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Yield Curve Inversion!? Flattening Yield Curve Explained

The Yield Curve Inversion Secrets! Understanding the Flattening Yield Curve is crucial for any trader or investor!

Today we’re going to talk about the yield curve. Recently the financial media has been raving about the yield curve getting closer and closer to inverting and how it’s a signal that a recession is right around the corner. In this video we’re going to go over what the yield curve is, how to use it, and what it’s really signalling about the market.

The yield curve is basically just a line that plots the yield of US treasury bonds (TLT) with different maturity dates. The curve lets you easily compare rates on short term bonds versus long term bonds. When long term bonds are yielding more than short term bonds, the line rises from left to right. And when this is the case, it’s called a normal yield curve. This is signal that the economy and market are doing okay.

When you start to see the yield curve flatten or even invert, meaning short-term rates become equal to or higher than long-term rates, and the line either becomes flat or sloped lower from left to right, then that usually signals trouble ahead in terms of a recession and lower market prices.

Two things happen for the yield curve to become like this. First, the Fed starts raising short-term rates. Based on their mandates, they may see the economy overheating and decide to raise rates to slow it down. Higher rates hurt economic expansions.

Second, investor expectations for the future become negative. And because of that, they buy up long-term bonds, lowering their yield. Those two together you a flat or inverted yield curve where short term bonds yield the same or even more than long-term bonds. And like this signals trouble ahead.

According to our analysis, yes the curve is beginning to flatten and invert, but we still have a lot of time left before this bull iis done. Make sure to watch the video above for more!

And as always, stay Fallible investors!

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High Quality Trading Is Episodic, Not Continuous

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

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

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

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

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

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

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

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

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

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

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

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

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

There’s a few reasons for this.

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

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

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

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

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

So if you’re an independent trader who

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

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

Start by weed wacking your trade “setups.”

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

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

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

Finally, expand your playing field as much as possible.

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

 

 

The 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!

 

 

Another Lesson In Position Sizing From The Volpocalypse of 2018
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Another Lesson In Position Sizing From The Volpocalypse of 2018

Most famous fund failures have leverage at their core. That’s the true culprit for disaster —  not the actual trade ideas. Bad position sizing kills.

Long Term Capital Management’s strategy involved scanning the world for bond spreads that diverged from historical values — something known as convergence trading. When spreads diverged from their means, LTCM would buy the cheap and sell the expensive bond. Then wait for prices to revert back to their “theoretical efficient” market price and make a small profit.

But LTCM wasn’t satisfied with the tiny profits on the spread. They were “Masters of the Universe” and wanted to put up bigly numbers that smoked the S&P. So they took this simple strategy and leveraged up to high heaven.

Before LTCM was incinerated they had a portfolio market value of $129 billion. Of which, $125 billion was borrowed money. That’s a leverage ratio of 32:1.

Once old lady volatility hit the market, those bond spreads that LTCM had leveraged to infinity betting that they would quickly converge just like all previous times… kept diverging… and diverging.  Until eventually LTCM was forced into liquidation.

Leverage and crowding caused the forced unwind of the trade. Not the strategy of buying cheap bonds and selling expensive bonds. LTCM had a good strategy that they ruined with excessive leverage.

The exact same leverage issue happened to Victor Niederhoffer in 1997.

After suffering from a huge loss on Thai stocks during the Thai Baht crisis, Niederhoffer turned to aggressive S&P 500 put writing in order to “make back” his losses.

Over the summer of 1997 he shorted out-of-the-money November 830 puts for prices between $4 and $6.

By October these puts were trading for just $0.60 and Niederhoffer had a large gain. But the Asian Contagion spread and eventually hit the S&P.

On Thursday October 23rd, 1997 the puts rose to $1.20. On Friday the S&P dropped further but closed well above Niederhoffer’s option strike. Niederhoffer still wasn’t worried — his puts were trading for $2.40.

Over the weekend Asian markets continued to sell off. Hong Kong dropped 5% during its session which triggered a risk off move in the US markets driving stocks down 7%. This rout continued into the next morning sending the S&P spiraling into the 800s.

