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Why The 90% Trader Failure Rate Is Good News

Tyler here.

It seems intimidating to tackle an endeavor where 90% of participants fail. The little voice whispers:

 Wow, nine out of ten people fail at this? What makes me so special then?

And yet, consider:

  • Nine out of ten small businesses fail.
  • Nine out of ten Americans can’t stay on a diet.
  • Nine out of ten Americans can’t get in the gym on a regular basis.
  • The vast majority of Americans don’t have the discipline to work from a home office.
  • That same majority lacks the basic business skills to run a corner grocery store…

Then too, consider the following in weeding out “the ninety percent:”

  • Those who trade for entertainment.
  • Those who trade because they like to gamble.
  • Those who trade because they hate their jobs.
  • Those who indulge in trading fantasies.
  • Those who trade without willingness to learn.
  • Those who refuse to admit their mistakes.
  • Those who are just plain stupid (dumb as a box of hammers).


WHY THE 90% IS GOOD NEWS

Once we move past the initial fear of the 90% barrier – the notion that “9 out of 10” is daunting – we can see that a 90% failure rate is very good news.

Why? Because of the zero-sum nature of the trading game:

  • If bad traders did not reliably lose money…
  • Then good traders could not reliably win it.
  • If the supply of bad traders dried up…
  • Then winning traders would be in trouble.
  • But the supply of bad traders is endless…

In Breaking Down A Market Edge, we explain how the mechanics of excess returns work. There’s only a set amount of alpha out there. Which means winning traders need must feast off of the errors of their inferiors in order to generate excess returns.

If this seems confusing, try thinking about it from the perspective of “who can make the fewest mistakes.” There is a collective pool of capital. The proper actions you take generate a positive expectation, which causes capital from that pool to flow towards your trading account. Meanwhile the mistakes you make generate a negative expectation, which causes capital to flow out of your trading account, back into the pool, and ultimately toward someone else. The picture is still one of a minus sum game, in which all participants compete and the house takes a vigorish — but you win by focusing deeply on the quality, clarity and consistency of your own actions. Your profits come from the 90%, but your focus is not on them… it is internal.

Good traders make money from bad traders (and bad investors)… and the supply of bad traders is endless. Human nature makes it so. For the past 100 years, the game has not fundamentally changed. The suckers will always hand over their money to the sharps.

 Livermore has been saying this since his day (via Reminiscences)

At first, when I listened to the accounts of old-time deals and devices I used to think that people were more gullible in the 1860’s and 70’s than in the 1900’s. But I was sure to read in the newspapers that very day or the next something about the latest Ponzi or the bust-up of some bucketing broker and about the millions of sucker money gone to join the silent majority of vanished savings…


It will not change for the next 100 either…

As a winning trader, your profits do NOT depend on:

  • a booming economy
  • a hot new technology
  • inside information
  • super powerful computing software
  • a secret “holy grail” trading recipe
  • a magical “genius” level talent
  • or anything of the above nature

Instead, your profits depend on the continuing presence of bad traders (the 90%) making mistakes that allow you, the 10% minority, to profit over time… and that supply will NEVER END.

So rejoice the 90% failure rate! That’s where the pile of money comes from for the sharps to harvest. As long as you don’t become part of the 90% trading will prove fruitful.

Going forward, how do you ensure that you stay in the 10% and don’t fall into the 90%?

  • Test your process! Before committing hard earned dollars to a trading program make sure properly vet your strategy. Does it make logical sense? Has it made money in the past? Do you have reason to believe it will continue making money in the future? Can you identify the sucker or group of suckers that will provide you with excess returns?
  • Continuously improve. The ‘vetting” process in trading never ends. Record your trading results, track the performance, and adjust fire.
  • Maintain emotional control. Play to win not to feel good. Emotions are a traders worst enemy, do whatever possible to control them and separate them from the trading process.
  • Never assume what you read in on a blog, textbook, of white paper is true! The trading advice might actually be helpful, but the 10%’ers will verify the claims through their own research. The 90% shortcut the process and immediately implement what they read on Fintwit or a random financial blog.
  • Join a community of like minded 10%’ers who will help you grow. Putting yourself in the company of an elite crew, will help keep your edge sharp.

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Breaking Down A Market Edge

To be an active investor, you must believe in inefficiency and efficiency. You need inefficiency to get opportunities and efficiency for those opportunities to turn into returns. ~ Michael Mauboussin

A limited amount of alpha exists out there in the trading universe. And these excess returns come from errors, missteps, and knee-jerk reactions from the market collective.

I like to think of active trading as a large poker game. Each day before the bell, traders from all over the globe take their chip stack to the exchange and bet on the returns for the day. The ones who were correct on that given day receive money from those who weren’t.

Just like in poker, luck determines performance over the short-term, but over the long-haul after many iterations and trades, those with skill over the others — those with an edge —  come out ahead. These winners earn alpha at the expense of other less skilled market participants. Succeeding in trading requires a clear understanding of edge.

In order for one trader to have an edge over the market, a market inefficiency must exist. Trading Great Ed Thorp said:

There is a market inefficiency if there is a participant who can generate excess risk-adjusted returns that can be logically explained in a way that is difficult to rebut.

Generally the more liquid the market, the less inefficient. If you’re into macro trading like us, you’re playing one of the hardest games out there. Full dedication to the craft is merely table stakes for macro traders.

Now here comes the million dollar question, how do we create a trading edge?

In his latest research paper “Who Is On The Other Side?” Michael Mauboussin, one of the world’s leading thinkers on market game theory, organizes available market edges into 4 different categories using the acronym BAIT. I’ll break them down one by one from here.

The B in Mauboussin’s acronym stands for Behavioral.

Behavioral edges come from a trader exercising superior emotional control over the market collective. These edges are extremely robust since from the dawn of markets, the herd’s emotional response to price movements has largely remained the same.

How can a macro trader effectively take advantage of behavioral inefficiencies?

This requires a careful examination of market sentiment.

This is because once the crowd has fully committed to one side — there is only one way to go, the opposite way. Mauboussin explains this concept in further detail (emphasis mine):

For a crowd to be wise, the members need to have heterogeneous views. To be more formal, consider the diversity prediction theorem, which says that given a crowd of predictive models, the collective error equals the average individual error minus the prediction diversity. You can think of “collective error” as the wisdom of the crowd, “average individual error” as smarts, and “prediction diversity” as the difference among predictive models. In markets, price veers from value when investors come to believe the same thing, or act as if they do. In other words, when investors lose diversity markets lose efficiency.

Once the market collective all agrees on a single outcome price has nowhere left to trend. “Greater fools” have all run out and there is literally no one else available to buy (or sell). To correct this market inefficiency, the price will snap back in the opposite direction. The graph below shows just how well expectations of the crowd line up with future returns. The higher the expectations the lower the future returns of equities.

We saw this play out recently in the S&P last 2018. Take a look at the graph below which shows AAII Bull-Bear Sentiment plotted alongside the SPX index.

Bullish sentiment peaked at the beginning of 2018 right before the volatility blow up. Later that same year, the market sold so hard into Christmas that bearish sentiment reached extreme (read: consensus) levels. Alex wrote about that at the time here and here.

When there was “no one left to buy” in Jan 2018, the market reversed and fell sharply. When there was “no one left to sell” in December 2018 the market turned around and embarked on an enormous rally.

Sentiment drives a significant amount of macro price action. Some traders can make money focusing on sentiment alone. It’s that powerful.

Sentiment indicators are not a panacea though. A bubble can continue growing in size and the sentiment indicator can go off the charts with it. That’s why it’s best practice to always pair price action with every type of trading edge. It keeps you from buying falling knives or selling into face ripping rallies too early.

The A in Mauboussin’s acronym stands for Analytical.

Analytical edges are created by processing publicly available information more effectively than other market participants.

Weighting information differently, updating your views more effectively or anticipating a change in the market’s narrative quicker than the majority are all examples of how one can create an analytical edge.

People incorrectly weight information due to confirmation bias and recency bias. It’s natural for traders to look for confirming evidence to back up a trade of their interest. Do the opposite to gain an analytical edge. Read the other side’s argument to red team your own trade idea.

Also, it’s easy to fall down the trap of looking at the most recent information and assuming it holds more weight going forward than other conflicting information. Just because an asset has been going up recently doesn’t mean that trend will continue. Analytical edges are created by looking at the entire picture without overweighting information from a particular time window.

Maintaining an analytical edge doesn’t end at trade entry. New information is constantly flowing in, and incorporating that into a trading view is important. Updating beliefs based on new information is called Bayesian analysis. When new data is released, price action evolves, sentiment changes, and the narrative morphs. Take these things into account.

It’s good practice to have predetermined time intervals where you check in to see if your trade thesis has strengthened or weakened. If things have changed its possible to increase your analytical edge by tweaking position size.

Finally, to stretch an analytical edge as far as possible, take a step back from the hard data and look at the market narrative.

Machines can analyze simple data sets extremely well, but they aren’t so great at evaluating market narratives. And at the end of the day, it’s the stories we tell ourselves that drive price.

The I in Mauboussin’s acronym stands for Informational.

Informational edge is one of the more obvious edges. If you knew what Apple earnings were before the market it wouldn’t be that hard to place bets the day of the earnings announcement and instantly pocket a nice chunk of change.

