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The Art of Totis Porcis
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The Difference Between Great Traders and Good Traders: The Art of Totis Porcis

The following is an excerpt from Barton Bigg’s book, Hedgehogging, where he relates a conversation with “Tim”, a successful macro investor (emphasis mine).

Tim works out of a quiet, spacious office filled with antique furniture, exquisite oriental rugs, and porcelain in a leafy suburb of London with only a secretary. My guess is he runs more than $1 billion, probably half of which is his. On his beautiful Chippendale desk sits a small plaque, which says totis porcis—the whole hog. There is also a small porcelain pig, which reads, “It takes Courage to be a Pig.” I think Stan Druckenmiller, who coined the phrase, gave him the pig.

To get really big long-term returns, you have to be a pig and ride your winners… When he lacks conviction, he reduces his leverage and takes off his bets. He describes this as “staying close to shore… When I asked him how he got his investment ideas, at first he was at a loss. Then, after thinking about it, he said that the trick was to accumulate over time a knowledge base. Then, out of the blue, some event or new piece of information triggers a thought process, and suddenly you have discovered an investment opportunity. You can’t force it. You have to be patient and wait for the light to go on. If it doesn’t go on, “Stay close to shore.”

What separates the great traders from those who are just good?

The answer is knowing when to size up and eat the whole hog.

Let me explain.

To become a good trader you have to master risk management. Managing risk is the foundation of successful speculation. It’s the core of ensuring your long-term survival.

After risk, there’s trade and portfolio management. These are not wholly separate from managing risk. But they have the added complexity of things like thinking about when to take profits on a trade or how the drivers of your book correlate across positions etc…

Risk and trade management are absolute critical skills to becoming a good trader. All good traders are masters in these two areas.

But the thing that makes great traders head and shoulders above the rest, is the skill in knowing when to go for the jugular. In sizing up and aggressively going for Totis Porcis, the full hog.

Great traders know how to exploit fat tail events — the large mispricings that only come around once in a blue moon. They swing for the fences when fat pitches come across their plate.

Examples of this are Livermore making a fortune shorting the 29’ crash. PTJ doing the same in the 87’ rout and the Nikkei fallout in 1990. Druck and Soros when they took down the Bank of England in 92’. Buffett, who’s a master of exploiting fat tails, did it when he put nearly half his capital into AXP when it was selling for dirt cheap prices.

This is something we at MO call FET which is just short for Fat-tail Exploitation Theory.

Markets and investor returns follow a power law. Similar to Pareto’s law, returns adhere to an extreme distribution of 90/10. This means, that amongst great traders and investors, 90% of their profits on average come from only 10% or less of their trades.

Let’s look at the following from Ken Grant (who’s worked with traders such as Cohen, PTJ et al.) in his book Trading Risk (emphasis mine):

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

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

To begin with, if we accept the notion that the entire profitability of your account will be captured in, say, the top 10% of your trades, then it follows by definition that the other 90% are a break-even proposition. Think about this for a moment: Literally 9 out of every 10 of your trades are likely to aggregate to produce profits of exactly zero.

This power law for investment returns is ironclad. Like Grant notes, it’s consistent “across trading styles, asset classes, instrument classes, and market conditions.”

And here’s where we get to the crux of the matter. Good traders don’t know how to harness this power law. While great traders do. They exploit it, using it to their full advantage.

Here’s Druckenmiller on the subject (emphasis mine):

The first thing I heard when I got in the business, from my mentor, was bulls make money, bears make money, and pigs get slaughtered.

I’m here to tell you I was a pig.

And I strongly believe the only way to make long-term returns in our business that are superior is by being a pig. I think diversification and all the stuff they’re teaching at business school today is probably the most misguided concept everywhere. And if you look at all the great investors that are as different as Warren Buffett, Carl Icahn, Ken Langone, they tend to be very, very concentrated bets. They see something, they bet it, and they bet the ranch on it. And that’s kind of the way my philosophy evolved, which was if you see – only maybe one or two times a year do you see something that really, really excites you… The mistake I’d say 98% of money managers and individuals make is they feel like they got to be playing in a bunch of stuff. And if you really see it, put all your eggs in one basket and then watch the basket very carefully.

But how can one be a pig while still being a good manager of risk. It kind of seems like a paradoxical statement doesn’t it?

Here’s how.

Your average trader picks trades that have symmetrical potential outcomes. This means that the market pricing is on average, correct. It’s efficient. And the distribution of returns for these trades will fall randomly within the cone of future possibilities.

On average, these trades don’t produce alpha.

Using trade and risk management, a good trader can take this symmetric futures cone and produce positive returns by reducing the downside of return outcomes through trade structure and stop losses. But their upside is limited to the average distribution of outcomes.

But great traders and investors are different. They are skilled at identifying highly asymmetric outcomes.

These trades have the potential to massively reprice in their favor. The distribution of future outcomes for these trades looks more like this.

And not only are they skilled at identifying these skewed setups but when all the stars align they go for the whole hog and exploit the market’s error. They know that these rare asymmetric opportunities don’t come around often.

Great traders have this ability not because they are any better at predicting the future. Prediction is a fool’s errand.

It’s because they have built up a store of knowledge and context and pattern recognition skills. This allows them to more effectively assess the range of possibilities for an outcome set and identify one’s that are highly skewed to the upside.

They have the experience base that allows them to aggressively size up while at the sametime properly manage their risk. Simply put, they’ve earned the right to have conviction. And the vast majority of good traders haven’t earned this right. So they’re better off sticking with consistent and manageable bet sizing.

Tim from Hedgehogging stated it perfectly in saying that “the trick was to accumulate over time a knowledge base. Then, out of the blue, some event or new piece of information triggers a thought process, and suddenly you have discovered an investment opportunity.”

The evolutionary process of a trader should be to focus on mastering risk management. Then trade management — riding winners to their full potential. All the while building up a library of experience and useful context that will give them tools to identify asymmetric opportunities down the road. And once they’ve earned the right to have conviction, they can go for Totis Porcis.

Until then, “stay close to shore”.

Some final words from Druckenmiller.

The way to build superior long-term returns is through preservation of capital and home runs…When you have tremendous conviction on a trade, you have to go for the jugular. It takes courage to be a pig.

 

 

The Management Principles of George Soros

The Management Principles of George Soros

The following is straight from Operator Kean, a member of the Macro Ops Collective. To contact Kean, visit his website here.

In the first and second articles of this 3-part series, we covered the philosophy and the investment principles and strategies of the famous Quantum Fund ran by billionaire investor George Soros.

In this third article, we will cover the management principles of this legendary firm.

(I) Be Part Of A Global ‘Intelligence Network’

One advantage that the Palindrome had was his ‘intelligence network’. His rise from obscurity in the early 1960s to commercial stardom on Wall Street brought him the powerful perks of wealth and fame. With this, he realized that he could access vital people from the upper echelons of government or commerce, and hence, worked hard to develop a professional network.

With this professional network, he could get the opinions of very informed people to ‘stress test’ his own views and alert him to new trading opportunities.

This is one reason I joined the Macro Ops Collective last year, as I wanted to be a part of a global ‘intelligence network’ and hopefully contribute to its growth. The MO Collective is a community of savvy macro traders from all over the world. It’s a place where I can gain perspectives and insights on markets as exotic as South America. It’s a place I can ‘stress test’ my investment strategies or ideas as well.

Widen your circle as much as possible. Network with as many people as possible — you’ll never know when and where your next best idea will come from.

Iron sharpens Iron Do you have a global ‘intelligence network’? Or are you part of one?

(II) Constantly Source For Talent

This may be a clichéd point, as it’s intuitive to any business person. Without competent and capable people in your firm, there can be no real progress. By allowing talented individuals to flourish and develop, you also allow them to contribute to the overall growth of your organization.

Time must be devoted to finding talented individuals. This process is continuous.

As the Quantum Fund got bigger due to its meteoric rise and stellar performance over the decades, Soros had to expand the organization and train up future successors and leaders of the firm. He was constantly on the lookout for talented macro traders such as Stanley Druckenmiller, Nicholas Roditi and Scott Bessent.

(III) Leverage External Expertise

Soros relied on external expertise to generate the best returns.

In the 1990s, Soros delegated some of his firm’s equity to Victor Niederhoffer after recognising his trading talent.

More recently, Soros allocated a substantial amount of his family office’s assets to bond king Bill Gross when he left PIMCO.

Soros doesn’t care if he’s actually placing the trades. Once he identifies an opportunity, he’s perfectly fine with sourcing outside expertise to help him capture it.

The trading universe is massive. There will be certain markets or segments that are niche, requiring expertise beyond your field or competency. You only need to identify the opportunity, and then find a way to leverage on external expertise.

Take these management principles and lessons from the world’s most famous hedge fund manager. It could take your own investment business to the next level!

