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

Making the Case for TLT

Being a contrarian for contrarian’s sake is a bad way to invest. However, going against the herd can be more profitable than not with a disciplined approach. This leads me to recommend a long-term investment in TLT for long only investors.

In this post, I’ll make the case for TLT by:

  • Analyzing previous and current drivers
  • Positioning and outlook
  • Considering the current consensus arguments

As the global economy continues to slow, the risk/reward scenario for TLT outperforming the S&P 500 is skewed to the reward side for investors with a multi-year investment horizon. There are obviously risks associated with TLT, as there are with any investment, but the pros outweigh the cons in my opinion.

Just a reminder, these are only my thoughts and please do your own research before making any investment.

Analyzing Previous and Current Drivers

When analyzing the various treasury yields, those with the longest maturity dates are the most sensitive to growth. The 30yr Treasury Bond is currently the longest bond issued by the US Treasury, thus the most sensitive. Prior to 1977, the 10yr Treasury Bond had the longest maturity.

Since the longest maturity bonds are the most sensitive to growth, the nominal yield of the long bond tends to be highly correlated to US Nominal GDP. (note: nominal = inflation + growth)

10yr Treasury Yield (yellow), US Nominal GDP (white), NBER Recession Indicator (red)
Source: Bloomberg

From 1960 until 1981, US Nominal GDP and the 10yr Yield were trending higher together. In the late 1970s, inflation was over 10%, which helped push yields higher despite US Nominal GDP falling.

Since bond yields peaked in 1982, the US economy began to mature as the US population aged, which has gradually decreased the overall demand of finished goods and helped push inflation down to the levels we have today. One item of note is that the increase in inflation we saw from 2004 to 2008 was largely contributed to the rise of China as they were building their massive infrastructure projects.

Source: St Louis Federal Reserve

Historically, the ISM Manufacturing Survey was the best way to measure global growth. From 1986 until 2000, when ISM peaked the 30yr Treasury Yield tended to peak with it.

ISM Manufacturing (white), 30yr Treasury Yield (yellow)
Source: Bloomberg

However, things began to change in the 2000s with the rise of China. Instead of the 30Yr Yield being solely correlated to ISM, it began to transition to global manufacturing. While the 30Yr did peak in 2004 with ISM, it remained elevated due to the inflation associated with China until global manufacturing peaked in 2007.

30Yr Treasury Yield (yellow), ISM (white), Japan’s Tankan (purple), Europe’s ESI (green)
Source: Bloomberg

Moving to our current period, global manufacturing slowed with ISM in 2011 but 2014 showed the disconnect once more. A larger separation has been seen over the past year as ISM increased to over 60 but the 30Yr Yield remained subdued.

ISM Manufacturing (white), 30yr Treasury Yield (yellow)
Source: Bloomberg

As discussed in previous posts, China is the growth driver of the world. While the 30Yr Treasury Bond is issued by the US, it can be argued that the main driver has become China. This becomes more apparent when China’s major trading partners began to see their exports slow in early 2011, early 2014, and throughout 2017, the 30Yr Yield tended to decline as demand from China slowed.

Australia (blue), Brazil (green), South Korea (red), US 30Yr Yield (black)
Source: Bloomberg

Comparing this to China’s 5Yr yield, it continued to increase as the PBOC pushed rates higher despite demand slowing.

Australia (blue), Brazil (green), South Korea (red), China 5Yr Yield (black)
Source: Bloomberg

However, we do know from recent history that the US 30Yr Yield and China’s 5Yr Yield tend to decline together as growth slows.

In the current situation, China is a little ahead in the recent decline. However, the PBOC pushed it to a level much higher than it should have been, just like they did in 2011 and 2013 in hopes of displaying a strong economy.

US 30Yr Yield (yellow), China 5Yr Yield (white)
Source: Bloomberg

Turning the focus to the US, we now have all three major segments of consumer discretionary spending beginning to show signs of slowing. This is the first time this has occurred in this business cycle.

Auto sales have been negative on a year over year (Y/Y) basis for a number of months. Based on the 1 and 3 month average, it looks like this could soon drag the more stable 6 month average lower.

US Auto Sales Y/Y: 6 month average (blue), 3 month average (green), monthly data point (red)
Source: Bloomberg

The Mortgage Bankers Association (MBA) Purchase Index began to decline a few months ago. While the contribution to GDP from housing has declined from the previous cycle, the multiplier effect still makes it a very important part of the US economy.

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

Lastly, Retail Sales saw a noticeable tick down this month after stalling around 4.5%. It’s too earlier to say this is definitely slowing but it’s worth noting as auto and home sales are slowing.

Retail Sales excluding Autos and Gasoline Y/Y: 6 month average (blue), 3 month average (green), monthly data point (red)
Source: Bloomberg

As mentioned in a previous post, the savings rate for the US consumer is near record lows, which does not bode well for an increase in demand of finished goods.

Source: St Louis Federal Reserve

Finally, the growth rate of balances on credit card is potentially peaking at a level lower than a year ago. Again, this would imply less future demand relative to the past. This is why I mentioned Retail Sales potentially slowing because customers tend to use their credit cards when making these types of purchases.