Volatility skyrocketed. And Niederhoffer’s puts shot up to $16. That’s 300% higher than the price he sold them for.

Refco, Niederhoffer’s broker at the time, was not happy. They called in his puts mid-morning on Tuesday October 28th for a loss of $90 million. Niederhoffer’s $70 million fund turned into a capital blackhole of -$20 million.

The market bottomed right after Niederhoffer was margin called. By November, the market was back near highs. His 830 puts went on to expire worthless — meaning his trade, had he been able to hold on, turned out to be profitable.

But his leverage forced his liquidation. He was oversized and couldn’t ride the trade out.

Niederhoffer had shorted so many puts that a run of the mill two-day market selloff sent him out on a stretcher.  

If he had sized the trade correctly, he would have survived the ride and took home a small profit. But the guy was playing on tilt, got greedy, maybe a bit arrogant, and lost all of his client’s money. (Here’s an interesting clip of him post blow up)

With the trading history books filled with examples like these where hubris and stupid sizing led to catastrophe you’d think trader’s today would maybe, learn from the past. But of course that’s not the case. Human nature is after all, human nature. And “easy” money is quite effective at clouding our better judgement.

The Volpocalype of 2018 showed us that both amateur and professional traders are still making the same mistakes with position size and leverage.

LJM partners, a mutual fund that sells options just like Niederhoffer did and whose tagline was “superior returns for the patient investor” followed the LTCM playbook.

A not-out-of-the-ordinary 10% fall in the S&P forced the fund to close positions at extremely unfavorable prices.

And then there was this amatuer XIV trader from Reddit who lost nearly $4 million dollars in XIV.

XIV goes up over time. But it also has incredibly nasty drawdowns that can exceed 90%. XIV trades more like an option than a stock. It has the ability to go up 100s of percent but also the ability to go down 90-100%.

Knowing this it’s crazy to think that anyone would allocate 100% of their portfolio into this exotic product.

So why did this Redditor do it?

Why did LTCM, and Niederhoffer and LJM carry such large positions?

Why do we constantly have a steady stream of stories about traders leveraging to the hilt and blowing out their accounts?

At the end of the day it all comes down to greed and hubris. It’s because traders want to turn a sound strategy that can produce 10% per annum returns into something that generates 30% per annum. And of course the only way to do this is to leverage the capital.

But as we’ve seen time and time again, the more you leverage the higher your chances are of ending the game bankrupt. And at a certain level of leverage your chances of going bankrupt actually converge to 100%.

That’s why it’s crucial to get position sizing right alongside a solid trading edge.

The late John Bender explains this perfectly in his interview inside Stock Market Wizards.

It might seem that if u have an edge, the way to maximize the edge is to trade as big as you can. But that’s not the case, because of risk. As a professional gambler or as a trader, you are constantly walking the line between maximizing edge & minimizing your risk of tapping out. ~ Market Wizard John Bender

I can illustrate this concept with a simple example.

Here’s a decent “good enough” trading strategy that starts with $10,000 in account equity.

From mid-2004 to mid-2010 it did pretty well. $10,000 turned into around $33,000.

Now here’s the exact same trading strategy, with the exact same starting equity, but with 10x the position size.

The allure of leverage is obvious. The 10x model at its height had a 1000x gain. $10k turned into $10 million. The prospect of outsized returns is what lures traders to lever.

But it’s a farce. Using this amount of leverage guarantees a blow up will occur at some point. And unfortunately for this trader he didn’t stop and ended the game with a $3 million debt to the broker.

To position size correctly you need robust risk management assumptions. That means assuming any product can trade at any price at any time.

If your trading VIX for example, assume it can go from 10 to 100 overnight. That might sound asinine but in reality it keeps you safe. Because at the end of the day anything can happen.

By putting extreme scenarios in your universe you can devise a way to survive should it occur. This way of thinking will keep you from botching position size.