 

 

Bruce Kovner On Listening To The Market, Politics, & Risk Control
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Bruce Kovner On Listening To The Market, Politics, & Risk Control

The following is a fantastic speech from Bruce Kovner on Caxton Associates’ 20th anniversary. Kovner shares a plethora of trading wisdoms including the three most important contributors to his hedge fund’s success. You can read the original speech from 2003 here.

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To all my colleagues, to friends and associates who have worked and invested with us over the years, may I say welcome to this 20th anniversary party. This is the first time Caxton has thrown a party for our extended family and I am happy and thrilled to welcome all of you. If we are able to catch Peter D’Angelo in a generous moment, we may not have to wait another twenty years for the next event!

This particular room has always been one of my favorites – combining a modern space with the elegant and mysterious beauty of this ancient Egyptian temple. But this setting also suggests another theme: that nothing is permanent in human affairs, that the apparent solidity of these stones of Egypt counted for nothing as dynasties came and went and especially when the Pharaoh of the 1950’s and 60’s, Gamal Abdul Nasser, now himself long gone, determined that the great Aswan Dam would flood the plains of the Nile, submerging much of Egypt’s history in the vast lake then to be formed.

The World changes. In some small sense, Caxton’s story has its roots in similar observations. Caxton was born twenty years ago amid extraordinary changes in the world of money, finance, and politics, changes that have helped transform the world economy. Tonight, I would like to talk briefly about the circumstances both in the markets and in my own life and experience that have shaped Caxton’s performance over the last two decades. I would like to start with events that predated the founding of Caxton but which are important in understanding the origins of the company. Then I would like to describe important periods in Caxton’s evolution and close with some thoughts about the future.

Caxton was started in a period of economic transition – a time of creative destruction, as fans of Professor Schumpeter would say – when the old order of fixed exchange rates and fixed gold prices ($35 per ounce, I believe) could no longer contain the enormous pressures of the 1960’s and 1970’s. We wanted guns and butter, Vietnam and the Great Society. Around the world there were vast and differentiated changes in inflation, productivity, and wealth. So, the Gold window was shut in 1968. Three years later, Richard Nixon abandoned fixed exchange rates and let the dollar float. A new economic era had begun.

The inflation, volatile exchange rates, rising commodity prices and high nominal interest rates that followed in the 1970’s created an environment in which the old ways of investing no longer functioned well. Long-only stock and bond trading were not the optimum ways to capture the opportunities that the 1970’s created. On the contrary, between 1968 and the early 1980’s, stocks and bonds suffered through a long bear market, destroying the value of equity and bond portfolios and undermining confidence in traditional investing styles. On the other hand, opportunities to profit from being long or short in currencies, fixed income, stocks and commodities abounded. The stage was set for active ‘macro trading’ as the increasingly popular term would label it.

New York, with its long-only equity culture and preponderance of establishment institutions, was not a congenial host for the new trading culture. That had to emerge in Chicago where people like Leo Melamed, a former egg broker, became head of the Chicago Mercantile Exchange and initiated trading of financial futures. The Chicago Board of Trade followed suit with the establishment of a market for trading Ginnie Mae futures. The process of creative destruction operated on the structure of financial markets far more effectively on the frontier in Chicago than it did in New York.

Cambridge, Massachusetts in the 1960’s was also not a bad place to learn that innovation and change are at the heart of survival. I had learned some of that from the history of my family – Jewish refugees from Czarist Russia. But I learned more after I enrolled as a freshman at Harvard College in 1962, reading Schumpeter on “creative destruction”, Keynes and Samuelson on counter cyclical fiscal policy, Tocqueville on the Ancien Regime, Fainsod on the Russian Revolution, Keynes (again) on the Economic Consequences of the Peace (meaning the punitive Treaty of Versailles), and a range of historians on the two World Wars. All were lessons on the impermanence of institutions and on the unintended consequences of government policy.

I did not know that these lessons were going to be put to any practical use by me. I had thought I would enter government service, not the financial world, when I left graduate school in 1970 and began to wander around the world for a few years. When I finally moved back to the United States in 1974, I was not seeking a Wall Street career (and I had no qualifications to begin one). I taught politics during the day and began to study financial markets at night. And by 1977, when I made my first tentative steps into financial markets, the financial world had already begun its remarkable transformation.

In my one-bedroom apartment on 57th Street, down the block from Carnegie Hall, I was only four miles away from Wall Street but a universe away in terms of my approach to markets. The new world of financial futures reduced the barriers to entry to currency and interest rate markets. Perhaps, I thought, efforts to understand what moved these markets might be well rewarded. I speculated on commodity prices, interest rates, currencies and was gratified to make money. And I found my way to Commodities Corporation, started by economists from MIT and Princeton, to learn more of my newly chosen trade. After five and a half years, with the blessings of my former employers, I decided to establish a company that reflected my own particular vision of how to adapt to this new financial world. With $7MM from investors and $5MM of my own funds, I started Caxton in March of 1983.

The new company’s operations were guided by principles and observations that helped us to pursue successful trading.

Barriers to entry to financial markets of all kinds were coming down. New markets were developing for the new financial instruments. Early providers of liquidity and expertise were likely to find excess returns.

Analysis of macro conditions was not being done systematically or well in most large money market institutions! Good analysis would provide excess returns.

Exogenous shocks – say, for example, oil price shocks – to the economies of the world were likely to be numerous. Being a quick responder to these shocks would provide excess returns.

Most investment managers and operators in equity and debt markets had institutional and cultural restraints on the kind of trading they could do – and tended heavily to favor long-only approaches. Few traders were highly skilled in the use of derivatives. Excess returns were therefore more likely to be earned by those who could go short as well as long, and who could use derivatives well.

More generally, Caxton adopted an institutional model that built in more flexibility in the creation of optimal portfolio mix than was normal on Wall Street. We had three structural advantages: First, there were no institutional limits on the range and style of our trading. We would go to any asset class where we saw opportunity, and we would trade in a range of trading styles (long, short, differential based, trend-following, mean-reversion, or arbitrage to name a few). Second, we chose to target risk levels, not nominal dollar levels, to calibrate our trading size. This enabled us to use leverage and portfolio theory to optimize our risk profile. There is plenty of opportunity to do risk management badly, of course; but the advantages of doing it well were enormous. And thirdly, we believed in a process of dynamic risk allocation – that is, we would put more capital at risk when either market conditions or macro economic conditions convinced us of the possibility of excess return. Caxton wouldn’t be stuck with a fixed asset allocation to stocks or bonds or currencies or commodities. We would change our capital allocation with conditions. Do that well and returns would not be a passive captive of the business cycle. On the contrary, dynamic capital allocation could turn what was for more inflexible institutions a source of difficulty into an advantage for a young firm capable of adapting to changing conditions.

The first ten years of Caxton’s existence certainly provided ample opportunity for us to test both premises of our new model and our skills in deploying it. We had macroeconomic shocks aplenty – rising and falling rates, oil shocks, the Plaza accord, the market crash of 1987, the Iran-Iraq War, not to mention the first US-Iraq War. We had new markets, new financial instruments, new Presidents, new Prime Ministers, currency unions … No shortage of fun, for we dyed-in-the wool macro traders. And, fortunately, although we made many, many mistakes, we managed to execute well enough to have good returns. During the first ten years of its existence, starting with about $10MM in capital, Caxton earned some $3 billion in profits, with a gross trading return of 55.6 percent per year. In the same period (although it included nearly all of the first ten years of a great bull market) the S&P 500 grew at the rate of about 15.7 percent per year. And even though Caxton’s trading during those years felt, to me, a little too much like Coney Island’s Cyclone roller coaster, the quality of our return, with a Sharpe ratio of 1.68, was about three teams higher than the S&P’s .54 during the same period.

Our success notwithstanding, by the mid-nineties, several of the opportunities which had facilitated Caxton’s success had changed. A large number of new players – hedge funds, prop desks at banks, speculators – had entered the market, reducing the advantages of early entrants. Macro analysis had become routine in wire houses, investment banks, and prop desks. And Caxton, with $1.6 billion in assets, was no longer small enough to make its returns with quick trades in smaller markets. We felt stale. Our performance – down 2.4% in 1994 – felt awful. It was time for a change. We sent our investors 60% of their funds, reduced our capital to $650MM, and went back to the drawing boards.

Prior to 1994, Caxton was largely focused on top-down macro trading. By 1994, we had concluded that we needed more tools than those that macro trading provided. Nothing works all the time. We wanted a variety of trading strategies across all liquid asset classes. And we didn’t want to be confined to one trading style, such as momentum-based trend following. So we began a systematic process of searching for new strategies, new styles, new markets and new traders. Let 1000 flowers bloom, it was said. But make sure they bloom with good risk management, and with low correlation! In the years since 1995, Caxton has spent a lot of time searching for these techniques, strategies and traders. We kissed a lot of frogs, as my good friend Joe Grundfest might say. (Actually, does say.) And we wound up with some 50 trading centers covering virtually all liquid asset classes, employing a multiplicity of approaches – trend following, of course, but also mean reversion strategies, fundamentals based models, arbitrage, computer-based approaches to markets, discretionary trading of equities, active trading of mortgage markets and related instruments, and many others.