Source: St Louis Federal Reserve

Putting this together, the two largest drivers of global growth are in the process of slowing. I still believe that China will begin to stimulate their economy and lead global growth higher later in 2018. However, they have yet to do so, thus delaying the potential rebound in growth.

Positioning and Outlook

When looking at the Commitment of Traders report, investors are positioned for the 30Yr Yield to increase despite growth beginning to slow globally. As the narrative changes from increased global growth, investors will need to reverse their positions like they did going into 2014. (note: when bond prices increase, yields decline and vis versa)

30Yr Bond Net Positioning
Source: freecotdata.com, @movement_cap

When considering the possible return an investor could make on the TLT, I prefer to look at it on a total return basis, which means the price appreciation plus reinvesting the dividends as they are received.

In the following chart I have the month that ISM peaked and troughed along with the total return of TLT and the S&P 500 during that time frame. With ISM over 60 for only the third time in the past 30 years, the risk/reward is tilted in favor of the investor that is willing to hold their investments for a number of years, thus delaying the expense of paying taxes by trading frequently.

A historical period where TLT performed poorly relative to the S&P 500 after ISM peaked was from June 2004 to June 2007. In this scenario, the US slowed while global growth and inflation accelerated due to China’s massive infrastructure projects. However, those that continued to hold TLT were rewarded as yields declined during the financial crisis, as seen by the bottom line in the chart above.

Considering my current outlook of growth reaccelerating in the second half of 2018, but not to the levels seen during 2017, the holding period for this investment would be approximately 30 months (i.e. 2020) with an estimated total return of 40-50%. While a 15% annualized return is nothing to get too excited, relative to how the S&P would do during a recession, it would be a great investment for a long-term investor.

By the way, if the US economy gets to 2020 before falling into a recession, it would be the longest economic cycle in history as it eclipses the previous record of 120 months from 1991-2001. Currently, the US is in its 104th month of economic expansion.

Considering the Current Consensus Arguments

There are three consensus arguments against investing in TLT:

  • The US deficit is rising and makes our debt less attractive
  • The Treasury Department is issuing more debt as Central Banks are reducing their purchases of debt (i.e. increased supply)
  • Additional tariffs and/or a trade war with China will increase prices and therefore inflation and yields

1st Argument – The US deficit is rising and makes our debt less attractive

While I am sympathetic to this argument, the debt issued by the US government is still the most sought after during periods of slowing global growth and especially during a recession.

The best example of this is during the US Financial Crisis. Despite everything going on with the US economy, our deficit increasing significantly, and the US Treasury department drastically increasing the debt outstanding, the yield of the 10Yr and 30Yr bond continued to decline as investors increased their purchases.

If the deficit continues to increase on an absolute level and relative to other countries, I would not want to own TLT during a typical economy growth cycle like we just went through the past two years.

Source: St Louis Federal Reserve

Source: St Louis Federal Reserve

2nd Argument – The Treasury Department is issuing more debt as Central Banks are reducing their purchases of debt (i.e. increased supply)

According to Bloomberg (https://www.bloomberg.com/news/articles/2018-03-12/bond-enforcers-reawakening-as-deficits-and-inflation-risks-build ), the amount of debt the US Treasury Department will issue is set to average $1.27 Trillion over the next five years after averaging half of that amount the previous five years.

This has been openly discussed by the Treasury Department after they were advised to issue predominantly shorter-term debt in November (https://www.bloomberg.com/news/articles/2018-01-23/welcome-to-the-new-reality-of-leaping-u-s-treasury-debt-sales ).

At the same time, the Federal Reserve has announced that it will begin to shrink its balance sheet that consist of Treasury Bonds and Mortgage Backed Securities (https://www.bloomberg.com/news/articles/2017-10-13/long-awaited-fed-balance-sheet-taper-begins-today-with-mortgages ).

Finally, the ECB is looking to reduce the number of bonds it purchases as well. (https://www.bloomberg.com/news/articles/2018-03-08/ecb-is-said-to-assume-final-qe-push-totaling-30-billion-euros )

Combine this together and it sounds like a potential disaster for the bond market. It also helps explain the positioning of investors and why yields have been rising in the Developed Markets the past few months. Keep in mind that this was also occurring during a time of economic growth.

As the market becomes more concerned about slowing global growth, investors should quickly soak up the additional supply in the market driving yields lower, especially those bonds that are the most sensitive to growth like the 30Yr.

Finally, as the market continues to decrease the difference in 30Yr Yield and 2Yr Yield, the market seems to be more concerned about shorter term rates rising due to the large increase in supply and the US Federal Reserve raising interest rates than it is about longer term rates and the much smaller increase in supply relative to shorter term maturities.

30Yr Yield – 2yr Yield (white)
Source: Bloomberg

3rd Argument – Additional tariffs and/or a trade war with China will increase prices and therefore inflation and yields

Additional tariffs and/or a trade war with China are my biggest concerns regarding TLT. The US economy can handle a small number of items that have increased prices due to tariffs (i.e. Canadian lumber tariff – https://www.bloomberg.com/news/articles/2018-01-03/u-s-trims-duties-on-canadian-lumber-in-lingering-softwood-spat ). The same could be said regarding the tariffs announced last week dealing with steel and aluminum (https://www.bloomberg.com/news/articles/2018-03-04/lessons-from-2002-show-economic-bang-from-steel-tariffs-was-tiny ).

