlines and tweets, everyone is very aware that the US doesn’t make a majority of its goods and we import quite a bit from China.

Looking first at US imports from China, we see that it actually peaked in 1Q18. On a short term basis, we saw a rebound in the Y/Y data in 2Q18 but that is beginning to fade.

US Imports From China

Source: Bloomberg

In a normal situation, I would expect this decline to show up in China’s Industrial Production numbers. However, it’s been flat as a pancake for years, which goes with why I (and numerous others) don’t trust data that comes from the Chinese government.

However, this does show up in the trade data for China’s largest trading partners, such as Australia, South Korea, and Brazil.

When thinking about previous periods, like 2014-2015, we see that exports Y/Y peaked in 1H14 for these countries, which is when ISM New Orders peaked as well.

Australia Exports

Source: Bloomberg

Brazil Exports

Source: Bloomberg

South Korea Exports

Source: Bloomberg

Additional, we see that Mexico saw somewhat similar data points as the other countries. Since 75% of Mexico’s exports come to the US, Mexico is more “in tuned” with the US economy so they tend to see turns in their export data at the same time end demand is declining.

Mexico Exports

Source: Bloomberg

When thinking about equities, we see a similar pattern as the export data on an absolute basis and relative to the US.

Emerging Markets (EEM): Absolute (white), Relative to S&P (yellow)

Source: Bloomberg

Developed Markets ex-US (EFA): Absolute (white), Relative to S&P (yellow)

Source: Bloomberg

South Korea (EWY): Absolute (white), Relative to S&P (yellow)

Source: Bloomberg

Mexico (EWW): Absolute (white), Relative to S&P (yellow)

Source: Bloomberg

Finally, with US demand slowing, China is going to have to decide if they want to do another massive stimulus program like they did in 2H15. Just a reminder, China’s M1 (12ma, Y/Y) tends to lead Global Manufacturing, ISM, and the trade data for Australia, Brazil and South Korea by about 6 months. Therefore, we have a long way to go before growth potentially returns that is being driven by Chinese demand.

China M1

Source: Bloomberg

Summary

As I’ve said numerous times, whether this is another mid-cycle slowdown or the beginning of a recession, the positioning will be the same. What is important to note is that we are still very early in this slowdown, since ISM tends to take about 18 months to go from peak to trough.

No changes in recommended asset allocation this month.

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Neutral (or 50% exposure) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

Markit vs ISM – Which US Manufacturing Survey is Right?

The title describes the thoughts of those that closely follow US manufacturing data. While other manufacturing surveys have declined, the headline ISM continues to hold fairly steady in the high 50s, low 60s. However, the optimism shown by the headline ISM is currently out of line with the message being told by the market.

In this post I will discuss:

  • Measuring the Impact of the US Fiscal Stimulus
  • Manufacturing Data and Signs From Market Leadership
  • Cracks Developing in Semiconductors

While I tend to reference ISM Manufacturing the most, the current environment is why I analyze numerous data points when building my fundamental view, which hasn’t changed despite ISM Manufacturing reaching a new economic cycle high.

Measuring the Impact of the US Fiscal Stimulus

As I mentioned a few months ago, the US government increased discretionary spending when the budget was approved in February. When thinking about its impact on the economy, it is important to remember that the government’s fiscal year ends September 30th. Therefore, the net change in discretionary spending for 2018, $220Bn, is actually impacting the US economy in only a six month period. Said differently, the net change could potentially stimulate the US economy by approximately 2.2% of GDP in this compressed time frame.

https://www.cbo.gov/system/files/115th-congress-2017-2018/reports/53696-sequestration.pdf

When looking at the results of Q2 GDP and the estimate for Q3 from the Atlanta Federal Reserve, we see how the growth rate has significantly increased since the fiscal stimulus was passed.

Source: Trading Economics

Putting this into a historical perspective, the increase in Discretionary Spending as a percentage of GDP is rather unprecedented, especially this far into an economic cycle.

Historically, fiscal stimulus tends to not have lasting effects on the economy once it is reversed. As stated by Richard Koo (former economist at the Federal Reserve Bank of New York and currently the Chief Economist at Nomura) in a Real Vision interview published October 7, 2016:

“Of course, whenever you put in a fiscal stimulus, the economy responds. But when it’s removed, it tanks again. It doesn’t have this pump priming function that we expect from fiscal stimulus.”

Keeping this in mind, and knowing that the US Fiscal Stimulus reverses on October 1st, watching for signs of the economy slowing in the leading economic indicators and the market becomes critically important.

Manufacturing Data and Signs From Market Leadership

As stated in the title of this post, there are two different stories being told by the US manufacturing data. First, the Markit US Manufacturing PMI slowed for its fourth consecutive month.

Markit US Manufacturing PMI


Source: Trading Economics

However, the headline number for ISM Manufacturing came in at an economic cycle high. One important note though is that New Orders increased but stayed below the January peak, which is similar to what we saw in 2H14.

ISM Manufacturing (white), ISM Manufacturing New Orders (yellow)


Source: Bloomberg

When there is conflicting data, my first inclination is to see what the market is telling us. As I’ve been showing for months, cyclicals have been underperforming counter-cyclicals.

ISM (yellow), SOX (Semiconductors) Index vs Health Care (white)


Source: Bloomberg

ISM (yellow), Industrials vs Staples (white)


Source: Bloomberg

ISM (yellow), Financials vs Utilities (white)


Source: Bloomberg

I have only shown the sector rotation previously with the large caps since they are large, stable, and more established. However, we know the global economy has been slowing for months and large caps are more exposed to these economies. To get a more US specific view, we should look at the small caps, which are showing us the exact same picture as the large caps, a change in leadership to the counter-cyclicals.

ISM (yellow), S&P 600 Semiconductors vs S&P 600 Health Care (white)


Source: Bloomberg

ISM (yellow), S&P 600 Industrials vs S&P 600 Staples (white)


Source: Bloomberg

ISM (yellow), S&P 600 Financials vs S&P 600 Utilities (white)

Source: Bloomberg

With large and small caps both telling the same narrative, an expectation of slowing growth in the future, I put more weight on the Markit data point than ISM.

Cracks Developing in Semiconductors

Semiconductors are arguably the best and most consistent industry to track in regards to the business cycle. At the beginning of the cycle, they tend to trough slightly before or with the other cyclicals. More importantly to the current situation, they tend to be one of the last cyclical industries to decline.

Over the past twenty years, once the Semis begin to show weakness, the S&P 500 tends to peaks shortly thereafter. This of course leads to the question of, how do you measure weakness in the Semiconductors?

SOX Index (white), S&P 500 (yellow) (1999-2007)


Source: Bloomberg

SOX Index (white), S&P 500 (yellow)(2009- 2018)


Source: Bloomberg

As discussed in April (https://wp.me/p9vaFZ-4J), the market tends to look for growth when the economy is expanding and stability when the economy is peaking and slowing. Additionally, in that post I showed how Texas Instruments (TXN) tends to outperform Micron (MU) as we get into the later stages of the business cycle because it has a more stable business. Therefore, the recent outperformance of TXN vs MU should not be surprising.

Texas Instruments (TXN) (white), Micron (MU) (yellow), Applied Materials (AMAT) (green)


Source: Bloomberg

I bring this up because we are now seeing the price of TXN decline. Typically, once TXN begins to break down, the SOX Index isn’t far behind.

Texas Instruments (TXN) (white), SOX Index (yellow)


Source: Bloomberg

Turning back to the SOX Index, or SOXX ETF, there are very clear areas of importance on relative and absolute basis.

The SOXX ETF relative to the S&P should show weakness (or underperformance) before it does on an absolute basis. We see that the SOXX couldn’t make a new high relative to the S&P in early June and since then it has been making a series of lower highs. Once the SOXX/S&P break the lows from the past nine months, then the focus turns to the SOXX on an absolute basis.

SOXX ETF vs S&P 500


Source: Bloomberg

On an absolute basis, the SOXX ETF is still in the middle of the range that it has been in for almost a year. However, if the underperformance vs the S&P 500 deteriorates, I would expect the SOXX ETF to begin to challenge ~$166.

SOXX ETF


Source: Bloomberg

Finally, once ~$166 is broken, then the concern for the S&P peaking begins immediately.