But technology and regulation, in particular, have mainly zeroed out this edge.

Jesse Livermore made a killing by reading the tape because price action data wasn’t widely available and not many people knew how to get it. These days everyone has that data and knows how to read a chart. Fundamental information has undergone a similar transformation. Everyone is a simple google search away from finding the key metrics to gauge a company’s health.

Government has made sure that all of this data is released in a fair and orderly manner to all market participants. Gone are the days where connected and high powered individuals could access company news before the public.

Now the new rage is alternative data. Things like satellite imagery of retail parking lots and oil tankers. Soon this information will lose its efficacy as well.

Information edge is a STRONG edge but it does not last and you need a large technical infrastructure in place to capitalize on it. Any individual or small trader is best served working on the other acronyms in BAIT. Leave the informational edges to the quant firms packed with Ph.D. data scientists.

The T in Mauboussin’s acronym stands for Technical.

Technical inefficiencies describe instances where other market participants are forced to transact in direct contradiction to their own forecast. For example, a trader sells a crashing stock even though he believes it will end up higher from the market price in 3 months time.

Common reasons for these forced transactions include laws, margin calls, fund redemptions, fund inflows, and other regulations. Technical edges often coincide with extreme market stress and they don’t last long.

In A Man For All Markets, trading wizard Ed Thorp describes how he exploited a technical edge during the 1987 stock market crash.

After thinking hard about it overnight I concluded that massive feedback selling by the portfolio insurers was the likely cause of Monday’s price collapse. The next morning S&P futures were trading at 185 to 190 and the corresponding price to buy the S&P itself was 220. This price difference of 30 to 35 was previously unheard of since arbitrageurs like us generally kept the two prices within a point or two of each other. But the institutions had sold massive amounts of futures, and the index itself didn’t fall nearly as far because the terrified arbitrageurs wouldn’t exploit the spread. Normally when futures were trading far enough below the index itself, the arbitrageurs sold short a basket of stocks that closely tracked the index and bought an offsetting position in the cheaper index futures. When the price of the futures and that of the basket of underlying stocks converged, as they do later when the futures contracts settle, the arbitrageur closes out the hedge and captures the original spread as a profit. But on Tuesday, October 20, 1987, many stocks were difficult or impossible to sell short. That was because of the uptick rule.

It specified that, with certain exceptions, short-sale transactions are allowed only at a price higher than the last previous different price (an “uptick”). This rule was supposed to prevent short sellers from deliberately driving down the price of a stock. Seeing an enormous profit potential from capturing the unprecedented spread between the futures and the index, I wanted to sell stocks short and buy index futures to capture the excess spread. The index was selling at 15 percent, or 30 points, over the futures. The potential profit in an arbitrage was 15 percent in a few days. But with prices collapsing, upticks were scarce. What to do?

I figured out a solution. I called our head trader, who as a minor general partner was highly compensated from his share of our fees, and gave him this order: Buy $5 million worth of index futures at whatever the current market price happened to be (about 190), and place orders to sell short at the market, with the index then trading at about 220, not $5 million worth of assorted stocks—which was the optimal amount to best hedge the futures—but $10 million. I chose twice as much stock as I wanted, guessing only about half would actually be shorted because of the scarcity of the required upticks, thus giving me the proper hedge. If substantially more or less stock was sold short, the hedge would not be as good but the 15 percent profit cushion gave us a wide band of protection against loss.

In the end, we did get roughly half our shorts off for a near-optimal hedge. We had about $9 million worth of futures long and $10 million worth of stock short, locking in $1 million profit. If my trader hadn’t wasted so much of the market day refusing to act, we could have done several more rounds and reaped additional millions.

Technical edges can be extremely lucrative but they don’t happen often, so you can’t rely on them for your entire trading process. They should be the icing on the cake.

There you have it Behavioral, Analytical, Informational, and Technical edges. Those are all the possible ways you can make money in the market.

Another thing to keep in mind while searching for edge is that generally the harder you worked for the edge the more robust it will be. Humans have a default mode to seek out the lowest hanging fruit. No one wants to put in extra hours at the office if they can avoid it.

That’s why, as Mauboussin notes in his paper, inefficiency is found in places where few are willing to venture and the information flow is complex.

Finally, before placing a trade think deeply about the question “Who is on the other side?”

If you can’t answer that question in a compelling and concise way, it may mean that you’re playing without an edge and engaged in a game of randomness.

If you want even more market wisdom check out our Lessons From The Trading Greats guide for free by clicking here!

2020 US Presidential Election
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Using Political Prediction Markets For Fun And Profit

Elections are interesting to us as macro traders. High-profile political election results can move the markets in a big way, Just look at how crazy the E-mini S&P’s traded during the US’s 2016 presidential election…

They had a 5.5% crash and rally when the cash markets were closed!

The magnitude of a macro market move after a political event depends on how much the results surprise traders. It works just like a stock’s earnings announcement. If results come in way above expectations the stock will rip hard. If results come in way below everyone’s expectations the stock tanks.

Up until recently, we’ve had to rely on sub-par polling models created by people who have no real money backing their predictions. These models did not give us a good indication of the true positioning of traders in the market.

Now, prediction markets like PredicIt allow us to get a glimpse of how people around the world are judging the odds of global political events (and backing those judgments with real money).

PredicIt operates based off a simple contract priced between $0.00 and $1.00. Traders have the option to either purchase “yes” or “no” shares on any given question or event. The market operates exactly like a futures market where for every “yes” contract there exists another trader holding “no.”

At the end of the event, the winners are each paid out $1.00 a share and the losers receive $0.00 a share. Leading up to the event the prices for “yes” and “no” fluctuate depending on supply and demand of the market. This floating opinion allows us to use PredicIt to assess how various political outcomes will impact markets.

Let’s look at a quick example.

PredicIt already has a market for the 2020 US Presidential Election.

If a trader thinks Trump will win again he can purchase “yes” shares on Donald for $0.30.

  • If Trump wins the trader will receive $1.00 for a net profit of $0.70
  • If Trump loses the trader will receive $0.00 for a net loss of $0.30

Now if the trader wanted to bet against Trump he could buy “no” shares for $0.71.

  • If Trump wins the trader will receive $0.00 for a net loss of $0.71
  • If Trump loses the trader will receive $1.00 for a net gain of $0.29

How does this help us handicap the actual event? It’s easy, simply take the price of the “yes” shares and use that as the implied probability of Trump getting elected. Do the opposite if you want to calculate the implied probability that Trump will not get elected.

In the Trump example, since “yes” shares cost $0.30 there’s a 30% chance that Trump goes on for a second term. There’s also a 71% chance that he will not get elected because “no” shares cost $0.71.

Here is a rule of thumb for quickly gauging the likelihood of an event using PredicIt:

  • If the “yes” shares are expensive (close to $1.00) you know that the probability of the outcome happening is high
  • If the “no” shares are expensive (close to $1.00) you know that the probability of the outcome happening is low

As the 2020 US election nears, the price of these contracts will fluctuate based on new information that materializes similar to how stock prices fluctuate based on the most recent earnings announcement.  

Once election time comes we’ll have a more clear indication of how markets will react to another Trump victory. If Trump “yes” shares come into the event cheap, then we know another Trump victory will rattle the markets since it was priced in as a low probability event.

We prefer using prediction markets over polling or bank forecasts. Why? Because in the prediction markets participants have skin in the game, while the modelers and pundits typically don’t. Without financial downside forecasts tend to suck. You need that potential for pain to get a real price on what will likely play out in the future.

Besides using PredicIt as a trading indicator it can actually be a fun way to separate the annoying political loudmouths in your life from their money. We all know a handful of people at work, on Facebook, or at the dinner table who babble on non-stop about their favorite candidate. And no matter what you say in response they won’t waver from their conviction because they are emotionally attached.

The trick here is finding someone who’s obsessed with a polarizing candidate even though that candidate is a cheap “yes” on PredicIt.

For example, let’s say this coworker, friend, or family member is adamant about Trump winning reelection and Predict it has Trump “yes” shares offered for $0.30 (30% chance of winning).

Here’s what you need to do.

  • Buy “yes” shares for Trump on PredictIt for 30 bucks.
  • Now go to the political loudmouth and bet 50 bucks against Trump. (Most people unfamiliar with betting will always accept 1:1 odds because it’s mentally simple and intuitive.)
  • Once both bets are locked in you have guaranteed yourself a $20 (minus PredictIt fees) no matter what happens with Trump
  • If Trump wins, you lose 50 bucks to your political loudmouth, but gain 70 bucks on PredicIt
  • If Trump loses, you win 50 bucks from your political loudmouth, but lose 30 bucks on PredicIt.

You can pull this arbitrage off again and again by finding more passionate Trump supporters in your circle to wager against (assuming they have no knowledge of PredicIt).

Or if you have a whale/ultra passionate person in your circle you can 10x your bet,  $500 against him, $300 on PredicIt and lock in a nice $200 for yourself — an entire free night out for a fancy steak dinner and a show with your significant other!

I’m always on the hunt for this type of stuff, it’s fun, and it helps train your mind for trading.

Just make sure before you wager your friend at 50 you can buy for cheaper than 50 on PredicIt. The lower the number on PredicIt the better the trade!