However, if Trump goes through with the tariffs on Chinese produced goods (https://www.reuters.com/article/us-usa-trump-china/trump-eyes-tariffs-on-up-to-60-billion-chinese-goods-tech-telecoms-apparel-targeted-idUSKCN1GP2X8 ), then we should expect China to deliver a strong response. This tit-for-tat would result in higher price tags for numerous products, which the US economy would not be able to absorb as easily.

While the increased prices would be transitory, the immediate and short-term effect would be higher inflation, thus higher bond yields. The size and scope of the price increase would determine the increase in inflation and the decline in demand for finished goods (i.e. slower growth). While this would initially be a poor environment to be invested in TLT, relative to the S&P 500, TLT would outperform.

One thing to keep in mind with Trump is that his bark tends to be worse than his bite. For example, when the steel and aluminum tariffs were first announced, the tariffs were going to be placed on every country, allies and enemies. A few days later during the signing ceremony, this changed to having numerous carve outs for allies that were willing to sit down and discuss the issues at hand. By the way, nations don’t like forced negotiations.

My thought is that he will once again have numerous carve outs once he realizes the number of products that are designed in the US by US companies but manufactured in China. The iPhone would be an example of this and is probably why Tim Cook (Apple CEO) was in D.C. this week having dinner with Ivanka Trump and Jared Kushner. I believe that this is what the market expects as well, which should result in a muted effect for bond yields when announced.

However, if we have an escalating trade war then I would expect yields to spike initially before eventually declining as global growth slows. A well-known reference for this is 1930 with the Smoot-Hawley Tariff Act, which resulted in yields initially spiking around the time of passage before declining as growth slowed.

Source: Bank of America, Merrill Lynch

Source: Bank of America, Merrill Lynch

Summary

While the arguments against TLT are compelling, my overall view of the global economy slowing swings the case to recommending an investment in TLT for those investors with a multi-year investment horizon on an absolute return basis and relative to the S&P 500.

Update on Stress in the Market

Two weeks ago I described how I analyze stress in the market (https://wp.me/p9vaFZ-3z). Based upon previous periods, Friday, March 2nd was not the end of the market stress we have witnessed over the past month. In this post I’ll make the case for my analysis by:

  • Analyzing characteristics in recent times of stress (2015 and 2016)
  • Comparing the previous periods to what occurred on Friday, March 2nd
  • Current outlook and expectation

The move in the VIX spread continues to tell me that we have not transitioned from the turbulent times of the past month. Also, the recent lack of improvement in the spreads leads me to believe we have more risk ahead of us.

Analyzing Recent Times of Stress (2015 and 2016)

When comparing previous moves in the spread during times of stress, March 2nd was not the bottom for the market.

When looking at what occurred from August – September 2015, the move on Monday, September 28th was a large move to the downside (i.e. a move with conviction). A move like this is typically associated with margin calls (i.e. forced sellers), which leads to a “flush” of the market to the downside and then a fast recovery higher.

S&P 500 (yellow), VIX Contract X 15 – VIX Contract V 15 (white)
Source: Bloomberg

A similar type of move can be seen in February 2016. In this time period we had a change in the front month contract, which complicates historical analysis. Also, by not having intraday data on the chart, it doesn’t show that at the worst point of February 15th, the market was down ~2.5% from the close on February 14th.

S&P 500 (yellow), VIX Contract G 16 – VIX Contract F 16 (white), VIX Contract H 16 – VIX Contract G 16 (white)
Source: Bloomberg

When there is a change in the contracts, as with 2016, it truly shows how important it is to analyze the individual contracts during times of increased stress instead of relying on continuous, or generic, contracts.

S&P 500 (yellow), Generic 2nd Month Contract (UX2) – Generic 1st Month Contract (UX1) (white)
Source: Bloomberg

Comparing the Previous Periods to What Occurred on Friday, March 2nd

When I compare 2015 and 2016 to what occurred on Friday, March 2nd, I see an orderly move lower in the spreads compared to the “flush” in the previous periods.

The first chart shows the 2nd month minus the 1st month ending on March 2nd. The move that began five days earlier descended in a linear fashion, which is not indicative of a “flush” or forced selling.

S&P 500 (yellow), VIX Contract J8 – VIX Contract H8 (white)
Source: Bloomberg

The same decline can be seen on the next chart showing the 3rd contract minus the 2nd contract.

S&P 500 (yellow), VIX Contract K8 – VIX Contract J8 (white)
Source: Bloomberg

To summarize, the lack of the “flush” last Friday has me believe that we have yet to see the bottom in the spreads, and the market, for the near term.

Current Outlook and Expectation

When looking at the charts of the spreads, we are once again seeing them stagnant, which is a concern. The concern is heightened because we have peaked at a lower high while still in backwardation.

S&P 500 (yellow), VIX Contract J8 – VIX Contract H8 (white)
Source: Bloomberg

S&P 500 (yellow), VIX Contract K8 – VIX Contract J8 (white)
Source: Bloomberg

As shown in the February post “Update on Macro and Markets” (https://wp.me/p9vaFZ-2T), we know volatility tends to first pick up when there is a change in market leadership (i.e. cyclical to defensive). Knowing this, I continue to closely watch the Euro and Oil.