Traders that blow up and over lever don’t think like this. Instead they use models that rely on past data to estimate “probable” risk.

Throw those methods out. Historical data means nothing when it comes to risk management. The future will always bring something more intense than the past.

Another thing to be cognizant of is that strategies with negative skewness (frequent small wins and large rare losses) are especially tricky to position size correctly.

LTCM, Niederhoffer, LJM, and that XIV Redditor were all implementing strategies with negative skewness.

If you’re strategy has these characteristics it’s even more important to run extreme stress testing on your process and assume that your trading vehicles can trade at any price at any time. Size your positions from that extreme stress test. Never rely on past historical moves to define your risk in a negative skew trading strategy. The traders that rely on past data to size up risk always blow up.

Please think deeply about your position sizing process. If you don’t get it right you’ll end up in Taleb’s Turkey Graveyard with the rest of the traders who flew too close to the sun.

 

 

Hedge Fund Letters For Generating New Equity Ideas
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Top Ten Hedge Fund Letters For Generating New Equity Ideas

I’m often asked how I come up with trading ideas. My usual response is that I do a lot of reading, talking to other traders, and thinking.

I don’t have a single funnel for sourcing trades. This is partly because we’re interested in all types of trades (ie, value, classic macro, special situation etc…) and don’t limit ourselves to a particular approach. What were concerned with, is asymmetry… the greater the convexity the better.

Since I can’t give you my network of traders and HF managers I talk shop with, I thought I’d do the next best thing and share with you my go-to reading list of quarterly fund letters, sites, and blogs that I read regularly for idea generation. There’s a lot of fund managers out there, and most aren’t worth their salt. The selection below includes the few I believe have the most talent.

You’ll notice this list is skewed heavily to small-cap value managers. The reason is that these are the ideas that I’m most interested in from others. I don’t read a lot of other macro work because that’s the world I live in. And many of these value fund managers can devote a lot more time to investigating a single company, than I ever could. We always do our own due diligence, of course. But when you have a stable of great value fund managers doing the initial filtering for you, it’s a big help.

Like Picasso said, “Good investors borrow, great investors steal”… or something along those lines.

Here are my quarterly must-reads. The few reports that I never miss and from which I have stolen many great ideas from. Also, reading these letters is like receiving a masters in value investing. Some great nuggets in all of them (links to report sections included on all names).

  • Greenhaven Road Capital: This is a small-cap value fund run by Scott Miller. Miller is kind of an unknown. He keeps his AUM small and maintains a low profile. But the guy knows how to value a business and his reports always make for a great read.
  • OakTree Capital – Howard Marks’ Memos: Marks is an investing legend and there’s not much else to add to that. You won’t find stock ideas in his memos but you’re almost certain to learn something.
  • Greenwood Investors: This fund is run by Steven Wood who’s also a relatively new up and comer. He’s got a similar style to Scott Miller and is a good resource for contrarian value plays.
  • Cable Car Capital: Is run by Jacob Ma-Weaver who’s a sharp value oriented investor. He always presents unique and interesting investing ideas in his letters. He also occasionally posts some great stuff on his blog.
  • Arkto Investors: Is run by Peter Rabover and focuses on value and special situations. Another great resource for the undiscovered stocks. His letters are hosted on Harvest, so you’ll have to create an account if you don’t have one already (it’s free).
  • Miller Value Funds: Run by Bill Miller, who’s another investing legend, though his record was tarnished in the GFC when his fund took a serious beating. But he’s back, with his own fund, and he’s putting up good numbers again. I really enjoy his thinking and writing and posts/letters found on the site are a great source of idea generation.
  • Horizon Kinetics: Horizon is a larger shop that specializes in bottom up fundamental research. Their quarterly letters are always an insightful and fun read.
  • Peters MacGregor Capital Management: Is another large shop, but with a global focus. It’s a great resource for stock/market idea gen outside of U.S. markets. They also regularly share decent video presentations where they talk over an investment their in.
  • Laughing Water Capital: Run by Matt Sweeney, LWC is a long-term value oriented shop.
  • Saber Capital Management: A value focused fund by John Hubner. Quarterly letters always include some great thoughts on investing theory/wisdom, along with some great investment ideas.

