How To Stay in a Trend and Not Get Treed By a Chihuahua

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The following is an excerpt from a monthly report that goes out to members of our Collective. Some of the details are redacted but my hope is that this report helps you look at trends and dips —  or what we can thorns — in a new light and as a result, you can avoid getting treed by a chihuahua… That’ll make more sense to you in a moment. Enjoy…

 “Well over half the men who started the course with me many weeks earlier were now gone. At the beginning of this, the final test of the course, we were told to pack a rucksack that weighed at least seventy pounds and prepare for a long-distance movement through the Appalachian Mountains. There was no guidance on how long the movement would be or how long we would be given to complete it. For me, Stress Phase started at 2:30 A.M. when, in total darkness, I was dropped on a dirt trail in the middle of the mountains (aka nowhere). A Delta cadre member handed me a piece of paper with map coordinates on it and told me to “Find my way to the next rendezvous point (RV), and take all instructions from the cadre.” And, oh, yeah, “Don’t be late, and don’t be light.”

This is former Delta Force Commander Peter Blaber recounting in his book “My Mission, My Men, and Me” his experience during the Delta Force’s grueling final phase of its selection process, appropriately called the “Stress Phase”.

About 15-hours into the maneuver Blaber was exhausted, near delirious, and not quite sure of his bearing after fighting his way through the thick vine-webbed underbrush of the Appalachian mountains. Needing to orient himself, he decided to make his way up a tree to see if he could spot the ridgeline that located his final rendezvous point. This was a bad idea.

Blaber was so discombobulated he forgot to take off his 70Ib ruck before the climb up. As soon as he reached the top and was about to survey his surroundings, the thin branch supporting him and his gear gave way and Blaber plummeted head over heels to the ground.

He likely would have broken his neck had it not been for the arresting force of the vines that had been tormenting him throughout the mission. This was lucky. Unfortunately… this luck was short-lived. As soon as Blaber finished checking in with himself to make sure he didn’t break any bones, he heard a noise.

I turned like an arthritic old man, head and upper torso as one. With the peripheral vision of one eye, I spotted a tiny black animal scurry out from under my ruck. How cool—a baby bear! Then my spider senses kicked in. Fifty or so feet to my rear, I heard the spastic scream of an enraged animal. It was violently thrashing the vines, and it was getting closer. Turbocharged by a heavy dose of fight-or-flight adrenaline, in one fluid motion I jumped up and bolted. What kind of screwed-up luck is this? Instead of finding my way out of the vines, I wandered into the middle of a black bear’s den—and now I’m gonna get my ass torn apart.

Blaber took off like a banshee out of hell but the sounds of the bear only grew closer. Knowing full well he had zero chance of outrunning a pissed off momma bear, he made a split-second decision. He came upon a cliff that led to a steep slope that ran for a couple hundred feet or so. Running at full bore, he jumped.

It was a magnificent leap, one I could likely never replicate without the motivational stimulus of an angry black bear on my heels. I landed on the slope precisely as I had hoped, at an angle, and feet first. But instead of rolling, my strength-sapped body betrayed me once again. I crumbled like a beanbag and immediately transitioned into a cartwheeling carcass. Arms and legs flailing violently, I rolled end over end. After a couple of hundred feet, I plowed into a medium-sized walnut tree and came to an abrupt stop. Once again, I conducted a quick survey of my limbs. Everything still worked. What about the bear? I wondered while maintaining statuelike stillness.

Using the tree as a pivot, I pushed myself up on my knees and slowly scanned upward toward the edge of the cliff. There, slightly occluded by the bramble bush I had so magnificently launched myself over, was baby and mother searching the hillside for my carcass. As so often happens when you stare and focus directly at another living being, the mother abruptly snapped her head in my direction and locked eyes with mine. To my simultaneous horror and shame, I discovered that she—was a pig!

Not a bear, or even a wild boar, but a freaking pig! Dirty and disgusting, it had likely escaped from a local farm. I had run for my life, and jumped off a cliff, all because I had jumped to the conclusion that my life was endangered by a nonexistent bear.

Blaber had flung himself over a cliff in full kit and cartwheeled for a couple hundred feet because he was getting chased down by a staple of American breakfast. To further salt the wound, he realized he’d also lost his map and flashlight in the tumble.

He was now completely lost, without map or light, as bone-weary as ever, and with just a few hours left to make rendezvous. Failure of which would make the last few months of suffering all for not. And…  he had all of this to thank for his mistaking Mrs. Piggy for an angry black bear.

Fortunately, Blaber made it to his destination by the very skin of his teeth. And he went on to become a decorated Delta Force Commander.

He attributes much of his follow-on success to an important lesson learned that fateful night.  A lesson he now refers to as “Don’t Get Treed By A Chihuahua”.

Blaber writes:

It’s been said that there are no mistakes in life, only lessons. Every mistake is an opportunity to ensure that we never make it again, especially when future consequences can be much more dire. When I saw the little black creature through the corner of my eye, my tired and frustrated mind took a shortcut. I decided it must have been a baby bear with a mother not too far behind. When I heard the spastic scream of the animal in the bushes, I decided it had to be the vicious growl of a mother bear instead of what it actually was—the vicious oink of a mother pig.

My contextless response was to run for my life and jump off a cliff; I got treed by a chihuahua. Getting treed by a chihuahua is a metaphor for making decisions without context. Context is the reality of the situation around us. Without context, our minds have a tendency to take shortcuts and recognize patterns that aren’t really there; we connect the dots without collecting the dots first. Overreacting, underreacting, and failing to do anything at all are all symptoms of “getting treed.”

Investors get treed by purse-sized yappy dogs, day in and day out. They make decisions without effective context before they’ve collected the dots. They mistake pigs for bears, minor dips for major crashes, and market tops for great buying opportunities.

Like Blaber on the final night of Stress Phase, they make biased decisions from points of emotion such as fear and greed. As a result, they have a tendency to recognize patterns that aren’t really there.

This is a function of our cognitive wiring.

The brain is an amazing piece of hardware. It is comprised of roughly 90 billion nerve cells which are linked together by trillions of synapses. It is estimated that the human brain operates at approximately 1 exaFLOP. That’s equivalent to a billion-billion calculations per second, multiples faster than what the largest supercomputer can accomplish over any meaningful period of time.

But all this processing power takes up a lot of energy — a bit over 20% of the body’s total usage — making it by far the most energy-intensive organ.

Because of these large energy needs, the brain has evolved like the rest of the human body for maximum efficiency. After all, the primary driver of evolution is survivability, and energy sources (food), used to be scarce. So the human body evolved to balance a brain that can solve complex tasks — helping us move to the top of the food chain — with a need to efficiently use the body’s energy.

As a result, we got a brain that’s awesome, but also lazy.

It uses a host of cognitive tools (ie, heuristics, biases, anchoring, etc.) as a way to jump to conclusions without expending too much energy consciously thinking through every single problem it’s faced with.

For the most part, this system works great. The brain is unmatched in its ability to subconsciously perform pattern recognition and come to an adequate conclusion with little information.

For the many advantages that our brains offer though, they can be extremely dangerous to our trading capital.

That’s due to the following two reasons:

    1. Our brains operate on pattern recognition and therefore like simple, linear answers.
    2. Information overload results in cognitive tunneling (System 1 thinking) and our minds instinctively follow the path of least resistance when confronted with complexity.

The problem with “reason 1” is that markets are not simple or linear. They are endlessly complex and dynamic.

Therefore “reason 2”, following the path of least resistance in coming to conclusions, is the opposite of what you should be doing.

But it doesn’t need to be like this. As Blaber learned, there’s a way to overcome this evolutionary handicap. He writes:

So how could I have known it wasn’t a bear? Because there was another, more enlightening pattern tugging at the shirttails of my common sense as I fled that day. It was the pattern of being treed by a chihuahua—all those times in my life when I had made chowderheaded decisions without understanding the reality of the situation around me. My common sense was telling me to take time to look, listen, and question everything. Common sense provides context, and context is common sense.