It seemed that during the first bout of volatility, market participants began to question their positions since they are no longer making new highs.

EUR/USD (white), Oil (yellow)
Source: Bloomberg

However, positioning has only declined slightly. Therefore, these are still very crowded trades.

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

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

In order for the market to complete the change in leadership from cyclical to defensive, the positioning in these trades will need to change.

Whether it occurs in the next bout of market stress or the one after that, I can’t be sure. However, with global manufacturing declining for the second consecutive month, it seems that we are getting closer to this occurring.

Source: Markit, JPM

Measuring the Level of Stress in the Market

According to WedMD, there are two types of stress:

  • Acute (temporary) stress, which your body recovers from quickly
  • Chronic (long term) stress, which can lead to serious health problems

Applying this rational to market declines:

  • Acute stress: no recession is imminent and the market should recover its losses
  • Chronic stress: recession risk is high and a large decline in equities is expected

Currently, the market is going through a higher level of acute stress. Please note, I do mean, “going through” because the market has not yet exited this period of increased stress.

In this post:

  • Process for measuring the level of stress in the market
  • Historical analysis of the VIX spread
  • The current level of stress in the market
  • Longer term expectation of volatility

Process for Measuring the Level of Stress in the Market

I measure the amount of stress in the market by analyzing the VIX futures curve, specifically the 1st and 2nd month contracts. On Bloomberg, these would be UX1 and UX2 for the generic (continuous) contracts.

Looking at the chart below, I would use the following checklist to analyze the spread between UX2 and UX1:

UX2-UX1 (white), S&P 500 (yellow)

Source: Bloomberg

ISM Manufacturing

Source: Bloomberg

Historical Analysis of the VIX Spread

The following is a brief description of what has occurred since the VIX futures began trading in 2004.

Keep in mind, when bouts of stress appear in the market, the periods of high stress have occurred after ISM has peaked and is declining. There are occurrences of low stress periods when ISM is increasing but the market tends to absorb these incidents easier. I don’t show nor discuss the direction of ISM in the following analysis so please reference the previous chart.

March 2004 – January 2006

After a volatile start to trading, the spread peaked in August and gradually decreased until reaching backwardation in March 2005.

The spread recovered until July 2005 when it began to decline once more until October 2005. October was also the first time we saw a retest in the lows of the spread a few weeks later, which we typically see in higher stress periods.


Source: Bloomberg

December 2005 – January 2008

After peaking in December, spreads declined until reaching a low of -2.00 before retesting the lows of the spread eights weeks later. This marked the first high stress period for the market during the decline of ISM.

After recovering, the spread decreased for another ten months before falling to -4.00. The spikes in the spread seen in September and October 2007 are examples of the problem associated with only using continuous futures in high stress periods. More on this later.


Source: Bloomberg

January 2007 – October 2008

After recovering from August 2007, the spread stayed at or near 0.00 until March 2008. The higher lows seen in January and March 2008 and again in July 2008 showed that the market was beginning to heal despite the S&P making new lows. However, this all changed September 2008 with Lehman Brothers.


Source: Bloomberg

October 2008 – January 2010

After seeing the large decline in the spread in October 2008, the stress in the market slowly began to dissipate and grind its way out of backwardation. If an investor was only looking at the price of the S&P, they would have missed the healing process the market was undertaking.


Source: Bloomberg

January 2010 – January 2012

Exiting the recession, we had a short-term scare with the spread declining to -1.00 before seeing a much larger decline in 2011 associated with the US Debt Ceiling Crisis and the European Banking Crisis.


Source: Bloomberg

November 2011 – January 2014

This time frame had little to no stress, similar to what the market went through from February 2016 until January 2018. The area circled is the Taper Tantrum.


Source: Bloomberg

July 2013 – June 2015

This time frame showed more stress in the spread than the previous period but again, nothing strenuous. October 2014 was the US Treasury Flash Crash, which took place only a few weeks after Mario Draghi announced that the ECB was going to begin Quantitative Easing (QE). Additionally, we had the Russian Ruble Crisis peak January 2015.


Source: Bloomberg

March 2015 – May 2017

The spread gradually moved lower from the March highs before seeing a tremendous drop after China devalued the Yuan. A few months later, we had another decline in the spread when there was a growing concern about the stability of the European Banks. Finally, the decline in June 2016 was when the UK voted to leave the EU.

An important note is that each decline in the spread was not as low as the previous (i.e. Aug ’15 > Sept ’15 > Jan ’16 > June ’16 > Nov ‘16) and ISM bottomed in January 2016. Meaning, the market and economy was gaining strength and was able to absorb the new concerns easier than previously.


Source: Bloomberg

December 2015 – February 2018

The spread increased from the August 2015 lows and eventually peaked in July 2016 after the UK vote. After peaking, we saw the spread slowly decline and face little to no stress for the next 18 months, which is similar to what we saw after the European Banking Crisis in 2011.


Source: Bloomberg

Current Level of Stress in the Market

Following the continuous (generic) futures contracts can be good when looking for a general idea of stress in the market.

