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Arlington Value Investor Letters: Five Invaluable Lessons On Value Investing

Mr. Bean here.

There aren’t many investors compounding capital at double digits over the course of decades and those that do are already well known (i.e., that guy from Omaha). However, in a small office above a taco shop, there’s a man running a hedge fund called Arlington Value who has demonstrated the advantage in simplicity, long-term thinking, and the power of compounding.

Arlington Value doesn’t have a large team of analysts. They don’t run advanced machine-learning algorithms or exploit esoteric satellite data and there’s not a single distinguished diploma on their walls.

Yet, Arlington Value has returned 18.36% CAGR over 11.5 years and its main fund, AVM Ranger Fund, has returned a mind-boggling 37.9% return since 2008. The man behind these numbers is Allan Mecham.

I spent all of last weekend pouring over his letters (s/o to Focused Compounding for the post) and there is plenty of nuggets to share. I’ve gone ahead and whittled down Mecham’s insights into five recurring lessons from his letters (spanning from 2008 – 2017) that are worth reviewing. Let’s get started!

1. Less (Not More) Information is Better — Avoid Noise

“I disagree with the notion that more information is always better.” – 2008 Letter

This may sound tongue-in-cheek as you’re reading this from an “information source” on investing, but bear with me. Mecham is old school. He reads print newspapers and avoids the sensationalist financial news media found on TV and the internet. Warren Buffett, Walter Schloss and countless other value investors follow similar practices (i.e., Buffett doesn’t have a computer in his office).

We know successful investors practice the art of “less is more”, but why exactly do they do it? What’s the edge?

The edge is found in clear thinking and an uncluttered mind. Our brains only have so much decision making power capacity each day. Disposing that energy into numerous outlets — reading too many blogs, following too many investors, watching Mad Money — reduces our brain’s capacity to make full-powered decisions on important questions. Mecham addresses these issues in his 2010 annual letter, saying (emphasis mine),

The steady surge of information coupled with short-term performance pressures can push rational long-term investing to the brink of extinction. The easy access to information, and the snack-bar nature of consuming it, suggests that disciplining one’s temperament rivals the need for energy and action.

The less information you consume the more time you have to ponder the few critical bits that really matter.

2. Selling Great Businesses Is Almost Always a Mistake

“Selling is difficult, and my track record suggests it’s usually a mistake.” – 2010 Letter

In a perfect world, we find businesses we love with management teams that know how to allocate capital well, and then we sit. Unfortunately, a small fraction of public companies meet that criteria, and even then, it’s tremendously difficult to sit and hold. In his 2010 Letter, Mecham addressed the issue of selling, saying (emphasis mine):

My view on selling is akin to the old sports adage, ‘the best defense is a good offense’; the best sell discipline is a stingy buy discipline — which couples proper analysis with a bargain price.

Mecham highlights his disdain for selling via his example of selling Autozone in 2010 — sale he admits was a mistake.

At the time, Autozone (AZO) comprised 18% of the Fund’s portfolio (something we’ll touch on later). Mecham sold at an average price of $155.67/share. Had Mecham held his shares till year end he would’ve seen share prices climb to $272.59/share (that’s good for a 75% increase in price). Hindsight is 20/20, so it’s not the share price increase I want to highlight, but Mecham’s post-mortem analysis on AZO:

We’ve followed and owned AZO for years and admire the intrinsic qualities of the business — a leading market position, durable and counter-cyclical characteristics, strong growth prospects, and an impressive managerial record of capital allocation.

Mecham sold a business with all of these characterisitcs (albeit for another great business in BRKB) and regretted doing so. Hold on to great businesses.

3. Inactivity Is The Key To Success — Learn To Do Nothing

We favor infrequent action (and commentary), patiently waiting for exceptional opportunities. – 2010 Letter

Takeaway #3 is a corollary to the cousin above as you cannot have one without the other.

If you don’t have an ability to be patient, do nothing and wait for opportunities, you’ll never be able to hold on to great businesses. In order to achieve the powerful effects of compounding, inactivity isn’t a preferred skill, it’s a must-have.

Although value investors talk about the necessity for long periods of inactivity, the reasons for doing so are not always clear. Mecham (like most successful value managers) buys only at deeply discounted prices — normally expressed during bouts of extreme pessimism. In his 2014 Letter, Mecham discusses his important practice of sitting on his hands (emphasis mine):

Our office feels more like an abandoned library with a couple of bums loitering around. We have yet to be swayed by the virtues of analyst teams and investment meetings. We’re old school. We mostly just sit around reading, thinking, and waiting. A quip by Stanley Druckenmiller describes our process best: ‘I like to be very patient and then when I see something, go a little bit crazy.

Not only does frequent activity result in reduced performance, but it also translates into higher costs of doing business (i.e., commissions and taxes). But why is inactivity so hard? =Two major reasons come to mind: job security and measurement barometer.

There’s an aura of legitimacy around seeing someone (or a group of people) frantically engaged in work. If you’re paying someone to do a job, your mind will more likely be at ease seeing that person at work. This plays into the first reason why it’s so hard to stay inactive: job security. Most money managers are closet indexers. In other words, they hug the index as close as possible to keep clients’ assets flowing in. And if you put yourself in the shoes of the average money manager — this makes sense. It’s a much easier conversation to have with a client if their assets move in line with the index (going up or down). It’s a much harder talk to have when the market is going up and your portfolio is stagnant (or God forbid down) during the same time frame.

Along with this crutch of job security, most managers — whether through their own blight or from their clients — measure themselves on too short of a time frame. For example, if clients expect you to outperform quarterly or monthly, how will the manager base his/her decisions on investments? Quarterly or monthly measurements leads to overtrading, selling too soon and getting into riskier positions to chase incrementally higher returns over a short time frame. This third takeaway is best surmised with the following quote from Phil Carret:

Turnover usually indicates a failure of judgement. It’s extremely difficult to figure out when to sell anything.

4. Focus On The Long Term — Play For Keeps

Our ideas and policies are all structured with one goal in mind: to cultivate a culture that encourages rational decision making that ultimately leads to solid risk-adjusted returns. – 2012 Letter

If there’s one takeaway that was mentioned the most throughout Mecham’s letters, it was Number 4. Playing for keeps.

Mecham routinely stresses the importance of an owner-like mindset and its impact on long-term investing success. Not only does an owner-like mindset change the time frame as an investor, it forces you to change what you care about when looking at businesses. Focusing on long-term investing (i.e., holding businesses for decades not decimal seconds) leads to a natural decline in the level of importance you place on quarterly results (earnings “beats”), short-term headwinds and temporary compressions in earnings and margins. When you think long-term, all of that doesn’t really matter. More than that, if you keep thinking like this, you’ll start to question why others even ask for quarterly guidance.