We wouldn’t be here tonight, having this rather wonderful celebration in the Metropolitan Museum, if the results of that effort had not been acceptable. In fact, since January 1995, Caxton has earned $8.5 billion in trading profits, starting with a base of $650MM. Our average annual return has been 33.1 percent, and our Sharpe ratio rose from the first decades 1.68 to just below 2.00. In the same period, the S&P’s annual return was 12.7% for the S&P, with a Sharpe ratio of .50.

Today, Caxton has nearly 50 trading centers, divided among:

Macro oriented centers, which deploy about 35% of the risk of the company;

Equity oriented centers, which deploy about 25% of our risk;

Quantitative systems, deploying another 25% of our risk; and

Fixed income strategies which deploy another 15% of risk.

My own role in all of this has changed substantially over these years. Whereas in the first years of Caxton, I had tactical responsibility for almost everything in the portfolio, my trading accounts for something like 10% to 15% of the company’s risk presently. I spend a great deal of time on strategic development. It is more important for me to help find and develop areas of opportunity than it is for me to trade them. And it is more important to have a robust process of strategic development than it is to have one dependent on one human being. That is why Caxton devotes many millions of dollars a year to research and development aimed at finding new quantitative techniques or new areas of trading likely to yield high returns, and developing information technology and risk control techniques. I spend most of my time on these efforts, and on working with traders when they need advice, encouragement or help.

In these efforts, I try to pass on something of the proverbs, ethos and culture of trading that I have regarded as essential to Caxton’s success. Of these, I will mention three:

  1. Listen to the market. Close observation of price behavior is always necessary for the discipline of successful trading and it is very often very helpful in providing evidence about the nature of current conditions. If we can understand what the market is telling us, we will most likely be able to understand how to trade it. Listen to the market, hear it, don’t tell it what to do. Listen.
  2. Take politics and policy seriously. Changes in policy matter. Changes in leadership matter. Study them seriously. This doesn’t mean that politicians and policy makers will get it right – indeed very often they will get it wrong and these ‘mistakes’ in and of themselves may be important to markets. But ignore them at your peril. Policy matters. Politics matter.
  3. Above everything else, never let the discipline of risk control become lax. Those 100-year storms have a way of coming round every few years. If in real estate it’s “location, location, location”, in leveraged trading it is “risk control, risk control, risk control”. It is surprising how often this focus is lost.

Listening to the market. Taking politics and policy seriously. Risk control – to these we need to add one more on the level of the firm. And that is our old friend “creative destruction”: the process of creative destruction operates on trading techniques (and their embodiment in individual traders) as much as it does on any market structure. Any trading technique has a finite life in which it yields extraordinary returns. As more capital and knowledge are applied, markets become more efficient and rates of return drop – until eventually high risk adjusted returns disappear. Then it is time to retire the technique and move on.

The flexibility and learning that must be applied to trading also should be applied to capital allocation. We can’t be static in how we allocate capital to a particular strategy, nor to all of them together. So Caxton only wants the amount of capital it can deploy successfully. We are not asset gatherers. Despite a long list of investors who want to get in to Caxton funds, we will most certainly send money back to investors again in the near future. Barring unforeseen developments, we will return between 10 and 20% of our capital to investors at the end of this year. Flexible capital allocation. When rate of return drops, send capital back home to our investors.

In the meantime, we will continue to develop new techniques and new trading centers. As they bear fruit, we will nurture them and introduce them into our portfolio as they are proven and as conditions permit.

There is little doubt in my mind that the financial markets will remain as dynamic in the next twenty years as they were in the last. Look at the enormous changes in Asia, where China is emerging as a giant already. One cannot understand world commodity markets today without understanding China – and therein, of course, lies much opportunity as well as risk. Look at the extraordinary long cycle in Japan. Twelve years of recession and decline, of policy mistakes, of opportunities lost. And perhaps now, finally, of some policy initiatives which may finally lift Japan deflation and seemingly unending recession.

And one doesn’t have to look only across the oceans for big structural changes that make markets different in this decade than in the last. Look at the fixed income market, where mortgages and floating rates have changed the character of supply and demand and market behavior in recent years. The mortgage market now dwarfs the U.S. Treasury market. Outstanding mortgage debt now exceeds total marketable Treasury debt to 50 percent. A decade ago that rate was reversed. No one can understand the path of yields in the United States without understanding these new conditions.

And look at the universe of possible exogenous shocks we confront today. Perhaps we all have some sense of the potential disturbance of terror attacks. But have we correctly priced them in the market? How do you price low probability high damage events? And how do you know the right probabilities?

And what about technological change, which still promises to create enormous values (I am thinking now of biotech as well as information technology)? And what about new oil shocks? Or geo-political conflict, such as India-Pakistan?

Clearly, this list could go on and on.

There is no certainty that Caxton will be able to adapt successfully to these and other risks and changes, but we do structure ourselves to be able to analyze such changes and risks and try to respond to them. And certainly those institutions which do not have the capability to respond leave themselves at the mercy of events. The premise of our operational philosophy was always and still is: The World Changes. Nothing is Permanent. Those who fail to adapt to change risk everything. Look around you, here in this beautiful room. Look at the magnificence of the Temple of Dendur and of the civilization of Egypt. The World Changes and nothing is permanent. If that is one of the lessons that family history and education taught me, it is also the lesson that imbues the practice of Caxton. Study the world. Study markets. Listen to the markets. Then, perhaps, with a little luck and skill, you may be able to find ways not simply to be a victim of circumstances but to profit from them.

Thank you.

 

 

Trading Wisdom From A JP Morgan Vet
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Trading Wisdom From A JP Morgan Vet

Every once in awhile a few gems will surface through Wall Street’s noise. Such is the case with a departing note from Jan Loeys, a senior strategist from J.P. Morgan who has been at this game for over 30 years.

In his final note, Loeys shares his thoughts on all the hot issues in finance and trading. The following are his most relevant comments to what we do at Macro Ops. The bolded emphasis is ours.   

Quant  Vs Discretionary

  • Quantitative techniques are indispensable, though, to deal with the complexity of financial instruments and the overload of information we face. Empirical evidence counts for more than theory, but you need theory to constrain empirical searchers and avoid spurious correlations.
  • Rules versus discretion? You need both. I have tried to have logical arguments to buy or sell certain assets, based on Finance. And I have tried to corral evidence that the signals I use have in the past had the assumed impact on asset prices. Each of these then became a rule, of the form: If X>0, buy A, and vice versa. As we collected these rules, and published them in our Investment Strategies series, the question came up naturally whether we should not simply make our investment process driven by a number of empirically proven rules, and to banish any discretion (emotion?) from the process. Over time, we converged on a mixture of the two as pure rules ran into the problem that the world is forever changing, partly as everyone else figures out the same rule and then arbitrages away the profit, and partly as economic structures and regimes similarly change over time in a way that we cannot capture with simple rules.
  • Much as I have been talking a lot about cycles, I do not think of the world as a stationary system described by a set of parameters that we steadily get to know more about. Instead, as economists we think of people constantly optimizing their objectives, under the constraints they face. Aside from truly exogenous shocks to the system, the main difference between today and yesterday is that today, we know what happened yesterday and that information allows us to constantly fine tune and thus change our behavior. That is, we constantly learn from the past, much to try to avoid making the same mistakes. At the macro level, this means that the system is constantly evolving. As Mark Twain said, “History doesn’t repeat itself, but it often rhymes”. As investors, we should look at the market as billions of people all learning and adapting. The best investors are those who get ahead of this by learning faster and understanding better how others are learning.

Forecasting

  • The starting point of Finance is the Theorem of Market Efficiency which posits that under ideal conditions what we all know should be in the price. Only new information moves the price. Hence, it is changes in expectations about the future that drive asset prices, not the level of anything.
  • How to forecast view changes? The good news is that changes in opinions about fundamentals such as growth and inflation tend to repeat. This is one driver of momentum in asset prices, and is likely driven by the positive feedback between risk markets and the economy that forecasters naturally find very difficult getting ahead of.
  • There is a fundamental difference between an asset price and a forecast. A forecast is a single outcome that you consider the most likely, among many. In statistics, we call this the mode. An asset price, in contrast, is closer to the probability-weighted mean of the different scenarios you consider possible in the future. When our own probability distribution for these different outcomes is not evenly balanced but instead skewed to, say, the upside, the market price will be above our modal view. Asset prices can thus move without a change in modal views if the market perceives a change in the risk distribution. An investor should thus monitor changing risk perceptions as much as changing modal views.
  • Do markets get ahead of reality? They do, yes, exactly because asset prices are probability-weighted means and the reality we perceive is coded as a modal view. Information arrives constantly and almost always only gently moves the risk distribution around a given modal view. Before we change our modal view of reality, the market will have seen the change in risk distribution and will have started moving already.
  • Levels or direction? In our business, we are asked to forecast asset prices and returns. I have found this very hard but fortunately have had the luxury to be able to stick to forecasting market direction rather than outright asset price levels. In markets that are close to efficiently priced, what we know is already in the price and we cannot really use that same information to make a coherent case for an asset price level that much different from today. All I have been able to do is to make a case that there are mild-to-decent odds in favor of the market going in one direction rather than the other. We have been much more successful in forecasting direction than actual asset price levels, and it is the direction that is more important for strategy.