 

 

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How To Earn $1 Billion Dollars

The father of modern physics, Albert Einstein was unquestionably a brilliant mind. Not only did he change the world with his work in physics, but he was also an avid sailor, played the violin and shared this gem with the world:

Compound interest is the eighth wonder of the world. He who understands it, earns it … he who doesn’t … pays it.

In investment circles, Warren Buffett is most credited with exploiting the benefit of compounding and, at 88 years old, has obviously figured out how to do just that!

It isn’t too challenging to understand and agree with what Einstein and Buffet have taught us: anyone in the markets understands that compounding is a powerful force. But, for fun, indulge me for just a second while I run through some good ol’ fashioned numbers to illustrate the point.

A couple of assumptions before we begin. For simplicity, I am not factoring in inflation, down years, depressions, unusual returns, time away from the markets, commissions and fees, and/or anything that would make this a more robust system than it needs to be for purposes of this exercise. The goal is to not get bogged down with details, but to take a step back and see what compounding interest can build over the long term.

I started the test out at age 30 with $10,000. Maybe you started earlier and already have $10,000 saved at age 21, or over $100,000 by age 50. If you’re one of these magic unicorns, kudos! You are already well ahead of the game and on the road to billionaire status. For the rest of us, here is what my model revealed.

The math is simple: if compounding can put 10% per year back into our accounts, then in theory, all we have to do is live longer to cross that $1 Billion threshold.

In my model, starting at age 30 with $10,000 means by 151 years of age you’ll be a billionaire.  

If you want just half a billion, then you only need to live to about 144 years old! Maybe $100 Million is more your sweet spot…that’s only to 126 years old.

Interestingly you don’t actually break the million dollar mark until your 79th year.

I’m not going to lie, it is slow going in the beginning, so it’ll be hard to keep your eyes on the prize until later in life, where the numbers really start to shoot up dramatically.

If you are 44 years old with $500,000 in assets, you reach the $100m mark on your 100th birthday! And a billion by the potentially attainable age of 124 years old.

Yes, I recognize that this simplified “all you have to do” theory may sound ridiculous, but we can all agree that if you have more time to earn, then your overall assets will grow much larger. So, it isn’t a question of whether or not the math works out (it does), but instead, how long you can live while still maintaining a high quality of life?

We need a lot of time to get to the billion dollar mark, but we also need to get there in as good as shape as possible, otherwise what’s the point? Our bodies and minds must be healthy enough to enjoy that large nest egg.

In 1955 the average life expectancy in North America was 69 years of age. In 2015, 50 years later, it was 79 years old. A nearly 15% increase. Using this metric, 50 years from now, our average life expectancy may be close to 90 years old. And it’s not crazy to think that life expectancy will exponentially increase over the next 50 years as we see rapid advances in tech and healthcare.

So there is a potential to earn a billion dollars like Charlie Munger says:

Sit on your ass. You’re paying less to brokers, you’re listening to less nonsense, and if it works, the tax system gives you an extra one, two, or three percentage points per annum.

And he’d know, at age 95 he’s made a lot of money just sitting on his ass and compounding.

If we want a chance to hit the $1 Billion mark we need to stay laser focused on increasing our own life expectancy.

Here are the leading causes of death in the United States from the Center for Disease Control.

And internationally it’s fairly similar according to the World Health Organization.

Generally speaking these are common worldwide:

  • Heart Disease
  • Cancer
  • Accidents
  • Stroke
  • Alzheimer and Dementia
  • Diabetes
  • Road Injury
  • Lower Respiratory Infections
  • Influenza
  • Suicide

Knowing that we don’t have cures for most of these just yet, it is a bit hard to optimize against them; however, we have lots of information regarding known causes of heart disease, cancer, diabetes, alzheimer’s and the flu. If you are living in a world where chronic disease is inevitable, we should chat more. It isn’t.

We know that diet, negative environmental factors, sleep, exercise, and sense of purpose have been directly linked to the most common causes of death.

To achieve a $1 Billion net worth we have to pour our energy into making sure our body and mind stay healthy for as long as possible.

Dr. Peter Attia is the foremost expert on the front lines of longevity. If you are interested in learning all about his work in the field of longevity, I highly recommend you go down this rabbit hole – it is well worth the read, watch the video, and then get to Googling.

If you’d rather just read an abbreviated version, here are a few of Dr. Attia’s suggestions:

  • Fast – 12-16 hours per day is good for metabolic health and weight management and something that can be practiced everyday. I’ve been doing this for about 15 years now, off and on.
  • Fast – A more challenging fast that lasts 2-3 days. It isn’t a complete fast, it is a fast mimicking diet called Prolon which increases autophagy or simply a cleaning of the bad stuff by your cells. And finally a 4-5 day Prolon fast really increases stem cell based rejuvenation. Research this before you undertake it.
  • Eat whole foods, the stuff our grandparents would recognize.
  • Drop the sugar and keep insulin low.
  • Sleep more and sleep better.
  • Drink more water.
  • Don’t Smoke.
  • Exercise, and focus on strength/resistance training above all other forms of exercise.
  • Live for something, have a mission!
  • And if you live in the United States, stay off the Opiates.

What’s the payoff?  Well, you’ll feel better almost immediately, but you also may have a shot at compounding your face off to a $1 Billion net worth!  

In summary, start purchasing cash flow producing assets, let them compound, don’t fiddle with them, eat less, exercise more, sleep more, drive safely, and live for something! Write to me when you turn 150 and cross the $1 Billion line so we can celebrate!

Age Assets

30 $10,000.00

31 $11,000.00

32 $12,100.00

33 $13,310.00

34 $14,641.00

35 $16,105.10

36 $17,715.61

37 $19,487.17

38 $21,435.89

39 $23,579.48

40 $25,937.42

41 $28,531.17

42 $31,384.28

43 $34,522.71

44 $37,974.98

45 $41,772.48

46 $45,949.73

47 $50,544.70

48 $55,599.17

49 $61,159.09

50 $67,275.00

51 $74,002.50

52 $81,402.75

53 $89,543.02

54 $98,497.33

55 $108,347.06

56 $119,181.77

57 $131,099.94

58 $144,209.94

59 $158,630.93

60 $174,494.02

61 $191,943.42

62 $211,137.77

63 $232,251.54

64 $255,476.70

65 $281,024.37

66 $309,126.81

67 $340,039.49

68 $374,043.43

69 $411,447.78

70 $452,592.56

71 $497,851.81

72 $547,636.99

73 $602,400.69

74 $662,640.76

75 $728,904.84

76 $801,795.32

77 $881,974.85

78 $970,172.34

79 $1,067,189.57

80 $1,173,908.53

81 $1,291,299.38

82 $1,420,429.32

83 $1,562,472.25

84 $1,718,719.48

85 $1,890,591.42

86 $2,079,650.57

87 $2,287,615.62

88 $2,516,377.19

89 $2,768,014.90

90 $3,044,816.40

91 $3,349,298.03

92 $3,684,227.84

93 $4,052,650.62

94 $4,457,915.68

95 $4,903,707.25

96 $5,394,077.98

97 $5,933,485.78

98 $6,526,834.35

99 $7,179,517.79

100 $7,897,469.57

101 $8,687,216.52

102 $9,555,938.18

103 $10,511,532.00

104 $11,562,685.19

105 $12,718,953.71

106 $13,990,849.09

107 $15,389,933.99

108 $16,928,927.39

109 $18,621,820.13

110 $20,484,002.15

111 $22,532,402.36

112 $24,785,642.60

113 $27,264,206.86

114 $29,990,627.54

115 $32,989,690.30

116 $36,288,659.33

117 $39,917,525.26

118 $43,909,277.78

119 $48,300,205.56

120 $53,130,226.12

121 $58,443,248.73

122 $64,287,573.60

123 $70,716,330.96

124 $77,787,964.06

125 $85,566,760.47

126 $94,123,436.51

127 $103,535,780.16

128 $113,889,358.18

129 $125,278,294.00

130 $137,806,123.40

131 $151,586,735.74

132 $166,745,409.31

133 $183,419,950.24

134 $201,761,945.27

135 $221,938,139.79

136 $244,131,953.77

137 $268,545,149.15

138 $295,399,664.07

139 $324,939,630.47

140 $357,433,593.52

141 $393,176,952.87

142 $432,494,648.16

143 $475,744,112.97

144 $523,318,524.27

145 $575,650,376.70

146 $633,215,414.37

147 $696,536,955.81

148 $766,190,651.39

149 $842,809,716.53

150 $927,090,688.18

151 $1,019,799,757.00

 

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Emergent Properties of the Market Collective

One of the coolest things to watch in nature is a Starling murmuration.

If you’ve never seen one before then give this video a watch.

Starlings — which are small and not particularly intelligent birds — are somehow able to form these amazingly complex and beautiful airborne systems that are capable of extremely intricate flight patterns which shift and shape with near instantaneous coordination.

They do this apparently in response to threats; to thwart off and confuse predators.

I’m fascinated by systems that display emergent properties such as murmurations. Where a network operating off simple behavioral rules can emerge complex, seemingly intelligent, behavior.

Scientists have long been awed by the same and using the latest technology they’ve been able to gain a fuller understanding of exactly how Starlings accomplish this.