Mecham makes this crystal clear when he discusses the long-term mind-set in his 2014 letter, writing (emphasis mine):

First and foremost, we adopt the mentality of a business owner buying for keeps. To us this means thinking about staying power, competitive threats, economics, and  comparing price to value … We don’t think quarterly “beats” are germane to intrinsic value.

In other words, changing the time frame in which you think about investments leads you to spend most of your time thinking about the above items instead of the quarterly metrics that everybody else is so focused on. Mecham drives this point home a couple pages later, claiming:

I believe the biggest difference (and our main advantage) between Arlington and the average fund is our ability to implement a framework of analyzing businesses like long-term owners.

5. Concentration (Not Diversification) Is Vital To Outperformance

The result is a concentrated portfolio that tends to be more volatile than the indices — a situation that’s not well tolerated by lay people and Wall Street alike. – 2010 Letter

The fifth and final takeaway is (arguably) the most important for investors looking to outperform the market over the long-term.

Concentration of assets is as counter-consensus as it gets within the investing community. As I’ve mentioned before, most money managers hug the index, investing in 30, 40 or 100 stocks. This is the recipe for average, something Allan recognized early on in his Fund’s existence.

Mecham keeps a concentrated portfolio of around 12 – 15 businesses. He isn’t afraid to allocate a large percentage of his Fund’s capital to a few select names. For example, we saw earlier where Mecham allocated 18% of his funds to Autozone. Even 18% pales in comparison to Mechem’s largest investment during the course of his letters. In 2011, Mecham made Berkshire Hathaway a 50% position in his Fund. That’s a five zero % position. In fact, Mecham went so far as to go on margin to purchase more shares of Berkshire Hathaway (1.5% margin cost) — leveraging up in his largest Fund position. Most run-of-the-mill managers would be on career suicide watch after a move like that. But, like Mecham illustrates, it made logical sense (emphasis mine):

Conventional fund management holds dogmatic disdain for highly concentrated positions. Needless to say, we hold a different view. To us, as a BRK owner, the contempt for concentration is acutely illogical as BRK provides ample diversity, with exposure to disparate businesses, sectors, and asset allocations.

This logic falls in line with Buffett’s old adage of adequate diversification in which he describes owning a few local businesses in your town as proper diversification. If you own a few of the best operations in town, wouldn’t that be considered properly diversified? Of course. Somehow when venturing into financial markets that same philosophy flies out the window. A portfolio of 10 – 15 strenuously researched companies bought at bargain-bin prices is as low of a risk investment strategy as they come. Mecham stresses this to his LP’s when he pens (emphasis mine):

While our focused portfolio is sometimes criticized by the financial mainstream, we think the judgements lack substance. We are a risk-averse fund looking for low-risk layup-type investments while other funds are akin to a run-and-gun offense that routinely takes a smattering of low-percentage shots.

If you want to beat the market over the long-term, you need to make concentrated bets in companies you believe will earn higher returns on their capital than the general market. Couple these concentrated bets with a long-term time horizon and steadfast determination to do nothing and you’re almost on your way to cloning Allan Mecham.

Here’s the link to all of Arlington Value’s Letters via Focused Compounding.

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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!

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Lessons From A Trading Great: Linda Bradford Raschke

I realize that I’m only human, and that I’ll always make mistakes. I just try to make them less frequently, recognize them faster, and correct them immediately!

We can thank Linda Bradford Raschke for that important bit of trading wisdom.  

Only the very best can battle the markets over the long-haul and still come out on top. Linda Bradford Raschke is one of these traders. She’s been at the game for over three decades and still manages to clean up. You probably know the name. She was featured in Schwager’s The New Market Wizards book (hers was the best chapter in your author’s opinion).

If you haven’t already I highly recommend you go and check out her latest book Trading Sardines. It’s a fantastic read, full of humor and valuable trading wisdom from a decorated veteran of the game.

Linda’s traded from all sides of the business; as a market maker in the open outcry pits, as an individual trader for her own account, as well as a fund manager for institutional investors. She’s literally done it all.

In this piece, we’re going to explore Linda’s methods, habits, and practices. We’ll breakdown how she approaches markets and the tools she’s used to make a consistent killing over the years. Let’s jump in!

Linda’s Trading Program

Linda segments her trading between four different strategies (she calls them profit centers). Each profit center has a different approach to the market so that she can diversify her revenue streams. Not all of them bring home the bacon each year, but she counts on at least one of them to make her nut for the year.

LBR Profit Center 1 — S&P Day Trading

S&P day trading is Linda’s bread and butter. 95% of this trading is in the E-mini S&P 500 futures contract as opposed to the other stock index futures like the Rut, DOW and NASDAQ. This was her original program and still to this day, her most consistent producer.

She stresses that successful day trading in the S&Ps requires contextual awareness. Do the odds favor a low to high day or a high to low day? Is it likely a trend day or a consolidation day? Getting this context right makes the trading day much easier.

Linda likes to fade the noisy fluctuations of the S&Ps as the market awaits a big economic report or FOMC release. On light volume days she likes to fade the tests of the intraday range.

But her biggest money maker is on high volume high vol trend days. Once Linda has the market by the tail she presses hard and rides her position into the close. There’s more on her big bet philosophy in the ensuing sections. Her “secret sauce” (like many of the other wizards) is knowing when to size up and “go for the jugular.”

LBR Profit Center 2 — Swing Trading

Her second profit center involves swing trading on the major futures contracts with a 1-3 day holding period. Losers get cut quickly.

For these swing trades, Linda generates entry signals based on 2-period ROCs and other momentum readings. Even with all the fancy computer equipment available, Linda still chooses to manually write down the indicator reading and closing prices for the 24+ futures markets that she tracks. Writing the data down every day helps keep her in tune with the market in a way that just following things on a screen can’t.

LBR Profit Center 3 — Daily and Weekly Classical Charting Trades

The third trading strategy generates profits using classical charting patterns with Peter Brandt style execution. Like Peter, her entry signals are discretionary but she does her best to quantify her process and patterns via ATRs, pivot points, and swing highs and lows.

To manage these trades she likes to use a trailing stop to see how much the market will give. If momentum begins to move against her, she will override the trailing stop and exit the market at the close.

She finds that her best trades come from daily swings turning up or down (false breakouts) rather than the breakouts of chart formations.

Over the course of her career, Linda has noticed that a particular market will give roughly 14-20 reasonable swings per year. Her goal is to just capture one great swing a month. If she does this then she’ll usually have a great year — provided she pulls back her aggressiveness when the market enters a period of low volume churn.