Finding Alpha

  • The Theorem of Market efficiency, which implies investors can’t beat the market, implies that asset prices will follow random walks, with drift and that asset price changes will be white noise, with no serial correlation. There are thus only two possible inefficiencies to be exploited: positive serial correlation, which we call Momentum, or negative serial correlation, which we call mean reversion, or Value (to become valuable, asset prices need first to go down, or fundamentals need to improve faster than the price). It is an empirical question which dominates where. At the asset class and sector level, we have found that Momentum dominates, while within the fixed income world, Value is more important.
  • Across time, market momentum at the macro level has been the best way to earn excess returns. I discussed above how some of this is due to the momentum in view changes. More fundamentally, in open markets, we frequently face a Fallacy of Composition according to which rational and equilibrating behavior at the micro level becomes destabilizing at the macro level. The free market is very good at motivating entrepreneurship and rational behavior at the micro level, but is subject to constant booms and busts at the macro level. Central banks try to control this instability through counter-cyclical policies but can’t undo it all.
  • Trade the risk bias. Even when markets price in exactly our modal views, I find it useful to consider how prices will move on new information and then try to position on any skew in the outlook. If I find that a particular price or spread will move a lot more on bullish than on bearish news, then I will position bullishly. This works at the portfolio level if I can combine different unrelated risk biases.

Red Team      

  • Cherish your errors. I have learned ten times more from being wrong than being right. Once you make a mistake, go public with it, analyze it in detail, and learn from it.
  • Be your own devil’s advocate, and spend most time with people who do not agree with you, or who have a different way of looking at things. Not always easy as being with like-minded people is more comforting.

 

 

Advice From Mark Sellers
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Hedge Fund Manager Mark Sellers On Becoming A Great Investor

This is a killer talk I came across from Hedge Fund manager Mark Sellers, speaking to some Harvard MBA kids on what it takes to make it in markets. Regardless of whether you consider yourself a trader or investor, Mark’s “seven traits” apply.

Enjoy…

First of all, I want to thank Daniel Goldberg for asking me to be here today and all of you for actually showing up. I haven’t been to Boston in a while but I did live here for a short time in 1991 & 1992 when I attended Berklee School of Music.

I was studying to be a jazz piano player but dropped out after a couple semesters to move to Los Angeles and join a band. I was so broke when I lived here that I didn’t take advantage of all the things there are to do in Boston, and I didn’t have a car to explore New England. I mostly spent 10-12 hours a day holed up in a practice room playing the piano. So whenever I come back to visit Boston, it’s like a new city to me.

One thing I will tell you right off the bat: I’m not here to teach you how to be a great investor. On the contrary, I’m here to tell you why very few of you can ever hope to achieve this status.

If you spend enough time studying investors like Charlie Munger, Warren Buffett, Bruce Berkowitz, Bill Miller, Eddie Lampert, Bill Ackman, and people who have been similarly successful in the investment world, you will understand what I mean.

I know that everyone in this room is exceedingly intelligent and you’ve all worked hard to get where you are. You are the brightest of the bright. And yet, there’s one thing you should remember if you remember nothing else from my talk: You have almost no chance of being a great investor.

You have a really, really low probability, like 2% or less. And I’m adjusting for the fact that you all have high IQs and are hard workers and will have an MBA from one of the top business schools in the country soon. If this audience was just a random sample of the population at large, the likelihood of anyone here becoming a great investor later on would be even less, like 1/50th of 1% or something.

You all have a lot of advantages over Joe Investor, and yet you have almost no chance of standing out from the crowd over a long period of time.

And the reason is that it doesn’t much matter what your IQ is, or how many books or magazines or newspapers you have read, or how much experience you have, or will have later in your career. These are things that many people have and yet almost none of them end up compounding at 20% or 25% over their careers.

I know this is a controversial thing to say and I don’t want to offend anyone in the audience. I’m not pointing out anyone specifically and saying that you have almost no chance to be great. There are probably one or two people in this room who will end up compounding money at 20% for their career, but it’s hard to tell in advance who those will be without knowing each of you personally.

On the bright side, although most of you will not be able to compound money at 20% for your entire career, a lot of you will turn out to be good, above average investors because you are a skewed sample, the Harvard MBAs. A person can learn to be an above-average investor. You can learn to do well enough, if you’re smart and hardworking and educated, to keep a good, high-paying job in the investment business for your entire career.

You can make millions without being a great investor. You can learn to outperform the averages by a couple points a year through hard work and an above average IQ and a lot of study. So there is no reason to be discouraged by what I’m saying today. You can have a really successful, lucrative career even if you’re not the next Warren Buffett.

But you can’t compound money at 20% forever unless you have that hard-wired into your brain from the age of 10 or 11 or 12.

I’m not sure if it’s nature or nurture, but by the time you’re a teenager, if you don’t already have it, you can’t get it. By the time your brain is developed, you either have the ability to run circles around other investors or you don’t.

Going to Harvard won’t change that and reading every book ever written on investing won’t either. Neither will years of experience. All of these things are necessary if you want to become a great investor, but in and of themselves aren’t enough because all of them can be duplicated by competitors.

As an analogy, think about competitive strategy in the corporate world. I’m sure all of you have had, or will have, a strategy course while you’re here. Maybe you’ll study Michael Porter’s research and his books, which is what I did on my own before I entered business school. I learned a lot from reading his books and still use it all the time when analyzing companies.

Now, as a CEO of a company, what are the types of advantages that help protect you from the competition?

How do you get to the point where you have a wide economic moat, as Buffett calls it?

Well one thing that isn’t a source of a moat is technology because that can be duplicated and always will be, eventually, if that’s the only advantage you have. Your best hope in a situation like this is to be acquired or go public and sell all your shares before investors realize you donít have a sustainable advantage.

Technology is one type of advantage that’s short-lived. There are others, such as a good management team or a catchy advertising campaign or a hot fashion trend. These things produce temporary advantages but they change over time, or can be duplicated by competitors.

An economic moat is a structural thing. It’s like Southwest Airlines in the 1990s, it was so deeply ingrained in the company culture, in every employee, that no one could copy it, even though everyone kind of knew how Southwest was doing it.

If your competitors know your secret and yet still can’t copy it, that’s a structural advantage. That’s a moat.

The way I see it, there are really only four sources of economic moats that are hard to duplicate, and thus, long-lasting. One source would be economies of scale and scope. Wal-Mart is an example of this, as is Cintas in the uniform rental business or Procter & Gamble or Home Depot and Lowe’s.

Another source is the network affect, ala eBay or Mastercard or Visa or American Express.

A third would be intellectual property rights, such as patents, trademarks, regulatory approvals, or customer goodwill. Disney, Nike, or Genentech would be good examples here. A fourth and final type of moat would be high customer switching costs. Paychex and Microsoft are great examples of companies that benefit from high customer switching costs.

These are the only four types of competitive advantages that are durable, because they are very difficult for competitors to duplicate. And just like a company needs to develop a moat or suffer from mediocrity, an investor needs some sort of edge over the competition or he’ll suffer from mediocrity.

There are 8,000 hedge funds and 10,000 mutual funds and millions of individuals trying to play the stock market every day. How can you get an advantage over all these people? What are the sources of the moat?

Well, one thing that is not a source is reading a lot of books and magazines and newspapers. Anyone can read a book.

Reading is incredibly important, but it won’t give you a big advantage over others. It will just allow you to keep up. Everyone reads a lot in this business. Some read more than others, but I don’t necessarily think there’s a correlation between investment performance and number of books read.

Once you reach a certain point in your knowledge base, there are diminishing returns to reading more. And in fact, reading too much news can actually be detrimental to performance because you start to believe all the crap the journalists pump out to sell more papers.

Another thing that won’t make you a great investor is an MBA from a top school or a CFA or PhD or CPA or MS or any of the other dozens of possible degrees and designations you can obtain.

Harvard can’t teach you to be a great investor. Neither can my alma mater, Northwestern University, or Chicago, or Wharton, or Stanford. I like to say that an MBA is the best way to learn how to exactly, precisely, equal the market return. You can reduce your tracking error dramatically by getting an MBA.

This often results in a big paycheck even though it’s the antithesis of what a great investor does. You can’t buy or study your way to being a great investor. These things won’t give you a moat. They are simply things that make it easier to get invited into the poker game.

Experience is another over-rated thing.