Summary

With the fiscal stimulus set to reverse on October 1st, market leadership showing an expectation for a decline in the future growth of the US economy, and the Semiconductor Industry showing weakness, it’s tough for me to continue to recommend being long the S&P 500. Maybe there’s 3-5% of upside left in the S&P 500 before it finally peaks, but I’m growing more concerned about the risk vs reward of being overweight with the negatives growing.

When I look at positioning, as shown by freecotdata.com (@movement_cap), we continue to see that investors, or speculators, are more exposed to the long side with the S&P 500 and Russell 2000. This leads me to the conclusion that market participates are currently not positioned for the scenario that I’ve discussed.

Commitment of Traders Report: S&P 500


Source: freecotdata.com, @movement_cap

Commitment of Traders Report: Russell 2000


Source: freecotdata.com, @movement_cap

Due to my concerns, my recommendation for the S&P 500 has moved to Neutral (or 50% exposure). Since I expect the counter-cyclicals to outperform the cyclicals, I continue to recommend increasing exposure to these sectors and industries while decreasing the overall exposure to US equities.

 

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Neutral (or 50% exposure) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US counter-cyclical sectors and industries
  • Underweight (or short) US cyclical sectors and industries

 

Updated Views on Macro and Markets

Updated Views on Macro and Markets

There are some market participants that see the weakness in Cyclicals and Emerging Markets as a buying opportunity. On the other hand, others are getting more concerned about the economic outlook, especially when the fiscal spending declines in October. When I analyze the economic indicators and market leadership, I continue to agree with the later.

In this post I discuss:

  • Global Manufacturing and Market Leadership
  • Update on China and Credit Spreads
  • Demand and Supply for Oil
  • Warning Signs for Volatility

Countertrend rallies, like we saw in July, can test the resolve of even the most confident investors. However, knowing that trades never go in straight line is why position sizing is so important when constructing a portfolio. Correct sizing should help you to stay with the long term trend, which in this case, are positions that outperform in a slowing global economy.

Global Manufacturing

Globally, the Manufacturing data continues to decline.


Source: Markit, JPM

More specifically, we have seen a sudden drop in Europe’s Manufacturing data…

…and in Japan.

However, as we saw in Brazil this past month, these moves rarely move in a straight line.

When looking at ISM Manufacturing, we continue to see the headline number and New Orders decline.

ISM Manufacturing (white), ISM New Orders (yellow)


Source: Bloomberg

Looking forward to the August numbers, we should expect to see another decline in the ISM data, as shown by @Not_Jim_Cramer.

Finally, equities are confirming the peak in manufacturing data and economic growth, as the market continues to transition towards more stable companies, industries, and sectors…

ISM (white), SOX (Semiconductors) Index vs Health Care (yellow)


Source: Bloomberg

ISM (white), Industrials vs Staples (yellow)


Source: Bloomberg

ISM (white), Financials vs Utilities (yellow)


Source: Bloomberg

…and to the most stable global economy, the US, which is seeing significant outperformance year to date.

Percentage Change YTD vs S&P 500: Europe (White), Emerging Markets (Purple), Brazil (Yellow)


Source: Bloomberg

Update on China

Focusing on China’s economy instead of the trade headlines, the Chinese government has been generating quite a bit of positive news lately. This is making some investors think that a rebound for China and Emerging Markets is in the cards. A recent example of this is from Reuters:

China almost quadrupled the value of fixed-asset investment projects approved in July from the previous month as Beijing looks to accelerate infrastructure spending to stabilize the cooling economy.

https://www.reuters.com/article/us-china-economy-projects/china-nearly-quadruples-infrastructure-approvals-in-july-idUSKBN1L106N

However, when you look at China’s M1 data, we see a completely different viewpoint than the narrative.

China M1 Money Supply Y/Y: 1ma (blue), 3ma (red), 6ma (green), 12ma (yellow)


Source: Bloomberg

The reason why the growth rate of M1 is declining despite the increase in infrastructure projects being approved is because of the decline in Shadow Banking Financing.  This was discussed in more detail in May (https://wp.me/p9vaFZ-5f).

China Shadow Banking Financing Y/Y (white), China’s 5yr Yield (yellow)


Source: Bloomberg

With China’s M1 still declining, demand of products and materials should continue to slow. In other words, the recent increase in Export data from China’s major trading partners shouldn’t be viewed as the beginning of a new trend.

China’s M1, 12ma Y/Y (black, 6 month lead), Exports Y/Y, 3ma: Australia (blue), Brazil (green), South Korea (red)


Source: Bloomberg

As Chinese demand continues to decline, we should expect the currencies of those countries to further depreciate against the USD as well.

China’s M1 12ma, Y/Y (black, 6 month lead), AUD/USD (blue), USD/BRL (green, inversed), EUR/USD (red)


Source: Bloomberg

Finally, the decline in demand and trade from China is part of the reason why we’ve seen European High Yield Spreads and Emerging Markets Spreads increase since the start of the year while the US Spreads have remained subdued.

Option Adjusted Spreads (OAS): US HY (white), US IG (red), Europe HY (yellow), Emerging Markets (green)


Source: Bloomberg

This helps explain why the US has outperformed the rest of the world, and in my opinion, will continue to until China changes from managing an economic slowdown to trying to stimulate growth in their economy.

Demand and Supply for Oil

Historically, at the end of an economic cycle we see oil prices increase significantly, which puts excess stress on consumers and businesses. If we are nearing the end of the economic cycle, the current outlook for oil would indicate that this time would be different, which makes me question the potential for a recession in 2020 since I tend to believe that history rhymes.

First, China is the marginal buyer of oil and we continue to see their demand slowing. This should be expected since the Chinese government is trying to manage, not stimulate, their economy as it slows. As usual, the 6 month average gives a better view of the trend compared to the more noisy monthly data point.


Source: Bloomberg

Turning to the Supply and Demand picture, we see the growth of Supply outpacing the growth of Demand on a Y/Y, 6 month average (6ma).

Oil Demand 6ma, Y/Y (blue), Oil Supply 6ma, Y/Y (red)


Source: Bloomberg

As mentioned a few months ago, the ratio of Total Demand/Total Supply on a 6ma continues to lead inflection points in WTI by ~6 months. It is important to note that this correlation broke down from 2001 – 2005 as China was building their massive cities.

Oil (blue), Oil Demand/Oil Supply: Monthly (red), 6ma (black)


Source: Bloomberg

We also see the ratio of Total Demand/Total Supply continuing to lead the EUR/USD by ~3 months.

EUR/USD (blue), Oil Demand/Oil Supply: Monthly (red), 6ma (black)


Source: Bloomberg

Finally, confirming the current decline of Oil is the Oil & Gas Exploration and Production Index underperforming the S&P 500 once more. Overall, the group has been under pressure as margins are getting squeezed. A decline in the price of Oil definitely doesn’t help improve that situation.

Oil (white), S&P Oil & Gas Exploration and Production Index vs S&P 500 (yellow)


Source: Bloomberg

It is important to mention that the news flow, or narrative, is very supportive of the price of Oil due to Venezuela production issues, Iran sanctions starting in November, and the potential inability of producers to expand production enough to keep up with the global demand.

While the narrative could end up being correct, as it could in China, the outlook portrayed by the Demand/Supply ratio shows that investing in Oil and Oil related companies means investing against the fundamental trend at this time.

Volatility Warning Signs

As mentioned in previous posts, Volatility spikes when we see ISM Manufacturing peak or trough. What we saw in at the beginning of the year was no different but the size of the spike was substantially larger compared to previous periods of ISM peaks.

We tend to see the number of shares traded in the market (i.e. volume) increase as ISM declines and vise versa. Additionally, we see Volatility trend in a similar pattern as volume, as shown by the arrows in the chart below.

A key point to understand with Volatility is that in order to see a sustainable increase you need to have ISM declining and the 90 day average volume increasing. Currently, we have ISM declining and Volatility trending higher but volume is declining. In this scenario, when we see short term spikes of Volatility, they should result in only small quick declines in the S&P, like we saw the week of August 13th– 17th. A large drawdown in the S&P becomes more likely when the 90 day average of volume begins to increase, like we saw six months ago.