In this report, we’re going to layout a three-part-framework for establishing context in markets.

The framework will keep you from getting knocked out by every minor dip in a major trend. It will help you know when it’s time to take profits and reverse your positioning. It’s the framework we used to flatten our longs, buy a bunch of bonds, and go short the market in late February before the crash. It’s the one I used to start adding some risk again shortly after the March 23rd bottom.

Is it this or is it that?  

Price action is fractal. There’s trends, counter-trends, and consolidations contained within every chart. This simply means that within every trend, like the one below, there are reversals and consolidations simultaneously taking place on various timeframes.

The difficulty in sitting tight and riding a trend out is when you get these little dips (highlighted candles). You don’t know whether they’re going to do this.

Or this…

Most investors sit on the sidelines for the meat of a trend. They console themselves with ALL the reasons why the trend will end, and they expect every dip to be the BIG one.

By necessity, it has to be this way. Trends are built on disbelief. They climb a wall of worry and fall down the stairs of hope. It’s the conversion of non-believers to full-on punch drinkers that eventually mark the major turning points.

The oscillations, the dips, the volatility along the way are the price the player pays to ride out a big move.

I can’t remember who made the analogy (Ed Seykota, maybe?). But they compared a trend to a rose. To hold a rose you have put up with the thorns. Most traders think the thorns are poison-tipped and quickly drop it like it’s a turd covered stick.

Experienced traders know that a thorn is an opportunity to enter or add to a position…

Thorns are a feature, not a bug.

They perpetuate the disbelief in the trend and keep positioning and sentiment from reaching a point of criticality that translates into trend fragility and raises the specter of a full-blown phase-shift (reversal). This is true for all complex systems as pointed out in this piece from Quanta Magazine.

A complex system that hovers between “boring randomness and boring regularity” is surprisingly stable overall, said Olaf Sporns, a cognitive neuroscientist at Indiana University. “Boring is bad,” he said, at least for a critical system. In fact, “if you try to avoid ever sparking an avalanche, eventually when one does occur, it is likely to be really large,” said Raissa D’Souza, a complex systems scientist at the University of California, Davis, who simulated just such a generic system last year. “If you spark avalanches all the time, you’ve used up all the fuel, so to speak, and so there is no opportunity for large avalanches.”

In markets, frequent dips help prevent major selloffs and effectively lengthen the duration of a given trend. Knowing this, as traders and investors, our process needs to exploit and harvest the positive function of dips (thorns) and not let them shake us out of positions. That’s what the following framework aims to do.

The Trifecta Lens is a 3-part decision tree that operates off of simple {if this, then that} conditional statements. The aim of which is to quantify our key indicators of breadth, liquidity, and sentiment in order to give us objective points of context. The result of which is it tells us whether a dip is a this or a that.

It looks like this:

    1. Setup
    2. Conditions
    3. Trigger

The tipping point into multiplicity

A Setup is a technical point on a chart. In physics terms, it would be called the critical point, which is the zone at which a complex system sits between order and disorder. The area at which a phase transition can take place.

In our framework, the Setup is when the price touches the lower band of a standard 20-day 2stdev Bollinger Band in an uptrend. But, in reality, it could be a number of things, such as a Keltner or Donchian Channel break, a swing below a pivot point, a percentage move off new highs, etc…

The exact details are fairly unimportant and you can use something else that better fits your process and objectives. The key is that it’s a critical point that shouldn’t be too frequently hit because you’ll end up with a lot of noise.

Many investors worry about a large selloff when the market is hitting new highs, which just boggles the mind because new highs are an obvious trait of a bull trend. A bull trend contains many oscillations that vary in amplitude. Again, these are thorns and they’re a good thing.

We don’t care about dips to the middle range of the band, because those are noisy and are more often than not, a buying opportunity — remember Newton’s First Law of Markets, a trend in motion tends to stay in motion — statistically speaking, a trend will continue 80% of the time.

A larger selloff is what we’re concerned with and it has to pass through the lower Bollinger Band. I know I’m making some obvious statements here, but bear with me as I build on the logic behind the framework.

So, it’s only when the price hits the lower Bollinger Band in an uptrend that we need to follow through on the rest of our framework. In order to see if it’s a this or a that… a dip or a potential crash…Otherwise, we should buy new highs; buy reversals after dips to the midline, buy because we have too much cash, buy because it’s sunny out, etc…

A measure of potentiality

If our Setup is a measure of frequency then Conditions are a measure of the potential amplitude or the overall fragility of the trend at that point in time. They give the probabilities for a phase-shift, a reversal of trend.

To use the sandpile analogy, we can think of Conditions as a measure of slope. The steeper the slope the greater the potential for an avalanche.

We measure Conditions through a Trifecta of Breadth, Liquidity, and Sentiment. There is no panacea or perfect indicator in markets. It can’t exist because if there was it would be arbed out and reflexivity would kill its value as a signal. Using the Trifecta approach of collecting data points from disparate areas of the market, we can holistically build out a more effective context.

So let’s walk through each one.

The strength of the line

A good way to think of market breadth is like an advancing military force. Strong breadth is similar to an army with a deep and disciplined line (think of old school battles where fighters stood shoulder to shoulder). That line has strength and weight behind it. It can move and push through barriers.

On the other hand, when the line is thin and begins to fracture. It doesn’t take much from the opposing force to break it completely. This is how major trend changes happen. Each issue in an index is equivalent to a soldier standing on that line. And that is what various indicators of breadth aim to measure.

The three breadth indicators used in our Trifecta Lens are: [Details have been redacted and are for Collective members only].

 

 

 

The conditional statements used for each one is:

 

 

 

We add these together to get a Breadth score. The score ranges between -3 and +3 with -3 indicating very negative breadth and +3, the opposite.

The strength of the current

Liquidity can be thought of as the trend in demand for risk. It’s best measured by tracking what’s going on in the credit markets. Since, as per our Hierarchy of Markets framework, credit markets are smarter than equity markets and more often than not, sniff out major trend changes before they show up in stock indices.

The three liquidity indicators used in our Trifecta Lens are:

 

 

 

The conditional statements used for each one is:

 

 

 

The yin and yang

Exuberant sentiment and crowded positioning are behind nearly every major market selloff. Overly eager investors out over their skis are what sows the seeds for a reversal in trend. It’s what drives the fractal risk-cycle and why there’s an embedded yin & yang flow to markets. You can read more about how we think about sentiment here.

The three sentiment indicators used in our Trifecta Lens are:

 

 

 

The conditional statements used for each one is:

 

 

 

We add the Breadth, Liquidity, and Sentiment scores together once a Setup point has been observed. The cumulative points give us a final score which ranges from -9 to +9.

The tape tells all…

A Trigger is a setup bar that leads to an action; an entry, exit, add to, or reduction of a position. We’re not going to dive too much into this concept today. We’ll leave that for another time. But essentially, it’s an additional and critical contextual point that precedes a trading action.

For instance, it could be a strong bullish reversal bar after a Setup is hit in a bull trend when the Conditions signal a high probability of trend continuation. And vice-versa, it could be a bearish follow-through after a Setup point is hit, indicating a high probability of further downside over the short-term, at minimum.

Putting it all together

Let’s now go through 12 Setups over the last 18-months and see how this framework would have kept you in the trends and out of the crashes.

Beginning at the bottom of the December 2018 selloff when everyone was talking about recession, the inverted yield curve, and trouble in China.

The Trifecta Lens gave us a score of +3. Any score from zero and above is bullish, so a positive three is a very strong reading. This reading was followed the next day by a large bullish reversal Trigger bar.

In March 2019, when everyone was calling the rise off the lows a bear market rally and pointing to indicators of a global recession. Our Trifecta Lens gave us a score of 0 on the March 18th Setup.

Again, this is a bullish score and it was followed the next day by a bullish reversal Trigger bar.