LBR Profit Center 4 — The Everything Else Bucket (Special Situations)

Linda dips into this bucket during severe market dislocations. One of her favorite trades is to fade sentiment extremes with an option structure that allows her to take the other side of consensus fear/greed while keeping her risk capped. For bullish bets she prefers the long call spread, and for bearish bets she deploys the long put spread. This keeps her risk tightly defined in the incredibly volatile market conditions that accompany extremes in sentiment.

She’ll also take seasonality trades under this bucket. Seasonality trades are generated from patterns in the commodity markets. Check out this website for more info on commodity seasonality.

The defining characteristic of this bucket is that the opportunities are rare. And because of that they are not easily modeled.

Rare opportunities usually mean fatter edges because they can’t as easily be arbitraged away by a professional quant firm that uses immense computing power to search for patterns in reams of market data.

That’s the skinny on Linda’s trading setups. But setups are only a small part of what makes a trader of Linda’s caliber. In Trading Sardines she explains how successful trading requires much more than finding a good chart pattern. It’s about having a sound process, robust research methods, solid position sizing, good market reads and a healthy lifestyle away from the trading screen.

A Strong Trading Process

In trading, a good process leads to good profits.

Linda refers to her trading as a business. She uses terms like profit centers and costs. That’s a great way to frame it because one must approach trading with the same seriousness and discipline as one would running a business.

Successful businesses keep meticulous records so they know what’s working and what isn’t. Based on this feedback the leader will adjust fire and calibrate the process appropriately.

Linda does the same for her trading.

She monitors each of her four profit centers on a quarterly basis. Her performance will come from different programs each quarter depending on market conditions. If she finds that one profit center is consistently underperforming she’ll tweak her approach until it starts producing again.

One indicator she likes to look at is trade frequency. If trade frequency for one of her programs comes in way higher or way lower than normal she knows there’s likely an execution error going on. This usually means she’s overtrading, not getting rid of losers quickly enough, or trading while sleep deprived.

We follow a similar protocol here at Macro Ops. Each quarter we review our results and segment them by market and trade strategy type. We discard what’s not working and keep what does.

Another thing all successful businesses have in place is a crisis management plan. Linda has hers for trading. If an execution error occurs she immediately corrects course, no questions asked.

Linda talks about a time where she came into the open incredibly bullish on the S&P E-minis. But instead of going long she accidentally put on a large short. Instead of monkeying around and trying to find the perfect exit to limit her losses, she immediately cut the trade and went long.

“Correct mistakes immediately” has saved Linda millions of dollars over her trading career.

On Models and System Building

Linda has her four core profit centers that work for her — but that doesn’t mean she stops refining her old edges and at the same time searching for new ones.

She is constantly scrutinizing and scouring around for new and improved approaches — the markets force you to continuously adapt or die.

Linda’s not a 100% mechanical trader but she tries to systematize as much as possible to take some mental burden off of herself so she can focus on the tape. Here’s her explaining this in Trading Sardines.

I was never a systems trader though I try to stay systematic. It is hard for me to give up the control I get with tape reading. I don’t want to give up control, period. I would like to believe my experience gives me an edge. But some people will only be able to make money following a system.

She also mentions that if you do use a system it has to be your system. This is in line with what we preach here at Macro Ops. You can’t succeed long-term blindly following somebody else’s approach. Here’s Linda again (emphasis mine).

The problem is, it’s hard to muster the necessary confidence in a system unless you develop it yourself. Systems, even ones that make 100 trades a month, can go through brutal drawdown periods. And if the system isn’t your baby, you’ll abandon it with a loss instead of adhering to it long enough to recover a drawdown.

To vet system ideas Linda is a fan of manual backtesting.

My best work came from testing by hand. I could see where a signal worked and why. I could also look at the conditions where signals failed. When testing with a computer, too much data gets lumped together. This often cancels things out and it is easy to miss the subtle nuances that lead to learning. I’ve learned more by notating signals on charts, studying when signals don’t work, looking for secondary or confirming signs, and recording seas of data by hand. There is no way I could have created my numerous nuanced tactics by backtesting and doing computer runs.

This is exactly how our resident systems trader at Macro Ops, Chris D. does his research.

He’s all about manual backtests so he can develop a feel for the signal and the underlying market. You also see ways to subtly improve things that a computer can’t catch.

Even though Linda is a discretionary trader she likes to build her trade ideas from the base of a model. Here’s why:

Most professional traders know things intuitively from experience. However, we are all subject to different cognitive biases. Models help us keep an open mind and guard against biases. They differ from mechanical systems but are an integral part of the trading process.

It’s possible to trade within the confines of a model or a framework but still allow enough flexibility so your trading is not 100% systematic. Using a model or framework to define trade ideas coupled with manual execution gives you the best of both worlds. The model keeps you from overtrading and the manual execution allows you to make adjustments depending on market conditions.

In Trading Sardines, Linda gives us some advice on how to start the modeling process. For her, it starts by asking some simple questions.

A modeling process starts out by asking simple questions. For example, what happens if you enter on a breakout of the first 15-minute bar after the opening? What is the distribution of how many ticks you can get in the next 15-minute bar? What happens if you enter on a breakout of the 15-minute bar going into the last hour and exit at MOC (market on close)? Is there a distribution pattern showing the most common time for highs and lows? The permutations are endless.

Once you discover the answers to these questions through backtesting and market research you can start to develop a real trading edge that will act as the foundation for your own profit center. Linda makes her models world-class by incorporating new information into each of her trades. This is a form of Bayesian inference — another concept we hound on again and again here at Macro Ops. Here’s Linda (emphasis mine):

Another essential step is to layer on top of our multiple model tree a form of Bayesian process. Start with the prior models and probabilities and then continuously update them as new information unfolds. One data point at a time. To go one step further, we can even weigh these new pieces of information. And as the volume of information increases exponentially, you see how easy it is to fall down a rabbit hole.

In regards to model building Linda offers up some wisdom on how to design exit criteria. She’s a fan of time-based exits.

Much of my modeling uses time-based exits. Exits on the close or the next day’s close, Exit after one hour. Exit when Europe closes. Time-based exits are not dependent on the range or volatility condition, and they are robust.

Instead of exiting based on a predetermined price target, time exits allow you to realize the full strength of the signal. Here’s more on her exit philosophy from her interview in New Market Wizards.

I’m also a firm believer in predicting price direction, but not magnitude. I don’t set price targets. I get out when the market action tells me it’s time to get out, rather than based on any consideration of how far the price has gone. You have to be willing to take what the market gives you. If it doesn’t give you very much, you can’t hesitate to get out with a small profit.