As noted previously, there are problems with only using the continuous futures. First, there can be sudden spikes in the data as Bloomberg transitions from one set of contracts to the next. Second, when we are in stressful periods, like we are now, it is best to look at the specific contracts for “healing points”.

To solve this issue, during periods of concern or stress I look at the two nearest spreads so I can see how the current and upcoming spread is developing.

The next chart shows the current 2nd month contract (UXJ8) minus the current 1st month contract (UXH8). The immediate short term healing point that needs to be exceeded is 0.20. More importantly, the longer term healing point is 0.60.

UXJ8 – UXH8
Source: Bloomberg

The next chart is the current 3rd month contract (UXK8) minus the current 2nd month contract (UXJ8). The immediate short term healing point is 0.15 and the longer term healing point is 0.60.

UXK8 – UXJ8 

Source: Bloomberg

Based upon prior periods that had the spread decline to -2.00 along with no recession (i.e. 2006, 2011, 2015), we will not pass 0.60 without retesting the lows of the spread. During these previous periods, we saw 3-4 weeks of calm from the lows before the market began to succumb to the sustained level of stress in the market. Meaning, the probability of a short-term market peak is increasing since the spread bottomed February 5th.

Longer Term Expectation of Volatility

When ISM peaked in the past, we tended to see bouts of high stress every 8-12 months. Between these periods of high stress, volatility declined back to low levels and the spread would increase to 1.00 or higher.

The only way we will see high stress remain constant is if we are heading into a recession, which I don’t foresee at this time.

Therefore, my base case is the first scenario since ISM peaked in September 2017. Updates on the volatility spread will be discussed in future posts since this has become a relevant topic once more.

My Framework Using Everyday Analogies

I started this blog as a way to help the layperson understand macro and how it drives equities. In another attempt to accomplish this, below are four analogies for my basic framework:

  • The Global Economy
  • Access to Credit (Debt)
  • Credit (Debt) and Spending Increasing/Decreasing
  • Global Manufacturing

 

The Global Economy

Think of the global economy as a NBA basketball team:

  • China is the star player that helps make everyone else rise to a higher level of performance. When China is on a roll you have one of the best teams in the league.
  • The US is the strong #2 player that every team wants because of its stability and consistency. If China goes down then your team might make the playoffs but there’s no expectation of winning a championship.
  • Europe, Japan, and the Emerging Markets are your other 3 starting players. Good roll players but they are lost without China and US. If your team is relying on them to win because China and the US are injured, the only thing you’ll be winning is the #1 draft pick

Access to Credit (Debt)

Think about access to credit as driving on the interstate:

  • When banks are loosening credit standards, there are no accidents, no road construction, no crazy drivers. Traffic (i.e. the economy) is moving and things are good.
  • When banks tightening credit standards, think of it as 1 lane being closed on a 3 lane interstate. Traffic (i.e. the economy) is still moving but much slower than it should.
  • When banks are continuing to tighten credit standards and we’re heading into a recession, it’s like 2 lanes of a 3 lane interstate being closed. Traffic (i.e. the economy) is barely moving and it feels like you’ll never get home.

Credit (Debt) and Spending Increasing/Decreasing

When debt levels are increasing, spending tends to increase, which is good for the economy because there is more risk taking. Think of it like partying back in college:

  • The beginning of the party starts off slow (i.e. economy coming out of a recession and spending is slowing starting to increase)
  • Around midnight things were getting good (i.e. economy is doing well but still room for improvement)
  • Around 2am you’re partying like a rock star (i.e. the economy is running full steam, full employment, and people are saving very little because they have the outlook that things will permanently be good).

However, when debt levels are decreasing, spending tends to slow, which isn’t good for the economy as people begin to take less risk. This would be like the day after the party. You feel like crap, you have to clean up the mess from the night before, and you think to yourself that you’ll never party like that again. (i.e. the economy and the market has to reset to a lower level of spending and figure out how to deal with the excess debt).

Global Manufacturing

Global manufacturing tends to lead all of these because (taken from my first Framework post):

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.

 

Update on Macro and Markets

Global growth continues to show signs of slowing and the recent market behavior is confirming this view.

In this post, I reexamine previous discussions:

  • Macro – Global Growth, Credit Standards, China
  • Markets – Change in Market Leadership, Positioning, Outlook

Over the next few weeks, we should see:

  • The move to defensives outperforming cyclicals completed
  • USD appreciating against other currencies
  • The 30yr treasury yield declining with the lowered expectation of global growth

Typically when we see this process completed, we have another bout of increased volatility in the market. Meaning, the rebound in the market since Friday afternoon should not be looked at as a new long-term trend to higher equity prices at this time.

Global Growth has Peaked

As discussed previously (https://wp.me/p9vaFZ-20 ), ISM peaked a few months ago (Sept ’17). However, other global manufacturing surveys continued to rise until this past month.

ISM Manufacturing
Source: Bloomberg

Eurozone PMI

Australia PMI

Source: Markit

Brazil PMI

Confirming that global growth has peaked are the “real time” indicators that are correlated to manufacturing.