So these are the quarterly letters that I make sure to at least skim through each quarter if not read in their entirety. For idea generation I also find sites like Value Investors Club, MOI Global, and SumZero useful. VIC and SZ are free as long as you submit an approved idea.

Some other sites that are worth checking out are The Patient Investor’s Blog (Longcast Advisers), Wiedower Capital is pretty good, and so are Dane Capital and Breach Inlet Capital on Seeking Alpha.

Shoot me a message at alex@macro-ops.com if you’ve got a letter/resource you use that I didn’t mention here.

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.

~~~~~~

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.

 

 

Ed Thorp
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Lessons From A Trading Great: Ed Thorp

Ed Thorp, the father of quant investing, might be the most impressive market wizard. He turned seemingly random processes into predictable events, transforming the art of speculation into a science decades before Wall Street’s quants became mainstream.

His domination in the financial world began in the casino. Thorp figured out how to beat the most “unbeatable” games. In roulette, he created a wearable computer that gave him a 44% edge. And in blackjack, he developed the very first card counting system that’s still widely used today.

These gambling skills transferred perfectly to markets. Thorp’s first hedge fund, Princeton Newport Partners, never had a down year. It compounded money at 19.1% for almost 20 years — destroying the S&P 500.

His second fund, which he ran from August 1992 to September 2002, performed just as well with an annualized return of 18.2%.

Thorp’s list of discoveries, inventions, and people he’s influenced and invested in is comically long:

  • He discovered an options pricing formula before the Black-Scholes model became public.
  • He started the first ever quant hedge fund.
  • He was the first to use convertible and statistical arbitrage.
  • He was the first limited partner in Ken Griffin’s Citadel — one of the most successful hedge funds ever.
  • His books on blackjack and trading heavily influenced “bond king” Bill Gross.
  • He discovered that Bernie Madoff was a fraud many years before it became public.

And the list goes on…

Thorp’s advice on approaching games of incomplete information is methodical and scientific, making it very useful to incorporate into your own trading process. The following is his most valuable wisdom with our commentary attached:

Rare Events (Fat Pitches)

Fat pitches — the types of trades Buffett, Druck, and Soros salivate over— happen seldomly. And that makes sense because is takes extraordinary circumstances to push markets far enough from equilibrium to create these opportunities.

When these dislocations occur, it pays to go on high alert. It’s possible to make your year or even your career in a few days by hitting these fat pitches on the nose.

Here are a few of Thorp’s best plays:

1987 Crash

Black Monday was a traumatizing experience for most traders… but not for Thorp. When the crash started to accelerate Thorp was having his daily lunch date with his wife Vivian. The office called to report the news and Thorp didn’t even flinch. He had already accounted for all possible market scenarios, including this one, and didn’t have any reason to panic. He calmly finished his lunch and then went home to think about how to exploit the situation. This is what he came up with:

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

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

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

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

Kovner Oil Tanker

In the 1980s, Bruce Kovner discovered a trading opportunity in buying oil tankers for scrap value. Thorp instantly recognized the fat pitch and invested.

Along with Jerry Baesel, the finance professor from UCI who joined me at PNP, I spent an afternoon with Bruce in the 1980s in his Manhattan apartment discussing how he thought and how he got his edge in the markets. Kovner was and is a generalist, who sees connections before others do.

About this time he realized large oil tankers were in such oversupply that the older ones were selling for little more than scrap value. Kovner formed a partnership to buy one. I was one of the limited partners. Here was an interesting option. We were largely protected against loss because we could always sell the tanker for scrap, recovering most of our investment; but we had a substantial upside: Historically, the demand for tankers had fluctuated widely and so had their price. Within a few years, our refurbished 475,000-ton monster, the Empress Des Mers, was profitably plying the world’s sea-lanes stuffed with oil. I liked to think of my part ownership as a twenty-foot section just forward of the bridge. Later the partnership negotiated to purchase what was then the largest ship ever built, the 650,000-ton Seawise Giant. Unfortunately for the sellers, while we were in escrow their ship unwisely ventured near Kharg Island in the Persian Gulf, where it was bombed by Iraqi aircraft, caught fire, and sank. The Empress Des Mers operated profitably into the twenty-first century, when the saga finally ended. Having generated a return on investment of 30 percent annualized, she was sold for scrap in 2004, fetching almost $23 million, far more than her purchase price of $6 million.