On Position Sizing and the Big Bet

At Macro Ops we’re huge proponents of the Big Bet and there’s a reason for that. All of the trading greats talk about how “going for the jugular” when the stars align with your approach to the markets.

Linda says the same thing in different words (emphasis mine).

When traders think about money management, they think about stops and trade management. But a big part of the equation is knowing when to go all in, increase the leverage and press your trading to the hilt. Load the boat. These opportunities have an increase in volume and volatility. There is no point in actively trading in a dull market. Let the market tip its hand and come to life first. And then if you are fortunate to be in the groove and know you’ve got a tiger by the tail, milk it for all it is worth. This is where the real money is made.

It’s possible to simply “get by” in trading by having an okay edge and proper risk control. But if you want to achieve market wizard status you have to know when to up size and bet big.

Linda’s first ever 7-figure day in the market came from utilizing the big bet strategy on the S&P E-mini contract (emphasis mine).

There is no more glorious feeling in the world than capturing a huge trend day. My first seven-digit day came from a short position in the S&Ps. The market was overbought, the sentiment readings showed too much bullishness, the 2-period rate of change was poised to flip down and my models lined up like a rare planetary alignment.

I had come into the day with a short side bias. When the market started selling off the opening, I added in a big way and held until the close.

I want to stress her planetary alignment comment here. Because this moment is similar to what Druck talks about when he says to go for the “whole hog” or when Warren Buffett mentions “swinging hard at the fat pitch.”

All market opportunities are not created equal which is why position size must vary depending on the expected value of the trade: EV = (Probability of Winning) x (Amount Won if Correct) – (Probability of Losing) x (Amount Lost If Wrong)

When trading a diverse set of markets like Linda it’s paramount to standardize the dollar risk of each contract so each trade risks a similar dollar amount. By not standardizing the risk between markets, the most volatile market will dominate the p&l.

Linda uses the average dollar daily range for each contract she trades in order to get all of her positions sized correctly.

Each quarter, we calculated the average daily dollar range per market. If gold had a 20-dollar average daily range over the previous 30 days, this translated into a $2,000 average daily dollar range. If the S&P e-minis had a 14-point average daily range, this is a $700 average daily dollar range. Gold sizing might be 4 contracts per million. If we had $100 million of AUM, it mean that 1 unit of gold equaled 400 contracts. In the S&P e-minis, 1 unit might be 10 contracts per million or 1000 contracts.

This is otherwise known as volatility-weighted position sizing. This ensures a trader risks similar amounts on each trade. Lower volatility instruments will need more contracts and higher volatility instruments mean fewer contracts. By sizing this way, fluctuations in highly volatile markets will equal the fluctuations in quieter markets.

In markets, there’s a time to play aggressive offense (and place the big bet), and then there’s a time to play aggressive defense. When positions move against you, Linda suggests to taking off size until you can think clearly again.

Whenever you have your back up against the wall, you have to get smaller. Reduce your size to the level where you can start trading again, because in these types of situations when there is uncertainty or unprecedented volatility, there is lots of money to be made. But you can’t do it if you are frozen or stressed, so figure out the level where you can function and trade freely again.

Taking size off when things go south will preserve mental capital and allow you to get ready to pile on again when general conditions favor your bias.

On Market Dynamics

It’s not the actual news that’s important — it’s the market’s reaction to that news that is most important to a trader.

Linda talks about this concept and gives guidance on how to best trade news driven moves.

If positive economic news is released and the market sells off on that news, this could also be perceived as an aberration. It is a divergence from what would normally be expected. But this, too, is the market’s way of imparting powerful information. In this case, it may be that there are no buyers left, or that the news has been long discounted.

Trade in the direction of the aberration. The market is never too high to buy or too low to sell.

Trading mastery requires a thorough understanding of the boom/bust process that plays out over and over again in public markets. Linda has studied the underlying dynamics of the boom/bust process to give her the confidence to trade bubbles when they are about to pop (emphasis mine).

There was a study done on price behavior when the field of behavioral finance was just coming on the scene. It simulated trading with groups of individuals who were not traders. The price of the market would always rise first. It kept inching higher until everyone had bid and there was nobody left to buy. At that point, it broke sharply with no support underneath.

To this day, this is one of the main reasons markets sell off—there is nobody left to buy.

That’s why at Macro Ops we are such huge fans of sentiment indicators. Sentiment indicators tell us when there is “no one left to buy.” Periods of extreme optimism set the stage for gut-wrenching selloffs. Linda exploits this same edge in her profit center 4 through the use of call spreads or put spreads.

On The Trifecta Approach: Combining Fundamentals and Technicals

The best traders in the game pull data and information from numerous sources to construct a trading thesis. Linda uses the “Marcus Trifecta” approach in her trading by first finding fundamental market imbalances and then entering the market via technical analysis cues.

She made tons of money trading the yen using this multi-faceted approach. Here’s an excerpt from Trading Sardines which describes the trade in more detail (emphasis mine).

The “carry trade” was a popular strategy from 2002-2007. Investors borrowed money in yen where interest rates were low and invested it in higher-yielding currencies. It was a crowded trade, meaning too many people were in this same position. What was going to happen when people needed to unwind?

I trade by technicals since I have not yet had much luck using fundamentals. But I am aware when there is a market imbalance implying a crowded trade. The yen was a ripe situation. It has left a bear trap or false downside breakout on the weekly charts. I tried twice to put on a position, both times unsuccessful. The third time I knew I got it right. It was our signal to load up. I don’t mind trying a few times if there is a basis for a position but the timing is off. The real key is to make it pay and use maximum leverage when the trade starts working. I told Judd to keep buying yen, and the ensuing rally made our year. The yen went straight up for the next five years as global interest rates came crashing down.

On Trading Lifestyle

Grinding an initial capital stake into millions of dollars takes time. Fortunes aren’t made overnight in the trading business. The big money is made by finishing the marathon, not the sprint.

Linda makes this clear and lays out many lifestyle strategies that maximize your chances of making a  real fortune from trading the markets.

She used the following three things over her long career to keep her mind and body fresh and ready to battle the markets day in and day out.

  • Gratitude practice
  • Physical fitness
  • Time off

The markets are volatile beasts which mean they will send your emotional brain into a whirlwind. In order to combat the push/pull of these emotions, Linda uses a gratitude practice to keep her grounded when things go wrong.