I mean, it’s incredibly important, but it’s not a source of competitive advantage. It’s another thing that is just required for admission. At some point the value of experience reaches the point of diminishing returns. If that wasn’t true, all the great money managers would have their best years in their 60s and 70s and 80s, and we know that’s not true. So some level of experience is necessary to play the game, but at some point, it doesn’t help any more and in any event, itís not a source of an economic moat for an investor.

Charlie Munger talks about this when he says you can recognize when someone gets it right away, and sometimes it’s someone who has almost no investing experience.

So what are the sources of competitive advantage for an investor?

Just as with a company or an industry, the moats for investors are structural. They have to do with psychology, and psychology is hard wired into your brain. It’s a part of you. You can’t do much to change it even if you read a lot of books on the subject.

The way I see it, there are at least seven traits great investors share that are true sources of advantage because they canít be learned once a person reaches adulthood. In fact, some of them can’t be learned at all; you’re either born with them or you aren’t.

Trait #1

Is the ability to buy stocks while others are panicking and sell stocks while others are euphoric.

Everyone thinks they can do this, but then when October 19, 1987 comes around and the market is crashing all around you, almost no one has the stomach to buy. When the year 1999 comes around and the market is going up almost every day, you can’t bring yourself to sell because if you do, you may fall behind your peers.

The vast majority of the people who manage money have MBAs and high IQs and have read a lot of books. By late 1999, all these people knew with great certainty that stocks were overvalued, and yet they couldn’t bring themselves to take money off the table because of the ìinstitutional imperative, as Buffett calls it.

Trait #2

The second character trait of a great investor is that he is obsessive about playing the game and wanting to win.

These people don’t just enjoy investing; they live it. They wake up in the morning and the first thing they think about, while they’re still half asleep, is a stock they have been researching, or one of the stocks they are thinking about selling, or what the greatest risk to their portfolio is and how they’re going to neutralize that risk.

They often have a hard time with personal relationships because, though they may truly enjoy other people, they don’t always give them much time. Their head is always in the clouds, dreaming about stocks.

Unfortunately, you can’t learn to be obsessive about something. You either are, or you aren’t. And if you aren’t, you can’t be the next Bruce Berkowitz.

Trait #3

A third trait is the willingness to learn from past mistakes. The thing that is so hard for people and what sets some investors apart is an intense desire to learn from their own mistakes so they can avoid repeating them.

Most people would much rather just move on and ignore the dumb things they’ve done in the past. I believe the term for this is repression.

But if you ignore mistakes without fully analyzing them, you will undoubtedly make a similar mistake later in your career. And in fact, even if you do analyze them it ís tough to avoid repeating the same mistakes.

Trait #4

A fourth trait is an inherent sense of risk based on common sense.

Most people know the story of Long Term Capital Management, where a team of 60 or 70 PhDs with sophisticated risk models failed to realize what, in retrospect, seemed obvious: they were dramatically over leveraged. They never stepped back and said to themselves, “Hey, even though the computer says this is ok, does it really make sense in real life?”

The ability to do this is not as prevalent among human beings as you might think. I believe the greatest risk control is common sense, but people fall into the habit of sleeping well at night because the computer says they should. They ignore common sense, a mistake I see repeated over and over in the investment world.

Trait #5

Great investors have confidence in their own convictions and stick with them, even when facing criticism. Buffett never get into the dot-com mania though he was being criticized publicly for ignoring technology stocks.

He stuck to his guns when everyone else was abandoning the value investing ship and Barron’s was publishing a picture of him on the cover with the headline “What’s Wrong, Warren?”

Of course, it worked out brilliantly for him and made Barron’s look like a perfect contrary indicator.

Personally, I’m amazed at how little conviction most investors have in the stocks they buy. Instead of putting 20% of their portfolio into a stock, as the Kelly Formula might say to do, they’ll put 2% into it.

Mathematically, using the Kelly Formula, it can be shown that a 2% position is the equivalent of betting on a stock has only a 51% chance of going up, and a 49% chance of going down. Why would you waste your time even making that bet? These guys are getting paid $1 million a year to identify stocks with a 51% chance of going up? It’s insane.

Trait #6

Sixth, it’s important to have both sides of your brain working, not just the left side (the side that’s good at math and organization.)

In business school, I met a lot of people who were incredibly smart. But those who were majoring in finance couldn’t write worth a damn and had a hard time coming up with inventive ways to look at a problem. I was a little shocked at this.

I later learned that some really smart people have only one side of their brains working, and that is enough to do very well in the world but not enough to be an entrepreneurial investor who thinks differently from the masses.

On the other hand, if the right side of your brain is dominant, you probably loathe math and therefore you don’t often find these people in the world of finance to begin with. So finance people tend to be very left-brain oriented and I think that’s a problem. I believe a great investor needs to have both sides turned on.

As an investor, you need to perform calculations and have a logical investment thesis. This is your left brain working.

But you also need to be able to do things such as judging a management team from subtle cues they give off. You need to be able to step back and take a big picture view of certain situations rather than analyzing them to death. You need to have a sense of humor and humility and common sense. And most important, I believe you need to be a good writer.

Look at Buffett; he’s one of the best writers ever in the business world. It’s not a coincidence that he’s also one of the best investors of all time. If you can’t write clearly, it is my opinion that you don’t think very clearly. And if you don’t think clearly, you’re in trouble. There are a lot of people who have genius IQs who can’t think clearly, though they can figure out bond or option pricing in their heads.

Trait #7

And finally the most important, and rarest, trait of all: The ability to live through volatility without changing your investment thought process.

This is almost impossible for most people to do; when the chips are down they have a terrible time not selling their stocks at a loss. They have a really hard time getting themselves to average down or to put any money into stocks at all when the market is going down.

People don’t like short term pain even if it would result in better long-term results. Very few investors can handle the volatility required for high portfolio returns.

They equate short-term volatility with risk. This is irrational; risk means that if you are wrong about a bet you make, you lose money. A swing up or down over a relatively short time period is not a loss and therefore not risk, unless you are prone to panicking at the bottom and locking in the loss.

But most people just can’t see it that way; their brains won’t let them. Their panic instinct steps in and shuts down the normal brain function.

I would argue that none of these traits can be learned once a person reaches adulthood. By that time, your potential to be an outstanding investor later in life has already been determined.

It can be honed, but not developed from scratch because it mostly has to do with the way your brain is wired and experiences you have as a child. That doesn’t mean financial education and reading and investing experience aren’t important.

Those are critical just to get into the game and keep playing. But those things can be copied by anyone.

The seven traits above can’t be.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Do you possess these 7 traits?

 

 

The Label Stupidity Loop
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The Label Stupidity Loop

“I’m a Democrat… I’m an Evangelical Christian… I’m a Trump Supporter… I’m a Value Investor… I’m a Bernie Bro… I’m a Neo-Keynesian… I’m a Scientologist… I’m a… I’m a…”

Humans love adopting labels.

We don them proudly, wearing them like sports jerseys. We proclaim our chosen identity to anybody that’ll listen. We want everyone to know what we stand for… and that we’re on the “right” side.

It’s impossible to know everything, and we hate that fact. People abhor uncertainty.

Labels fix this.

They give us pre-packaged sets of beliefs/heuristics/frameworks for dealing with and understanding the world.

Labels also give us a tribe.

By declaring yourself a Republican, you’re signaling to other Republicans that you’re “one of them”. You’re letting them know that you share the same beliefs and values. You’re part of the team. The same goes for Democrats, Libertarians, and every other label.

Having a tribe is important to us. It gives us a sense of safety and community — two things we’re evolutionary wired to crave.

So adopting labels is great.

They help us operate in a complex world and make it easier to choose the people we want to identify with — our tribe mates.

The only thing is… labels make us stupid.

Really, really stupid.

Because once we don a label, it becomes part of our identity.

And there are few things we hate more than attacks on our identity.

Ideas, evidence, events, or questions that don’t confirm our adopted labels feel like personal attacks.  

Humans will do just about anything to repel these attacks and maintain their belief in their beliefs.

And since no packaged belief set is 100% correct, it means all of us carry belief structures that fall somewhere on the scale between somewhat wrong and very wrong.

We employ mental contortions that would impress the US Olympic gymnast team… all to avoid acknowledging the wrongness of these beliefs.

Psychologists call this, “Identity Protective Cognition”.

Vox described IPC as:

A way of avoiding dissonance and estrangement from valued groups, individuals subconsciously resist factual information that threatens their defining values… What we believe about the facts, tells us who we are… And the most important psychological imperative most of us have in a given day is protecting our idea of who we are, and our relationships with the people we trust and love.

Why does this matter?

Well, if we all carry some number of untrue beliefs, yet hold them with high conviction, it’ll inevitably lead to friction when our packaged beliefs don’t conform to how reality actually is.

It also makes getting at truth (finding out how things really are) much more difficult.

Take politics for example.

All 200 million US registered voters are pretty evenly split amongst Democrats and Republicans.