Top Panel: ISM Manufacturing (red, inversed), Total Market Volume: 45 day average (blue), 90 day average (yellow)
Bottom Panel: Generic 2ndmonth Volatility Futures Contract (green)


Source: Bloomberg

I’ve previously described the importance of tracking the Volatility Spreads (https://wp.me/p9vaFZ-3z). Since that post, we continue to see the S&P 500 move with the difference of the 2ndand 1stmonth Volatility Futures contract, as seen below. As stated in that post, when the spread moves below 0.60 the risk of a market decline increases and a move below 0.0 tends to coincide with a large market decline.

S&P 500 (yellow), 2ndMonth – 1stMonth Volatility Futures Contract (white)


Source: Bloomberg

Breaking down this statement into something more meaningful, only 23% of the weekly data points of the Volatility Spread since May 2009 are below 0.50. Furthermore, of that 23% we see a distribution of:

  • 0.5 to 0.1 -> 12.8%
  • 0.1 to -0.1 -> 5.8%
  • -0.1 and below -> 3.8%

In other words, over the past 10 years, it is rare for the Volatility Spread to get below 0.5 and especially below 0. However, each of these occurrences are associated with market declines, thus the importance of tracking the Volatility Spread.

Weekly Chart: 2ndMonth – 1stMonth Volatility Futures Contract (Up weeks: green, Down weeks: red), Distribution of Data Points on Left Side


Source: Bloomberg

Finally, we are seeing the correlation of the S&P and Volatility Spread currently ranked in the top 15% over the past 10 years.  Overall, tracking the Volatility Spread and watching the 90 day average of volume becomes an important part of risk management with ISM Manufacturing declining and Volatility trending higher.

Top Panel: S&P 500 (orange), 2ndMonth – 1stMonth Volatility Futures Contract (white)
Bottom Panel: Correlation of Top Panel with Distributions on Left Side


Source: Bloomberg

Summary

As discussed in the various section of this post, the growth rate of the global economy continues to decline. Therefore, maintaining an allocation tilted towards a stronger USD and counter cyclicals will be a benefit to the performance of your portfolio. At some point, reducing exposure to US equities will be advised, but not yet.

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Overweight (or long) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

Tracking the Demand of Goods in the US with Equities

I’ve previously shown how the change in the demand of goods in China can affect its largest trading partners economically and financially (i.e. equities, currency, rates). This post is going to focus on how I analyze the demand of goods in the US using economic data and confirm it with the relative performance of equities.

In this post, I’ll break down the data into three categories:

  • New manufacturing orders and utilization
  • The transportation of goods: shipping and rails
  • The purchase of goods by consumers: autos, retail sales, and housing

What this post will show is that the US leading indicators topped months ago and the hard data is currently peaking or starting to decline. Unfortunately, this is already occurring while discretionary spending from the US Government is a tailwind for the economy.

 

New Manufacturing Orders and Utilization

The ISM manufacturing survey has long been considered a leading indicator of the US economy regarding future demand of goods.  Here’s an example that I’ve shared previously describing why it leads:

Before a consumer can purchase a new car, an order must first be placed to produce all the parts that are needed to make the car before it can be assembled and then transported by rail and truck to the dealership. An increase in demand for new autos will see more parts and autos being assembled leading to companies and workers making more money that can be spent. As these workers make more money, they spent more at restaurants, retailers, concerts, etc. As these businesses begin to see more demand, these workers get paid more and can purchase additional items as well, like a new car or truck, leading to additional new orders at the auto plants to keep up with the increased demand. At some point, the demand for new cars that will slow, which leads to fewer orders being placed, less money being paid to the auto manufacturing workers, who in turn spend less at restaurants, retailers, concerts, etc. As the demand at these businesses slow, the workers get paid less leading them to decrease their spending as well.

Within the ISM survey are various sub-indices. The most forward looking indicator in the ISM survey is the New Orders. Presently, ISM New Orders peaked in January while ISM peaked a month later.

ISM New Orders (white), ISM Manufacturing (red)

Source: Bloomberg

The surveys are considered soft data points because these are estimates, or guesses, as to how the future will look. Even though these are estimates, the results of the survey have been robust for over 100 years.

Confirming the peak in ISM New Orders is the relative performance of the Machinery Industry, which has been very correlated to ISM New Orders and/or global growth for decades. During the last economic cycle (2000-2008), these companies benefited from the growth of China and Emerging Markets. As the growth rates in those areas of the world have slowed since 2011, the Machinery stocks have traded closer to the ISM New Orders like they did in the 1990s.

ISM New Orders (white), Machinery vs S&P 500 (red)

Source: Bloomberg

Since these data points are from surveys (i.e. ISM New Orders, ISM, Machinery vs S&P), there are two other sets of economic data that I track to confirm a peak in manufacturing.

The first set of data points are the new orders associated with Durable Goods, Capital Goods Non-Defense, and US Manufacturing. All three of these report the orders they have actually received compared to the ISM New Orders, which is an estimate of what they believe they will receive.

Historically, these data points peak about six months after ISM New Orders. By the time this peaks, the Machinery and most cyclical stocks have already declined so this is not a leading indicator for these stocks, hence why I use it to confirm the previous data points.

Currently, these three indicators are going through the process of peaking, thus confirming the decline in ISM New Orders and the Machinery stocks underperforming the S&P.

ISM New Orders (green, 3ma Y/Y), Durable Goods New Orders (blue, 6ma Y/Y), Capital Goods New Orders Non-Defense (red, 6ma Y/Y), US Manufactures New Orders (yellow, 6ma Y/Y)

Source: Bloomberg

The second set that I track deals with the efficiency of manufacturing facilities: Industrial Production, Capacity Utilization, and Industrial Production for Manufacturers. These data points are historically less noisy and have a tendency to peak slightly before the New Orders received data series.

Similar to the New Orders received, two of the three indicators look like they are peaking.

Industrial Production (blue, 6ma Y/Y), Capacity Utilization (green, 6ma Y/Y), Industrial Production for Manufacturers(purple, 6ma Y/Y), ISM Manufacturing (yellow)

Source: Bloomberg

 

The Transportation of Goods in the US

One area that doesn’t get a lot of focus is the shipping data because of it is lack of depth. While the Los Angeles (LA) and Long Beach (LB) data begins in 2000, the third biggest US port (NY-NJ) starts in 2011. However, and this is shown in the charts below, the difference in only looking at the LA, LB and Savannah data compared to all five major ports is minimal (i.e. variance of approximately one month in turning points).

Within the shipping data there are two data points that I follow closely:

  • Empty Containers
  • Inbound Containers

Those that follow the shipping industry usually ignore the Empty containers. However, if the growth rate of Empty containers is declining, this means there is a decline in the expected growth rate of demand for goods. Additionally, when Empties go negative, it means that shipping container companies (i.e. CAI, TGH) would rather pay to have their containers sit ideal at the ports rather than moving it to a different location to be filled with goods to make money.

Inbound container data is noisier than Empties so I use it as confirmation of the trend in Empties. Similar to Empties though, a declining and negative growth rate means a decline in the expected demand of goods.

I don’t focus too much on the Outbound containers because it is half the size of Inbound and tends to be driven by changes in the USD rather than actual demand growth.

Currently, Empties peaked in September 2017 on a 6 month average and should go negative when the June data is released. Inbound peaked a month earlier than Empties but has seen a slower rate of decline.

Source: TEU Data from Port Websites

Source: TEU Data from Port Websites

Finally, in terms of shipping related equities, I tend to focus more on the container companies than the actual shipping companies due to the simpler business models. In 2013, these companies had issues with overcapacity as trade peaked but they recently topped in 4Q17 when Empties and Inbound began to decline.

Textainer Group (TGH) vs S&P (white), CAI International (CAI) vs S&P (yellow)

Source: Bloomberg

The other data point that I watch regarding the transportation of goods is the Intermodal rail volume. Broadly, Intermodal volume deals with the movement of finished goods, which is going to be correlated to the demand of goods by consumers. The other data point that others tend to follow is the Carload rail volume, which deals with the movement of raw materials. The problem with Carloads is that a third of it is coal and the demand of coal is easily affected by the price of natural gas, which the US has ample amounts.