Sometimes the best trades aren’t on public exchanges. Looking outside traditional trading vehicles can reveal huge opportunities other traders pass up.

SPACs

An unusual opportunity to buy assets at a discount arose during the financial crash of 2008–09, in the form of certain closed-end funds called SPACs. These “special purpose acquisition corporations” were marketed during the preceding boom in private equity investing. Escrowing the proceeds from the initial public offering (IPO) of the SPAC, the managers promised to invest in a specified type of start-up company. SPACs had a dismal record by the time of the crash, their investments in actual companies losing, on average, 78 percent. When formed, a typical SPAC agreed to invest the money within two years, with investors having the choice—prior to the SPAC buying into companies—of getting back their money plus interest instead of participating.

By December 2008, panic had driven even those SPACs that still owned only US Treasuries to a discount to NAV. These SPACs had from two years to just a few remaining months either to invest or to liquidate and, before investing, offer investors a chance to cash out at NAV. In some cases we could even buy SPACs holding US Treasuries at annualized rates of return to us of 10 to 12 percent, cashing out in a few months. This was at a time when short-term rates on US Treasuries had fallen to approximately zero!

Runaway Inflation

Short-term US Treasury bill returns went into double-digit territory, yielding almost 15 percent in 1981. The interest on fixed-rate home mortgages peaked at more than 18 percent per year. Inflation was not far behind. These unprecedented price moves gave us new ways to profit. One of these was in the gold futures markets.

At one point, gold, for delivery two months in the future, was trading at $400 an ounce and gold futures fourteen months out were trading for $500 an ounce. Our trade was to buy the gold at $400 and sell it at $500. If, in two months, the gold we paid $400 for was delivered to us, we could store it for a nominal cost for a year, then deliver it for $500, gaining 25 percent in twelve months.

Notice the commonalities between Thorp’s fat pitches:

  • They’re rare and typically occur during crises. Crises create large dislocations that cause investors to act irrationally, creating huge opportunities.
  • They all have asymmetric risk/reward ratios.
  • Fast action was needed to capture each of them. Fat pitches don’t last long. Other traders will eventually find them and pounce.
  • They’re all “one of a kind” opportunities. The exact scenario had never happened before and creative thinking was needed to capitalize. Although history rhymes, it does not repeat. The next fat pitch won’t be exactly like the last one.  

Gambling As Training

Understanding gambling games like blackjack and some of the others is one of the best possible training grounds for getting into the investment world. You learn how to manage money, you learn how to compute odds, you learn how to reason what to do when you have an advantage.

Gambling is investing simplified. Both can be analyzed using mathematics, statistics, and computers. Each requires money management, choosing the proper balance between risk and return. Betting too much, even though each individual bet is in your favor, can be ruinous.

Notice how Thorp didn’t say anything about MBAs, economic degrees, or finance classes. Those don’t prepare you for the core challenges you’ll face as a trader like position sizing and risk management.

Our favorite cross-training exercise at Macro Ops is poker. Poker forces you to think in terms of probabilistic outcomes while managing your risk and establishing an edge.

Edge

You can’t succeed in trading without an edge. And a good way to find that edge is by asking yourself how the market is inefficient and how you can exploit it.

In A Man For All Markets Thorp details sources of inefficiency:

In our odyssey through the real world of investing, we have seen an inefficient market that some of us can beat where:

  1. Some information is instantly available to the minority that happen to be listening at the right time and place. Much information starts out known only to a limited number of people, then spreads to a wider group in stages. This spreading could take from minutes to months, depending on the situation. The first people to act on the information capture the gains. The others get nothing or lose. (Note: The use of early information by insiders can be either legal or illegal, depending on the type of information, how it is obtained, and how it’s used.)