Copper/Gold (white), ISM (Yellow)

Source: Bloomberg

AUD/JPY (Australian Dollar/Japanese Yen) (white), ISM (Yellow)

Source: Bloomberg

Central Bank Surveys

Currently, the Central Bank lending surveys are not showing any signs of tightening.

In the US, credit cards actually saw their standards loosen…


Source: St. Louis Federal Reserve

…which is a good thing because the US consumer is saving very little. As a consumer driven economy, the US needs the consumer to increase their spending for it to grow.


Source: St. Louis Federal Reserve

As discussed previously ( https://wp.me/p9vaFZ-1H ), the expectation is for the balance sheet of the US consumer to weaken and real wages to decline.

However, many are expecting the US tax reform bill to increase wages. Only time will tell but Street Account did note on January 26th that:

Many executives and analysts have said in recent weeks that much of the benefit will go to dividends and buybacks. There has also been a focus on bonuses vs. pay increases. More companies have offered bonuses but are hesitant to increase pay, as higher salaries compound over time and increase a company’s costs.

Turning to US business loans, we continue to see these standards loosening as well…


Source: St. Louis Federal Reserve

…but businesses are not increasing their demand for credit. Maybe the US tax reform bill will change this behavior but if we see a decline in the growth rate along with a weakening consumer, it makes it very difficult for the business cycle to continue.


Source: St. Louis Federal Reserve

Finally, Japan looks similar to the previous data point. No update from the ECB at this time.

Japanese Lending Survey to Small and Medium Sized Businesses

Source: Bloomberg

China Still Slowing

Something that continues to receive little to no dialog is the fact that China is slowing. As discussed a few weeks ago (https://wp.me/p9vaFZ-2w ), China is the global growth driver so if they are slowing, the world is slowing.

Inflation data released on February 8th showed a decline in the costs of goods for consumers and producers. If this is occurring in China, who is the world’s largest user of commodities and has seen a large increase in wages, then the inflation scare debated by the media is transitory. Even if the data is “altered”, the general trend over the past few months has been lower.



Source: ISI

I previously mentioned that China said they are not going to be as restrictive on reducing debt as previous discussed.

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

However, China saw another decrease in new loans generated. Looking at loan growth on a year over year, six month average shows the continued slowdown in credit generation. Similar to the inflation data, regardless of if the data has been “altered”, the trend is lower, which isn’t good for growth.

China Total Social Financing (Y/Y, 6 month average)

Source: Bloomberg

Once a new loan is issued, it takes approximately six months for it to affect the economy. I still have the thesis that growth will pick up in the second half of 2018, led by China and the Emerging Markets. However, for this to occur, we’re going to have to see a change in the trend of the data very soon.

Finally, comments printed in the China Daily on February 10th have the potential to aid in the Chinese recovery and support the next phase of this business cycle.

Steven Zhang, chief economist at Morgan Stanley Huaxin Securities, said Chinese policymakers will likely lessen the pushing of financial deleveraging to cope with external shocks and to prevent short-term financial risks amid rising volatility in the stock market.

https://www.chinadailyhk.com/articles/164/2/26/1518247515915.html

Change in Market Leadership

The market leadership continues to transition. The cyclical industries and sectors are no long making new highs against the S&P 500 and vise versa for the defensives.

Here are a few examples:

ISM (yellow), Industrials vs S&P 500 (white)

Source: Bloomberg

ISM (yellow), Semiconductors (SOX Index) vs S&P 500 (white)

Source: Bloomberg

ISM (yellow), Small Caps (Russell 2000) vs Large Caps (S&P 500) (white)

Source: Bloomberg

ISM (yellow), Emerging Markets vs Developed Markets ex-US (white)

Source: Bloomberg

ISM (inversed – yellow), Consumer Staples vs S&P 500 (white)

Source: Bloomberg

ISM (inversed – yellow), Utilities vs S&P 500 (white)

Source: Bloomberg

Another way to look at this transition is by analyzing Industrials vs Staples. We see once again, that this ratio tends to directionally move with ISM.

ISM (yellow), Industrials vs Staples (white)

Source: Bloomberg

More importantly, when a change in leadership takes place, volatility should be expected to increase like we saw last week.

ISM (yellow), Industrials vs Staples (white), VIX (green)

Source: Bloomberg

Market Positioning and Outlook

Going into this transition, the market was ill prepared, which is one of the reasons why we saw volatility increase as much as we did. As you can see in the following charts, Speculators (white line) were more long going into last week than they have been at almost any time since 2011.

S&P 500 Commitment of Traders (COT)

Source: freecotdata.com (@movement_cap)

WTI Oil (COT)

Source: freecotdata.com (@movement_cap)

EUR/USD (COT)

Source: freecotdata.com (@movement_cap)

When you look at these three items and add in Emerging Markets, you can see that they have all moved from the lower left to the upper right since January 2016, which is when ISM bottomed (not shown). In other words, as the global economy improved and volatility declined, they have all moved higher together (i.e. they are all the same trade). Therefore, as the global economy slows and volatility increases, it should be expected that these items should all move lower until global growth returns.