Nearly two months later we got another setup. The narrative was the same: inverted yield curve, China recession, liquidity issues, yadda… yadda… yadda…. On the May 7th Setup, we got a reading of -1.

This is a bearish reading indicating there’s a higher chance of downside follow-through — which is exactly what we saw. But it’s not an extremely bearish reading, one that would normally precede a major selloff or change of trend. Those typically occur at -3 or below.

Four weeks later, the selloff concluded with a reading of 0 followed by a large bullish reversal Trigger bar.

Towards the end of July, the whole Repo Rate Hysteria began kicking up, feeding the bearish machine.

This, of course, was a bunch of nonsense. Anybody who knew even a little bit about how the financial plumbing works, should have known that. Regardless, it didn’t matter, because the Trifecta Lens would have told you to stay long the trend.

In the July 31st Setup, we got a reading of positive 2. There wasn’t an immediate bullish follow-on Trigger bar, but it at least told you that the odds favored a minor pullback over the bear market everyone was predicting.

All you had to do was stay long and wait for a bullish Trigger to enter or add to your position.

October 2019 was peak Repo Hysteria… We got a Setup on the first of the month and a very bullish reading of positive 3. Again, all you had to do was wait for a bullish reversal and buy/add to longs.

In December of that year, our bullish tailwinds began to dissipate somewhat. And on our December 3rd Setup, we got a reading of negative 1.

A reading of negative 1 doesn’t mean there’s a high probability of a major trend change. It just means fragility has increased and Setups can turn into deeper pullbacks. That wasn’t the case here as this was quickly followed by a bullish Trigger bar. So again, you wanted to stay long and add to your positions.

The trend-fragility increased though… And nearly 2-months later, when the narrative was outright bullish and long positioning was at record levels, our Trifecta Lens gave us a score of negative 6.

Negative 6 is about as bad as it gets as it’s very rare that all the indicators signal the same thing. This reading was coupled with a Bull Volatile Regime (shown by the SQN dark green bars). And Bull Volatile Regimes are hallmarks of major turning points.

So though this Setup was quickly followed by a bullish reversal Trigger bar, it was a good spot to begin lightening up on risk, selling down positions, and looking to start hedging your book.

One month later we got another Setup. And this one gave us another extremely bearish reading of negative 6. Plus, it was preceded by a very large bear bar and then immediately followed by another one.

This was a clear signal to batten down the hatches and prepare for a large selloff and potential primary trend reversal.

The crash bottomed on March 23rd. While the entire world was predicting a LOT more downside, our framework gave a reading of positive 3. This was followed the next day by a very large bullish reversal Trigger bar.

It was followed up a month and a half later by a reading of positive 6 during the May 14th Setup.

A positive 6 is about as bullish a reading as you can get. So… buy dips, buy rips, buy new highs.

Again, a month in a half later, another Setup with another bullish reading, shortly followed by a Bullish Trigger bar.

And this brings us up to the present day [Note: this report was published to Collective members on August 20th. The TL score has since changed dramatically. Sign up for our Collective to find out more]… We’re still in a primary bull trend. And though we’re not currently at a Setup, our Trifecta Lens gives us a score of positive 0.

So while bullish tailwinds are dissipating they’re still positive and the path of least resistance remains up, for now. Though we should expect the TL score to continue to deteriorate and give a sell signal sometime in the coming weeks.

 

And there you have it… That’s the Trifecta Lens for assessing the strength and durability of trends.

This is just one way to codify a framework for building context. And this framework, or something similar, doesn’t need to be quantified (though, the more systematic you can be in your approach, the better). I can quickly eyeball all these indicators and decision tree them in a matter of seconds and arrive at the same place.

The important part is that we use the entirety of the framework; the Tape, the Breadth, the Liquidity, and the Sentiment/Positioning to build a contextualized picture of what’s really going on in the market. This prevents biases from creeping in, clouding our judgment, and leading to emotionally reactive decision making.

A recent example is all the very smart, yet very misguided technicians out there who’ve been sitting on the sidelines for the last couple of months calling for a market crash because Put/Call ratios have been extended. That was only a single piece of the puzzle. That’s not context… That’s confirmation bias.

Now, this framework isn’t a crystal ball. It doesn’t make predictions. It just gives context. Very valuable context that allows you to constructively assess the odds and probabilities. It empowers you to be proactive and not reactive to market moves. Most importantly, it will keep you from getting Treed.

Risk aversion and fear of the unknown are direct symptoms of a lack of context and are the polar opposites of audacity. ~ Pete Blaber

If you’ve enjoyed reading this report then you should think about joining our Collective. The Collective is the anti-newsletter trading and investing service. Unlike others in this space, we at MO don’t peddle constant doom narratives or seek to confirm biases.

Our aim is simple… make high risk-adjusted returns consistently. Continuously learn while doing so, and have a lot of fun along the way. And in this regard, our record speaks for itself. This is partly why we have BY FAR the highest retention rates of any investing service in the industry. Collective members tend to stay members for a long time because there really is nothing else like us.

Our doors are open until the end of day Sunday. At which point we’ll be closing the enrollment period and won’t be opening back up for some time.

We offer differentiated research, theory and education resources, plus a killer community (Slack) filled with some of the smartest Operators from around the world. Our members are predominantly professionals but we also have a number of highly motivated retail players. The one thing we all share is a deep love for the game and an unquenchable thirst to get better.

If this sounds like you then consider signing up and checking us out. I look forward to seeing you in the group! And as always, don’t hesitate to shoot me any questions.

Click here to sign up for the Collective

IT’S ALL MONTE CARLO

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In the original Market Wizards, commodities trader Larry Hite talked about four types of bets: Good Bets, Bad Bets, Winning Bets, and Losing Bets.

Hite’s point was that a winning bet is not always a good one, and a losing bet is not always a bad one. We can see why through the lens of Expected Value (EV). It’s possible to do something smart and still lose money. It’s also possible to do something dumb and make a profit. But only in the short run — in the long run, the law of averages settles all accounts.

Expected Value gets down to the deep nitty-gritty difference between winning players and losing players:

Winning players strive to always take positive EV actions (make “good bets”) without concern for the immediate outcome.

Winning players seek to AVOID negative EV actions at all costs.

Losing players routinely indulge in negative EV actions, i.e. make “bad bets,” because they don’t know any better… aren’t disciplined enough to avoid temptation… or just want to have fun.

Consider the city of Las Vegas. (or Macau, which now has more than nine times the gambling revenue of Las Vegas.)

Vegas and Macau are, quite literally, funded by negative EV activities. Tourists engage in games of chance where the odds, on an expected value (EV) basis, are either slightly against them or greatly against them. The casinos are on the other side of this — which explains why most Vegas casinos are publicly traded with revenues in the billions.

Not everyone who goes to “Lost Wages” for a little gambling is irrational of course. Losing money in a fun way, surrounded by friends and coaxed by free drinks, can be a worthwhile vacation activity. Many who come to the strip and drop their $500 or $1,000, or whatever amount is designated for the trip, feel they got their money’s worth in terms of a good time.

Many traders and poker players are the same way. Having a good time, either consciously or subconsciously, is the driving point of why they play. And that bias strongly favors unprofitable decision making. In trading and poker, the positive EV decision is often the emotionally hard thing to do… whereas the negative EV decision is the emotionally easy thing to do.

Calling with a draw where you should’ve folded? Negative EV, but more fun.

Playing too many hands preflop? Negative EV, but less boring (and thus more fun).

Playing too passively or with too small a stack? Negative EV, but less scary (and thus more fun).

Shorting Tesla (TSLA) when it’s shooting the moon and you’re getting repeatedly blundered, but you’re part of the hip $TSLAQ crowd (and thus more fun… I guess?)

And so on and so forth… the desire to be entertained is antithetical to profitable play. The antidote is to redefine “fun” as something else — the fun of training, the fun of being a true competitor, and the fun of winning.

IT’S  ALL MONTE CARLO

The “Monte Carlo method” is used by scientists and mathematicians. It is also used by poker players and traders on an intuitive basis.