Gratitude is a key ingredient of success. It means that even when bad things are happening, you always have something to focus on. Just like pilots have a gauge to make sure they can still tell which way is up, gratitude keeps me from ever feeling upside down. When you are trading the markets, you have to have a separate source of happiness —- to know that there are still wonderful things all around, most of which do not require money. It is easier to take risks when you remove your personal happiness and well-being from the equation.

Gratitude leads to optimism, and a positive attitude is 90% of the game.

Linda was extremely active in the gym and even competed as a bodybuilder! The discipline required for her to compete in bodybuilding carried over into her trading program.

Trading and physical training have a lot in common. Every successful training routine requires the following:

  • A sound methodology
  • Consistent execution of that methodology through the use of daily rituals
  • Records of progress
  • Positive thinking and optimism

These are the exact same things needed to succeed in the trading grind! So if you aren’t already, get in the gym!

Finally, Linda recommends taking time away from the trading screens to refresh and recharge. A hobby helps to relieve stress. For her, this was horseback riding.

LBR has the whole package of a legendary trader — a burning desire to win, emotional fortitude to withstand the ups and downs of a trading career and the ability to “go for the jugular” when the market required it.

I want to end this piece with her advice on how to find success as a new trader (emphasis mine).

Understand that learning the markets can take years. Immerse yourself in the world of trading and give up everything else. Get as close to other successful traders as you can. Consider working for one for free. Start by finding a niche and specializing. Pick one market or pattern and leam it inside out before expanding your focus.

Finally, remember that a trader is someone who does his own work, has his own game plan, and makes his own decisions. Only by acting and thinking independently can a trader hope to know when a trade isn’t working out. If you ever find yourself tempted to seek out someone else’s opinion on a trade, that’s usually a sure sign that you should get out of your position.

Well said Linda… Now time to get to work!

If you liked this article, you will love Lessons From The Trading Greats Volume 1 which has more insight from the world’s best traders. Click here for a free copy!

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Investing in Shipping Stocks: Lessons from Walter Schloss

He knows how to identify securities that sell at considerably less than their value to a private owner; And that’s all he does … He owns many more stocks than I do and is far less interested in the underlying nature of the business; I don’t seem to have very much influence on [him]. That is one of his strengths; No one has much influence on him.

Those words, spoken by Warren Buffett, describe one of the greatest value investors of all time. No, Buffett isn’t referring to his longtime business partner Charlie Munger nor his famed teacher Benjamin Graham.

The investor is Walter Schloss.

Schloss is a wellspring of value investing wisdom.

Over the course of this piece we’ll dive into Schloss’ principles for investing. His ideas on portfolio construction. And we’ll finish with applying these lessons learned to analyzing shipping stocks. An industry we’re particularly bullish on at the moment.

Battlefields to Balance Sheets

Schloss enlisted in the US Army Signal Corps at the end of 1945 after his stint as a runner on Wall Street. Before being shipped overseas, Benjamin Graham offered Walter the opportunity to join his firm, Graham-Newman Corporation, as a security analyst. Schloss accepted the offer after returning from service and quickly learned the ropes of value investing through real-world applications of Ben Graham’s classroom teachings.

After working under Graham for nine years, Schloss opened up a one man shop, Walter J. Schloss Associates.

As the saying goes, the rest was history.

Schloss took his original partnership money and spent the next 32 years compounding capital at 16.4% annually compared to the S&P return of 9.8%.

Schloss accomplished this impressive feat while operating out of a small room (Warren Buffett referred to it as, “a portion of a closet”) at Tweedy, Browne’s offices. He didn’t use a computer or a team of analysts. Just a monthly paper subscription to Value Line. He was the embodiment of a spartan approach to investing.

How was Schloss able to compound capital at such high rates over such a long period of time? What was his secret sauce?

Schloss kept a low profile (similar to the Chandler Brothers) and routinely shied away from press coverage or interviews with journalists for the majority of his career. However, as he got older, he started sharing his wisdom in the form of articles and speaking events. Through these sporadic public appearances we can get a better picture of just who this man is and how he invested in markets.

Investment Philosophy: Buy Stocks Like Groceries, Not Perfume

Like other successful investors, Schloss followed a simple yet robust approach to amass his fortunes. This approach can be surmised in the following bullets:

  • Start with beaten-down losers, the 52-week lows and companies with temporary issues.
  • Don’t lose money.
  • Avoid debt like the plague.
  • Try to buy stocks that manufactured products while sporting long histories of operations (20+ years).
  • Focus on assets rather than earnings, citing the claim that earnings aren’t as predictable as assets on the balance sheet.
  • Avoid talking to management.
  • Read the entire annual report and familiarize himself with the basics of each business he bought.
  • Purchase hundreds of stocks, keeping a well diversified portfolio.
  • Exhibit around 25% turnover — i.e., holding period of four years.

Above all else, Schloss didn’t want to lose money. He had a tremendous respect for his limited partners’ trust in his ability to manage their capital, and did everything in his power to limit his losses. Schloss had a tremendous grasp on the psychology of the average investor and frequently used it to his advantage. During an interview with Barron’s in 1955, Schloss said (emphasis mine),

They [stocks] tended to be ignored by the public because they didn’t have any sex appeal, there wasn’t any growth — there was always trouble with them. You were buying trouble when you bought these companies … Basically, it’s a contrarian philosophy, and people really like buying things that are doing well.

I wish Schloss was more complicated — it would help me get more pages out of the piece — but that’s really all there was to it.

He would fish in the ponds that looked like radioactive cest-pools, hold on to the ones that were the cheapest and sell when he had at least a 50% gain.

Schloss was so focused on not losing money, he often left a lot of meat on the bone — something he was perfectly fine with. In that same Barron’s article Schloss examined that,

One of the tricks of this business is to keep your losses down and then, if you have a few good breaks, the compounding works well for you.

These simple principles guided Schloss’ stellar 16.4% net annualized return.

Along with the above fundamental tenants, Schloss offered investors 16 rules, which he called Factors Needed to Make Money in the Stock Market. As with most rules / checklists, it’s not the points themselves that matter, but the individual’s ability to stick to the rules. The rules are attached at the end of this piece. I encourage you to print it out and keep it by your desk, laptop or wherever you do your investment work.

If you would like free access to my value investing checklist click here! 

Qualitative Aspects Don’t Matter

Walter Schloss didn’t care about the qualitative aspects of the business when he invested — something attributed to his inability to judge management’s acumen — and focused only on the numbers. This flies in the face of many value investors’ creeds that claim management and incentives matter amongst other areas like marketing and customer acquisition cost. There was a reason why Schloss preferred to invest this way: it helped him sleep at night.