  2. Each of us is financially rational only in a limited way. We vary from those who are almost totally irrational to some who strive to be financially rational in nearly all their actions. In real markets the rationality of the participants is limited.
  3. Participants typically have only some of the relevant information for determining the fair price of a security. For each situation, both the time to process the information and the ability to analyze it generally vary widely.
  4. The buy and sell orders that come in response to an item of information sometimes arrive in a flood within a few seconds, causing the price to gap or nearly gap to a new level. More often, however, the reaction to news is spread out over minutes, hours, days, or months, as the academic literature documents.

He then explains how to exploit these inefficiencies (emphasis mine):

  1. Get good information early. How do you know if your information is good enough or early enough? If you are not sure, then it probably isn’t.
  2. Be a disciplined rational investor. Follow logic and analysis rather than sales pitches, whims, or emotion. Assume you may have an edge only when you can make a rational affirmative case that withstands your attempts to tear it down. Don’t gamble unless you are highly confident you have the edge. As Buffett says, “Only swing at the fat pitches.”
  3. Find a superior method of analysis. Ones that you have seen pay off for me include statistical arbitrage, convertible hedging, the Black-Scholes formula, and card counting at blackjack. Other winning strategies include superior security analysis by the gifted few and the methods of the better hedge funds.
  4. When securities are known to be mispriced and people take advantage of this, their trading tends to eliminate the mispricing. This means the earliest traders gain the most and their continued trading tends to reduce or eliminate the mispricing. When you have identified an opportunity, invest ahead of the crowd.

Pay special attention to his second point: Don’t trade unless you’re sure you have an edge that’ll create better than random outcomes.

An easy way to do this is by backtesting or paper trading your strategy before investing in it.

It’s also a good idea to try finding a solid trading edge in markets you love. As Thorp explains:  

To beat the market, focus on investments well within your knowledge and ability to evaluate, your “circle of competence.”

If you love following small companies then just trade those. If you come from an energy background then focus on crude oil and natural gas. And if you like math and volatility, options are a good place to start. Only venture into a new market after spending a significant amount of time studying it!

Efficient Markets

Anyone who’s actually traded knows the Efficient Market Hypothesis is bogus. It’s a poor mental model used by lazy academics. Thorp has a much better take:

When people talk about efficient markets they think it’s a property of the market. But I think that’s not the way to look at it. The market is a process that goes on. And we have, depending on who we are, different degrees of knowledge about different parts of that process.

. . . market inefficiency depends on the observer’s knowledge. Most market participants have no demonstrable advantage. For them, just as the cards in blackjack or the numbers at roulette seem to appear at random, the market appears to be completely efficient.

Markets aren’t actually random. They only appear random to those without expertise. The right knowledge transforms the market from a sequence of random numbers into a predictable process.

Combining Technicals With Fundamentals

In the mid 2000s Thorp developed a trend following futures strategy. During the process he discovered that combining fundamental information with technical signals was superior to just technicals alone.

Here he is in Hedge Fund Market Wizards:  

The fundamental factors we took into account varied with the market sector. In metal and agricultural markets, the spread structure—whether a market is in backwardation or contango—can be important, as can the amount in storage relative to storage capacity. In markets like currencies, however, those types of factors are irrelevant.

Combining technicals with fundamentals can boost your win rate. Find the key fundamental drivers in your market and add them into your process.

Anchoring

In A Man For All Markets Thorp describes his first ever trade buying a company called Electric Autolite. In the subsequent two years the stock declined 50%. He decided to hold out, hoping it would return to his entry point so he could break even. The stock eventually did rebound and Thorp got out for a scratch, but he later realized how stupid that was. Here’s Thorp reflecting on it:

What I had done was focus on a price that was of unique historical significance to me, only me, namely, my purchase price.