To run a Monte Carlo simulation in your head, do the following:

    • Imagine a situation where your opponent has a potential range of holdings
    • Imagine all variables are fixed except which cards your opponent actually has
    • Insert various possibilities based on you knowledge of the likely range
    • Insert various probabilities based on future turn, river, and bet scenarios
    • Estimate the average across all results
    • Determine whether EV is positive or negative for various decisions
    • Make the decision with the highest EV based on your analysis

To put it another way: In any poker or trading situation, you want to figure out what the reasonable parameters are for that situation — what your opponent could be holding — and then you want to run that simulation in your head a thousand times. Not literally “a thousand times,” but that is the mental picture.

The “Monte Carlo” aspect of this is traversing the range of probabilities. You also weight various scenarios in occurrence with their likelihood. So, for example, if you think there is a 10% chance your opponent is stone-cold bluffing, you factor that in at 10 percent. If you have pocket queens,  and you think there is a 30% chance your opponent has pocket kings or aces, you factor that accordingly as well. You must get comfortable with “probability weighting.”

This type of scenario-based Monte Carlo simulation, in order to deliver a weighted expectation result, is what winning poker players and traders do constantly. It is their analytical bread and butter in the quest to make positive EV decisions.

For winning poker players and traders, “everything is Monte Carlo” because all decisions are constantly weighted and assessed in respect to EV. Outcomes have an element of randomness and will display meaningful variation at any given time. But the PROCESS is always relentlessly positive EV.

You have probably heard the phrase “process over outcome.” Gearing all decisions toward positive EV is a literal interpretation of process over outcome. If your decision was plus EV, it doesn’t matter whether the short-term result was unprofitable (as long as you can handle short-term volatility). The process trumps all over time. With patience, the law of large numbers (aka the law of averages) delivers the goods.

This further explains why winning players are not perturbed by temporary setbacks or negative results. When you understand probability distribution, you also understand that X percent of the time, you will get the negative result rather than the positive one. This is not a bad thing —  it is simply part of poker and trading.

And in fact, it is a very good thing, because if negative expectation bets did not pay off a fair percentage of the time, bad players/traders would stop making them!

Do you know why there is almost no money in chess? Because all the weak chess players know that they are weak. There aren’t enough instances of negative expectations payoff to fool them and entice them. If you are bad at chess you will get your butt whipped dozens of games in a row, and then you will work hard to get better or quit.

In poker and markets, though, the randomly distributed payoff of negative expectation bets — coupled with the fact that the untrained human brain is fundamentally bad at math — means that bad players can persist in playing for years, or even decades, mistakenly convincing themselves they are good.

And thankfully that’s the case because, in the zero-sum games of poker and markets, it’s the players who consistently make negative EV bets, that fill our pockets.

If you’d like to join our group of ruthless-calculating-positive-EV-profiteers, then check out our Collective. Due to a technical issue that prevented a number of you from being able to sign up last week we’ve extended the enrollment period until midnight this Sunday. As always, don’t hesitate to shoot me any Qs… Hope to see you in the group!

CLICK HERE TO LEARN MORE ABOUT OUR COLLECTIVE

The Law of Returns and How To Exploit it

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Vilfredo Pareto was an Italian economist born in the mid-19th century who made an interesting discovery about land ownership in Italy.

While surveying his Italian city he found that 80% of the land was owned by only 20% of the population. After further inquiry, he found that this 80/20 distribution was prevalent in other cities as well. And in fact, this 80/20 rule didn’t seem to apply just to land ownership; but also income distribution, and revenue origination streams. Pareto had stumbled upon a naturally occurring power law.

A power law, as known in mathematics, is a relationship between two quantities such that one is proportional to the fixed power of the other. Power laws are embedded in the very fabric of the universe; applying to the size of solar flares, the populations of cities, and the intensities of earthquakes to name only a few.

The 80/20 rule, now known as Pareto’s law is often used as a guiding principle in business and productivity decisions. Trading and investing profits adhere to this power law too. In fact, they follow an even more extreme distribution of 90/10. Meaning, amongst great traders and investors, 90% of their profits tend to come from 10% or less of their trades. Let’s look at the following from Ken Grant in his book Trading Risk:

“Some years ago in my observation of P/L patterns, I noticed the following interesting trend: For virtually every account I encountered, the overwhelming majority of profitability was concentrated in a handful of trades. Once this pattern became clear to me, I decided to test the hypothesis across a large sample of portfolio managers for whom transaction-level data was available. Specifically, I took each transaction in every account and ranked them in descending order by profitability. I then went to the top of the list of trades and started adding the profits for each transaction until the total was equal to the overall profitability of the account.

“What I found reinforced this hypothesis in surprisingly unambiguous terms. For nearly every account in our sample, the top 10% of all transactions ranked by profitability accounted for 100% or more of the P/L for the account. In many cases, the 100% threshold was crossed at 5% or lower. Moreover, this pattern repeated itself consistently across trading styles, asset classes, instrument classes, and market conditions. This is an important concept that has far-reaching implications for portfolio management, many of which I will attempt to address here.

“To begin with, if we accept the notion that the entire profitability of your account will be captured in, say, the top 10% of your trades, then it follows by definition that the other 90% are a break-even proposition. Think about this for a moment: Literally 9 out of every 10 of your trades are likely to aggregate to produce profits of exactly zero. It almost makes you want to pack up your charts and go home, doesn’t it? Indeed, the main danger in being aware of this concept is the tendency to misinterpret its implications. For this reason, we want to be very careful about how we use the information in driving the portfolio management process and all of its components.

“Most people’s first reaction when they see their “90/10″ score is to assume that it is a problem that wants correcting. This is simply not so; and if they respond by trading less, concentrating their portfolio exclusively on what they feel to be their best ideas, they are likely to be disappointed by the results. The 90/10 rule is hard to overcome, and so I think the better way of looking at it is that you need the 90 to get the 10.

“To best understand this, let’s use a baseball analogy (why not, everyone else does). Think of the situation faced by a .300 hitter in baseball, who, even though he knows he’s going to be unsuccessful 70% of the time cannot simply decline to step up to the plate on the 7 out of 10 occasions where (statistically speaking) he isn’t likely to get a hit.

“Truth is, the 7 outs he makes in 10 at-bats are a necessary condition of his .300 batting average, and he can no more expect to be more successful by limiting his at-bats than you can expect to be successful in your trading by reducing your number of transactions. True, just as the batter may know that he does better against certain teams and pitchers and in certain parks than others, so will you as a portfolio manager have some insights into the conditions that are most conducive to maximum profitability – across individual names, market cycles, and other factors. However, in both cases, the individual in question cannot expect to gain any benefit through a lack of participation.

“Therefore, the principal lesson you should derive from 90/10 may well be that the lower 90% of your transactions, which are likely to sum up to zero P/L, are a critical component of your success. If properly analyzed, these trades can provide insights into the controllable elements of your portfolio management activities that can be enormously valuable to your bottom line. However, if you fight against this tide, you are likely to fall into a large group of market participants who have very useful skill sets but who inevitably become their own worst enemies.”

The Macro Ops Portfolio’s return distribution follows this 90/10 rule, as well — and this is very much by design.

The majority of our annual profits come from just a handful of trades throughout the year. Conversely, most of our trades/investments we enter (on average 75% of them) will effectively cancel one another out. We will have a lot of small losers and some small winners… and then we’ll have 3-5 massive winners that generally makeup over 90% of our bottom line.

This is a fundamental fact of successful trading and investing. Buffett, Soros, Druckenmiller, and Dalio all live by this same law of distribution. If you study their returns, the 90/10 rule is prevalent amongst all of the greats. One of the reasons why they’re “great” is because they have learned to actively embrace this truth and build their strategies in a way that exploits this power law to its full effect.

