Milestones in Market Mania

“Watching neighbors get rich at the end of a bubble while you sit it out is pure torture”. Jeremy Grantham

Why be masochistic and sit out one of the greatest bull markets in history? If you have clear guidelines: milestones based on other bubbles such as stock markets in the 1920s and 1980s, then you can profit from both the bubble inflation and when it bursts. Like then, current stock market valuations are not sustainable. But, even with the anticipated Trump inspired increase in inflation, that doesn’t stop valuations going much higher before much lower. That is the nature of a bubble.

George Soros: “When Alan Greenspan spoke about irrational exuberance in the 1996, he misrepresented bubbles. When I see a bubble forming I rush into buy, adding fuel to the fire. That is not irrational”

In the week that the DJIA uptrend matched the 2,002-day equally irrational uptrend of 1929, we outline what we believe are the key milestones to this blowout before a crash. We had originally planned just one article highlighting these milestones based on our core FITS approach to any market: Fundamentals, Intermarket relationships, Technical and Sentiment. However, the more we investigated historical and theoretical milestones the more we found a wealth of further evidence: invaluable information that should stand us in good stead in the latter stages of this 7 year bull market. This should provides us with a much clearer idea of how to exploit the remaining stock rally and ensuing crash. After all, Paul Tudor Jones made his fortune and name on this very play in the 1987 US stock market based on a similar approach. But Trumpflation is also dominating other global markets to a varying extent. This not only provides further clues on how to trade this last phase of the US stock rally. But a similar effect on other markets in other stock bubbles should help us trade those other markets more effectively as well.

Today we outline the research that is guiding us, and a further six articles based on bubbles and in particular a comparison with 1929 and 1987. These will focus on each of the FITS that drives our analysis and the Volatility and Clarity (probability) that frames our trading strategies.

Trump Mania (or 2010s Bubble)

There can be little doubt that, as it stands, Donald Trump is helping to create a stock market bubble. Promises of ‘phenomenal’ tax cuts and fiscal expansion funded presumably by greater government debt in the near term has fueled expectations of inflationary growth (Trumpflation). History shows that the consequent triangle of rising interest rates, stocks and the US Dollar higher is typical in the last phase of a major stock uptrend and is therefore not sustainable in the medium term. The last time a Republican President had a Republican majority in both Houses of 2000 witnessed a smaller rally and reversal.

2000 Triangle of Rising Yields, Stocks and Dollar

US stocks, as measured by actual and inflation adjusted price earnings ratios, are reaching dangerous and unsustainable levels by historical standards.


Is this bubble ready to burst? To avoid a major reversal PE ratios can, of course, come down on higher earnings. The last time a Republican President embarked on aggressive fiscal expansion was in 1953 when Eisenhower spent $26bn on a new interstate road network. But the resulting stock rally, from levels we haven’t seen since, started from a much lower PE level depressed by the Second World War. In other words, this time really is different.

What is a Bubble?

The term bubble originates from the term applied to the companies involved in the 1711–1720 South Sea Bubble. Their stock prices became so inflated based on nothing but air that they became fragile and burst.

Bubbles are defined as a situation where the price for an asset exceeds its fundamental or intrinsic value by a large margin and, by implication, produce a pronounced and unsustainable market rise ( Perhaps the most striking example of a mispriced asset bubble was Tulipmania in the 17th century when even the most intelligent of men, Sir Isaac Newton, lost a fortune.

Tulipmania lasted six months. We are now in the eighth year of the DJIA uptrend.

The definition of a bubble begs important topical questions about the difference between the nominal and real (adjusted for inflation) price of an asset, its fundamental value (as the discounted value of future expected earnings), the scale of the margin and, notably by its omission, the length of time this margin can persist. Robert Shiller perhaps defined a bubble best: “It refers to a period of enthusiastic bidding up of prices by a growing group of enthusiastic investors that goes on too long and is carried away by its own momentum.”

Many column inches are written every day about each of the component parts of the current bubble. But few address how they interact to create a bull market like the one we are enjoying. Much of the work on bubbles centers around changes in sentiment that accompanies the blowout to the upside before an inevitable reversion to mean. The reason is simple: there is a disconnection between the market and the real world. George Soros: “Every bubble has two components: an underlying trend that prevails in reality and a misconception relating to that trend”.


DJIA and Classic Bubble Theory.

Many of the theories of bubbles stem from analysis of the 1929 bull market and crash. Milton Friedman attributed the 1920s boom and bust to US monetary policy. But Kindleberg believed it was a result of  “a complex systematic set of causes, international in scope and partly monetary or at least financial”. It is this recognition of a varying set of causes that underlies our approach at Matrix. In Manias, Panics and Crashes Kindelberger identified five phases of a bubble inspired heavily by the economist Hyman Minsk whose theories and Minksy Moment gained notoriety as prices collapsed in the sub-prime crisis.

Displacement: All bubbles start with a real cause. Sometimes it is a fundamental change in the economy or government policy (eg QE in 2009) a new technology (eg cars and planes in the 1920s, the internet in the bubble). This change often excites everyone but it tends to be only smart investors who invest at this early stage.

Boom: Shortly after a bubble starts, a compelling narrative gains traction and becomes self-reinforcing. One of the drivers of any bubble is liquidity normally through loose credit and lending. The housing boom in the 2000s was fueled by sub prime lending.

Euphoria: The euphoria phase is characterized by people’s awareness and desire to participate in the boom. The level of involvement increases significantly. In the 1920s shoeshine boys were buying stocks. At the peak of the tech bubble, Internet stocks changed hands three times as quickly as other shares. This buying phase tends be steep yet so brief that many are rushed into trading larger amounts more quickly.