S&P 500 (white), Emerging Markets (yellow), EUR/USD (green), Oil (purple)

Source: Bloomberg

Finally, when we saw weakness in the S&P 500 and Oil last week, we didn’t see the same reaction in the Euro. Meaning, this shoe has yet to drop. The other area of the market that didn’t react was the US 30yr Treasury Yield. I expect both of these to decline shortly after the Chinese financial market reopens (Chinese New Year: Feb 15th – Feb 21st). When this transition occurs, we should see another period of high volatility in the market.

Going into the holiday, the PBOC has historically wanted to portray a strong economy by having high stable yields and a strong currency. Recently, we’ve seen China’s 1yr yield drop but the 5yr and SHIBOR have remained stable.

China 5yr yield (white), 1yr yield (yellow), SHIBOR (green)

Source: Bloomberg

Additionally, we’ve seen the CNY move higher over the past few months despite the Chinese 5yr remaining flat and the difference between the Chinese 5yr yield and the US 5 yr yield declining.

China 5 yr Yield (yellow), CNY (red), China 5yr – US 5 yr (white)

Source: Bloomberg

Finally, since China is the growth driver of the world and the US 30yr is highly sensitive to growth, China’s 5yr and the US 30yr should remain correlated to the downside.

China 5 yr Yield (white), US 30 yr Yield (yellow)

Source: Bloomberg

Analyzing the Strength of the Chinese Economy & the Interactions of the PBOC

Over the past few years, there have been three things that I have learned when analyzing the strength of the Chinese economy and the interaction of the PBOC:

  • The data reported by China and the PBOC (i.e. GDP, retail sales, manufacturing surveys, short term funding, loan growth) should not be relied upon.
  • Data points in the market (i.e. interest rates and implied volatility of the currency) and export data of close trading partners of China are the most reliable indicators.
  • All market data points must be analyzed together to avoid false positives and negatives.

These market based data points shows that China is beginning to slow. Therefore, the manufacturing and sentiment surveys at multi-decade highs around the world are not sustainable, something the market is not pricing in at this time based upon the Sectors and Industries currently leading the market.

Questionable Data Reported by China and the PBOC

There have always been questions regarding the data being reported by China and the PBOC whether it is GDP, retail sales, the value of the PBOC’s reserves, etc. It is enough of an issue that it can be reasonable to question any data being reported by the Chinese.

I thought that loan growth and short-term liquidity was still a good data point to watch. However, I began to question these a few months ago. Apparently Citi published a note the first week of January questioning this as well.

I would also question the accuracy of the manufacturing surveys for China. The reason is simple, if the Chinese want to portray a strong economy in the data being reported, it is likely that they are telling the companies surveyed to give answers depicting an improving or strong outlook.

In other words, if the Chinese reports it then I tend to ignore it.

Rates and the Currency

When China’s interest rates are rising, an appreciating currency (CNY) should be expected since higher rates portray an improving and/or strong economy.

China 5 year Yield (white), CNY (yellow)

Source: Bloomberg

However, as quoted in a December 14, 2017 South China Morning Post (SCMP) article, the PBOC is more focused on the interest rate difference between China and the US when pricing the CNY against the USD.

Former PBOC economist Ma Jun said China’s move on Thursday was symbolic rather than a serious step to raise rates.

“It sends a message to the international market that China cares about monetary policy coordination and stabilizing the interest rate gap between China and the US,” Xinhua quoted Ma as saying.

The 5 basis points increase also “sends a warning to overseas speculators who are trying to short the yuan” because it showed the PBOC could act to discourage capital outflows, he said.

http://www.scmp.com/news/china/economy/article/2124254/china-raises-interbank-policy-rate-after-fed-hike

When looking at the difference, or the spread, between the Chinese and US 5yr and 10 yr yields, we see a strong correlation with the CNY.

China 5yr Yield – US 5yr Yield (white), CNY (yellow)

Source: Bloomberg

China 10yr Yield – US 10yr Yield (white), CNY (yellow)

Source: Bloomberg

However, we know that by looking at other currencies, and using the EUR as an example, this correlation breaks down frequently and is never this precise.

EUR (white), German 10yr – US 10yr (yellow)

Source: Bloomberg

Lastly, when comparing the chart of the China – US spread to the chart of the China’s 5yr yield, the spread tends to decline approximately three months prior to the absolute interest rate declining. Currently, the spread peaked in December.

Export Data of China’s Trading Partners

To solve the issue of questionable data being reported by the Chinese and PBOC, I look at the export data for three of China’s trading partners that have a large percentage of exports going to China. This gives me a broad view of what demand is like within the Chinese economy. Those countries are:

  • Australia: China receives 36.1% of all exports

  • South Korea: 26.1%

  • Brazil: 19.0%

When analyzing all three countries together, we find that they all have similar peaks and bottoms:

  • Bottomed 2009
  • Peaked 2011
  • Bottomed 2012
  • Peaked 2014
  • Bottomed 2016
  • Peaked 2017

Comparing this information to the charts showing the China – US spread, this is very similar including the recent decline in both the export data and the peak in the spread.

A better way to look at the export data is on a year over year basis with a 3-month average to see how it is changing. Comparing the export data to China’s 5yr yield and ISM shows that starting in 2014, ISM became less correlated to the turning points in the export data. Currently, we see the export data declining but the 5yr has been relatively steady since it hasn’t exceeded the November highs nor dipped below the December lows.