The fight against the natural distribution of returns is one of the most common failure points among traders and investors… it’s why 90% of traders fail to beat the market and only 10% succeed (ironic, right?). Over-optimization, trying to improve one’s win rate is a common trap and a loser’s game. Like Grant said, “you need the 90 to get the 10.”

90/10 distribution is also a product of creating asymmetry in one’s trades. Asymmetry is the result of finding opportunities and structuring trades in a way where the potential profit far exceeds the maximum loss. This is partially created by taking quick and small losses while giving winners much more room to run. It’s the timeless axiom “cut your losses short and let your winners run”.

Here’s Bruce Kovner on the reality of return distributions:

Michael Marcus taught me one other thing that is absolutely critical: You have to be willing to make mistakes regularly; there is nothing wrong with it. He taught me about making your best judgment, being wrong, making your next best judgment, being wrong, making your third best judgment, and then doubling your money.

Embracing these truths is one of the most difficult hurdles for traders and investors. Humans just aren’t wired for losing and a key to being a good trader is to be an excellent “loser”. And this is because a master trader will enter far more losing trades than winning ones. Mark Spitznagel recounts in his book The Dao of Capital how he was taught this lesson early on by his mentor Everett Klipp who told him “to be successful you have to love to lose.”

Amateurs want high win rates and think every next trade is going to be 5-bagger. The Master trader is infinitely patient and has enough faith in his method — gained through experience —  that he remains cold and calculating and lets Pareto’s law work its magic.

If you’d like to join our group as we search out the 10% bottom-liners for the rest of the year (we have our eyes on a few at the moment) then check out our Collective. Enrollment closes on Sunday. Looking forward to seeing you in the group!

CLICK HERE TO LEARN MORE ABOUT OUR COLLECTIVE

Our Framework For Analyzing Gold

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In March 2019, we pointed out the incredibly tight compression regime in gold, writing:

Volatility in gold as measured by the width of its monthly Bollinger Band is at levels last seen over 17-years ago, in 02’ right before the barbarous relic began its decade-plus run…

Markets tend to work like rubber bands. The tighter they’re wound up, the more explosive they unravel. In other words, compression regimes lead to expansionary ones. The size and velocity of the move often mirror the preceding level of contraction in vol. There are logical reasons for why this occurs (it has to do with positioning and narrative cascades).

The current level of compression suggests something big is coming around the corner. As macro traders, it’s regimes like these where we need to be at the ready. An explosive macro trend is about to be born…

We pounded the bullion table some more a month later, writing:

It seems we have the two necessary ingredients for a major bull market in gold. These are (1) low expected returns for long-term financial assets and (2) a global money stock that is likely to keep growing (potentially by A LOT).

When we combine this with the current low vol regime + the textbook long-term inverted H&S bottom pattern forming, we get a clear trading opportunity….

Looking at the tapes of a number of gold miners I can’t help but salivate. There are a few stocks here that look ready to explode…

The background timing of the current macro environment tells us something big is coming, something that’s not yet fully known or fully discounted by the market…

This means some major trends are on the horizon. And along with major trends come major opportunities to profit.

Gold is just one area I see that’s ripe for exploitation…

And finally, we trumpeted the bullish clarion again in April of this year:

I expect gold will take out its all-time high made in 2011 within the next six months. After that, the sky is the limit.

I have high conviction on this trade over the long-term.

Gold closed the month of June near its highs — a bullish development. And is now less than 7% away from taking out its all-time highs.

You can find the links for each of these timestamped reports here, here, and here.

Alright… enough with the self-congratulatory hubris. That’s not the point of this piece. I share this so you can see how much you can improve your analysis of the metals market when you have a hard and consistent framework for doing so. A framework that I’m going to share a key part of with you right now.

Similar to all other markets we trade, the foundation of our precious metals framework is the “Marcus Trifecta”. A triangulation of the Macro, Technicals, and Sentiment. We’re going to cover the macro.

The macro framework is simple… It has little to do with inflation or “crisis insurance” of any other of the perfunctory narratives that commonly get passed around as wisdom.

Okay… so here it is… our macro framework is: RED. That’s it, what do you think… Pretty good, huh?

Not impressed? Okay, that’s fine, let me break it down for you then. RED is an acronym that stands for.

    • Relative Size
    • Expected Real Returns
    • Demand

Here’s what each of those means.

Relative Size

Less than 15% of the gold mined throughout history is held in investment form. Gold’s total market cap is somewhere in the ballpark of $1-$2trn. While the global capital stock (equity + debt) is in the realm of $250-$300trn. This creates a positively sloped investment demand function. More on that below.

Expected Returns

Read the following from a 1985 NBER working paper titled “Gibson’s Paradox And The Gold Standard”. Here’s the link to the paper (emphasis from me):

Gold is a highly durable asset, and thus, as stressed by Levhari and Pindyck (1981), the demand for the existing stock (as opposed to the new flow) must be modeled. The willingness to hold the stock of gold depends on the rate of return available on alternative assets. We assume that the alternative assets are physical capital with a (instantaneous) real rate of return r, and nominal bonds with (instantaneous) nominal return i = r + P/P = r — Pg/Pg. The real rate of return is exogenous to the model, but subject to shocks. These shocks reflect changes in the actual or perceived productivity of capital as envisioned by Keynes and Wicksell.

The above is just a fancy of way of saying two things (1) since gold is a non-perishable metal and the amount mined each year (new flow) is tiny relative to the existing stock, we should focus on the latter in our supply & demand calculations and (2) the attractiveness of gold is ALL relative and demand only becomes positive when the expected real rate of return offered on other assets (stocks and bonds) is low.

Demand

Demand, not supply, is what matters. Remember, potential demand is many multiples the size of the existing gold stock, which is fairly inelastic. So it doesn’t take much of a change at the margins of asset preferences to cause very big moves in the yellow metal. And as we learned above, this demand or asset preferences are driven by the expected real returns of stocks and bonds. This is why gold tracks the real yield on bonds very closely. When the real yield offered on bonds is trending lower, gold goes up. And vice versa.

This inverse relationship can be seen below in the following matrix via the excellent book Hedgehogging, written by Barton Biggs (the chapter with Peter, the “Gold Guru” is also where I first became aware fo the above NBER paper).

So that’s it… That’s RED. Our fundamental framework for analyzing gold.

The entire thing can be boiled down further into just two key points:

    1. Over the long run (and this is one of Ray Dalio’s “principles” regarding gold, as well) the price of gold will approximate the total amount of money in circulation divided by the size of the gold stock
    2.  And it’s not inflation or deflation that is the principal driver of gold, but the expected real return from other long-term financial assets, particular equities.

Using the above we can quickly discern that there’s a very high probability the bull market in gold will continue for the foreseeable future.

The global money stock has exploded and continues to rise… While the expected real return on financial assets is very low. Even negative in some cases. See GMO’s 7-year forecast as case in point.

Gold obviously isn’t going to go straight up from here. So, if you’re a trader, then you’ll want to pay attention to some key indicators and of course, read the tape.

Here’s a slide from our regular weekly Trifecta Report that goes out every Saturday. In the report, we analyze the four main macro instruments: SPX, UST 10yr Bonds, Gold, and the dollar.

The below slide shows some of the key positioning, sentiment, and seasonal data that we track for gold. As of right now, fund flows, sentiment, and positioning all remain supportive of higher prices. Not to mention, gold is about to enter the strongest 2-months of the year for returns on a seasonal basis.

The tape says we’ll probably see a little pullback over the short-term as stocks get bid up. But, that’ll just offer us another good opportunity to add to our position.

So there you have it. That’s our RED system for analyzing gold. I hope you find it useful. We didn’t even cover silver, which according to our framework, should outperform gold over the coming months.

If you appreciate this kind of first principles research and analysis. And you’d like to join our Collective of traders and investors from around the world, please click the link below to check us out. Our community is comprised of the full spectrum of market participants, from wealthy retirees to hard-charging college students, to a handful of billionaire hedge fund managers who are household names. The one thing we all have in common is that we’re maniacally devoted to mastering this great game.