These political labels have become a big part of our identities. The sense of tribe within each is strong.

Most of us passively adopted these labels.

We may like to think we actively chose them because of their superiority, but that’s generally not the case.

Most of us adopted the political label of the family we were born into, of the friends we grew up with, of the community we live within.

Just like our religion, this belief set was given to us. Just as it was given to those who gave it to us and on and on. So we passively adopt most of our labels and beliefs without any true stress testing.

The problem is that it’s our default condition to value knowing and “feeling right” over actually being right and getting at truth.

We adopt and cling to false beliefs because we’re afraid of accepting that we don’t know, that we don’t have an answer. We don’t want to acknowledge that the world is infinitely complex and uncertain, and that maybe the things our identities are built upon are wrong.

So we all live in varying degrees of an illusory reality dominated by cognitive dissonance and kept unaware by pride.

And with the rise of the digital era and the constant algorithmic selected news flow, that’s mathematically curated to cater to our labels and flip our emotional switches, we’re becoming more and more attached to these belief sets.

To manage the information/stimulus overload we more tightly cling to our labels to help manage the uncertainty. And the more we do this, the more our belief sets are likely to drift further from reality, from being true.

So we live in an increasingly vicious “Label Stupidity Loop.”

Where the more large and complex the things we’re supposed to care about become, and the more information we’re inundated with, the more fiercely we defend our packaged belief sets and the more wrong we all become.

Blogger Paul Graham wrote about this phenomenon in a post titled “Keep Your Identity Small.” He concludes the piece with:

If people can’t think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible.

He’s saying that the way to align more closely with reality and to end up with better outcomes is to be wary of the labels you adopt. And try to keep these labels to a minimum.

This requires a big shift in the way you interact with the world.

You’ll have to transition from a state of false-certainty to one of accepted unknowing.

You’ll need to embrace your fallibility and acknowledge that the world is large and that human nature is complex and that no one has all the answers.

You need to realize that humans will always operate at a knowledge deficit. Where the amount of things we don’t know will always outweigh the things we do. And even those things we “think” we know, need to be held with suspicion, because it’s just as likely that we’re wrong on them too.

In short, be humble and open minded… about everything.

Now since this is a trading blog about markets and such, here’s how this is relevant to you.

Do you classify yourself as a Value Investor? Technical trader? Macro guy? Elliott Wave Theorist?

Do you believe that your method is the best and the other methods are lacking?

Do you identify with your market approach?

Do you think that there’s nothing to gain by objectively studying and putting to the fire the validity of the other styles?

Is it not the most important thing to find any tool or method that you can logically understand and apply to extract money from the markets?

So why would you care what label it falls under?

I’ve long called myself a Macro trader. But that doesn’t mean that I only take what’s considered typical macro trades or only apply macro tools and thinking.

I say macro because I have to give a response. But really, all macro means to me, is to be unconstrained, not boxed in, capable of using all available and effective means to win.

I like the idea of being able to go anywhere and trade anything for whatever compelling reason that makes me think there’s asymmetry.

A trade is a trade is a trade in my book.

And I study all the disciplines that logically make sense to me and which I know others have successfully employed.

These are tools that I get to add to my trading kit.

Value investing? Yeah it works, tons of evidence of it working and lots of successful value only investors out there.

Technical analysis? Of course, PLB is living proof it’s effective… Top down classical macro? Absolutely… another valuable approach to understand and implement.

If it works I want to study it. I want to study the best and I want to know what they know. I want to dive into it with an open mind and find what makes sense, what doesn’t, and what maybe can be approved upon.

We should seek to imitate Bruce Lee and his approach to martial arts and living. Lee explains:

Each man belongs to a style which claims to possess truth to the exclusion of all other styles. These styles become institutes with their explanations of the “Way,” dissecting and isolating the harmony of firmness and gentleness, establishing rhythmic forms as the particular state of their techniques.

Instead of facing combat in its suchness, then, most systems of martial art accumulate a “fancy mess” that distorts and cramps their practitioners and distracts them from the actual reality of combate, which is simple and direct. Instead of going immediately to the heart of things, flowery forms (organized despair) and artificial techniques are ritualistically practiced to simulate actual combat. Thus, instead of “being” in combat these practitioners are “doing” something “about” combat.

Worse still, super mental power and spiritual this and spiritual that are desperately incorporated until these practitioners drift further and further into mystery and abstraction. All such things are futile attempts to arrest and fix the ever-changing movements in combat and to dissect and analyze them like a corpse.

Set patterns, incapable of adaptability, of pliability, only offer a better cage. Truth is outside of all patterns.

What labels do you wear?

What type of belief cage have you built for yourself?

Are you willing to step outside of all patterns, into uncertainty, in order to move closer to truth?

 

 

The Dark Side of Jesse Livermore
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Jesse Livermore’s Strategy Had A Major Flaw: Position Sizing

Jesse Livermore is commonly cited as one of the best market speculators of all time.

But is this true?  

On the one hand he did invent solid trading rules for his strategy that have stood the test of time:

  • Cut Your Losses: Never average down and never hope your losses reverse. Just cut them.
  • Infinite Patience: Good trades are rare. Trade for profits, not for action.
  • Learn Macro: Understanding general conditions is essential to market mastery.
  • Price Action Is King: Learn to read the tape and don’t argue with markets — they know more than you.
  • Bet Big / Sit Tight: Ride your winners for all they’re worth.
  • Self-mastery: You are the greatest impediment to your own success. “Know thyself”.

But this widely worshipped man also had a fatal flaw.

Jesse Livermore could create tremendous wealth, but he couldn’t hold onto it.

When you go back and read the newspapers from later in JL’s career, it’s not a pretty picture.

Here’s an NY Times excerpt from April 18th, 1934, right in the middle of the Great Depression, when Livermore was filing for bankruptcy:

Mr. Livermore filed a bankruptcy petition in Federal court on March 5, listing liabilities of $2,259,212.48 and assets of $184,000. It was his fourth failure and second formal bankruptcy. After each previous failure he has been able to come back and repay his creditors, and he appeared confident yesterday he would be able to so again.

Going bust multiple times is not something you’d expect from a master trader. It’s what amateurs do…  

After the 1929 crash, Livermore had amassed $100 million dollars ($1.39 billion in today’s terms). Yet somehow, within just five years, he managed to torch that lofty sum and find himself back in bankruptcy court…

JL definitely had an edge — it’s hard to run up multiple accounts like he did without one — but why did he keep going broke?

It’s because Jesse Livermore habitually bet too large.

This explains how he accumulated mind boggling amounts of money in short periods of time, only to lose it all just as quickly.

And unfortunately for him, JL’s fatal flaw created his fame.

The larger the swings, the more interesting the news story. And since JL took the biggest swings around, he was the one written about in the papers.

The upswings reinforced his bad habit, while the downswings were explained away as “bad luck.”

JL consistently underestimated the size of his edge and bet amounts that guaranteed his bankruptcy over time.

Even if you have a solid edge, luck still plays a role in the outcome of any particular trade. You have to size your positions so that a string of losers won’t blow out your trading account.

At Macro Ops we’re all for sizing large when the stars align — it’s how the trading greats achieved stellar returns. But there’s a limit to how much you can safely bet.

Take the simple example of an unfair coin where heads comes up 90% of the time. And say you’re playing someone willing to give you 1:1 on your money if you guess right.

Obviously betting on heads makes the most sense here. There’s a huge edge. But how much money should you bet?

  • 10% of your net worth?
  • 20%?
  • 100%?

It’s easy to see that if you bet your whole wod every time you’ll eventually go broke. Hit just one tails and you’re in bankruptcy court with Livermore.

You could make huge bets and make astronomical sums in a short time, but keep playing like that and there’s a 100% chance of going belly up.

Jesse Livermore kept betting too large on his unfair coin, hence the nickname “boy plunger.” The deck was stacked in his favor but he lacked the bankroll management to successfully realize his edge over the long haul.

The science behind bet sizing came long after JL’s colorful career. A math genius by the name of Edward Thorp popularized the use of the Kelly Criterion in markets. The Kelly number tells us the maximum amount we can bet on an edge without risking bankruptcy.

Had Livermore known about this concept back in his day, he might of been able to avoid the insane swings that ultimately drove him to suicide.

It takes balls to bet big and jettison yourself to trading greatness. But be aware of the consequences.

The larger you size your trades, the more your success becomes a function of luck rather than skill.

Food for thought: If Livermore bet smaller, would we even know of his name today?

If you would like to know how we approach the bet sizing problem you can check out our investment handbook here.

 

 

How George Soros Finds His Trades

George Soros’ Trading Strategy: How Soros Finds Trades

The following is straight from Operator Kean, a member of the Macro Ops Collective. To contact Kean, visit his website here.

One of the things that makes George Soros a market legend is his uncanny ability to find lucrative trades.

Let’s take a look at how his trading strategy helps him do it.

(I) Look Forward!