The following excerpt is from a paper on murmurations by Italian researchers. You can find the whole thing here (emphasis by me).

From bird flocks to fish schools, animal groups often seem to react to environmental perturbations as if of one mindHere we suggest that collective response in animal groups may be achieved through scale-free behavioral correlations… This result indicates that behavioral correlations are scale-free: The change in the behavioral state of one animal affects and is affected by that of all other animals in the group, no matter how large the group is. Scale-free correlations provide each animal with an effective perception range much larger than the direct interindividual interaction range, thus enhancing global response to perturbations.

Scale-free correlations mean that the noise-to-signal ratio in a Starling murmuration does not increase with the size of the flock.

It doesn’t matter what the size of the group is, or if two birds are on complete opposite ends. It’s as if every individual is linked-up to the same network.

The Starlings accomplish this feat by following very simple behavioral rules. Wired magazine notes the following:

At the individual level, the rules guiding this are relatively simple. When a neighbor moves, so do you. Depending on the flock’s size and speed and its members’ flight physiologies, the large-scale pattern changes.

It’s easy for a starling to turn when its neighbor turns – but what physiological mechanisms allow it to happen almost simultaneously in two birds separated by hundreds of feet and hundreds of other birds? That remains to be discovered, and the implications extend beyond birds. Starlings may simply be the most visible and beautiful example of a biological criticality that also seems to operate in proteins and neurons, hinting at universal principles yet to be understood.

A Starling murmuration is a system that is said to always be on the “edge”. These are systems that exist in what’s called a “critical state” and are always, at any time, susceptible to complete total change.

Wired writes that Starling murmurations are “systems that are poised to tip, to be almost instantly and completely transformed, like metals becoming magnetized or liquid turning to gas. Each starling in a flock is connected to every other. When a flock turns in unison, it’s a phase transition.”

What are the benefits of this emergent behavior?

The broader effective perception range combined with their existing in a constant state of criticality, provide Starlings with a strong competitive advantage for survival. The Italian researchers conclude that:

Being critical is a way for the system to be always ready to optimally respond to an external perturbation, such as a predator attack as in the case of flocks.

Individual Starlings operating off their own simple self-interested rules in aggregate create a vastly superior “collective mind” that broadens their perception range — and thus information intake — which enables them to operate in a continuously critical state. A state that’s optimal for responding to threats which helps raise their odds of survival.

You might be asking at this point, “Interesting stuff Alex, but what does this have to do with markets?”

Fair question…

Well, isn’t the market just one big collective mind?

Similar to a murmuration, the market is just the aggregation of individual actors operating off simple inputs (prices, data, narratives) in order to try and avert danger (ie, lose money on the way down or miss out on the way up).

Like Starlings, market participants instinctively key off one another. Robert Prechter, the popularizer of Elliott Wave Theory, writes in his book “The Socionomic Theory Of Finance” that:

Aggregate investor thought is not conscious reason but unconscious impulsion. The herding impulse is an instrument designed, however improperly for some settings, to reduce risk.

Human herding behavior results from impulsive mental activity in individuals responding to signals from the behavior of others. Impulsive thought originates in the basal ganglia and limbic system. In emotionally charged situations, the limbic system’s impulses are typically faster than the rational reflection performed by the neocortex… The interaction of many minds in a collective setting produces super-organic behavior that is patterned according to the survival-related functions of the primitive portions of the brain. As long as the human mind comprises the triune construction and its functions, patterns of herding behavior will remain immutable.

These simple inputs create a market that is collectively smarter than its individual constituents. It has a much broader perception range and exists in a critical state (always ready to phase shift from bull to bear regime) which allows it to more ably respond to changes in the environment.

When Stanley Druckenmiller first got into the game, his first mentor Speros Drelles — the person he credits with teaching him the art of investing — would always say to him that, “60 million Frenchmen can’t be wrong.”

What he meant by that is that the market is smarter than you. It knows more than you thus its message should be heeded because 60 million Frenchmen can’t be wrong…

Druckenmiller often says that “The best economist I know is the inside of the stock market. I’m not that smart, the market is much smarter than me. I look to the market for signals.”

We’ve known about the wisdom of crowds and the power of collective intelligence ever since Francis Galton — a British statistician and Charles Darwin’s cousin — discovered the phenomena while observing groups of people guess the weight of an ox at a county fair (the individual guesses were far off but the average of all guesses were spot on). There’s since been a significant amount of work done on the topic; The Wisdom of Crowds by James Surowiecki is a good summation of it.

But, there are a few key differences between markets and murmurations and the unique impact and limitations of crowd intelligence in financial markets, specifically.

The first is —  and this is a big one —  that markets are reflexive.

George Soros was the first to discover this truth. He wrote that “Reflexivity sets up a feedback loop between market valuations and the so-called fundamentals which are being valued.” This means that the act of valuing a stock, bond, or currency, actually affects the underlying fundamentals on which they are valued, thus changing participants perceptions of what their prices should be. A process that plays out in a never-ending loop…

This is why Soros says that “Financial markets, far from accurately reflecting all the available knowledge, always provide a distorted view of reality.” And that the level of distortion is “sometimes quite insignificant, and at other times quite pronounced.”

This means that markets are efficient most of the time except for some of the times when they become wildly not so.

The key driver between low and high distortion regimes are the combined effect of (narrative adoption + price trends + time). These three inputs all work in unison. So when there’s a narrative that becomes broadly adopted, it drives steady price trends, and when these price trends last for a significant amount of time, they then drive more extreme narrative adoption. And so on and so forth…

This positive feedback loop hits at the unconscious impulsion herding tendencies of investors and drives them to focus on trending prices in the act of valuation at the near exclusion of all other factors (ie, earnings, cash flows, valuation multiples etc…).

Most of the time, there are enough competing narratives which drive price volatility and keep the market fairly balanced.

Another major difference is that Starlings aren’t aware of the broader complex system they are an integral part of. It’s all instincts… evolutionary programming… they turn when the bird next to them does.

Whereas in markets, we can be aware of the system of which we form. We can consciously separate ourselves from the herd and view the whole objectively (at least to the best of our abilities).

This is important. Because as traders, we’re in competition for alpha with the rest of the flock. We don’t just want to turn when and where the others turn. We want to get to where they’re going before them. And to do this, we need to be able to develop a sense for where they’re headed…

Which brings us to the lesson I”m trying to impart.

The reason I’ve been chatting so much about birds, collective intelligence, and reality distortion and all that jazz… is because if we understand the signaling power of certain areas of the market, whether in a low or high distortion regime, we can eschew the need to try and predict all together and instead let the market tell us where things are headed.

I was reminded of this while listening to this Knowledge Project podcast interview with Adam Robinson. Here’s Part 1 and Part 2.

For those of you who don’t know him, Adam is a prodigy who “cracked the SAT” and created The Princeton Review. He now spends his time thinking, writing, and advising hedge funds on strategy. He’s the penultimate first principles thinker. He shared some of these principles in the above interview which we’ll cover now.

To begin with here’s Adam summarizing the lens in which he views markets (emphasis by me):

The fundamental view of investing is that you can figure out something about the world that no one else has figured out. It’s a bit like prospecting, right, gold prospecting. You can go out with your pan and find something that no one else has found. Well, the difference between investing and gold prospecting is that gold prospecting, you actually find gold that you can actually go sell, right? If you find a value that no one else has found, what makes you think… If people are irrational enough to believe that the price of gold is different from what you think it is or should be, what makes you think they’re going to become rational tomorrow? There’s that great quote by John Maynard Keynes, “Markets can stay irrational longer than you can stay solvent.” Good luck with that.

So, there’s a third way, and John Maynard Keynes said, “Successful investing is anticipating the anticipation of others.”

My approach to markets is simply this, to wait for different groups of investors to express different views of the future, and to figure out which group is right. I look for differences of opinion strongly expressed, and decide which one is right.

Whatever else you may think about the world, the world is the product of our thinking. So is the economy. So are our investments. If you think about it, an investment is nothing more than the expression of a view of the future. So when you buy Facebook, or you short the dollar-yen, or you buy gold or short US Treasuries, you are expressing a view of the future. Your view of the future can be right or wrong, and your means of expression can be right or wrong, but that’s what you’re attempting to do, right?

So, if you and I were to go to Columbia Business School or Harvard Business School right now and ask the assembled MBA students, “What is a trend?” They wouldn’t be able to define it at all. In fact, I don’t know that any investor in the world can define a trend. They can define it simplistically like this: “A trend is the continuation of a price series.” Yeah, well that’s great. What’s causing the continuation? Right? And I’ll tell you what a trend is—this is an investment trend—actually it’s true for all trends. A trend is the spread of an idea. That’s all a trend is. It’s the spread of an idea.

Adam doesn’t believe in the existence of intrinsic value but rather views markets as an evolutionary narrative continuum; where stories spawn, develop, spread, only to eventually get outcompeted and then wither and die.

This is similar to what The Philosopher said in Drobny’s The Invisible Hands which I discussed in my piece on How To Be a Smart Contrarian. Here’s the Philosopher in his own words (emphasis by me):

Market prices reflect the probability of potential future outcomes at that moment, not the outcomes themselves.