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

Finally, China is the largest global manufacturer at $3.2 Trillion while the US and the Eurozone are significantly smaller at $2.0-2.2 Trillion. As the leader in global manufacturing and the market share leader in most industrial commodities, if exports of China’s closest trading partners are slowing, then we should expect numerous others items to begin to slow and decline as well.

PBOC Controlling the CNY

From 2014-2016, we know the PBOC was in the currency market trying to prevent the CNY from depreciating too much against the USD. This interaction shows up in the Implied Volatility of the CNH (offshore CNY).

CNY (yellow), Implied Volatility (white)

Source: Bloomberg

As we’ve seen multiple times, the PBOC is only able to restrict the movement of the CNY so much. Eventually, the economy and the market are too great for the PBOC to withstand, leading to the CNY depreciating against the USD.

The reason why I didn’t draw a trend line beginning in December 2016 is because this is when the China – US spread and China’s 5yr yield bottomed. Therefore, the CNY should have been expected to appreciate as the economy improved so any interaction by the PBOC should have been limited.

Ultimately, when interest rates are declining and the CNY is depreciating, the implied volatility of the CNH becomes an important factor to consider but not when the CNY is appreciating.

Rates and Access to Credit

The PBOC, like other central banks, controls the shorter-term rates such as SHIBOR. Traditionally, when the direction of interest rates changes, the shorter-term rates move a greater amount than the longer-term rates.

China 5yr yield (yellow), China 1yr yield (white), SHIBOR (green)

Source: Bloomberg

China tends to have a very flat yield curve relative to other markets like the US. However, the differences between the 5yr yield and the 1yr yield can, in my view, give you insight into what is going on in the Chinese financial system:

  • Under 0.25: Tight lending environment
  • 25 – 0.50: Normal lending environment
  • 50 – 1.00: Stressed environment and the PBOC is trying to stimulate
  • Above 1.00: Extremely stressed environment and the PBOC is aggressively trying to stimulate

China 5yr – China 1yr (white)

Source: Bloomberg

Since 2013, the PBOC has only been able to tighten twice before financial stress increased too much, which resulted in them lowering rates to help stimulate their economy. This time, they’ve been able to do it three times (Dec ’16, June ’17, and Dec ’17).

The key thing to remember is to put the complete picture together. When this is done, it makes sense that the PBOC has been able to tighten three times because the 5yr yield continues to rise (i.e. an improving and/or strong Chinese economy).

Thinking of seasonality, which is important to keep in mind, the PBOC tends supports the Chinese financial system approximately 3-4 weeks before the Chinese New Year:

  • 2014: Jan 31st
  • 2015: Feb 19th
  • 2016: Feb 8th
  • 2017: Jan 28th
  • 2018: Feb 16th

This year, the access to credit began to loosen a few weeks earlier but it goes with what was mentioned in mid-December:

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

Summary and Current Outlook

When it comes to analyzing the Chinese economy and the interactions of the PBOC, here are the items that I consider:

  1. Is the difference between the China 5yr and the US 5yr increasing or decreasing?
  2. Is the export data for China’s closest trading partners increasing or decreasing?
  3. Is China’s 5yr yield heading higher or lower?
  4. Is the Implied Volatility of the CNH declining?
  5. Is the spread of the 5yr and 1yr yields above 1.0?

If #1 and #2 are increasing, then I would expect an improving Chinese economy. #3 should be increasing as well along with an appreciating CNY.

If #1 and #2 are decreasing, then I would expect a slowing Chinese economy. This is the situation we currently find ourselves in.

With #3, the 5yr yield is currently stable so I would not expect the CNY to depreciate against the USD at this time. If the 5yr yield moves below the December low, then the probability of interest rates declining in China increases, which means the CNY should begin to depreciate against the USD. This move would be confirmed by a move below the January lows by the 1yr yield and SHIBOR.

China 5yr yield (white), China 1yr yield (yellow), SHIBOR (green)

Source: Bloomberg

Since the Chinese New Year is three weeks away, I would expect the PBOC to try to maintain higher interest rates to give the impression that the Chinese economy is strong. If they are unable to, then we should expect the PBOC to try to maintain a stable CNY, like they have historically going into the Chinese New Year.

After the holiday is over, and if #1 and #2 have not changed, then I would expect China’s 5yr yield to begin to decline and the CNY to depreciate as well.

Once the 5yr declines, I would move to #4 to see how much the PBOC is trying to control the CNY. If implied volatility is declining, then the PBOC is attempting to control the CNY.

If #5 is confirmed AND implied volatility is declining AND China’s 5yr yield is declining AND exports of close trading partners are declining AND the spread of the China – US 5yr is declining, then the probability of the PBOC devaluing the CNY increases.

Like I’ve stated previously, I expect China and the Emerging Markets to lead the next phase of growth six to nine months from now. For this to occur, the first three items listed have to be supportive of an improving Chinese economy.

In the near term, once #3 is confirmed, we should see the US 30yr yield begin to decline as global growth slows, which would be one more step in the market rotating sector leadership from the cyclical sectors and industries to the more defensive ( https://wp.me/p9vaFZ-20 ).

China 5yr yield (white), US 30yr yield (yellow)

Source: Bloomberg