Unlike Buffett, Schloss made a point of not talking to management or factoring them in at all. His reason was that good management would eventually show up in a higher stock price and a higher multiple

This makes sense if you’re buying the assets of a business rather than their earnings and future growth prospects. You don’t need to know how management will grow earnings and reinvest their capital if you’re investing because its asset value per share is higher than what you’re paying on the open market.

Applying Schloss’ Methodology to Shipping Stocks

Equipped with this knowledge of Schloss’ methods and criteria for investing in public companies, we can construct a framework to help us analyze shipping stocks.

Shippers represent a perfect harmony for the type of companies Schloss would be interested in buying: cyclical lows, asset heavy businesses trading at steep discounts to liquidation values. Let’s go through a few of Schloss’ 16 Rules and see how we can apply those directly to the messy, “road-kill” industry of shipping.

Rule 1: Price is the most important factor to use in relation to value

Shipping stocks are stupid cheap with prices for a majority of these companies trodding around all-time-lows. No matter how you look at shipping companies its undeniable that on a purely quantitative measure, they’re selling for pennies on the dollar.  

That’s not to say that qualitatively there are issues — i.e., bad management, low growth prospects — but on price alone, Schloss would be interested.

Rule 4: Have patience. Stocks don’t go up immediately.

I was asked via email from one of the MO members about the difference between being early vs. being wrong — and how can I tell the difference?

Schloss is frequently quoted for buying stocks “on a scale”; as share prices fell he would buy more. This is where patience comes in. Schloss reminds us that stocks don’t go up right after you buy them — especially if you’re buying the troubled, “ick” factor stocks that Schloss made his fortune on.

Having the patience to endure a short-term selloff in share prices cannot be understated. Schloss would not have generated the returns he did if he sold quickly after share prices went against him (remember his 25% turnover rate!).

Rule 6: Don’t be afraid to be a loner but be sure that you are correct in your judgement. You can’t be 100% certain but try to look for weaknesses in your thinking. Buy on a scale and sell on a scale up.”

When investing in Schloss-type stocks, you will by default be a loner. You can’t have one without the other. Shipping stocks are at all time lows because the industry isn’t experiencing that inflow of serious capital … yet.

We know the thesis for why the shipping industry will probably heat up over the next two years, but Schloss tells us that knowing our judgement isn’t enough. Schloss encourages us to look for weaknesses.

What does this look like?

Try Googling the bearish thesis for the shipping industry and compare it its bullish cousin you’ve subscribed to. This is called Red Teaming your thesis.

Is there anything you missed in your initial assessment? Can you identify major weak points to your thesis? Are there any biases possibly clouding your judgement etc…

Buying on a scale allows us to account for our inability to time when the market will become less irrational. Schloss wouldn’t take his full position all at once because he knew the stocks he bought were in trouble, and they were likely to fall further.

Selling on a scale works for the inverse reason as buying on a scale — the stock could keep going up as you unload your position, giving you incrementally higher profits as opposed to dumping the entire position at once.

Rule 10: “When buying a stock, I find it helpful to buy near the low of the past few years. A stock may go as high as 125 and then decline to 60 and you think its attractive. 3 years before, the stock sold at 20 which shows that there is some vulnerability in it.”

Following the vein of Rule 1, Rule 10 provides the investor with an increased margin of safety when making their initial investment. According to Schloss, If buying a stock at its 52-week low is good, buying a stock at its all-time low is even better.

The good news for investors is that the majority of companies in the shipping industry are trading at all time lows.

Once again, these stocks have problems (whether industry specific, company specific or a combination) they’re currently dealing with. Buying these companies at all-time lows helps us sleep at night.

Rule 11: “Try to buy assets at a discount rather than earnings. Earnings can change dramatically in a short time. Usually, assets change slowly. One has to know how much more about a company if one buys earnings.”

Schloss focused only on the balance sheet and the assets that could be liquidated for cash. Applying this to the shipping industry gives us an easier framework for analysis. We don’t have to understand management and the intricacies of the businesses if the company is selling at below half its net asset value measured by the active secondary scrap market.

Putting Words Into Action: Next Steps

How do Schloss’ principles coupled with the value opportunity in the shipping industry play out in real time? What are actionable steps to take if you want to invest in these shippers?

The plan itself is simple in theory — but like Schloss’ rules — hard to follow:

1) Find a basket of the cheapest shipping stocks with the greatest margin of safety / discount to fair value

2) Allocate a specific amount of your portfolio to this basket of stocks and

3) Forget about them for 1-3 years.

Conclusion

Walter Schloss stuck to his rules and stayed in his well-defined lane. And by doing so, he generated “super-investor” level returns.

I’m not saying you need to do a full 180 on your current strategy in order to generate Schloss-like returns, but I am advocating for an appreciation of Schloss’ tactics — and consider adding a few tools to your investment toolkit.

(** all information for this report was sourced via www.walterschloss.com **)

Walter Schloss’ 16 Rules

 

  1. PRICE IS THE MOST IMPORTANT FACTOR TO USE IN RELATION TO VALUE

 

  1. TRY TO ESTABLISH THE VALUE OF THE COMPANY. REMEMBER THAT A SHARE OF STOCK REPRESENTS A PART OF A BUSINESS AND IS NOT JUST A PIECE OF PAPER.

 

  1. USE BOOK VALUE AS A STARTING POINT TO TRY AND ESTABLISH THE VALUE OF THE ENTERPRISE. BE SURE THAT DEBT DOES NOT EQUAL 100% OF THE EQUITY. (CAPITAL AND SURPLUS FOR THE COMMON STOCK).

 

  1. HAVE PATIENCE. STOCKS DON’T GO UP IMMEDIATELY.

 

  1. DON’T BUY ON TIPS OR FOR A QUICK MOVE. LET THE PROFESSIONALS DO THAT, IF THEY CAN. DON’T SELL ON BAD NEWS.

 

  1. DON’T BE AFRAID TO BE A LONER BUT BE SURE THAT YOU ARE CORRECT IN YOUR JUDGMENT. YOU CAN’T BE 100% CERTAIN BUT TRY TO LOOK FOR THE WEAKNESSES IN YOUR THINKING. BUY ON A SCALE DOWN AND SELL ON A SCALE UP.