One way to think about my process is to view markets in terms of the range of reasonable opinions. The opinion that we are going to have declining and low inflation for the next decade is entirely reasonable. The opinion that we are going to have inflation because central banks have printed trillions of dollars if also reasonable. While most pundits and many market participants try to decide which potential outcome will be the right one, I am much more interested in finding out where the market is mispricing the skew of probabilities. If the market is pricing that inflation will go to the moon, then I will start talking about unemployment rates, wages going down, and how we are going to have disinflation. If you tell me the markets are pricing in deflation forever, I will start talking about the quantity theory of money, explaining how this skews outcomes the other way… People tell stories to rationalize historical price action more frequently than they use potential future hypotheses to work out where prices could be.

Adam references the work done by Everett Rogers in the study of the Diffusion of Innovations (Rogers has a book by the same title which is well worth a read). This line of study is about how the adoption of technology spreads but the work really can be applied to how everything spreads: narratives, ideas, social norms etc…

Rogers breaks down the categories of adopters as: innovators, early adopters, early majority, late majority, and laggards. Well in markets there is a similar breakdown of participants who are consistently early or late to the adoption of narratives and thus trends.

Knowing which groups are which and what their signaling means has been a critical part of Druckenmiller’s process over the years. Here’s Druck in his own words:

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.

Adam breaks down these groups as follows, from earliest trend spotters to later adopters:

    1. Metal traders
    1. Bond traders
    1. Equity Traders
    1. Oil Traders
    1. Currency Traders
    1. Economists
  1. Central Bankers

What does this mean in practical terms?

Well, metal traders tend to be the most farsighted of the group. They are usually right and early about changing trends in the economy.

Why is this?

Adam gives three reasons, “The first is, they [metal traders] are the Forrest Gumps of the investing world. Their view of the world is very simplistic. Are people buying copper? And if they are, thumbs up. All is good in the world’s economy. Great. I guess interest rates are going higher. That’s the way metal traders view the world. And if people are buying less copper, they go, ‘Oh, that’s bad. Economic slowdown’.”

Secondly, “People buy and sell copper. It’s used — it’s a thing. It’s not just a number on a screen, which is all currency traders look at. Right?” And third is time frame, “Commercial metal traders look months to years ahead. Because if you want to take copper out of the earth, it’s going to take years to open that mine, right? So, metal traders are the most farsighted. They have the simplest model of the world, and they are actually in touch with the world economy.”

In our November MIR, China is a Teacup, we pitched the case for buying US treasuries. One of the reasons why was because metal traders were signaling slowing economic growth ahead and slower growth means lower rates (bonds get bought). The trade was an easy layup…

,

Play To Win Or Go Out Like Broomcorn’s Uncle

There is a passage from a classical Chinese text, written thousands of years ago, that describes the plight of
many struggling traders today.

It’s from The Zhuangzi and translates as follows:

They are consumed with anxiety over trivial matters but remain arrogantly oblivious to the things truly worth fearing. Their words fly from their mouths like crossbow bolts, so sure are they that they know right from wrong. They cling to their positions as though they had sworn an oath, so sure are they of victory. Their gradual decline is like autumn fading into winter ­­this is how they dwindle day by day. They drown in what they do­ you cannot make them turn back. They begin to suffocate, as though sealed up in a box­­ this is how they decline into senility. And as their minds approach death, nothing can cause them to turn back to the light.

Bleak stuff indeed. So how does it apply to struggling traders?

Well, first consider there is a whole contingent of people familiar with “the rules,” yet still not satisfied with their results or where they have wound up. And when I refer to “the rules” in air quotes, I mean the stuff you will find in just about every trading book that was ever published.

Stuff like this:

● Cut your losses and let your profits run.
● The first loss is the best loss.
● Always plan your trade and trade your plan.
● Trade with the trend.

Now hold on, isn’t that stuff legitimate? Don’t all those old truisms have merit?

Sure they do. But they certainly aren’t enough ON THEIR OWN MERITS to succeed in trading. If you hang out on trading websites, or in the trading and investing section of bookstores, you will find those “truths” posted everywhere. You will hear them preached like gospel, with an implied message of profit salvation.

Yet those wise old truths sure haven’t helped the vast majority of traders who can parrot them. There are no bonus points (let alone extra profits in the trading account) for being able to recite that stuff in your sleep.

That Zhuangzhi passage reminded me of struggling traders who stick to “the old truths”… despite a perpetual track record of sub-par performance. They never do anything special, never make life ­changing profits, and never actually­­ ­­experience enough success to feel like they have truly succeeded at trading.

Let’s break down the Zhuangzhi passage sentence by sentence and see how it can apply to struggling traders.

They are consumed with anxiety over trivial matters but remain arrogantly oblivious to the things truly worth fearing.

You know the thing that is REALLY worth fearing?

Time, or rather, the loss of opportunity to learn and grow, which primarily relies on time as an input.

With time comes opportunity to learn. With opportunity to learn comes opportunity to grow… and with sufficient growth one can find the necessary breakthroughs to reach full potential.

The passage of time in the absence of real growth ­­when time is wasted spinning one’s wheels ­­is such that core lessons are never learned… core breakthroughs are never experienced… and then, time’s up!

You can always earn more capital… unless you run out of time.

That is why one might argue it is far better to blow up a few trading stakes at small recoverable levels, and learn quality lessons from the experience, than to stay at hobbyist level permanently.

By the way, regarding the strategy of blowing up early to acquire seasoning and skills — that is exactly what Paul Tudor Jones did. He understood that the point of trading small was learning the ropes in order to trade big… which meant pushing the envelope and learning from the results.

The following is from a PTJ interview in the foreword of an updated Reminiscences of a Stock Operator edition:

In the book I think [Livermore] lost his entire fortune four or five times. I did the same thing but was fortunate enough to do it all in my early twenties on very small stakes of capital. I think I lost $10,000 when I was 22, and when I was 25 I lost about $50,000, which was all I had to my name. It felt like a fortune at the time. It was then that my father flew up from Memphis and sat me down in my tiny New York City apartment and began lecturing me as lawyers do. He commanded, “Leave the gambling den behind. Come home and get a real job in a safe profession like real estate.” Of course, I did not, and the rest is history…

The thing to fear, as the young PTJ knew, was not the risk of temporary small­-stakes capital loss for the sake of a learning curve… but the danger of a boring and unfulfilling life, having turned away from the trading game before the lessons clicked.

And thus, to the degree the experienced trader continues to dabble and play footsie with markets while fearing inconsequential things, he or she might miss the thing to REALLY fear… a loss of time that means a loss of learning and a loss of breakthrough… which means never graduating to the fulfillment of one’s potential. Just being a dabbler forever… an aphorism quoter on Twitter for all time.

Continuing with the Zhuangzhi breakdown:

Their words fly from their mouths like crossbow bolts, so sure are they that they know right from wrong. They cling to their positions as though they had sworn an oath, so sure are they of victory.

These traders are “sure” they know right from wrong (in terms of what trading success consists of). They are sure it is all contained in the trading commandments they have memorized, which they then repeat dutifully and often to everyone around them. (We all know the guy who tweets the same things over and over, day after day, ad infinitum…)

These traders “cling to their positions” of “knowing” the trading rules in the sense of never examining their rigid mindset ­­never stopping and saying “Wait… perhaps I am missing something crucial here…”

They keep the faith with religious fervor. And the net result is generally as follows (Zhuangzi again):

Their gradual decline is like autumn fading into winter ­­this is how they dwindle day by day. They drown in what they do ­­you cannot make them turn back. They begin to suffocate, as though sealed up in a box­­ this is how they decline into senility. And as their minds approach death, nothing can cause them to turn back to the light.

This is not the spectacular blow­up of the short vol seller. It’s a slow churning death of small loss after small loss. The slow bleed of thousands of trades with stops placed too close… and profits too meager to move any kind of needle.

There is no graduation, no transition to meaningful size­up, no scaling to a position of strength and fulfillment… no making the light worth the candle.

There is just playing around without building… tinkering without learning… churn without growth. It’s a sort of thin­gruel persistence… a stubborn surviving, and then a fading away.

In poker there is a saying attributed to the legendary Doyle Brunson: “Going out like Broomcorn’s Uncle.”

Nobody really ever figured out who Broomcorn’s Uncle is, but the saying refers to a poker player who is so meek and conservative he simply lets himself get anted to death. He takes nick after nick and cut after cut until finally his stack is chiseled down to oblivion, like the fading dwindlers of the Zhuangzhi passage.

It’s a strange thing. If a poker player goes out like Broomcorn’s Uncle, he was playing the game ­­sitting there at the table, engaging with opponents ­­but he wasn’t actually “playing the game.”

Instead that player becomes so focused on the mere aspect of surviving… the mere angle of not losing… that he lost sight of the fact that you need courage, guts, strategic vision, and the passion to step forth and exploit victory’s bold moments ­­if you choose to play the game in the first place.

There is a sort of rigor mortis that can set in for the hobbyist trader ­­set in their ways, set in their habits and set in their permanent biases. They’ve been trading for years, so they “know” all there is to know ­­or so they think­­ because the old truths are seen as be­all end­all, and years in the saddle give them license to be cranky.