Crisis: In the crisis phase, the earlier investors or traders start to sell while the late retail investors increase their leverage. This often causes a liquidity problem as the market reverses and the decline gathers momentum as people sell at any price.

Revulsion: In almost a mirror image of the climax of the prior uptrend, falling prices become exaggerated and out of line with their fundamental values. As value investors stay out prices can fall to irrationally low levels.

The theory behind bubbles remains remarkably under-developed given their significance and potential damage to the global economy.

Some of this neglect was once a hangover of the mathematical orthodoxy that stated exorbitant rises that precede crashes are random – circumventing any further meaningful analysis. This more obvious conclusion of chaos theory was rightly challenged by the likes of the late Benoit Mandelbrot in his The Misbehavior of Markets. These bubbles are far more common than log normal distribution would suggest. The existence of highly apparent probable causes such as loose house lending into 2008 belies this bell curve orthodoxy. The ability to identify causes does place greater responsibility on the financial institutions that tend to exaggerate them and policy makers that could arguably prevent or alleviate them. But it is complexity rather than complacency that hinders the prevention of bubbles or our understanding of them. Taleb’s Black Swans or outliers are hard to nail down precisely due to the black box nature of causes and effects. We all know sub-prime triggered the 2009 meltdown but such wisdom is easy in hindsight and doesn’t account for the extent or nature of the subsequent fallout.

George Soros took the complex nature of cause and effect within bubbles one step further in his Theory of Reflexivity and the self-reinforcing effect of market sentiment: A bull market will attract buyers whose actions drive prices higher still until the process becomes unsustainable – a positive feedback loop.

This is reflected in his 7 stages of Boom and Bust, an adaptation of the Kindleberger Minsky Model.

At Matrix we attempt to embrace this complexity and reflexivity by assessing the variable FITS causes, how that manifests itself in price and whether that can be accurately compared to another time in history. If it is not possible to identify the exact relationship between self-reinforcing causes and effects, we can at least look at similar set ups. We open that black box and try to identify the wiring that will create a similar effect to one that has happened before. Anyone who recognizes our logo as the Sierpinski triangle may appreciate that out of chaos order can still be found.

Application – If it FITS trade it!

Many have called for a premature top and crash in the stock market since 2011 partly due to the inability to grasp the true nature of market volatility. Because of the clear similarity of the uptrend since 2009 to the 1921-1929 and 1980-1987 bull markets we have and hope to continue avoiding this fate.

The Current Bull Market compared to the 1920s

The Current Bull Market compared to the 1980s

One reason we have been able to stay with this uptrend is that is none of the FITS criteria have fitted with a top.


George Soros again:

“Financial markets.. always provide a distorted view of reality. When there is a significant divergence between market prices and the underlying reality, there is a lack of equilibrium conditions.”

According to the textbook, the final leg of an uptrend often sees prices advance without the fundamentals. And yet the same textbook will tell you prices often turn first. The reality is frequently in between. The rate of improvement in the underlying asset or some component parts (such as market sectors) frequently fall in the final leg higher. But it is only as these leading sectors accelerate their decline that the main markets turn. House prices in several US cities had already turned lower before the actual 2008 top.

The current US economy has neither deteriorated not overheated yet even though it is getting close to full capacity. But the disparate nature of President Trump’s proposed fiscal expansion could well be sowing the seeds of its own destruction.

Intermarket Relationships: We are blessed in financial markets by the fact markets and sectors often move in sequence rather than simultaneously and often in the same order. This provides an early warning as the final leg is dominated by a break down in correlation and cohesion – something we are seeing markedly already. However it is only as some of the early markets sustain a reversal that it confirms the lack of breadth and sustainability in the main lead market necessary for the top, and that others will soon follow.

Technicals: There are a whole host of technical indicators and formations that perform well at a top but poorly if it isn’t. Technical analysis is after all probabilistic.. However, if all the other conditions are suggesting a reversal is imminent, then their probability of success increases significantly. In isolation and in combination the technicals suggest we are in the final leg, but not yet at a top.

Sentiment: Much of the theory of bubbles centers around the changes in sentiment. And yet sentiment data is arguably the least accurate and most open to misinterpretation. One of the reasons is that the data assumes a finite capacity and yet, for example, the euphoria phase is characterized by a flood of new entrants swelling capacity. This is one reason why people wrongly associate price with the market’s position. However, just like the technicals there are several sentiment indicators that help determine whether the market is near a top or has further to go. The readiness of so many to call a top in the last 3 years was enough alone to suggest it had further to go. Similarly as sentiment in an increasing number of other markets indicate a reversal has already started, the stark contrast with the still extreme bullishness in the main market suggests it will soon follow.

Volatility: (Or distance over time) A major stock trend normally ends with extreme volatility. It is only after Donald Trump was elected President that we have seen the volatility normally associated with the final leg. But we are still a long way off the percentages rise we saw in 1929 or 1987. The uptrend from 2009 has been noticeably slower than either the 1920s and 1980s. We believe one reason for this relative slowness has been the pre-eminent role of VIX (and the lower implied volatility associated with rallies).

Clarity: With clarity comes higher probability. And the more indicators that clearly say the same thing the greater the likelihood they will be right. We previously have had few such indicators telling us DJIA and SPX were anywhere near a top and many saying they had further to go. That has started to change.

At Matrix, like any other trading establishment, we seek volatility and clarity. 2017 has been good so far and looks set to continue.

In the ensuing articles (based on FITS VC) we will identify and apply specific milestones in order to continue with the uptrend into an aggressive top. Only when we are closer to that top will we go through the same process for an even more aggressive reversal.