Thorp’s early mistake is called anchoring. Humans tend to place special significance on price levels they originally entered at. But in reality, these prices have little significance. Don’t ever emotionally attach yourself to any price.

Interpreting Financial Headlines

It’s important to take news headlines with a grain of salt. Journalists build narratives behind every market move because it’s their job. Thorp warns about getting caught up in the noise:

Routine financial reporting also fools investors. “Stocks Slump on Earnings Concern” cried a New York Times Business Day headline. The article continued, “Stock prices fell as investors continued to be concerned about third-quarter results.” A slump? Let’s see. “The Dow Jones Industrial Average (DJIA) declined 2.96 points, to 10,628.36.” That’s 0.03 percent, compared with a typical daily change of about 1 percent. Based on the historical behavior of changes in the DJIA, a percentage change greater than this happens more than 97 percent of the time. The Dow is likely to be this close to even on fewer than eight days a year, hardly evidence of investor concern.

One way to separate signal from noise is to track the market’s expected move for the day. To calculate the expected percentage move of the S&P 500, take the VIX and divide it by the the square root of 252. If price stays within that band, any “news” for the day is likely not worth paying attention to.

Correlation

All the trading greats stress the importance of correlation. A low correlation among positions diversifies the portfolio and creates a much better risk/reward profile.

Here’s Thorp from HFMW:

We tracked a correlation matrix that was used to reduce exposures in correlated markets. If two markets were highly correlated, and the technical system went long one and short the other, that was great. But if it wanted to go long both or short both, we would take a smaller position in each.

A common problem traders face when monitoring correlation is the lookback period. Thorp found that 60 days was best. A shorter window is too noisy and a longer one will produce correlations that aren’t relevant anymore.

The Moore Research Center has a free to use correlation matrix for all major macro markets. Check it here.

Leverage

Use leverage incorrectly and you’ll blow up. But properly harness it and you can engineer a risk to reward ratio that perfectly suits you.

Heres Thorp:

The lesson of leverage is this: Assume that the worst imaginable outcome will occur and ask whether you can tolerate it. If the answer is no, then reduce your borrowing.

Don’t rely on a risk control model that uses probability to estimate your max loss. Always assume the absolute worst case and manage from there.

Position Sizing

Thorp popularized the position sizing formula called the Kelly Criterion. Here he is from Hedge Fund Market Wizards:

The Kelly criterion is the bet size that will produce the greatest expected growth rate in the long term. If you can calculate the probability of winning on each bet or trade and the ratio of the average win to average loss, then the Kelly criterion will give you the optimal fraction to bet so that your long-term growth rate is maximized.

Here’s the version of the formula that works best for trading:

So for example, if a trade has a 1:1 reward to risk ratio, with a 60% chance of winning, you would bet:

((1)(.6)-(.4))/1 = .2 or 20% of your account

The one issue with Kelly sizing is that we’ll never know our true win rate or reward to risk ratio in markets. The best we can do is estimate.

Also, the effectiveness of a trading edge changes over time. Because markets evolve, the same edge won’t work forever.

This is why Thorp only uses the Kelly number as a reference. In practice it’s better to bet around half-Kelly because you get about three-quarters of the return with half the volatility.

If you’re less certain of your edge, you should bet an even smaller amount. When Thorp was working on his trend following model in the mid 2000s, he was simulating 1/10 of the Kelly number.

Thorp also has advice on drawdowns. He suggests lowering your position size during rough patches and then ramping up again as you come out of them.

If we lost 5 percent, we would shrink our positions. If we lost another few percent, we would shrink our positions more. The program would therefore gradually shut itself down, as we got deeper in the hole, and then it had to earn its way out. We would wait for a threshold point between a 5 percent and 10 percent drawdown before beginning to reduce our positions, and then we would incrementally reduce our position with each additional 1 percent drawdown.

This is an extremely robust risk management technique used by almost all the trading greats. To read more about them, download our special report by clicking here.

 

 

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.

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Do you possess these 7 traits?