Contemplating knowledge gaps becomes a less and less palatable thing over time, because that would require admitting that knowledge gaps exist. And so they harden… but never break through… and then finally fade.

How do you avoid this fate? In a nutshell, first by remembering that taking on risk ­­at the right time and place is the whole point of trading. If you are scared to ever go for the gusto, there was no point in entering markets in the first place. It’s good to survive and not blow up… but not if the follow-­on recipe is bread and thin gruel forever!

It’s hard to do that, of course. It’s hard to control risk most of the time, then press aggressively in the opportune windows. It’s hard to scale up in windows of true opportunity, while maintaining deep patience otherwise. But this hardness is a feature not a bug, because if it wasn’t damn hard there wouldn’t be so much profit in it!

Traders who have survived but not thrived have typically learned the basics of preserving their capital. The next hard lesson is learning how to push hard when it counts… how to make the light worth the candle via size.

This is how the legends like Stan Druckenmiller produced their outsized returns. They understood the concept of the big bet and when to swing hard. Druck’s words below:

The first thing I heard when I got in the business, not from my mentor, was bulls make money, bears make money, and pigs get slaughtered. I’m here to tell you I was a pig. And I strongly believe the only way to make long-term returns in our business that are superior is by being a pig. I think diversification and all the stuff they’re teaching at business school today is probably the most misguided concept everywhere. And if you look at all the great investors that are as different as Warren Buffett, Carl Icahn, Ken Langone, they tend to be very, very concentrated bets. They see something, they bet it, and they bet the ranch on it. And that’s kind of the way my philosophy evolved, which was if you see – only maybe one or two times a year do you see something that really, really excites you… The mistake I’d say 98% of money managers and individuals make is they feel like they got to be playing in a bunch of stuff. And if you really see it, put all your eggs in one basket and then watch the basket very carefully.

And there is just no easy way to learn that. No easy way. It CAN be learned, yes of course. But the learning of it is hard. It is a hard thing. And again this makes sense. If learning how to make big bets at the right time, while maintaining risk control properly, was an easy thing, then lots of people would do it. The reason only a small handful of traders pull it off is precisely BECAUSE OF the hardness and challenge of the path.

But the payoff for doing this ­­ for trying and succeeding ­­is far more than money. The pursuit itself sings to the practitioner’s soul, and as such the vitality of the adventurous trader’s spirit does not fade. Hunter S. Thompson:

Turn back the pages of history and see the men who have shaped the destiny of the world. Security was never theirs, but they lived rather than existed. Where would the world be if all men had sought security and not taken risks or gambled with their lives on the chance that, if they won, life would be different and richer? It is from the bystanders (who are in the vast majority) that we receive the propaganda that life is not worth living, that life is drudgery, that the ambitions of youth must he laid aside for a life which is but a painful wait for death. These are the ones who squeeze what excitement they can from life out of the imaginations and experiences of others through books and movies. These are the insignificant and forgotten men who preach conformity because it is all they know. These are the men who dream at night of what could have been, but who wake at dawn to take their places at the now-­familiar rut and to merely exist through another day. For them, the romance of life is long dead and they are forced to go through the years on a treadmill, cursing their existence, yet afraid to die because of the unknown which faces them after death. They lacked the only true courage: the kind which enables men to face the unknown regardless of the consequences.

As an afterthought, it seems hardly proper to write of life without once mentioning happiness; so we shall let the reader answer this question for himself: who is the happier man, he who has braved the storm of life and lived or he who has stayed securely on shore and merely existed?

 

,

The Human Trader’s Secret Weapon

Choosing individual stocks without any idea of what you’re looking for is like running through a dynamite factory with a burning match. You may live, but you’re still an idiot. ~ Joel Greenblatt

Investing is hard.

It’s a game of relative comparisons. We have limited capital and nearly unlimited opportunities to deploy it. Our job then as traders/investors (I use the terms interchangeably but will use investor from here on out) is to use our tools to sift through the thousands of stocks, bonds, and currencies to pick and select the handful of assets we think will give us a higher return than the market. This is obviously no easy feat…

The question we get from readers more than any other is about the framework we use to identify these asymmetric opportunities. They want to know how to sift through all the noise and numbers and find the stocks that are going to make them money!

A big piece of this puzzle is by first defining what exactly it is you’re looking for so you’ll know it when you see it. Once you’ve defined it, you can create a framework and process for identifying it. Then rinse and repeat…

That’s what we’re going to do in this month’s report. We’re going to discuss the different classifications of equity investing opportunities and then focus on our favorite, that of the long-term compounder. We’ll walk you through the first principles of value investing and then go through the step-by-step process of our framework for identifying stocks with massive long-term compounding potential.

You may be asking, aren’t you guys macro traders? Why are you writing about fundamental value investing?

That’s a fair question… You see, the key point about being a macro trader is that we’re not constrained by a rigid and narrow approach to markets. Our sole guiding philosophy is to make high risk-adjusted returns using whatever means necessary.

This is a flexible and opportunistic approach. We care only about positive asymmetry and not about what tools or mental frameworks (ie, technicals, fundamentals, classical macro etc…) we need to use to find them.

In reality, nearly every investment includes some combination of different factors and drivers. The best trades are the ones where the entire Marcus Trifecta of technicals, sentiment, and fundamentals align together in a fat pitch setup.

Like a warrior going into battle we don’t see the utility in limiting ourselves to a single weapon or style of fighting. Similar to Bruce Lee’s Jeet Kune Do, we aim to use anything and everything that works to help us win.

Value investing and understanding how to discover and identify long-term compounders is an essential tool in the macro trader’s toolkit. And that’s what we’re going to give you a master class in today. We’ll conclude by using this framework to analyze two stocks that we believe have long-term multibagger potential.

And hopefully after reading this report you’ll never feel like you’re running through a dynamite factory with a burning match again…

Breaking it down to the principle level

I believe there are an infinite number of laws of the universe and that all progress or dreams achieved come from operating in a way that’s consistent with them. These laws and the principles of how to operate in harmony with them have always existed. We were given these laws by nature. Man didn’t and can’t make them up. He can only hope to understand them and use them to get what he wants. ~ Ray Dalio

Every investing framework and process we build needs to be built upon clear, simple, and universal principles. Let’s discuss what some of these are.

An investor can have any combination of the following three edges:

  1. Informational: They can be privy to information that the market is not; through proprietary data (ie, using satellites to track foot traffic at stores) or by extreme due diligence in less watched areas of the market (really digging into the micro cap space) or by less scrupulous methods (insider knowledge).
  2. Analytical: They can look at the same data but come to different and superior conclusions through greater due diligence and/or better frameworks for understanding the world.
  3. Behavioral: They have better understanding and control of their own nature and thus exploit behavioral anomalies that arise in markets largely due to short-term emotional overreactions.

We briefly touched upon in last week’s note how the informational advantage has largely been arbed away due to the wide scale availability of powerful quantitative tools and screeners and information dissemination in general. At least for the retail investor, who doesn’t have access to proprietary credit card and store receipt data, and can’t plug into their satellite that’s tracking Walmart North American store traffic, they are left with the final two edges of analytical and behavioral — we can use this fact to our advantage.

The talented hedge fund manager and value investor Scott Miller said recently in an interview that he welcomes the proliferation of quantitative investing, remarking (emphasis mine):

I actually want quantitative strategies to proliferate. I want money to pile into them, gobs and gobs of it. The more money into quant strategies the better, as I think they are likely to create distortions that I can take advantage of over time. You can have your backward looking quantitative data and use that for the foundation of your decisions. I would rather understand the product, market, and management team of the companies I am investing in.  

We agree with Scott.

Our analytical edge needs to be in seeing the same data but assembling the pieces differently, in the hopes of creating a truer representation of the underlying business and its intrinsic value.

Joel Greenblatt often mentioned in his investing class at Columbia that he believed he was only average at valuation work (he had little edge there), but where he excelled — where his edge lay — came in being able to put the information together in context; view things from the bigger picture and pinpoint the factors that really mattered.

He was quoted as saying:

Explain the big picture. Your predecessors (MBAs) failed over a long period of time. It has nothing to do about their ability to do a spreadsheet. It has more to do with the big picture. I focus on the big picture. Think of the logic, not just the formula.

He only had access to the information everyone else had but he was able to piece it together to come to a completely different and more true conclusion — develop a variant perception. This is what an analytical edge is.

So we know that our value investing framework needs to include mental models for viewing and interpreting data in a more useful way. It needs to help give us a variant perception of reality and strengthen our analytical edge.

There are a number of ways to think about the behavioral edge. One being the emotionally driven overreactions to certain events (could be a missed earnings, negative press, or a broader market selloff) that create large valuation gaps. Long-time hedge fund manager, Bill Miller, puts it like this:

The securities we typically analyze are those that reflect the behavioral anomalies arising from largely emotional reactions to events. In the broadest sense, those securities reflect low expectations of future value creation, usually arising from either macroeconomic or microeconomic events or fears. Our research efforts are oriented toward determining whether a large gap exists between those low embedded expectations and the likely intrinsic value of the security. The ideal security is one that exhibits what Sir John Templeton referred to as “the point of maximum pessimism.”