 

  1. HAVE THE COURAGE OF YOUR CONVICTIONS ONCE YOU HAVE MADE A DECISION.

 

  1. HAVE A PHILOSOPHY OF INVESTMENT AND TRY TO FOLLOW IT. THE ABOVE IS A WAY THAT I’VE FOUND SUCCESSFUL.

 

  1. DON’T BE IN TOO MUCH OF A HURRY TO SEE. IF THE STOCK REACHES A PRICE THAT YOU THINK IS A FAIR ONE, THEN YOU CAN SELL BUT OFTEN BECAUSE A STOCK GOES UP SAY 50%, PEOPLE SAY SELL IT AND BUTTON UP YOUR PROFIT. BEFORE SELLING TRY TO REEVALUATE THE COMPANY AGAIN AND SEE WHERE THE STOCK SELLS IN RELATION TO ITS BOOK VALUE. BE AWARE OF THE LEVEL OF THE STOCK MARKET. ARE YIELDS LOW AND P-E RATIOS HIGH. IF THE STOCK MARKET HISTORICALLY HIGH. ARE PEOPLE VERY OPTIMISTIC ETC?

 

  1. WHEN BUYING A STOCK, I FIND IT HELPFUL TO BUY NEAR THE LOW OF THE PAST FEW YEARS. A STOCK MAY GO AS HIGH AS 125 AND THEN DECLINE TO 60 AND YOU THINK IT ATTRACTIVE. 3 YEARS BEFORE THE STOCK SOLD AT 20 WHICH SHOWS THAT THERE IS SOME VULNERABILITY IN IT.

 

  1. TRY TO BUY ASSETS AT A DISCOUNT THAN TO BUY EARNINGS. EARNING CAN CHANGE DRAMATICALLY IN A SHORT TIME. USUALLY ASSETS CHANGE SLOWLY. ONE HAS TO KNOW MUCH MORE ABOUT A COMPANY IF ONE BUYS EARNINGS.

 

  1. LISTEN TO SUGGESTIONS FROM PEOPLE YOU RESPECT. THIS DOESN’T MEAN YOU HAVE TO ACCEPT THEM. REMEMBER IT’S YOUR MONEY AND GENERALLY IT IS HARDER TO KEEP MONEY THAN TO MAKE IT. ONCE YOU LOSE A LOT OF MONEY, IT IS HARD TO MAKE IT BACK.

 

  1. TRY NOT TO LET YOUR EMOTIONS AFFECT YOUR JUDGMENT. FEAR AND GREED ARE PROBABLY THE WORST EMOTIONS TO HAVE IN CONNECTION WITH PURCHASE AND SALE OF STOCKS.

 

  1. REMEMBER THE WORK COMPOUNDING. FOR EXAMPLE, IF YOU CAN MAKE 12% A YEAR AND REINVEST THE MONEY BACK, YOU WILL DOUBLE YOUR MONEY IN 6 YRS, TAXES EXCLUDED. REMEMBER THE RULE OF 72. YOUR RATE OF RETURN INTO 72 WILL TELL YOU THE NUMBER OF YEARS TO DOUBLE YOUR MONEY.

 

  1. PREFER STOCK OVER BONDS. BONDS WILL LIMIT YOUR GAINS AND INFLATION WILL REDUCE YOUR PURCHASING POWER.

 

  1. BE CAREFUL OF LEVERAGE. IT CAN GO AGAINST YOU.

 

If you want access to my personal value investing checklist click here to secure your free copy!

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The Danger of “Vision macro” and How to Avoid It

“Our knowledge can only be finite, while our ignorance must necessarily be infinite.” ~ Karl Popper

Something that’s helped me in my trading journey is adopting the practice of multivariate critical thinking (MCT).

MCT is the application of considering multiple hypotheses and then dispassionately applying critical judgment to each. It requires updating the probabilistic weighting for each, as new information becomes available — practical Bayesian analysis.

This seems simple and easy, and on the surface it is, or at least should be. But the difficulties come in its application. Specifically concerning the “dispassionate” part.

The problem is — at least it was for me — is that we’re naturally linear thinkers inhabiting a non-linear world. And to top things off, we have a stubborn ego-sensitive brain that wants simple answers and to always “be right”.

It’s a tough circle to square for sure. But not impossible.

If you wonder if you suffer from ego dominated linear thinking (let’s call this EDLT), just think back to the last time you were wrong on a trade or a market call. And ask yourself, did you get upset? Did you not enjoy the process of “being wrong”? Did the most dangerous four-letter word in trading, “HOPE”, become a part of your thought process? If the answer is yes, and it will be for the majority of people, then you’re practicing our instinctual EDLT.

When operating in EDLT mode the brain latches onto a hypothesis and then focuses in on “being right”. It doesn’t do this through objective assessment but rather by employing a tool kit full of anchoring, confirmation biases, and heuristics to cherry-pick information that supports it in “being right”.

The irony is that by focusing on “being right”, we more often than not end up “being wrong”.

This is an important habit to break. Doing so leads to better outcomes.

Practicing MCT is invaluable because it focuses the brain on finding the errors in its own logic. Because the brain no longer has to defend a single thesis but instead is forced to continuously analyze and weight numerous possible outcomes. Which switches its focus from trying to “be right” to figuring out how it’s wrong. This makes you better at “being wrong”. And being better at “being wrong” is vital to making money.

The trader who most fully practices MCT is George Soros. He said the following about this process:

The Secret to my success is that I’m always wrong. I’m ALWAYS wrong. And I try to correct my mistakes. That’s the secret of my success.

And

My approach works not by making valid predictions, but by allowing me to correct false ones.

Most read these statements from Soros and think he’s being glib. That’s because they’re playing the “being right” game. They’re too busy looking for some “secret” that’s going to help them “be right” more. But all they need to do is “invert, always invert!” their thinking process.

Soros adopted this unnatural mode of analyzing the world from philosopher Karl Popper. Popper established the epistemological philosophy of critical rationalism. He took these ideas from David Hume, who took them from Pyrrhonian skepticism, which evolved out of the ancient school of Indian Philosophy, Carvaka. At the foundation of all of these schools of thought is that “nothing can be known for certain”.

Since nothing can be known for certain we need to be good at being uncertain. The MCT framework helps us to do do just that. The Philosopher from Drobny’s The Invisible Hands discusses how this works (emphasis mine).

I try to develop a hypothesis about how the world is working and how it could work in the future. Therefore, information to us is a collection of theories and ideas, together with evidence that either supports or falsifies these theories and ideas. Information can come from fundamental economic drivers, such as growth, inflation, and other variables, or it can come from more technical, market-based factors such as flows, liquidity, etc.

We are not engaged in what I describe as “vision macro,” whereby one tries to work out some kind of single truth about how the world works. Rather, we form a probabilistic set of hypotheses about how the world could look and what might drive markets going forward, focusing on the market impact in all scenarios and looking for good risk-versus-reward trades around these hypotheses.

“Vision macro” is standard EDLT. There’s plenty of examples of EDLT thinkers in the finance space; they are a dime a dozen on the fintwit. Their modus operandi is to lock onto a “single truth” and become a torchbearer for that narrative. They make themselves champions for their “truth”. As a result, they blind themselves stupid and end up fighting the market for LONG periods.