Similar to other hard data, Intermodal volume tends to confirm peaks in the ISM. Currently, Intermodal is still increasing and not showing the same concern as the shipping data.

ISM Manufacturing (red), Intermodal Rail Volume (blue, 26 week average)

Source: Bloomberg

Looking at the Rail Industry, the group continues to outperform the S&P. Rail stocks tend to peak after the Intermodal volume because we usually see Oil declining as manufacturing declines, thus decreasing their operating expenses and increasing their margins.

Rail Industry vs S&P

Source: Bloomberg

 

The Purchase of Goods by Consumers

Since 70% of the US economy is consumption driven, the purchase of goods by consumers is an important final step in this analysis.

First, the growth rate of auto sales tends to peak early in the economic cycle and then slowly decline until the cycle ends. Therefore, while it’s good to see the current increase in auto sales, I don’t expect it to be sustainable based upon previous economic cycles.

US Auto Sales (3ma, Y/Y)

Source: Bloomberg

Confirming my view on auto sales is the Auto Manufacturers and Components Index, which continues to underperform the S&P 500.

Auto Manufacturers and Components Index vs S&P

Source: Bloomberg

Second, Retail Sales. The most quoted number by investors and the media is the broad based Retail Sales data point, which includes auto and gasoline sales. However, auto sales can skew the data (peaks early and large dollar amounts) and changes in gasoline sales can be driven more by the change in the price of gasoline, not an increase in demand. Therefore, analyzing Retail Sales ex Autos and Gasoline allows me to focus on the actual demand for goods by the consumer.

When looking at Retail Sales ex Autos and Gasoline, we see the growth rate peaked in 4Q17 at 5% and has held steady in the high 4% the past few months. In other words, not accelerating but not declining either.

Retail Sales (red, 3ma Y/Y), Retail Sales ex Autos and Gasoline (blue, 3ma y/y)

Source: Bloomberg

Specialty Retailers tend to outperform the S&P in the early and mid-point of the cycle regardless of the growth rate due to the broad growth seen by the economy and consumer. As we move further into the cycle the group tends to move with the growth rates of Retail Sales ex Autos and Gasoline, as seen with the 2000, 2006, and 2016 peaks in performance.

Specialty Retailers Index vs S&P 500

Source: Bloomberg

Finally, housing. When looking at housing, it’s important to understand that Existing Home Sales are nine times greater than New Home Sales. Currently, Existing Home Sales are seeing a negative growth rate and New Home Sales peaked in February.

Existing Home Sales (blue, 6ma Y/Y), New Home Sales (red, 6ma Y/Y)

Source: Bloomberg

The MBA Purchase Index is also confirming the weakness in the housing data.

MBA Purchase Index Y/Y: 26 wk average (blue), 12 wk average (green), 8 wk average (yellow)

Source: Bloomberg

When looking at equities, and specifically Whirlpool (WHR) and Lennar (LEN), we see that the relative performance topped in 2015. This was slightly before the MBA Purchase Index peaked in 1Q16 and when interest rates (Fed Funds and the National 30yr Fixed Rate) began to increase.

Whirlpool (WHR) vs S&P (white), Fed Funds Rate (yellow, inversed), Bank Rate National 30yr Fixed Rate Average (green, inversed)

Source: Bloomberg

Lennar (LEN) vs S&P (white), Fed Funds Rate (yellow, inversed), Bank Rate National 30yr Fixed Rate Average (green, inversed)

Source: Bloomberg

 

Summary

When looking at the overall demand of goods in the US, we see:

While it is a major concern that everything seems to be lining up to slow all at the same time, there are still areas of the economy doing ok. My uneasiness with the US economy will begin to increase as the discretionary spending by the US Government begins to fade when the new fiscal year begins October 1st.

Something I underappreciated earlier this year was the strength of the tailwind from the fiscal spending provided to the US economy the past few months. However, this turns into a headwind as the spending is reversed with the new fiscal year.

https://www.cbo.gov/system/files/115th-congress-2017-2018/reports/53696-sequestration.pdf

As demand for goods in the US slows, this will put additional pressure on China, Emerging Markets, and the other Developed Economies that manufacture the goods purchased in the US. In this scenario, and since these areas are already slowing, I would continue to expect US equities to outperform on a relative basis and is why I continue to recommend the same allocation I have previously.

On an absolute basis, I am getting more concerned about the ability for US equities to continue to move higher once all the economic data points slow. However, it seems that we are still a few months away from that occurring at this time.

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Overweight (or long) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

 

Breaking Down Brazil

Most of my posts have been focused on China and US. This one will be centered on specific indicators that I use to follow Brazil.

In this post I’ll discuss:

  • Indicators of focus separated into Leading, Coinciding, and Lagging
  • Charts for each indicator
  • Summary and specific notes about each indicator

While Brazil is down 25-30% from the January peak, to me, we are still early in the move based upon my analysis.

MSCI Brazil (weekly chart)
Source: Bloomberg

 

Indicators of Focus

On a relative basis, Brazil vs the S&P 500 is near the lows seen in 1999, 2002, and 2016.

MSCI Brazil vs S&P 500 (monthly chart)
Source: Bloomberg

Meanwhile, the currency (USD/BRL) is approximately 15% from the 2016 highs.

MSCI Brazil vs S&P 500 (white), USD/BRL (inversed, yellow) (daily chart)
Source: Bloomberg

To help explain what has been driving the performance of Brazil, there are eight indicators that I focus on that I separate into Leading, Coinciding, and Lagging.

Leading Indicators (tend to inflect before the change in relative price)

  • China’s M1
  • Brazil’s Terms of Trade
  • Brazil’s Industrial Production and Manufacturing PMI
  • Brazil’s exports
  • Brazil’s Credit Default Swap (CDS)

Coinciding Indicators (tend to inflect with the change in relative price)

  • Currency (USD/BRL)
  • Emerging Markets OAS

Lagging Indicator (tend to inflect after the change in relative price)

  • Relative Fundamentals

 

Charts for Each Indicator

China’s Impact on Brazil

Since China accounts for ~20% of all Brazil’s exports, what happens in China directly impacts Brazil.

Comparing China’s M1 Money Supply to the relative performance of Brazil vs the S&P 500, Brazil saw significant outperformance from 2002 – 2010 when China’s economy and M1 was growing tremendously. However, as China has slowed since 2010, the relative performance of Brazil has been the complete opposite of the prior period.

China M1 (blue – 1ma, red – 3ma, green – 6ma, yellow – 12ma)
Source: Bloomberg

MSCI Brazil vs S&P 500 (monthly chart)
Source: Bloomberg

As seen over the past 10 years, if the growth rate of China’s money supply is declining than the probability of global trade (i.e. demand) increasing is extremely low.

China’s M1 12ma, Y/Y (light blue), Australia (blue), Brazil (green), South Korea (red) (note – country data Y/Y and 6 month average)
Source: Bloomberg

Manufacturing and Trade

While both are broad indicators of potential global demand, I do watch ISM Manufacturing and Japan’s Leading Index. Currently, it seems that both peaked 4-6 months ago.

MSCI Brazil vs S&P 500 (white), ISM Manufacturing (yellow), Japan Leading Index (green) (monthly chart)
Source: Bloomberg

Turning to Brazil specific data, Industrial Production and Manufacturing PMI are showing signs of additional slowing after peaking about 6 months ago. (note – image shifted so it can be compared to the previous chart)

As shown in the second China M1 chart, the growth rate of Brazilian Exports is slowing and looks similar to the 2000-2001 period.

Brazil Exports: blue – 3ma, Y/Y; red – 6ma, Y/Y (monthly chart)
Source: Bloomberg

MSCI Brazil vs S&P 500 (monthly chart)
Source: Bloomberg

Similarly, Brazil’s Terms of Trade (value of exports relative to the value of imports) is declining.

MSCI Brazil vs S&P 500 (white), Brazil Terms of Trade (yellow) (monthly chart)
Source: Bloomberg

Credit Risks

Starting with the broad indicator of Emerging Market OAS, we see that spreads are still very tight for Emerging Markets.