This devotion shows in our performance. While the market is negative on the year, we are up double digits so far. Not to mention we’ve had to stomach MUCH less portfolio volatility. This is a testament to our ruthless devotion to truth in this game and building an approach from the ground up, starting with foundational principles.

This enrollment period closes this coming Sunday. Afterward, the discounted price will no longer be offered and we won’t be reopening our doors for some time.

I hope to see you in the group. It’d be great to have you on the team. We expect the rest of the year to be a wild one for markets. It’d be a lot of fun (and hopefully very profitable) to tackle them together.

Sign me up for the MO Collective

How To Read Market Sentiment

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On being a contrarian from Michael Lewis’ Liar’s Poker:

Everyone wants to be, but no one is, for the sad reason that most investors are scared of looking foolish. Investors do not fear losing money as much as they fear solitude, by which I mean taking risks that others avoid. When they are caught losing money alone, they have no excuse for their mistake, and most investors, like most people, need excuses. They are, strangely enough, happy to stand on the edge of a precipice as long as they are joined by a few thousand others…

Contrarianism is the most abused and empty platitude in trading and investing. Everybody thinks they’re one, but few are.

And that, by its very nature, has to be the case. Because to be a contrarian is to go against the herd, the majority.

Hedge-fund legend Ray Dalio puts it like this, “You can’t make money agreeing with the consensus view, which is already embedded in the price.”

In case you don’t have twitter (good on you, you’re a better person than I!) or missed my recent thread on the subject of “How To Read Market Sentiment”. You can find the entire thread here. Let me know if you have any thoughts or comments.

 

2. Speros Drelles was teaching the young Druckenmiller about the wisdom of the market, which is based on the idea that the crowd is collectively smarter than any one individual. This collective intelligence was first stumbled upon by the late great statistician, Francis Galton, who…

3. …in 1906 observed a competition at a local fair where approx. 800 people tried to guess the weight of an ox. To his surprise, the avg of all the guesses was 1,197lbs. The real weight… 1,198lbs. Countless studies have been done since. All show similar results…

4. Crowd > any individual. Scott Page, in his book “The Difference”, lays out the “diversity prediction theorem” to explain how this works and what variables are needed to make a crowd wise. The theorem states that: Collective error = avg individual error – prediction diversity.

5. The implications of this are 3-fold:

    1. A diverse crowd will always predict more accurately than the avg individual
    2. A crowd is often smarter than even the best of its individuals
    3. Collective predictive ability is equal parts accuracy & diversity.

6. Takeaway: Crowds are smarter than any single person, as long as there’s a diversity of opinion. This theorem is based on math and is always true. @mjmauboussin has a great paper on this for those of you who want to explore more (link here).  

7. To take this back to markets. Here’s Soros explaining why it’s KEY to know when to be a part of the “herd” (ie, follow the trend) and when to disengage & be a contrarian: 

Being so critical, I am often considered a contrarian. But I am very cautious about going against the herd; I am liable to be trampled on… Most of the time I am a trend follower, but all the time I am aware that I am a member of the herd and I am on the lookout for inflection points… I watch out for telltale signs that a trend may be exhausted. Then I disengage from the herd and look for a different investment thesis. Or, if I think the trend has been carried to excess, I may probe going against it. ~ George Soros

8. You want to be a trend follower when there’s a lot of people saying “this move makes NO SENSE” and a contrarian when people are saying “this makes so much sense”. This is why a bull climbs a wall of worry & a bear falls down the stairs of hope. Trends are driven by (dis)belief

9. But… and this is important. You ONLY want to be a contrarian once the tape STOPS confirming the consensus narrative. Reading the sentiment tea leaves is as much an art as it is a science. And when in doubt, defer to the market.

10. Blake LeBaron, an economist,  modeled how this diverse opinion/wise crowd & consensus/dumb crowd works in markets to create trends and crashes. Here’s his paper

11. He built a computer model and imbued “agents” with decision-making rules such as: make money, try not to lose money, don’t underperform the average for long periods etc…

12. What he found was that “During the run-up to a crash, population diversity falls. Agents begin to use very similar trading strategies as their common good performance begins to reinforce… This makes the population brittle…Traders have a hard time finding…

13. …anyone to sell to in a falling market since everyone else is following very similar strategies.” This confirms Page’s “diversity…” theorem and explains the mechanics of why markets trend and revert, or move in sine waves.

14. Trends that “make no sense” = robust. Trends that become consensus = fragile. Soros thought of this phenomenon as high and low “distortion regimes”. High distortion regimes = when price & sentiment form a reflexive loop, which then creates a budding consensus.

15. Low distortion = diverse opinion. This price/sentiment loop, or what I call the “Narrative Pendulum” becomes obvious once you learn to look for it.

16. For example, watch this video I clipped together last year that shows the dramatic shift in the dominant narrative that occurred in just two-weeks time (link here).

17. Price drives sentiment which drives price, ad Infinium. And THERE IS NO “SMART-MONEY” other than the mrkt itself. 

All of us are part of the “DUMB MONEY” crowd. The 2 “Bond Kings” calling the end of the bond bull at the exact bottom in 18′ is case in point. THIS GAME IS HARD

18. So that’s what Drelles meant & also what makes Druckenmiller so good. He learned early on to listen and respect the market, to harness the wisdom of the crowds, and to only step in to fade a trend once a consensus was clear & the tape no longer confirmed it.

One of my strengths over the years was having deep respect for the markets and using the markets to predict the economy, and particularly using internal groups within the market to make predictions. And I think I was always open-minded enough and had enough humility that if those signals challenged my opinion, I went back to the drawing board and made sure things weren’t changing. ~ Stanley Druckenmiller

Fin/ 

Whether one knows it or not, we’re all playing Keynes’s Beauty Contest. Most dither at the first level completely unawares. Hopefully, this thread helps you see the market for what it really is so you can begin playing the game at the second, third levels, and beyond…

We’re currently working on a report about where we see the MOST one-sided positioning and consensus out of any market around the world. This consensus has created what we believe is an extraordinarily asymmetric opportunity.

Jim Rogers, the famed partner to George Soros during the ole’ Quantum days, likes to say:

The way of the successful investor is normally to do nothing — not until you see money lying there, somewhere over in the corner, and all that is left for you to do is go over and pick it up.

Well, suffice to say, we at MO see a disgustingly large pile of money just sitting over in the corner right now… just waiting for some free-thinking investors to come and scoop it up.

If you’re interested in finding out more then click the link below and join our group while the enrollment period is still open and the discounted rate still applies. I hope to see you in our group.

I Want To Join The MO Collective

Thinking In Essentials

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The other day I shared my thoughts on E.O. Wilson’s quote, you know the one where he writes “We are drowning in information while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely.”

Here’s a link to it in case you missed it. Anyways… one of the problem sets that we work really hard on solving here at MO is to cut through all the gross noise —  and there’s A LOT of it — in order to tease out the valuable signal. You know, separate the wheat from chaff, synthesize the goods, and all that.

This requires something that we call Ruthless Reductionism, which is really just a fancy way of saying “we work tirelessly to cut away the fat from our process and only use the effective essentials”. In visual form, the process looks like this.

Victor Sperandeo, one of the Trading Greats of the 70’s/80’s era and author of the fantastic book “Trader Vic”, also wrote about the importance  of focusing on essentials. Here’s Vic in his own words (emphasis by me):

“If I had to reduce all the components of my methods to a single phrase, it would be thinking in essentials.

“It’s not necessarily how much you know, but the truth and quality of what you know that counts. Every week in Barron’s there are dozens of pages of fine print summarizing the week’s activities in stocks, bonds, commodities, options, and so forth. There is so much information that to process all of it, and make sense out of it, is a task beyond any genius’s mental capacity.

“One way to narrow down the data is to specialize in one or two areas. Another way is to use computers to do a lot of the sorting out for you. But no matter how you reduce the data, the key to processing information is the ability to abstract the essential information from the bounty of data produced each day.