The old Wall St. adage that it’s not about being right but about making money is an adage for a reason. You only need to be “right” at the right time and the way to do that is by being good at “being wrong”. Critically assessing multiple hypotheses with MCT is the way you get there.

EDLT is centered around seeking out confirming evidence. MCT looks for disconfirming information. EDLT is fragile while MCT is robust. Most people utilize the former because practicing the latter is tough.

If you find yourself latched onto a “single truth”, Karl Popper would ask you “how would you disprove yourself?”

Drop the search for grand narratives and invert your thinking.

Final call for the Macro Ops Collective! After tonight at midnight we’ll be shutting enrollment down until the summer.

If you would like to receive all of our premium research, stock picks, macro trades, and be apart of the most elite macro trading community on the net sign up now before midnight.

All purchases come with a 60-day money back guarantee so there’s no risk to join. Come check it out!

Click here to enroll in the Macro Ops Collective!

2020 US Presidential Election
,

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!

 

 

,

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

 

,

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…

,

Trading During 9/11 Attacks And Why I Became A Systems Trader

The S&P 500 was down. Really down. Down hard. Then I heard the news on CNBC behind me.

“Another plane just crashed into the World Trade Center.”

I was short the S&P 500 E-mini futures. My system had me short. I had no idea what was causing the S&P to fall so much up to this point, and it had been falling since the May highs of $1320. I had been aggressively short selling since $1209 on August 8th, 2001.

The market had been selling off since March of 2000, the dot com bubble had burst, and we were generally in a bear market, trending lower and lower. By the summer of 2001, we had already sold off about 30% from the highs, officially entering bear market territory; but the buzz from the roaring tech bubble bull market was still a star in everyone’s eye. We all wanted that big dip buying momentum to return.

Spoiler: it didn’t.

When the news hit CNBC on September 11, 2001, I was already profitable well over 100 points on my short position. Each point in the E-mini S&P 500 is worth $50 per contract (multiply that by how many contracts you have), so I was well positioned at this point, with massive profits.

When I woke up that morning I had no idea what was happening. I checked my screen’s as I did back then when I first woke up (see my post from last week about my “new” morning routine); futures were down again, my trade was working, and I was ecstatic. This was the first time I had built such a massive position and it had played out. I thought about taking some profits, but held true to course as my system kept telling me to stay in.

I had a plan, but I wasn’t really sure exactly how to navigate these waters. This was unprecedented. I was in disbelief watching what was happening on TV, watching my screen as the market went “limit down,” and watching as the entire world stopped trading.

(Note: Limit Down means that the exchanges stop trading for a period of time to let things cool off a bit before trading can commence again. This event was so big that the market continued with this closure for another four days – the longest duration in modern history.)

As anyone around during that time remembers, prior to 9/11 the market had been selling off, and was selling off hard. I kept getting more and more indicators to add to my short position, so I kept adding. I had the maximum position allowed for me at that time.

There I was: massive profits thanks to a huge short position that my technical analysis had “predicted.”

I did everything according to my trading plan. I had proper position sizing. I increased my position as new levels were breached. Everything was “by the book,” minus the World Trade Center collapsing on live TV right before my eyes.

Other planes were still in the sky., The Pentagon got hit. This was unprecedented fear and chaos.

While trading was halted, there was nothing I could do but watch, and worry.

Where would they attack next?

Were there more planes out there ready to attack?

Would my location (Los Angeles) be hit?

Was it safe to leave? Should I go get food? Was anyone working today?

All I could do was watch live news coverage and listen to people speculate as to what might happen next.

The next four days, while the markets were closed, we all just watched and waited for more information.

Traders talk to each other day in and day out about the market, market analysis, market news, and what they think will happen. We speculated when trading would resume, how far the market would plummet before it was opened again, and if the government would intervene and support the market by buying everything until it stopped selling (aka the rumored “Plunge Protection Team”).

No one knew anything.

We started building out plans for the “what if” scenarios.

What if…when trading opens they only allow single contract trades, so I can’t cover my position quickly?

What if…the market is down 1,000 points on the open? Do I cover?

What if…the market is up 1,000 points on the open and I can’t cover in time?

What if…the market is open, but no one is trading, and I can’t cover my position?

What if…they don’t open the market until 2002?

On Sept 17th, they did re-open the market. The New York Stock Exchange was so kind as to inform the public when they would open, so other markets followed suit, and things resumed some sort of normalcy.

The S&P 500 opened 50 points lower on the morning of the 17th, and traded within a 40 point range.

It was insanity, complete chaos. Volume was huge, the world was ending, then the world was saved. This cycle seemed to be on repeat for days on end.

Believe it or not, I did not cover my short position.

Having the time to think through everything during those days off, I realized that I needed to stick to my trading plan and prove my thesis.

Why? If there was no signal to cover my short position, and my trade was sized correctly, then it follows that I wouldn’t suffer enough to take me out of the game.

This outlier event, 9/11, the most dramatic event to ever happen in the United States, was actually covered in my trading plan. Not by name, but certainly the rules were broad and effective enough to keep me in winning trades.

Eventually I did cover, and for a massive profit. But, I left plenty on the table, like nearly every good trade.

I learned a lot about myself in the days that the market was closed, reflecting on what happened.

I learned that the market can give you insight before something happens. There is speculation that 9/11 was heavily shorted by certain parties that participated in the planning and execution of the attacks. I can assure you I wasn’t one of those parties, however, my trading plan identified and planned for the events that followed the terror attacks.

I learned that taking time to breath, think, and relax is usually a better tactic than immediately reacting. I started to invest a little more in my meditation practice.

I learned to imagine and consider more outcomes and new threats.  The crazier the better! Approaching the future in a reality that was entirely different and unexpected than the present resulted in my ability to create new strategies to handle the unexpected.

Trading is a job;  emotions about the current state of affairs is not. I have learned that while I can be angry, sad or any other emotion about something that is happening, not letting that interfere with decision making is a muscle that needs to be exercised often. In the markets, math generally wins over emotion.

Most importantly, what I took out of this outlier incident is what led me to become a systems trader. I now trade mechanically and algorithmically instead of subjectively and discretionarily.

In the event you find yourself in another “outlier incident,” I highly recommend to do the same.  

Focus on finding a slight edge in the market, then exploiting that edge with the most powerful tools at our disposal (position sizing and exits) in order to make meaningful and very consistent returns over time.  

Remove your emotions from trading.  Let your system do the work for you, and trust that it will do what it takes.