MSCI Brazil vs S&P 500 (white), Barclays Emerging Markets OAS (yellow) (daily chart)
Source: Bloomberg

More specifically, Brazil’s 5yr Credit Default Swaps (CDS) is showing stress but it is still a long way from the levels seen in 2008 and 2015.

MSCI Brazil vs S&P 500 (white), Brazil 5yr CDS (yellow) (daily chart)
Source: Bloomberg

Relative Fundamentals

Turning to the relative fundamentals, there is about a 6 month lag from when China’s M1 increases to when Brazil sees a higher sales growth than the S&P.

Quarterly Chart
Source: Bloomberg

However, investors haven’t been rewarding Brazil during the higher growth periods.

MSCI Brazil vs S&P 500 (higher sales growth periods circled) (daily chart)
Source: Bloomberg

Turning to Operating Margins, when China was seeing strong growth (2002-2010), the relative profitability didn’t matter to the market as it was primarily focused on growth. However, that changed around 2011. Since then, when relative profitability declined, so has the relative performance of Brazil.

MSCI Brazil vs S&P 500 (white), Operating Margins: Brazil vs S&P (yellow) (monthly chart)
Source: Bloomberg

 

Summary and Notes about Specific Indicators

Comparing the leading indicators to 2000-2002 and 2014-2016, this trade seems to be in the early stages.

Leading Indicators

  • China’s M1 – Currently not looking to reaccelerate, staying focused on 6 and 12 month average
  • Brazil’s Terms of Trade – Bottomed long before others indicators in 2001 and 2015. No sign of that occurring at this time
  • Brazil Industrial Production and Manufacturing PMI – Would expect PMI to bottom before IP but that wasn’t the case in 2015-2016.
  • Brazil’s exports – Growth rate still declining and I would expect the 6ma to continue to slow
  • Brazil’s CDS – Small reversals are to be expected, staying focused on bigger move later in the slowdown, waiting for a lower high before fully closing trade.

Coincident Indicators

  • Currency (USD/BRL) – Will probably confirm the lower high of Brazil’s CDS, like in 2016
  • Emerging Markets OAS – Will probably confirm the lower high of Brazil’s CDS, like in 2016

Lagging Indicators

  • Relative Fundamentals – Only a lagging indicator because of the need for companies to report

 

Until the Leading Indicators begin to turn, I would continue to expect Brazil to underperform and would not recommend allocating money to Brazilian Equities despite the Index being 25-30% off the January high.

The Continued Market Rotation From Cyclical to Defensive

One thing I continue to remind myself of is that narratives can be a very powerful driver for the market. During times of market rotation, investors on both sides of the discussion can have clearly articulated near term fundamental reasons for the stock, commodity, etc to go up or down. In the end, taking a broad approach to evaluating the market tends to work out because while history doesn’t repeat, it does tend to rhyme.

In this post I discuss:

  • Changes in currencies and ex-US equities
  • Analyzing commodities and the US rotation
  • Items of considerable interest

Currently the US is showing the greatest economic strength but it is probably only a matter of time before it exhibits characteristics of a slowing economy like the rest of the world. Therefore, the positioning I recommended a few weeks ago remains my current positioning.

Changes in Currencies and ex-US Equities

The Trade Weighted USD has made quite the rebound despite numerous strategists and investors, many of whom I respect, calling for the USD to decline further.

Trade Weighted US Dollar
Source: Bloomberg

Their viewpoint makes sense as the USD has seen its share of foreign exchange reserves and international transactions continue to decline.

Percentage of Foreign Exchange Holdings in USD
Source: Bloomberg

SWIFT Transactions: Percentage in USD (white), Percentage in EUR (yellow)
Source: Bloomberg

However, as trade data in China continues to decline (discussed here: https://wp.me/p9vaFZ-5f) and Loaded and Empty TEUs at the three major ports in the US are slowing, the use of the USD in international trade should increase relative to other currencies, leading to it appreciate.

Total Change of TEUs at Major US Ports (6 month moving average)
Source: Port of Long Beach, Los Angeles, and NY/NJ

Even though the EUR peaked approximately two months ago, investors are still positioned for the EUR to appreciate. Just a reminder, I showed in the China post how the EUR tends to move with the Export Data of China’s major trading partners but with a lag.

EUR/USD Commitment of Traders (COT)
Source: freecotdata.com (@movement_cap)

A more consistent correlation for the EUR is actually with a chart I’ve been posting on Twitter showing the change in Demand/Supply for Oil. Since 2005, the EUR has lagged major inflection points of the six-month average of Demand/Supply by four months.

EUR/USD (blue), Oil Demand/Supply lagged four months: monthly data point (red), 6ma (black)
Source: Bloomberg

As the EUR has declined, numerous ETFs associated with Europe have begun to look quite weak. Given the news, it’s no surprise that Italy and Spain are weak relative to the S&P. However, it is surprising that more stable economies, like Germany and Switzerland, look similar.

Italy (EWI) vs S&P 500 (white), ISM Manufacturing (yellow)
Source: Bloomberg

Spain (EWP) vs S&P 500 (white), ISM Manufacturing (yellow)
Source: Bloomberg

Germany (EWG) vs S&P 500 (white), ISM Manufacturing (yellow)
Source: Bloomberg

Switzerland (EWL) vs S&P 500 (white), ISM Manufacturing (yellow)
Source: Bloomberg

Turning to Emerging Market Currencies, a basket compiled by JP Morgan continues to weaken. There wasn’t much of a rebound from the 2016 lows, which initially made me think they had more room to run in the future. Now I’m wondering if it remained low for a reason.

Regardless, as ISM Manufacturing and EM FX declines, the performance of the Emerging Markets Index relative to the S&P 500 should continue to decline.

JPM EM Currency Index (black), Emerging Markets vs S&P 500 (blue), ISM Manufacturing (orange)
Source: Bloomberg

Besides Turkey, Brazil’s currency has been one of the weakest in this basket the past few months and is getting close to the worst level seen in 2015.

USD/BRL
Source: Bloomberg

Despite the fact that the Brazil ETF, EWZ, is near all time lows relative to the S&P, I think that this has a long way to go since China’s trade data is still declining and ISM Manufacturing peaked only a few months ago in February. FYI, since 1980 the average peak to trough for ISM is ~18 months.

Brazil (EWZ) vs S&P 500 (white), ISM Manufacturing (yellow)
Source: Bloomberg

Analyzing Commodities and the US Rotation

While ex-US is showing how the market is changing from a cyclical, or weak USD perspective, to a defensive, or strong USD outlook, this is just beginning to show in commodities and in US sector rotation.

With commodities, there are three that I pay the most attention to: Oil, Copper, Lumber.

Starting with Oil, I showed in the previous EUR chart how Demand is weakening relative to Supply. This could change when the May and June data is released (Summer driving season). However, the EUR tends to lead changes in the price of Oil by two months. Therefore, the recent weakness in Oil could go on for some time.

EUR/USD with a 2 month lead (white), Oil (yellow)
Source: Bloomberg

The chart of Copper looks very similar to numerous other charts. More importantly, traders are still positioned for Copper to move higher.

Copper Commitment of Traders (COT)
Source: freecotdata.com (@movement_cap)

This is despite the fact that the change in Copper year over year is highly correlated to ISM.

Source: Raoul Pal, Global Macro Investor

At the same point, the price of Lumber has exceeded the previous 30 year high by over 30%. FYI, this is a great example why previous highs should not be viewed as the potential limit, which is a mistake I made when opining on the price of Lumber six months ago.

Lumber
Source: Bloomberg

Turning to US equities, it looked like there was numerous times when investors were changing their allocation to the Defensive Sectors and Industries. Each time though this failed despite the change in allocation for Currencies and ex-US the past few months. I continue to point to the increase in the Markit PMI data, which is more US focused manufacturing survey compared to the ISM.

However, as UBS showed a few months ago (h/t @TeddyVallee), the US economy is benefiting significantly from the boost in Oil.

As Oil begins to fade, I would expect the other Cyclical Sectors and Industries to begin to underperform the more Defensive Sectors and Industries. As a reminder, market rotation tends to occur around the peaks and troughs of ISM Manufacturing.