Which brings us to another foundational principle about value investing: The best value investments will always have a well articulated and very convincing logic as to why they’re priced the way they are. These bearish arguments will always be predicated on a certain amount of truth. It’s this convincing narrative that creates the large mispricing. The thing is, these narratives tend to build on themselves. As they become more popular they tend to extrapolate the negative data points on which they’re built, further and further out the left tail, driving the price lower and further away from probable outcomes.

And like Howard Marks likes to say, there’s no such thing as a good or bad stock just good or bad prices.

A value investor must use their analytical edge to develop a variant perception in order to capitalize off the market’s behavioral overreaction.

Another aspect of behavioral edge is one of timeframe. The market which is becoming increasingly quantitatively focused has gotten very good at predicting earnings 1 to 2 quarters out. But with this short-term quantitative edge, comes the loss of long-term context and so the players in the market have become more and more myopic and short-term focused.

This trend towards market myopia widens the behavioral edge for those willing to peer a little further into the future and play the long game in their investing. This is a kind of time arbitrage that allows a patient investor to capitalize on the market’s broader short-termism.

To turn back to Bill Miller who said this about time arbitrage:

For the market broadly, the recent trends are toward shorter investing time horizons and less active stock selection, which gives us confidence in our competitive advantages of long-term, actively managed investing. The average holding period for mutual funds is now down to just six months, compared to our time horizon of three to five years. We believe that the one constant in the markets is the behaviors of groups of people and the advantages provided by a focus of behavior inefficiencies. The broad features of human behavior have not changed, and social psychologists have mapped pretty well how large numbers of people behave under various conditions. We try to arbitrage between perception and reality in behavior.

Our value investing framework needs to capitalize on our behavioral edge by objectively exploiting market overreactions — letting the fundamentals dictate our actions and not be reactive to short-term price moves —  and arbitraging time by peering further into the future and being more patient with our investments.

And so we have some clear foundational principles on which our framework can be built. We need to:

  • Utilize an analytical edge to arrive at a variant perception.
  • Exploit behavioral driven market overreactions that result in large mispricings.
  • Arbitrage time by playing the long game of peering further into the future and practicing infinite patience.

Moving on…

In our quest to further define what it is we’re looking for we can bucket equity investments into two broad categories:

    1. Macro: These are trades where the primary driver of returns is from macro inputs and not due to individual stock specifics. Cyclical commodity stocks fall under this category where their returns are driven by the capital cycle and the price of the underlying commodity. Market timing and sentiment driven trades also fall under this category.
  1. Fundamental Value:  These trades are primarily driven by the conditions and valuation of the underlying company. Fundamental value trades can be bucketed further into three separate categories.
      1. Classic value: These are the deep value sum of the part investments and the classic Graham net-net plays where the investment thesis rests on the mispricing of the company’s current intrinsic valuation; a valuation which depends less on the company’s future growth and more on the price given to its current assets and earnings stream.  
      1. Special situation: These are Joel Greenblatt style anomalous mispricings caused by spinoffs or a host of other reasons. These aren’t typically long-term plays but are held until the valuation gap caused by an event is closed.
    1. Long-term compounders: These are the real money makers. These are the special stocks that grow in value exponentially over long periods of time. They are run by skilled capital allocators, typically with large amounts of skin in the game, and are companies with wide moats that allow for enduring returns above the cost of capital.

These graphs below from Hayden Capital show the different intrinsic value growth curves and stock price path.

It’s the graph over on the right hand side where we want to focus the majority of our time and which we’re going to discuss today.

Long-term compounders are the stocks that can create generational wealth — if held on to. The problem is that they can be difficult to identify a priori but that’s what we’re going to solve for today.

First, let’s start with a simple math exercise from Scott Miller that shows the incredible power of compounding.

Example:  We underestimate the power of compounding and the impact of difference in return rates over a long period of time.

Question: What is the difference in ending capital between $100K that grows at 10% for 30 years vs. $100K that grows at 20% for 30 years?

Answer: $21M+

10% -> $1,744,940

20% -> $23,373,631

$21M+ dollars is quite a lot from just a 10% difference in annual returns over a long period. George Soros and Stanley Druckenmiller are both worth billions of dollars because they compounded money at an average of 30% return over decades!

This brings us to another foundational principle in markets and the people who play in them:

Humans are inherently bad at understanding the scale of exponential growth and the power of compounding…

We’re linear creatures who think in logarithmic terms. But if we want to harness the 90/10 distribution of market returns and put the power of compounding to work then we need to think in and seek out exponential growth opportunities for our capital.

Investing in a long-term compounder is essentially like allocating your capital to a compounding wizard like Druck or Soros. You can think of these companies almost as the best private equity firms, but ones with access to niche markets and the best information and deal flow available; along with an appropriate incentive structure that creates the opportunity for extraordinary alpha.

William Thorndike’s excellent book The Outsiders is a case study of the 8 best long-term compounders and the operators who ran them. Below are graphs to show the difference in returns over long periods of time that identifying and investing in a long-term compounder, an Outsider stock, can provide.

The differences in return outcomes are extraordinary… they’re exponential…

The market’s inability to properly comprehend and analyze exponential growth is one of our biggest analytical edges. It’s the reason why you have many self proclaimed “value” guys shorting high growth stocks — stocks with super high ROICs — and essentially throwing themselves on the burning pyre as sacrificial lambs because they’re doing linear math in a geometric world *cough Einhorn cough*…

Hopefully, you now get my point about the power of long-term compounding and exponential growth and how finding these stocks can be life changing. Understanding the power of compound growth and factoring that into your value analysis makes for a big analytical edge.

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The Principle of Bubble Rotation

In the book Business cycles: history, theory and investment reality, the author Lars Tvede talks briefly about a cycle phenomenon he calls The Principle of Bubble Rotation. He writes:

There is one further common aspect of all these asset classes. We have seen that business cycles from time to time create monetary environments that are conductive to asset bubbles. However, people will recall past crashes for a while, and this means that whatever asset people bought in the last bubble will rarely be chosen for the next. This leads to a systematic bubble rotation. There was a bubble in precious metals/diamonds in 1980, for instance, and then in collectibles (and Japanese land) in 1990, and then in equities in 2000.

Essentially, what Lars is saying boils down to, “what outperformed in the last cycle will not outperform in the next.”

Since trading and investing is a game of comparisons, we evaluate all assets on a relative basis and then choose to buy one thing over another. Using The Principle of Bubble Rotation we can underweight assets/sectors/industries that may look attractive at first glance but are unlikely to outperform for the simple reason that they did so in the prior cycle.

Let’s look at the outperformers from the last cycle and see how they’ve done in the current one.

The top performing assets/sectors/industries in the 02’ to 08’ cycle were:

  • Emerging markets
  • Homebuilders
  • Financials
  • Commodities

So far each of these assets/sectors/industries have adhered to The Principle of Bubble Rotation.

The reasons why this cycle skip exists are three fold:

  1. Psychological: Investors who were burned buying into a bubble in the previous cycle are likely to be hesitant to buy into those same assets in the next. We call these “event echoes” where the psychological scarring from a jarring market event affects investor behavior well into the future. This usually takes two cycles to reset because most investing careers don’t last much longer than that.
  2. Capital Cycle: Asset bubbles are born from overoptimism. This optimism attracts capital and competition which leads to large amounts of capital expenditure into future supply. This leads to over-capacity which takes the subsequent cycle to clear.
  3. Regulatory: There’s a regulatory cycle that is always fighting the last war and which typically goes into motion following the bust process where many investors were hurt or financial instability occurred. Take banks following the GFC or cryptos following the current bust process as an example. These regulations typically take the completion of another cycle before deregulation occurs.

The Principle of Bubble Rotation isn’t a hard and fast rule. There’s examples where it didn’t hold true and certain industries are susceptible to their own unique capital cycles which affect the length of their boom/bust process.

Still, it’s a useful heuristic to use for filtering down your universe of potential trades. It would have kept you from buying financials this cycle, which has been a popular but dead money trade. Also, it would have alerted you to areas of the market that were more likely to outperform since they underperformed in the previous cycle; the technology sector being a perfect example.

 

 

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High Quality Trading Is Episodic, Not Continuous

There’s two types of market returns. Alpha and beta. Beta is what you get for diversifying and passively holding the market. Alpha is the opposite. It requires an edge, of which there are three: informational, analytical, and behavioral.

And as Ray Dalio says, “Alpha is zero sum. In order to earn more than the market return, you have to take money from somebody else.”

Harvesting alpha takes significant work because it involves separating someone else from their capital. And that someone else is trying to do the same to you. Most traders and active investors are in the game to produce alpha.

The competition among alpha players is what creates mostly efficient markets.

Once in awhile, Mr. Market throws a tantrum (or gets too excited) and a mispricing occurs. This opens up an opportunity for alpha players to profit. These opportunities often don’t last long. Other alpha players swarm to take advantage the second they detect blood in the water. Once enough catch on the market returns to an efficient state i.e. random forward returns.

Using this mental model of the game we can deduce that high quality trading is episodic, not continuous.

Trying to capture alpha continuously would be like playing every starting hand in Texas Hold’em. Expert poker players know that it’s virtually impossible to win long-term with the bottom 80% of starting hands no matter how good your post-flop play is.

In trading, it’s impossible to harvest alpha every single day. The market is highly competitive and Mr. Market rarely screws up with such high frequency.