Most traders realize they need to be forward looking. But few practice it.

The reality is… herd mentality and groupthink are hard forces to overcome.

Instead of looking at the recent past and extrapolating into the future, Soros focuses on variables that might be misunderstood or overlooked. If one of these variables upsets the present consensus, he knows a large move will likely occur and reward those who anticipated the potential disruption.

In John Train’s Money Masters Of Our Time, Jim Rogers, an ex-colleague of Soros, explained their process:

We aren’t as much interested in what a company is going to earn next quarter, or what 1975 aluminium shipments are going to be, as we are in how broad social, economic, and political factors will alter the destiny of an industry or stock group for some time to come. If there is a wide difference between what we see and the market price of a stock, all the better, because then we can make money.

Stanley Druckenmiller, Soros’ right hand man during Quantum’s epic performance, outlines this concept further:

[My] job for 30 years was to anticipate changes in the economic trends that were not expected by others, and, therefore not yet reflected in security prices.

Too many investors look at the present; the present is already in the price. You’ve got to think out of the box and visualise 18 to 24 months from now what the world is going to be and what (level) securities might trade at… what a company has been earning doesn’t mean anything, what you’ve got to look at is what people think a company’s going to earn and if you can see something in 2 years that’s going to be entirely different than the conventional wisdom, that’s how you make money.

Soros’ Japanese trade in 2012 and 2013 is the best modern example of the master riding a forward looking idea to enormous gains.

After the 2011 Fukushima disaster, foreign investors fled Japanese financial assets. Pessimism surrounding the struggling economy was extremely high.

There were talks of a “nuclear holocaust” as people became concerned about a radiation fallout. And the Eurozone’s sovereign debt crisis (happening at the same time) didn’t help either.

Together they fueled risk aversion across global financial markets, causing the Japanese Yen to strengthen relative to other currencies.

The stronger JPY caused Japanese exporters to earn less after currency translation, which meant their stock prices struggled as well.

For nearly a year after the Fukushima disaster sent prices tumbling lower, the market did next to nothing. Valuations were cheap and depressed.

No one was interested in Japan. Investors were convinced the country would continue its decades-long battle with deflation.

With all this negative sentiment, the market completely overlooked Shinzo Abe taking leadership of the LDP in September 2012…

But Soros didn’t.

Forbes reported that Soros was actively participating in the Japanese equity markets while being short their currency as early as October 2012.

Abe-san only assumed the role of Prime Minister in December, meaning Soros’ firm was early in anticipating the “Abe” variable’s potential effect on Japan’s asset markets. He was positioned before reality materialised.

Anticipating how variables (that the majority aren’t thinking about) could change current security pricing is the hallmark of a successful speculator.

We all know what happened after that.

PM Abe pushed for his promise of “ending deflation’” and the Bank of Japan (BOJ) launched its aggressive monetary easing programme in April 2013.

The JPY got crushed and Japanese equities took off.

An investor using either traditional valuation metrics or plain old technicals would likely have been reluctant to foray into Japan before Abe-san was elected (there would be no buy signal according to their framework). But Soros was able to stay ahead of the crowd and capitalise when the unexpected situation materialised. 

This is macro investing on a higher level. Learn to anticipate!

(II) False Trends —  Learn To Play Them!

Soros once said there are 3 realities:

  1. Things that are true
  2. Things that are untrue
  3. And things that are reflexive

He believes we need to differentiate our circumstances to understand these 3 types of realities. In particular, he emphasises defining false trendswhich occur when a belief is founded on false assumptions, but many believe it.

Since there’s nothing in financial markets that can be determined for sure (with 100% confidence), false trends and reflexive realities are prevalent.

According to Soros, false trends can be so dominant, that they move financial markets, causing a cascading effect on asset prices and secondary effects that reinforce the initial false beliefs. This reflexiveness creates a false reality, which is exactly how bubbles form.

Soros believes you can make money from these trends, even when you know they’re false. Doing so requires establishing positions at appropriate times while maintaining objectivity and flexibility. And of course, sticking to your risk management plan is key.

The steps to exploit a false trend are:

  1. Analyze assumptions to determine if they’re true or not
  2. Identify false trends based on those assumptions
  3. Evaluate how feedback loops form and affect the fundamental reality

Don’t strive for an ideal or perfect explanation in the markets. Be sober, analytical, and pragmatic. Seek to invert your thinking and understand all possible viewpoints.

Big questions of our time like ‘Is China imploding?’ or ‘Are cryptocurrencies the future?’ are issues that fall into these realities. Whether they’re true or not doesn’t matter to the master speculator. What matters is whether you can exploit them to profit!

(III) Look For “Experimental Economics”

Soros is constantly on the lookout for financial situations where there’s a “great amount of experimenting”.

Experimenting with complex systems like economies generally leads to imbalances and unintended consequences. Soros loves to exploit these. As he once said, “the accumulated drawbacks of specific imposed economic models simply provide a playground for financial market speculators”.

Is there a government meddling with the free market (capital controls and such)?

Is there a central bank, for whatever illogical reason, pegging its currency?

These are circumstances that pique Soros’ interest. He’s ruthlessly speculated in many of these situations during his career. The most famous example is his bet against the Bank of England in 1992.

There was also another situation in the 1990s where Soros observed that the boom in Asian economies would reverse and come crashing down if liquidity conditions changed.

The stage was set as most Asian economies had their debt denominated in hard currencies like the US Dollar, while they booked their revenues in their own local currencies. Additionally, many Asian central banks maintained a peg to the greenback to help them tap into international debt financing.

This was a classic reflexive scenario where a strengthening USD would cause severe economic contractions throughout emerging Asian economies. A stronger dollar would also lead an even stronger dollar as the situation reinforced itself, trouncing the Asian economies.

This eventually forced Asian central banks to break their dollar peg after finally being overwhelmed. Soros positioned himself in several markets like Thailand, profiting from the 1997 crisis.

Macro dislocations, far-from-equilibrium situations, politicians meddling with free market affairs… these are all playgrounds for the macro speculator. Look around you — is there any ‘experimental economics’ going on?

(IV) Fade Extreme Investor Positioning

In December 2012, activist investor Bill Ackman went public in his crusade against Herbalife (HLF). He was shorting the company’s stock while accusing it of conducting a huge pyramid scheme.

Ackman’s war against Herbalife also sparked “billionaire battles” as other well-known Wall Street tycoons took sides. The most prominent of them all was Carl Icahn, who went long HLF and publicly sparred against Ackman, debating his claims.

It was reported that Soros went long HLF  sometime in the second quarter of 2013, which spurred a rally in the stock price. About 2 years later, Soros fully exited his long position during the third quarter of 2015.

Soros slipped in and out of the stock while Ackman and Icahn were playing tug-of-war over who was right…

We don’t know who’ll eventually be right, but we do know that Soros profited during that tug-of-war. Regardless of his fundamental view, market sentiment and positioning gave Soros the opportunity to profit off a gigantic short squeeze.

Look for popular trades or overcrowded positions. You may agree with the consensus view, but if most participants are positioned that way, you may want to fade them.

This fourth point may be unorthodox, but that’s how the Palindrome played the game. Remember, you’re here to make money, not to prove whether your opinion is right or wrong!

To learn more from George Soros and other investing legends, click here.

Review:

  1. Be Forward Looking
    • Anticipating how variables (that the majority aren’t thinking about) could change current security pricing is the hallmark of a successful speculator.
  2. Learn To Play False Trend
    • Analyze assumptions to determine if they’re true or not
    • Identify false trends based on those assumptions
    • Evaluate how feedback loops form and affect the fundamental reality
  3. Look For Experimental Economics
    • Governments experimenting with complex economic systems generally leads to imbalances and unintended consequences ripe for exploitation by smart speculators.
  4. Fade Extreme Investor Positioning
    • When everyone is on one side of the boat, sometimes it pays to take the other side!

 

 

Stanley Druckenmiller On Liquidity Macro and Margins
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Stanley Druckenmiller On Liquidity, Macro, & Margins

(Note: If you’re interested in learning how to gauge liquidity and sidestep the next market selloff, then download our Liquidity Tracking Guide here.)

What’s obvious is obviously wrong… The present is already in the price… And it’s margins and capacity that matter ~ Stanley Druckenmiller

The following are some more words of wisdom from Druck pulled from an old Barron’s interview in 88’. There’s a few notes from me as well…

Gauging the macro environment through three different lens (emphasis by me):

We look at the market in three different ways — and each of them is flashing warning signals. First of all, we look at valuations. We use them to determine, really, the market’s risk level, as opposed to its direction… Valuation is something you have to keep in mind in terms of the market’s risk level… when catalyst’s come in and change the market’s direction… the decline could be very major if you’re coming from the kinds of overvaluation levels witnessed in ‘29 and the fourth quarter of last year (note: this was in the year following the 87’ crash). So valuation is something we keep in the back of our minds.