ISM Manufacturing (yellow), Semiconductors vs Health Care (white)
Source: Bloomberg

ISM Manufacturing (yellow), Financials vs Consumer Staples (white)
Source: Bloomberg

Items of Considerable Interest

Despite the move off the February lows, the Volatility Spreads (initially discussed here: https://wp.me/p9vaFZ-3z ) have stayed compressed and never fully recovered. This morning (May 29th), they were under considerable pressure but did recover off the lows by the end of the day.

Generic Volatility Spreads (2ndmonth – 1stmonth) (white), S&P 500 (yellow)
Source: Bloomberg

However, the Volatility Curve is in backwardation for the first time in over a month.

Volatility Curve: May 29th(green), May 25th(orange), May 18th(blue)
Source: Bloomberg

For the rotation from ex-US to US and Cyclical to Defensive to last more than a few months, the Option Adjusted Spreads (OAS) has to increase. As discussed in the China post, there’s little to no financial stress when looking at the spreads. However, it seems like this is beginning to change.

ISM Manufacturing (yellow), Investment Grade OAS (red), High Yield OAS (white), Emerging Markets OAS (green)
Source: Bloomberg

If the Spreads do continue to widen, then the next step is for the lending conditions of US Banks to tighten to businesses of all sizes.

Source: St Louis Federal Reserve

US Banks have already tighten the lending conditions for credit cards and auto loans towards US consumers with lower credit scores.

Source: Barclays

Source: St Louis Federal Reserve

Outside the US, we’ve already seen China’s major trading partners export data decline and the Leading Indicators for Japan decline, which has correlated well with global manufacturing.

Finally, the European Banks tend to be the last ones to tighten their lending conditions.

ECB Survey of Lending Conditions to European Businesses
Source: Bloomberg

Summary

Currently the US is showing the greatest economic strength but it is probably only a matter of time before it exhibits characteristics of a slowing economy like the rest of the world. Therefore, the positioning I recommended a few weeks ago remains my current positioning:

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Overweight (or long) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

Revisiting and Reiterating the Call that China is Slowing

In January I made the case that China was slowing (https://wp.me/p9vaFZ-2w). By all accounts, this continues to play out and doesn’t seem to be changing course any time soon.

In this post I’ll discuss:

  • China’s continued slowing demand of foreign goods and its correlation to debt
  • Why the decline of Shadow Banking must lead to an increase of traditional lending
  • Other indicators of importance

In previous posts I’ve stated that I expected growth to recover in the second half of 2018. However, it’s beginning to seem that I was potentially too optimistic with this outlook as China has yet to begin to restimulate their economy and instead has been managing the slowdown.

Note – this post will not thoroughly explain my thought process on specific topics that were discussed in the previous China post so please reference it as needed.

China’s Continued Slowing Demand of Foreign Goods and its Correlation to Debt

As shown previously, the Export Data of China’s largest trading partners correlates well to China’s 5yr yield. This continues to be the case, providing us a real-time market based indicator of China’s economy.

China’s 5yr yield (black), ISM (purple), Australia (blue), Brazil (green), South Korea (red) (note – country data Y/Y and 3 month average)

Source: Bloomberg

A well-known fact is that China’s economic growth has been driven by debt. From an article published by the WSJ in December 2017:

In the blueprint to be unveiled on Wednesday, past talk of bringing down debt, the priority for the past two years, is gone in favor of a pledge to just control the rise in borrowing, according to these people.

The softening of the goal, decided earlier this month by the Communist Party’s top leadership, is an official acknowledgment of how hard it is for Beijing to wean the economy off debt-driven growth.

“Let’s face it,” said an official involved in policy discussions, “it’s not realistic to reduce leverage when the whole economy relies on banks for financing.”

https://www.wsj.com/articles/china-seeking-growth-softens-focus-on-cutting-debt-1513700557

A broad form of analyzing credit in China is Total Social Financing (TSF). When comparing the next chart to the previous chart, we see that inflection points in TSF led changes in the trade data by ~6 months. However, this broke down as a leading indicator in 2017 as the trade data began to decline as TSF peaked.

China’s Total Social Financing (note – turning points in the growth rate circled)

Source: Bloomberg

Why the Decline of Shadow Banking Must Lead to an Increase of Traditional Lending

Historically, there has been a strong relationship between Shadow Banking and the Export Data of major trading partners. Similar to TSF, when Shadow Banking Y/Y peaked in the past, demand of foreign goods would peak 6-12 months later. This time, when Shadow Banking peaked, demand immediately rolled over.

China’s Shadow Banking Y/Y (black), Australia (blue), Brazil (green), South Korea (red) (note – country data Y/Y and 3 month average)

Source: Bloomberg

The change in the relationship of TSF and Shadow Banking with the Export Data might be due to the government’s plan to effectively ban Entrusted Loans. From the South China Morning Post (SCMP):

Entrusted loans often take the form of banks buying investment products from asset management plan providers, who in turn would lend the money to borrowers designated by the banks. 

“Since the only channel for asset management plans to allocate funds to the end borrowers is via entrusted loans, the ban on using funds from the plans from brokers, fund management subsidiaries and private funds for entrusted loans will effectively put an end to the most popular structure for non-standardised credit assets”

He predicted that the new rule could reduce the amount of non-standard credit by 80 to 90 per cent over time, and push most credit back to regular channels such as loans and bonds.

“The message is very clear-cut, you just have to give up the non-standard credit business,” Xu said in a separate briefing on Monday.

http://www.scmp.com/business/banking-finance/article/2127527/chinas-ban-entrusted-loans-set-end-popular-form-shadow

In the past, Entrusted Loans accounted for ~15% of TSF. Therefore, the declining use of these loans will be a headwind for quite some time. Finally, we see that when Entrusted Loans Y/Y peaked in early 2017, the Export Data peaked like it has historically.

China’s Entrusted Loans: 12 month average, Y/Y (red), 12 month average (blue)

Source: Bloomberg

Understanding the relationship of growth and Shadow Banking is important for three reasons:

1) As shown by Moody’s, Shadow Banking has grown in importance over the years and is now as large as 80% of the Chinese economy. Keep in mind, Shadow Banking is only 25% of Total Bank Assets, which is why most investors are concerned about the debt levels in China (Debt to GDP in China is ~325% compared to the US at ~105%) and it’s ability to stimulate their economy effectively.


2) As examined by the Bank of International Settlements (BIS) in February 2018:

While growth of shadow credit to ultimate borrowers has slowed, the use of shadow saving instruments (eg wealth management products, trust products) has continued to expand at a fast pace. New and more complex “structured” shadow credit intermediation aimed at reducing banks’ regulatory burden has emerged and quickly reached a large scale. The bond market has become highly dependent on funding channelled through wealth management products. 

https://www.bis.org/publ/work701.htm

In layman’s terms, Shadow Banking has not only grown in importance but is highly integrated into the Chinese financial industry.

3) As discussed by the SCMP on March 30, 2018:

“A massive clean-up is likely to take place in China’s 100 trillion yuan (US$15 trillion) asset management industry after new regulations targeting “shadow banking” were approved.

“The message is clear that China will proceed with strong financial regulations to defuse risks,” said Raymond Yeung, chief Greater China economist of ANZ Bank.

There will be little prospect of policy loosening “no matter how the regulatory regime is reshuffled or external tensions escalate,” Yeung added.”

http://www.scmp.com/news/china/economy/article/2139695/chinas-leaders-sign-new-rules-crack-down-shadow-banking

Since we know that China’s Shadow Banking has grown in size and importance and the government wants to increase the regulation of Shadow Banking, this should result in less demand of foreign goods until China can replace this credit with more traditional means of financing, loan growth.

As seen in the next chart, when demand of foreign goods have slowed in the past, the growth of new Yuan denominated loans have increased. I would expect the Chinese to use this same playbook during the current slowdown but in a more meaningful way since it has to make up for the decline in Shadow Banking, Entrusted Loans, and restimulate their economy.

China’s CNY Monthly New Loans Y/Y, 12 month average (black, inversed), ISM (purple), Australia (blue), Brazil (green), South Korea (red) (note – country data Y/Y and 3 month average)

Source: Bloomberg

So far, the strategy of increasing new CNY loans and reducing interest rates has resulted in little to no financial stress compared to 2009-2010 and 2015, as shown in the bottom panel of the next chart.