Being a trader, you need to learn to patiently sit through long stretches of getting dealt duds. In poker we call this “sitting in Siberia.” This is when you have to sit and fold for hours and hours waiting for cards that have a positive expectation while the rest of the table has fun pushing chips into the middle. Trying to trade during these “Siberia moments” in markets is a profitless endeavor over the long haul.

Continuous trading creates subpar performance because exposure to inefficient market states get mixed in with exposure to efficient market states.

If you take the right side of the market during an inefficient state you will make money long-term. But when you initiate a trade in an efficient market your expected return is 0. And you still have to suffer through the volatility of each trade. It’s a waste of time, resources, and energy. You have to go through all of the work for no reward.

That’s why it’s important to think of trading episodically and not continuously. You don’t want to mix the good with the bad. Structure your trading similar to how a sniper goes about his business on the battlefield — a series of high impact and deadly episodic strikes.

The corollary to “high quality trading is episodic not continuous” is the rarer the market dislocation the greater the edge.

There’s a few reasons for this.

First off, an event that occurs seldomly is less understood than an event that happens frequently.

Uncertainty and confusion in the market is what creates an edge for the alpha players who are able to make sense of things.

Second, the professional quant community ignores rare events as sources of edge — which creates less competition.

Conventional quant techniques look for statistical significance. That means quants need to see lots of historical occurrence to prove that their trading methodology is legit. If there aren’t enough historical occurrences, they will write off the approach as spurious.

The ‘professional’ quant methodology guarantees that they won’t and can’t act on the highest alpha opportunities in the marketplace, leaving the lion’s share to human traders utilizing intuition and experience. Trader intuition and experience is powerful because it enables traders to identify rare alpha opportunities despite a low number of historical occurrences.

So if you’re an independent trader who

  1. Believes that high alpha trading is episodic not continuous
  2. The rarer the dislocation the more alpha

Here’s what you can do to shift your approach to produce better risk adjusted returns.

Start by weed wacking your trade “setups.”

Take the bottom 50% of your trading opportunities and cut them out. Then take the remaining trade setups and cut them by 50% again. This will align you with the philosophy of rare events (the most optimal setups) and make your trading episodic rather than continuous.

Then consider trades that make logical sense to you but don’t have many historical occurrences.

These trades will always have the fattest edge and the least amount of competition because other traders will pass them up.

Finally, expand your playing field as much as possible.

This is in line with our global macro approach at Macro Ops. Because high alpha opportunities are rare, a particular market will only generate a few quality signals a year. That puts a cap on your earning potential. The only way to make more money is to increase your discovery space. That means getting involved with other markets like currencies, rates, grains, meats, softs, volatility, crypto, energy, micro-caps and metals. Hopefully over the course of the year these markets will generate additional rare alpha opportunities that you can capitalize on.

 

 

The Distribution Of Returns
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The Distribution Of Returns & The Randomness Embedded In Them

Daily Speculations are for me (Alex) to share some quick thoughts on charts/trades I’m looking at, books and articles I find interesting, or maybe just some photos of my dog Mars. As the name states, I’ll be sharing something daily except for some days when I don’t.

As traders, one of the most important traits we can adopt is humility. We have to embrace our fallibility.

Markets are complex systems. We cannot know all the relevant variables and causal relationships. Therefore, when we make a market prediction or place a trade, we can’t truly know if the subsequent outcome occurred for the reasons we believed, for reasons we’re unaware of, or if it was all just random noise.

This presents us with a dilemma: We must act on incomplete information and then iterate off results where we can’t fully know the causes.

So we never really know if we were right for the right reasons, right for the wrong reasons (i.e., lucky), or a little bit of both. Hence the need to stay humble.

Where traders get into trouble is when they’re right a lot for the wrong reasons but they think they’re right for all the right reasons. They think they’re making money because they’re skilled but really they’re just lucky.

Nassim Taleb writes about this problem, saying:

At any point in time, the richest traders are often the worst traders. This, I will call the cross-sectional problem: At a given time in the market, the most successful traders are likely to be those that are best fit to the latest cycle.

Being aware of the randomness embedded in the distribution of markets returns keeps us from falling for the ego trap where we mistake skill for luck or information for noise. And since the two are difficult to distinguish over a short time frame, it forces us to focus on managing our risk in a way that tilts the odds for success in our favor over the longer term.

In his book Fooled by Randomness, Nassim Taleb offers a useful analogy of the “dentist investor” on the difference between noise and information. Here it is:

The wise man listens to meaning; the fool only gets the noise. The modern Greek poet C.P. Cavafy wrote a piece in 1915 after Philostratus’ adage “For the gods perceive things in the future, ordinary people things in the present, but the wise perceive things about to happen.” Cavafy wrote:

“In their intense meditation the hidden sound of things approaching reaches them and they listen reverently while in the street outside the people hear nothing at all.”

I thought hard and long on how to explain with as little mathematics as possible the difference between noise and meaning, and how to show why the time scale is important in judging a historical event. The Monte Carlo simulator can provide us with such an intuition. We will start with an example borrowed from the investment world, as it can be explained rather easily, but the concept can be used in any application.

Let us manufacture a happily retired dentist, living in a pleasant, sunnytown. We know a priori that he is an excellent investor, and that he will be expected to earn a return of 15% in excess of Treasury bills, with a 10% error rate per annum (what we call volatility). It means that out of 100 sample paths, we expect close to to 68 of them to fall within a band of plus and minus 10% around the 15% excess return, i.e. between 5% and 25% (to be technical: the bell-shaped normal distribution has 68% of all observations falling between -1 and 1 standard deviations). It also means that 95 sample paths would fall between -5% and 35%.

Clearly, we are dealing with a very optimistic situation. The dentist builds for himself a nice trading desk in his attic, aiming to spend every business day there watching the market, while sipping decaffeinated cappuccino. He has an adventurous temperament, so he finds this activity more attractive than drilling the teeth of reluctant old Park Avenue ladies.

He subscribed to a web-based service that supplies him with continuous prices, now to be obtained for a fraction of what he pays for his coffee. He puts his inventory of securities in his spreadsheet and can thus instantaneously monitor the value of his speculative portfolio. We are living in the era of connectivity.

A 15% return with a 10% volatility (or uncertainty) per annum translates into a 93% probability of making money in any given year. But seen at a narrow time scale, this translates into a mere 50.02% probability of making money over any given second as shown in Table 3.1. Over the very narrow time increment, the observation will reveal close to nothing. Yet the dentist’s heart will not tell him that. Being emotional, he feels a pang with every loss, as it shows in red on his screen. He feels some pleasure when the performance is positive, but not in equivalent amount as the pain experienced when the performance is negative.

Probability of Making Money

At the end of every day the dentist will be emotionally drained. A minute-by-minute examination of his performance means that each day (assuming eight hours per day) he will have 241 pleasurable minutes against 239 unpleasurable ones. These amount to 60,688 and 60,271, respectively, per year. Now realize that if the unpleasurable minute is worse in reverse pleasure than the pleasurable minute is in pleasure terms, then the dentist incurs a large deficit when examining his performance at a high frequency.

Consider the situation where the dentist examines his portfolio only upon receiving the monthly account from the brokerage house. As 67% of his months will be positive, he incurs only four pangs of pain per annum and eight uplifting experiences. This is the same dentist following the same strategy. Now consider the dentist looking at his performance only every year. Over the next 20 years that he is expected to live, he will experience 19 pleasant surprises for every unpleasant one!

This scaling property of randomness is generally misunderstood, even by professionals. I have seen Ph.D.s argue over a performance observed in a narrow time scale (meaningless by any standard). Before additional dumping on the journalist, more observations seem in order.

Viewing it from another angle, if we take the ratio of noise to what we call nonnoise (i.e., left column/right column), which we have the privilege here of examining quantitatively, then we have the following. Over one year we observe roughly 0.7 parts noise for every one part performance. Over one month, we observe roughly 2.32 parts noise for every one part performance. Over one hour, 30 parts noise for every one part performance, and over one second, 1,796 parts noise for every one part performance.

A few conclusions:

  1. Over a short time increment, one observes the variability of the portfolio, not the returns. In other words, one sees the variance, little else. I always remind myself that what one observes is at best a combination of variance and returns, no just returns (but my emotions do not care about what I tell myself).
  2. Our emotions are not designed to understand the point. The dentist did better when he dealt with monthly statements rather than more frequent ones. Perhaps it would be even better for him if he limited himself to yearly statements. (If you think that you can control your emotions, think that some people also believe that they can control their heartbeat or hair growth.)
  3. When I see an investor monitoring his portfolio with live prices on his cellular telephone or his handheld, I smile and smile.

George Soros once wrote, “I contend that taking fallibility as the starting point makes my conceptual framework more realistic. But at a price: the idea that laws or models of universal validity can predict the future must be abandoned.”

And market wizard Mark Weinstein would say, “Don’t be arrogant. When you get arrogant, you for sake risk control. The best traders are the most humble.”

So be humble. Take fallibility as your starting point. Be aware of the random nature of markets over various temporal cycles. Don’t mistake noise for information or skill for luck. And always focus on protecting your capital first.

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock along with your email below.

Thanks for reading,

Alex