The major thing we look at is liquidity, meaning as a combination of an economic overview. Contrary to what a lot of the financial press has stated, looking at the great bull markets of this century, the best environment for stocks is a very dull, slow economy that the Federal Reserve is trying to get going… Once an economy reaches a certain level of acceleration… the Fed is no longer with you… The Fed, instead of trying to get the economy moving, reverts to acting like the central bankers they are and starts worrying about inflation and things getting too hot. So it tries to cool things off… shrinking liquidity [While at the same time] The corporations start having to build inventory, which again takes money out of the financial assets… finally, if things get really heated, companies start engaging in capital spending… All three of these things, tend to shrink the overall money available for investing in stocks and stock prices go down…

Druck has also said:

Earnings don’t move the overall market; it’s the Federal Reserve Board… focus on the central banks and focus on the movement of liquidity… most people in the market are looking for earnings and conventional measures. It’s liquidity that moves markets.

This is absolutely true. Liquidity is a key metric we track at Macro Ops. It’s also the most misunderstood by market players. To read more on the topic of liquidity, check out this piece.

(Note: If you want to learn how to track liquidity to identify the next market crash, then check out this guide right now.)

Also, this next line is so important to understand:

…the best environment for stocks is a very dull, slow economy that the Federal Reserve is trying to get going.

Once you understand how and why liquidity works, you’ll fully grasp the old Wall St. adage of “Don’t fight the Fed”. The Fed controls the biggest lever on global liquidity. And liquidity is what drives stocks… NOT the economy.

Think about the last eight years of the current bull market. Economic growth has been pathetic, inflation fleeting, and confidence in the direction of the economy dour. But at the same time we’ve experienced one of the largest and longest bull markets in history…  

The pundits and fin-twit bears who’ve been shouting about impending doom and gloom, crying about how detached the market is from the “fundamentals”, don’t understand the most important fundamentals of them all: liquidity and sentiment.

The worse thing that could happen to this current bull market is for the economy to markedly pick up. That growth would spur inflation, which along with improved sentiment, would make the Fed a lot more comfortable tightening at a faster pace. Liquidity would then be pulled from the system and drive the stock market lower.

Don’t confuse the stock market with the economy. Understand that the market is forward looking and the biggest lever on future demand is liquidity. That’s why you need to understand the reaction function of the Federal Reserve.

On valuations and market moves:

In this century the stock market has tended to trade between 1.1 and 2.2 times book… And stocks generally yield between 6% or 7%. When people are feeling good about the world, for some reason, 2.1 to 2.2 times book and 3% yield tend to be the cap…

I do know that every time the stock market has gone down 30% in this century, we’ve had a recession. The only good economist I have found is the stock market. To people who say it has predicted seven out of the last four recessions, or whatever, my response is that it’s still a lot better than any of the other economists I know.

Concentrated bets and the importance of focusing on margins:

To try to add value to our portfolio, we make very concentrated bets in industry sectors, rather than simply being overweight or underweighted in terms of the S&P. If you look at our portfolios over time, four to five industries tend to represent 90% of the holdings — long and short… We choose these industries by trying to buy companies where we feel the margins are going to be higher in one to three years and selling companies where we feel they’re going to be lower in one to three years.

[In response to the question of why focus on margins?] It’s tied in with my liquidity argument. When corporate America is operating at very high rates, it starts building capacity, which sucks out liquidity; it also lowers companies margins two years out. And that’s the opposite of when a bull market starts…

With the longs, we are trying to identify situations where we feel that margins are going to be higher over the next year or two. We’re trying to identify industries that are operating at fairly low rates, which will be rising, but where you won’t see capacity increases for at least a couple of years, and where the profit margins will be much higher by then. [And] we don’t sell things just on a valuation basis… We need to see what is going to make the margins come down…

There are a number of important points here. Druck is noting the importance of trading off future outcomes in relation to current expectations instead of trading the present reality. In a talk at USC a number of years ago he said:

Too many investors look at the present, the present is already in the price. You have to look think of the box and sort of visualize 18 to 24 months from now what the world is going to look like and what securities might trade at.” What a company is earning right now doesn’t mean anything. What you have to look at is, what a company is earning and what people think it’s going to earn and if you can see something that in two years is going to be entirely different than the conventional wisdom, that’s how you make money. My first boss said “what’s obvious is obviously wrong.”

A useful tool for valuing potential future outcomes is the margins of sectors and industries. There’s a cyclicality in margins that provides a window into the point of the capital cycle a particularly industry or sector is in.

Fat profit margins attract competition. Competition leads to increased investment. Increased investment leads to glut and contracting margins until capacity is taken offline. And then the cycle begins anew.

Stanley Druckenmiller is among the greatest traders to ever play the game. His big advantage is that he understands liquidity and how it drives macro. And knowing macro is one of the most important keys to market success. As one of Druck’s proteges, Scott Bessent put it:

Recently, I was at a money manager roundtable dinner where everyone was talking about “my stock this” and “my stock that”. Their attitude was that it doesn’t matter what is going to happen in the world because their favorite stock is generating free cash flow, buying back shares, and doing XYZ. People always forget that 50% of a stock’s move is the overall market, 30% is the industry group, and then maybe 20% is the extra alpha from stock picking. And stock picking is full of macro bets. When an equity guy is playing airlines, he’s making an embedded macro call on oil.

 

To learn how to gauge liquidity and sidestep the next market crash, download our liquidity tracking guide and cheat sheet here.

What Traders Can Learn From Professional Horse Betting
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What Traders Can Learn From Professional Horse Betting

Thegreek.com, a horse racing blog, discusses the “seven deadly sins” losing horse bettors commit. Repeat these sins in your trading and you’ll suffer the same fate as the losers at the track.

Here are the four most important sins to avoid:  

Deadly Sin No.1: The most important thing is picking winners.

Wrong! Professional horse bettors will tell you that trying to pick the winner of the race is a failed strategy and that it’s far more important to get value. What’s “value?” Consider this: A horse that you handicap as a legitimate even-money favorite should win about half the time. So that horse is a bad play at 4/5 or less. A horse that you analyze should win about one in four times the race is run, should be about 3/1. That horse won’t win as often as the even money shot but if you can get value, say 5/1 or higher, you’ll make money in the long run.

The few horse bettors good enough to make a living know it’s not about picking a winner. It’s about identifying positive expected value. Oftentimes that means the lower probability play is the better bet.

If an option is currently priced to profit 1 in 10 times, but you think it’ll profit 2 in 10 times, then buy it. It’s a value. It doesn’t matter that most of the time the option will expire worthless. Over the long haul, the buyer will walk away profitable.

Deadly Sin No.3: You should bet more on a horse you really like, such as your “best bet.”

Ridiculous. Why bet if you don’t like who you’re betting? Put another way, any horse worth betting is one worth betting significantly. Sophisticated bettors usually bet about the same amount on every bet. After all, as one professional gambler told me, “If I knew what my ‘best bets’ were I’d only bet those.” A “best bet” is a media creation. If you know what you’re doing, your best bet always should be the next bet you make.

Professional track gamblers understand that bet size is incredibly important. Sizing your bets based on “hunches” leaves you susceptible to accidently betting big on losers and tiny on winners.

Imagine three trades where you’re right on the first two and wrong on the last. And since you thought you had a “hot hand”, you bet really big on that last loser. This would result in the losses from the last trade cancelling out the gains from your first two winners. Your account would end up net negative.

Sizing up has a time and a place in trading. Soros would bet big when the stars aligned. But you need lots of experience before you can start sizing up on what you think are great trades.

Until you’re seasoned and able to decipher between a good and great bet, keep your position sizes consistent. If you don’t, you risk going broke from bad luck.

Deadly Sin No. 4: Statistical betting trends are important.

Actually, they’re not. “Technical handicapping,” as it’s called, is another of those manufactured disciplines used by professional touts, not professional horse racing bettors. Mostly, technical handicapping—wherein statistics are employed to predict an outcome—are little more than “backfitting,” a practice where someone makes up a theory to fit a set of numbers. It’s a lazy handicapping shortcut and no replacement for hard analysis.

Ever wonder why those really smart quants with the fancy degrees end up blowing up? It’s because they have too much trust in a model tightly fit to past data.

Studying the past can help you figure out what’ll happen in the future, but only within reason. If you create a trading model based on the premise that the future will play out exactly like the past… it will fail.

Keep historically based assumptions as simple as possible. That will help thread the needle between useful insight and robustness.

Deadly Sin No. 7: Specialize in certain aspects of the game and pick your spots.

Why limit yourself? If you never bet grass races or stay away from maidens you may be missing some great betting opportunities. When you gamble, having more options always is preferable.

That’s why our team at Macro Ops trades global macro. If stocks dry up, we have the flexibility to drop into the grains market or currencies or any other market where there’s high expected value profit opportunities. The more markets you learn to trade, the easier it is to trade only the most attractive setups.

For a deeper look into our team’s trading strategy, check out our Macro Ops Handbook here.