Top Panel: 5yr Yield (blue), 1yr Yield (Black), SHIBOR (red), CNY (purple); Bottom Panel: 5yr – 1yr

Source: Bloomberg

However, it seems that it’s only a matter of time before this potentially changes as financial conditions in Asia ex-Japan have declined with ISM Manufacturing and the Option Adjusted Spread on Emerging Market debt has begun to increase from a very low level.

Barclays EM OAS (inversed, blue), Bloomberg Financial Conditions Asia ex-Japan (black), ISM Manufacturing (red)

Source: Bloomberg

Finally, despite little to no financial stress showing in the 5yr – 1yr spread, it’s important to note that defaults are already on the rise again in China, as discussed by the SCMP on May 14th:

China’s private sector firms are facing a debt crisis amid falling profits and rising financing costs, with the value of bond defaults in the sector rising by more than a third in the first four months of the year

“No matter what industry they are in, what these companies have in common is that they are finding it much harder than state-owned enterprises to get financing,” Qin Han, chief fixed income analyst at Guotai Junan Securities, wrote in a note.

“Deteriorating business could lead banks to withdraw loans and cause a cash shortage. Eventually, it will lead to more defaults. State-owned enterprises [in contrast] can rely on other sources of borrowing to sustain them, even if their businesses are feeling the strain,” he said.

http://www.scmp.com/news/china/economy/article/2145934/chinas-private-firms-default-us2-billion-bond-repayments-beijings

Other Indicators of Importance

Since I tend to not trust the absolute value of the Chinese data, hence the reason why I look at the long term trend of the data, there are a few other indicators that I feel are important to keep an eye on that are outside of China’s control.

First, the currencies of Australia and Brazil, which tend to move fairly well with the Export Data shown previously.

AUD/USD (light blue), USD/BRL (black), Export Data Y/Y, 3ma: Australia (blue), Brazil (green), South Korea (red)

Source: Bloomberg

Next are the EUR/USD and US 30yr. The EUR has had a delayed move to the trade data the past few years, possibly because of its rising status as a funding currency alternative to the USD. With the US 30yr yield, it continues to stay around 3.1-3.2% for the time being. However, as global growth slows, I still believe that the 30yr will decline like it has previously.

EUR/USD (light blue), US 30yr Yield (black), Export Data Y/Y, 3ma: Australia (blue), Brazil (green), South Korea (red)

Source: Bloomberg

Turning to the lending surveys of US and European banks, both are still reporting loose lending conditions for large businesses. Based upon previous periods of stress, I would expect a tightening of lending standards to show up in the US first while Europe will probably wait until the last minute before tightening.


Source: St. Louis Federal Reserve

ECB Survey of Credit Standards for Businesses

Source: Bloomberg

The last indicators of importance are the shares outstanding for the iShares Emerging Markets ETF (EEM) and iShares Emerging Market Debt ETF (EMB). The reason why I’m focused on shares outstanding is because I’m looking for when investors change their thoughts on allocating money towards the Emerging Markets. Said a different way, how much pain are they willing to take before they want out.

EEM: Price (white), Shares Outstanding (red)

Source: Bloomberg

EMB: Price (white), Shares Outstanding (red)

Source: Bloomberg

Summary

While China continues to slow, there is no way to know whether this ends as another period of increased financial stress or a crisis, which so many have predicted in the past. What’s more important is knowing and understanding that asset allocation remains the same through this part of the cycle regardless of the end result in China.

Currencies

  • Overweight (or long) the USD
  • Underweight (or short) Emerging Market currencies

Bonds

  • Overweight (or long) long dated maturing US debt
  • Underweight (or short) Emerging Market debt

Equities

  • Overweight (or long) S&P 500
  • Underweight (or short) Emerging Markets
  • Overweight (or long) US defensive sectors and industries
  • Underweight (or short) US cyclical sectors and industries

 

Drivers of Sector Rotation & Relative Performance of Equities

Drivers of Sector Rotation & Relative Performance of Equities

Since starting www.equitiesandmacro.com, most of my posts have been focused on looking for signs from the market as to when it will rotate market leadership from Cyclical to Defensive equities. In this post, I detail the key drivers of sector rotation and the relative performance of equities by analyzing:

  • What the market tends to focus on in various parts of the business cycle
  • Translating this into factors driving relative performance
  • Summary of analysis

Being too soon or late with sector rotation can be quite painful for the active investor. This can be exasperated because “tops are a process and bottoms are an event.” Understanding what to look for can help improving the timing of when to change positioning along with holding it through periods when the investment is going against you.

What the Market Focuses on in Various Parts of the Business Cycle

The market tends to focus on two key items during the fluctuations of the business cycle:

  • When economic growth is increasing, the market is focused on companies that have revenue growth increasing at a higher rate than the market.
  • When economic growth is decreasing, the market is focused on companies with more stabile businesses than the market

The following chart displays this in a simple way with the line representing economic growth (i.e. global manufacturing).


Elaborating on this further, when growth is increasing the market tends to have little to no concerns. The main focus of the market is to find the companies that are growing revenues and profitability the fastest. Those that are not growing as fast as the market might still see their price improve on an absolute level, but the probability of it outperforming the market is low. This is why there is a higher probability of more Cyclical equities outperforming the Defensive equities when economic growth is increasing.

This dynamic changes once global growth has peaked and begins to slow. When this occurs, the equities that have more stable business models (i.e. less cyclical) tend to outperform.

Translating This into Factors Driving Relative Performance

Keeping the information from the last segment in mind, the relative fundamentals of equities drives the relative performance of equities. Please note that I wrote relative and not absolute, which is an entirely different discussion.

When determining relative performance, there are three items that I analyze before estimating future fundamentals:

Using this information, I will go through the following examples:

  • Relative to Benchmark: Micron (MU) vs S&P 500
  • Relative to Industry Peer: Micron (MU) vs Texas Instruments (TXN)
  • Relative to Cross-Sector Peer: Micron (MU) vs Johnson & Johnson (JNJ)
  • Relative to Cross-Sector Peer: Micron (MU) vs Aqua America (WTR)

The reason why I use Micron (MU) is because it is one of the best companies that follow the relative fundamentals in an exaggerated boom-bust format, thus making it an easy to use example.

Relative to Benchmark: Micron (MU) vs S&P 500

As seen in the revenue chart and mentioned earlier, MU is a boom-bust company. The difference of revenue growth tends to coincide with the relative performance of MU vs the S&P 500. In this circumstance, the level of revenue outperformance does not dictate the level of price outperformance. More specifically, the difference of revenue in 2014 was greater than 2018 but MU has seen significantly more outperformance in 2018 relative to 2014.


Source: Bloomberg

Micron (MU) vs S&P 500 (SPX): Price

Source: Bloomberg

Relative gross and operating margins tend to peak around the time as relative performance. Showing how the market looks for stability in a declining growth environment, even though MU’s relative revenue growth was lower in 2016 than 2012, MU’s trough relative performance was approximately the same as MU’s gross and operating margins relative to the S&P 500 declined less in 2016 compared to 2012.

Micron (MU) vs S&P 500: Price (white), Gross Margin (yellow)

Source: Bloomberg

Micron (MU) vs S&P 500: Price (white), Operating Margin (yellow)

Source: Bloomberg

Relative performance peaks and troughs around the turning points in ISM Manufacturing.

ISM Manufacturing (yellow), Micron (MU) vs S&P 500: Price (white)

Source: Bloomberg

Relative valuation is not consistent with ISM or relative fundamentals. In 2008, MU was expensive relative to the S&P 500 and probably limited the potential outperformance of MU. In 2012, MU was cheap relative to the S&P 500 when ISM and relative fundamentals inflected. While it initially bounced in 2016, MU’s multiple underperformed the S&P 500 the past 18 months despite having higher revenue growth and an increasing difference of margins in MU’s favor.

ISM Manufacturing (red), Micron (MU) vs S&P 500: EV/EBITDA (blue)

Source: FactSet

Summarizing MU vs the S&P 500, relative revenue growth was the main driver of relative performance. Relative margins became more important when revenue growth was slowing. The inflection point for relative performance tended to occur with ISM. Low relative valuation helps MU at inflection points but it doesn’t seem to prohibit the ability of MU to outperform on a relative basis.