“To do this, you have to relate the information to principles — to fundamental concepts that define the nature of the financial markets. A principle is a broad generalization that describes an unlimited number of specific events and correlates vast amounts of data. It is with principles that you can take complex market data and make it relatively simple and manageable.

So you could say that taking complex market data and making it relatively simple and manageable is what the team and I at MO do. Not just for our own process but for fellow Operators in our Collective. Our strategies, the tools and indicators we use, the information we aim to share, is tirelessly tested for its efficacy.

For it to get into our toolbox it needs to be able to make us money… We don’t aim to participate in confirmation bias or sensational prediction making here.

I write all this because since we’ve opened up enrollment into our Collective this week. I wanted to share with you the research we sent out to our group over the weekend. So you can take a look for yourself to see if it’s something you may be interested in.

Here’s the link to our Trifecta Report. This report is a macro chartbook that breaks down the: sentiment/positioning, technicals, and fundamentals of the main macro assets we track weekly. It consists of all the primary indicators and charts we look at each week for those markets.

It’s meant to offer a quick scroll through so you don’t start the week unprepared. It goes out every Saturday along with this Stock Alerts report put together by my teammate Brandon. This report shows the most actionable technical chart setups that he’s tracking each week.

And then on Sunday, I sent out this short Market Note discussing the two opposing macro forces at work in markets, currently.

This is just a sampling of what goes out over the weekend. Much more is included with entry into the group. Anyways, if you’re tired of reacting to the financial new click-bate’ery and want to cut out the noise, increase some zen in your investing life, then come and trial us and see if we’re a fit.

Click Here To Read More About The Macro Ops Collective

Synthesizers Win

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“We are drowning in information, while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely.”

– Edward O. Wilson

It is mind-blowing to think about how much information is available now versus 20 years ago, or even just 5 years ago. And yet part of the problem is a data deluge. It is incredibly tempting to be distracted by useless information… or to pay undue attention to the wrong information… or to self-select news sources and get trapped in an echo chamber… the potential pitfalls go on and on.

As the flow and volume of information increases, the ability to parse and sort that information becomes an ever more valuable skill. There are parallels here to the way grandmaster chess players process chessboard information versus amateurs. While the amateur has to painstakingly work through a complex situation — analyzing, say, ten different possibilities in detail — the grandmaster uses a process called “chunking” to reference a library of patterns in his head, then immediately zeroes in on the one or two pattern matches that are relevant.

This creates both a speed advantage and a depth of analysis advantage: Having cut away the subpar lines of play more quickly, the grandmaster can either move more quickly (saving time and energy) or invest a savings of time and energy in deeper, more nuanced analysis of the two moves that matter. The natural synthesis process increases speed, accuracy, and efficiency simultaneously, thus allowing for compound investment of the surplus.

An accumulation of small advantages in the information processing space can strengthen and reinforce itself, in small subtle ways, until finally becoming indomitable. The ability to put together “the right information at the right time,” thus allowing the ability to act with conviction before a window of opportunity closes, is in some ways the essence of trading.

What are you doing to enhance your “synthesizer” skills? Are you distracted by low-value information, or focused on high-value information? Do your data streams drown you… or act as a rich source of nourishment? Do you have a reliable means of strengthening conviction — or diluting pre-existing conviction as appropriate — based on what the information flow tells you?

I talk about the exact process we at MO use to separate the wheat from chaff in this short video I put together, which you can watch here. I cover a number of important concepts, most of which I haven’t seen discussed anywhere else. Now, more than ever, it’s critical to have a process for bypassing the noise and getting to the signal. Give the video a watch if you want to learn exactly how we do that.

The Narrative Pendulum

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Fractalized sine waves are encoded into the very fabric of our reality. Like the Golden Ratio and the second law of thermodynamics, they appear throughout the universe on nearly every level of scale and function. It’s no surprise then that they underlie the structure of our market.

This makes intuitive sense because a sine wave is just a continuously swinging pendulum. And crowd dynamics naturally follow the path of a pendulum. Swinging from one local extreme to another. 

The market is in effect a large complex information transmission system. All acting participants make bets using their particular knowledge set which then in aggregate sets the market price. This, then, provides new information for the actors to incorporate into their decision-making process so they can then make new bets. Thus, creating a neverending feedback loop of information, assessment, action, new information.  

These infinite feedback loops, when combined with group psychology and crowd dynamics, necessitate the constant back and forth we see in markets.

Each rally sows the seeds for a reversal and each reversal sows the seeds for a rally. Ad infinitum. 

Michael Mauboussin discusses how this dynamic creates a neverending process of market trends and crashes in a paper titled “Who Is On the Other Side?”. In it, he shares work done by economist Blake LeBaron which animates this concept using an agent-based model (here’s a link to the original paper). 

The model is computer generated and the “agents” are imbued with decision-making rules and objectives similar to those that drive market participants (i.e., make money, try not to lose money, don’t underperform the average for long periods, etc…) 

Here’s a section from the paper (emphasis by me): 

LeBaron’s model replicates many of the empirical features of markets, including clustered volatility, variable trading volumes, and fat tails. For the purpose of this discussion, the crucial observation is that sharp rises in the asset price are preceded by a reduction in the number of rules the traders used (see exhibit 5). LeBaron describes it this way:

“During the run-up to a crash, population diversity falls. Agents begin to use very similar trading strategies as their common good performance begins to self-reinforce. This makes the population very brittle, in that a small reduction in the demand for shares could have a strong destabilizing impact on the market. The economic mechanism here is clear. Traders have a hard time finding anyone to sell to in a falling market since everyone else is following very similar strategies. In the Walrasian setup used here, this forces the price to drop by a large magnitude to clear the market. The population homogeneity translates into a reduction in market liquidity. 

“Because the traders were using the same rules, diversity dropped and they pushed the asset price into bubble territory. At the same time, the market’s fragility rose.”

 

Really grokking this concept and understanding how this plays out in markets is critical to learning to play this game at the second and third levels and beyond. It’s the fundamental difference between being a reactionary self-proclaimed contrarian that routinely gets steamrolled by price-trends. And an effective contrarian, who knows how to read something I call the “Narrative Pendulum”, which allows you to get on and stay on the right side of the trend. 

I talk about this concept in-depth in a recent video I put together. If you’re interested in giving it a watch just click the link below. It’s free and doesn’t require anything on your end, other than just an hour of your time. But I promise the information is illuminating and will change the way you view and interact with markets in more ways than one.

Video: How To Read the Swing of the Narrative Pendulum

I’d love to hear your feedback after you’ve given it a watch. Just shoot me an email at alex@macro-ops.com with any Q’s and comments you have. I look forward to hearing from you!

Sifting For Asymmetry

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The market moves off stories. These stories are based on both the underlying fundamentals and people’s perceptions of the underlying fundamentals.

Our job as traders isn’t to try and predict where the market is going (that’s a fool’s game). Rather, it’s to identify areas of potential asymmetry.

We like asymmetric opportunities as traders because they allow us to be wrong a lot, and still make a boatload of money. And that’s the key to this game. Finding asymmetric opportunities and also creating them through trade management.

The majority of the time, assets and markets, reflect a wide range of stories (ie, people’s perceptions of the underlying fundamentals). This means the market is pricing in a wide range of potential future outcomes. When that’s the case, there tends to be little asymmetry in the price.

Asymmetry is born when a story becomes popular (ie, consensus) and it prices an asset/market to only reflect a very narrow range of outcomes.

Humans are really bad at predicting the future. Probably why Mark Twain said, “Whenever you find yourself on the side of the majority, it is time to pause and reflect.”

This is why it pays to be a contrarian.

The following three things help with identifying asymmetry.