Relative to Industry Peer: Micron (MU) vs Texas Instruments (TXN)

While MU and TXN are both semiconductor manufacturers, MU manufactures memory chips (i.e. stores data) while TXN builds analog and digital chips (i.e. process commands).

As seen in the revenue chart, TXN is not a boom bust company despite being in the same industry. However, the chart shows that the revenues of TXN tends to ebb and flow on a slightly delayed basis relative to MU.

As with MU vs the S&P 500, the difference of revenue growth tends to coincide with the relative performance of MU and TXN. Also, the level of revenue outperformance tends to correlate with the level of price outperformance. More specifically, the difference of revenue in 2014 was greater than 2018, which coincides with the MU seeing significantly more outperformance in 2014 relative to 2018.


Source: FactSet

Micron (MU) vs Texas Instruments (TXN): Price (white)

Source: Bloomberg

Relative gross and operating margins tend to peak around the time as relative performance. Similar to the S&P 500, as MU’s gross and operating margins relative to TXN declined less in 2016 compared to 2012, MU’s trough relative performance was approximately the same despite the larger difference in revenue growth in those periods.

Micron (MU) vs Texas Instruments (TXN): Price (white), Gross Margin (yellow)

Source: Bloomberg

Micron (MU) vs Texas Instruments (TXN): Price (white), Operating Margin (yellow)

Source: Bloomberg

Relative performance peaks and troughs around the turning points in ISM Manufacturing.

ISM Manufacturing (yellow), Micron (MU) vs Texas Instruments (TXN): Price (white)

Source: Bloomberg

Relative valuation is not consistent with ISM or relative fundamentals. As with the S&P 500, MU was expensive relative to TXN in 2008 and probably limited the potential outperformance of MU. In 2012, MU was cheap relative to TXN when ISM and relative fundamentals inflected. While it initially bounced in 2016, MU’s multiple underperformed TXN the past 18 months despite having higher revenue growth and an increasing difference of margins in MU’s favor.

ISM Manufacturing (red), Micron (MU) vs Texas Instruments (TXN): EV/EBITDA (blue)

Source: FactSet

Summarizing MU vs TXN, relative revenue growth was the main driver of relative performance. Relative margins became more important when revenue growth was slowing. The inflection point for relative performance tended to occur with ISM. Low relative valuation helps MU at inflection points but it doesn’t seem to prohibit the ability of MU to outperform on a relative basis.

Relative to Cross-Sector Peer: Micron (MU) vs Johnson & Johnson (JNJ)

Moving to the cross-sector level, JNJ is considered a more defensive company than MU as it manufactures less cyclical products such as pharmaceuticals and medical devices.

The difference of revenue growth coincides with the relative performance of MU and JNJ. Similar to the S&P 500, this is less of a driver of the level of outperformance. More specifically, the relative level of MU’s revenue growth was similar in 2010, 2014, and 2018 but MU has seen the highest level of price outperformance relative to JNJ in the most recent period.


Source: FactSet

Micron (MU) vs Johnson & Johnson (JNJ): Price (white)

Source: Bloomberg

Relative gross and operating margins tend to peak around the time relative performance peaked. MU’s relative margins increased more in the latest economic growth cycle compared to the prior two cycles.

Similar to TXN, as MU’s gross and operating margins relative to JNJ declined less in 2016 compared to 2012, MU’s trough relative performance was the same despite the larger difference in revenue growth in those periods.

Micron (MU) vs Johnson & Johnson (JNJ): Price (white), Gross Margin (yellow)

Source: Bloomberg

Micron (MU) vs Johnson & Johnson (JNJ): Price (white), Operating Margin (yellow)

Source: Bloomberg

Relative performance peaks and troughs around the turning points in ISM Manufacturing.

ISM Manufacturing (yellow), Micron (MU) vs Johnson & Johnson (JNJ): Price (white)

Source: Bloomberg

As with prior analysis, relative valuation is not consistent with ISM or relative fundamentals. MU was expensive relative to JNJ in 2008 and probably limited the potential outperformance of MU vs JNJ. In 2012, MU was cheap relative to JNJ when ISM and relative fundamentals inflected. While it initially bounced in 2016, MU’s multiple underperformed JNJ the past 18 months despite having higher revenue growth and an increasing difference of margins in MU’s favor.

ISM Manufacturing (red), Micron (MU) vs Johnson & Johnson (JNJ): EV/EBITDA (blue)

Source: FactSet

Summarizing MU vs JNJ, relative revenue growth is the main driver of relative performance. Relative margins became more important when revenue growth was slowing. The inflection point for relative performance tended to occur with ISM. Low relative valuation helps MU at the inflection point but it doesn’t seem to prohibit the ability of MU to outperform on a relative basis.

Relative to Cross-Sector Peer: Micron (MU) vs Aqua America (WTR)

Showing one more cross-sector example, being a water utility company, WTR is considered a more defensive company than MU.

The difference of revenue growth coincides with the relative performance of MU and WTR. Similar to the S&P 500 and JNJ, this is less of a driver of the level of outperformance. More specifically, the relative level of MU’s revenue growth was similar in 2010, 2014, and 2018 but MU has seen the highest level of price outperformance relative to WTR in the most recent period.


Source: FactSet

Micron (MU) vs Aqua America (WTR): Price (white)

Source: Bloomberg

Relative operating margin tend to peak around the time relative performance peaked. MU’s relative margin increased more in the latest economic growth cycles compared to the prior two cycles.

Similar to the other examples, as MU’s operating margin relative to WTR declined less in 2016 compared to 2012, MU’s trough relative performance was the same despite the larger difference in revenue growth in those periods.

Micron (MU) vs Aqua America (WTR): Price (white), Operating Margin (yellow)

Source: Bloomberg

Relative performance peaks and troughs around the turning points in ISM Manufacturing.

ISM Manufacturing (yellow), Micron (MU) vs Aqua America (WTR): Price (white)

Source: Bloomberg

As with the prior examples, relative valuation is not consistent with ISM or relative fundamentals. MU was expensive relative to WTR in 2008 and probably limited the potential outperformance of MU vs WTR. In 2012, MU was cheap relative to WTR when ISM and relative fundamentals inflected. While it initially bounced in 2016, MU’s multiple underperformed WTR the past 18 months despite having higher revenue growth and an increasing difference of margins in MU’s favor.

ISM Manufacturing (red), Micron (MU) vs Aqua America (WTR): EV/EBITDA (blue)

Source: FactSet

Summarizing MU vs WTR, relative revenue growth is the main driver of relative performance. Relative margins became more important when revenue growth was slowing. The inflection point for relative performance tended to occur with ISM. Low relative valuation helps MU at the inflection point but it doesn’t seem to inhibit the ability of MU to outperform on a relative basis.

Summary of Analysis

The equity analysis I’ve shared is different to the more common approach of focusing primarily on absolute valuation and fundamentals.

To summarize the approach of analyzing on a relative basis:

As stated at the beginning, “tops are a process and bottoms are an event.” Since bottoms are an event, this is why determining what the market views as a leading indicator of revenue growth is important. Once the market believes revenues are going to improve, the multiple moves the equity price higher before the fundamentals change. Those that are short tend to get caught off guard and get squeezed by the sudden change in expectation.

Since tops are a process, this is why we tend to see the relative equity price peak with the leading indicator and the relative fundamentals. Those that are only looking at absolute price performance are typically slower to realize that the price of the equity is trailing the performance of the market as the relative fundamentals and leading indicator decline.

There are times when this analysis does not work as well. The most consistent is after a period of significant wealth destruction. When equities decline by 80% or more, the market tends to overly punish these equities for approximately five to ten years before the “mental scars” of the previous period wears off. A few examples of industries that faced wealth destruction after peaking in the year listed are:

  • Technology in 2000
  • Housing in 2006
  • Commodities in 2011-2012
  • Oil in 2014

Finally, when applying this analysis, the modus operandi I follow to help increase the probability of making an investment that outperforms is:

  • Absolute analysis to understand the fundamental drivers and leading indicator
  • Relative analysis vs the benchmark to corroborate the thesis for outperformance
  • Relative analysis vs peers to support the thesis that this equity is the most likely to outperform