    1. Understand the popular models/beliefs: Know the popular economic models, theories, and beliefs that people use to assess the market and understand the world. This allows you to get a feel for how the market will react to and interpret certain data and events.
    2. Know the stories: This is more art than science and it’s helped by having a firm grasp on the above. But read constantly, study the headlines, and develop a feel for the stories that are driving prices. Bruce Kovner calls this “listening to the market.”  Dominant stories are actually pretty easy to spot, the problem is is that we’re likely to believe in them too. Stories only become consensus because they’re convincing.
    3. Understand how the economic machine works: Markets and economies are complex systems. It’s impossible to “know” how things will unfold, which is why prediction is pointless. But, even complex systems follow broad-based principles. Knowing these first principles and understanding how the economic machine works a little better than the average market participant allows you to identify dominant stories predicated on faulty models/beliefs. Market prices based on faulty think = mispricings and asymmetry.

It’s not about trying to predict the future. It’s about being aware of many probable outcomes and comparing those to what the market is over/underpricing. You want positive EV, high expected value opportunities, which is (Probability of Winning) x (Amount Won if Correct) – (Probability of Losing) x (Amount Lost If Wrong).

It’s a different approach to markets than the way most do it. It’s an inversion of conventional thinking. Most try to predict where the market is going… they play the “game of being right”. We compare where the market is, to a range of where it could be, and focus on how we can be wrong a lot but still get paid.

Ray Dalio, put it best when he said, “You can’t make money agreeing with the consensus view, which is already embedded in the price. Yet whenever you’re betting against the consensus, there’s a significant probability you’re going to be wrong, so you have to be humble.”

The Perils of Too Much Information

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The other day I was flipping through Tim Ferriss’ book “Tribe of Mentors” and came across this great section from Adam Robinson. For those of you not familiar with Adam, he’s a rated chess master, founder of the Princeton Review, and now a global macro advisor to some of the world’s most successful hedge funds and family offices — amongst many other impressive things.

What Adam writes about markets in the book is pure gold. It needs to be read by everybody, printed out and taped above your trading desks and then tattooed across your forearms. It gets at a central truth of markets and what we can do as traders (aka. professional uncertainty managers) to best exploit it.

Without further ado, here’s Adam:

“Virtually all investors have been told when they were younger—or implicitly believe, or have been tacitly encouraged to do so by the cookie-cutter curriculums of the business schools they all attend—that the more they understand the world, the better their investment results. It makes sense, doesn’t it? The more information we acquire and evaluate, the “better informed” we become, the better our decisions. Accumulating information, becoming “better informed,” is certainly an advantage in numerous, if not most, fields. But not in the counterintuitive world of investing, where accumulating information can hurt your investment results.

“In 1974, Paul Slovic—a world-class psychologist, and a peer of Nobel laureate Daniel Kahneman—decided to evaluate the effect of information on decision-making. This study should be taught at every business school in the country. Slovic gathered eight professional horse handicappers and announced, “I want to see how well you predict the winners of horse races.” Now, these handicappers were all seasoned professionals who made their livings solely on their gambling skills. Slovic told them the test would consist of predicting 40 horse races in four consecutive rounds. In the first round, each gambler would be given the five pieces of information he wanted on each horse, which would vary from handicapper to handicapper. One handicapper might want the years of experience the jockey had as one of his top five variables, while another might not care about that at all but want the fastest speed any given horse had achieved in the past year, or whatever.

“Finally, in addition to asking the handicappers to predict the winner of each race, he asked each one also to state how confident he was in his prediction. Now, as it turns out, there were an average of ten horses in each race, so we would expect by blind chance—random guessing—each handicapper would be right 10 percent of the time, and that their confidence with a blind guess to be 10 percent.

“So in round one, with just five pieces of information, the handicappers were 17 percent accurate, which is pretty good, 70 percent better than the 10 percent chance they started with when given zero pieces of information. And interestingly, their confidence was 19 percent—almost exactly as confident as they should have been. They were 17 percent accurate and 19 percent confident in their predictions.

“In round two, they were given ten pieces of information. In round three, 20 pieces of information. And in the fourth and final round, 40 pieces of information. That’s a whole lot more than the five pieces of information they started with. Surprisingly, their accuracy had flatlined at 17 percent; they were no more accurate with the additional 35 pieces of information. Unfortunately, their confidence nearly doubled—to 34 percent! So the additional information made them no more accurate but a whole lot more confident. Which would have led them to increase the size of their bets and lose money as a result.

“Beyond a certain minimum amount, additional information only feeds—leaving aside the considerable cost of and delay occasioned in acquiring it—what psychologists call “confirmation bias.” The information we gain that conflicts with our original assessment or conclusion, we conveniently ignore or dismiss, while the information that confirms our original decision makes us increasingly certain that our conclusion was correct.

“So, to return to investing, the second problem with trying to understand the world is that it is simply far too complex to grasp, and the more dogged our attempts to understand the world, the more we earnestly want to “explain” events and trends in it, the more we become attached to our resulting beliefs—which are always more or less mistaken—blinding us to the financial trends that are actually unfolding. Worse, we think we understand the world, giving investors a false sense of confidence, when in fact we always more or less misunderstand it. You hear it all the time from even the most seasoned investors and financial “experts” that this trend or that “doesn’t make sense.” “It doesn’t make sense that the dollar keeps going lower” or “it makes no sense that stocks keep going higher.” But what’s really going on when investors say that something makes no sense is that they have a dozen or whatever reasons why the trend should be moving in the opposite direction . . . yet it keeps moving in the current direction. So they believe the trend makes no sense. But what makes no sense is their model of the world. That’s what doesn’t make sense. The world always makes sense.

“In fact, because financial trends involve human behavior and human beliefs on a global scale, the most powerful trends won’t make sense until it becomes too late to profit from them. By the time investors formulate an understanding that gives them the confidence to invest, the investment opportunity has already passed.

“So when I hear sophisticated investors or financial commentators say, for example, that it makes no sense how energy stocks keep going lower, I know that energy stocks have a lot lower to go. Because all those investors are on the wrong side of the trade, in denial, probably doubling down on their original decision to buy energy stocks. Eventually, they will throw in the towel and have to sell those energy stocks, driving prices lower still.”

Stanley Druckenmiller’s first mentor Speros Drelles — the man Druck credits with teaching him the art of investing — would always say that “60 million Frenchmen can’t be wrong.

What Drelles meant by that is that the market is smarter than you. It’s smarter than me. It’s smart than all of us. This is why its message should always be heeded. 60 million Frenchmen can’t be wrong…

Markets are incredibly complex which is why there’s a measurable downside to accumulating too much information, as we saw with the horse bettors. It can lead to confirmation bias and overconfidence as Adam points out.

I read a study a couple of years ago. I want to say it was done by the shared research site SumZero. I’ll have to see if I can find the link and add it to this post when I get a chance. But what this study found was that there was a significant difference in performance between short sub-500 word stock pitches and long 10-page+ writeups.

The short and sweet stock pitches outperformed their longer-winded brethren by a country mile.

German psychologist, Gerd Gigerenzer, calls this “The less-is-more Effect”. If you’d like to really dive into this then I highly recommend picking up his book “Gut Feelings”. But, essentially what the less-is-more effect refers to is that heuristic decision strategies can yield more accurate judgments than strategies that utilize large amounts of information. The way I think about this in trading and investing is that if you need 20-pages of notes to convince you to put on a trade then you shouldn’t put on the trade.

Rather, a seasoned trader should have a framework for what constitutes a good trade and a bad one. This framework is focused on the key drivers — the few essential pieces of information needed to make an informed positive expectancy bet. This should be able to fit on the back of a napkin. Literally.

Remember this the next time your scrolling through a 334 slide deck on why Herbalife (HLF) is a zero or reading through a “Macro Strategists” 75-page report on what he thinks the market is going to do over the next 3-months.

Ruthless reductionism and Occam’s Razor may make for cold bedfellows but they’ll help keep you from shooting yourself in the foot. Which, if you can avoid doing, will put you a few steps ahead of your peers.

So remember… Respect the market, seek to get just enough information, and keep things simple but no simpler (to bastardize a popular Einstein quote).