Becoming a millionaire, even a multimillionaire is not all that extraordinary, becoming a billionaire is. What do self-made billionaires (and there are about 800 of them in the world) have that the rest of us don't? John Sviokla and Mitch Cohen tackle this question in The Self-Made Billionaire Effect: How Extreme Producers Create Massive Value (Portfolio / Penguin, 2014).
These billionaires (or Producers, as the authors call them) may be wired differently. They certainly think differently. They balance judgment and imaginative vision, a daunting mental task since “for most people, judgment and imagination sit on opposite ends of a mental spectrum. The more skilled one is at seeing things as they are (judgment) the harder it is to see things as they might be (imagination).“ (p. 4) Not only do they “revel in bringing clashing elements together,” “they seamlessly hold on to multiple ideas, multiple perspectives, and multiple scales.” (pp. 16, 15)
Since they “cannot predict the exact time to make an investment, … they are willing to operate simultaneously at multiple speeds and time frames. They accept that timing is not under their control, and so they work fast, slow, super slow, or in all these modes at the same time. They urgently prepare to seize an opportunity but patiently wait for that opportunity to fully emerge.” (p. 19)
Self-made billionaires are strict managers of their own time. “They appear far less busy than most executives… They intentionally guard their time, doing away with extras, distractions, and nonessential activities…. By guarding their time preciously billionaires are able to constantly cultivate and grow their innate curiosity. It gives them the time to read or converse widely on the subjects that let them make remote connections.” (p. 76)
They also have a different attitude to risk from most people, who “overestimate the risk of failure and underestimate the risk of missing out on a gain.” (p. 115) Self-made billionaires are willing to risk failure but not the chance to capture an opportunity. Contrary to myth, they don’t take irrational risks. They always want to be able to make the next investment if the first one doesn’t pan out. And, unlike most people, they have the emotional resilience to do just that.
The Self-Made Billionaire Effect is not intended to be a how-to manual for the budding billionaire. It’s written for corporate executives who have done a poor job of recognizing Producer behavior, knowing what to do with it when they find it, and figuring out how to grow the number of Producers in their firm. Even so, it provides individual entrepreneurs with a useful catalogue of attributes, habits of mind and action, they should cultivate. With a new year right around the corner, see what you can add to your list of resolutions that, this time, you’re definitely going to keep.
Tuesday, December 30, 2014
Monday, December 29, 2014
Oettingen, Rethinking Positive Thinking
Do you have some dreams for next year? What is it in you that might hold you back from realizing them? Are you simply not thinking positively enough?
Gabriele Oettingen, a professor of psychology at New York University and the University of Hamburg, has done extensive research on the power—and impotence—of positive thinking. Her findings in Rethinking Positive Thinking: Inside the New Science of Motivation (Current/Penguin, 2014) undercut the view that positive thinking can transform dreams into reality. Instead, “the obstacles that we think most impede us from realizing our deepest wishes can actually hasten their fulfillment.” (p. 8)
Positive thinking can sometimes be perilous, especially when it comes in the form of collective positive thinking. The author analyzed articles in the financial pages of USA Today dating from the beginnings of the financial crisis during 2007-2009. Using a computer program that extracted all words that dealt with the future or that carried a positive valence as well as all words that were negative or dealt with the past, they created a “future positive” index. They then used this index to explore whether positive thinking in the media correlated with movements in the Dow. Contrarians won’t be surprised to learn that they “found a clear correlation: the more positive newspaper reporting was in a given week, the more the Dow declined in the week and month that followed.” A similar finding: “the more positive the inaugural address for a given presidential term, the lower the GDP and the higher the unemployment rates were in the following presidential term.” (p. 25)
Returning to individual self-sabotaging, Oettingen found that dreaming, or positive fantasizing about something, relaxes us. It even lowers our blood pressure. That’s a problem. “In dreaming it, you undercut the energy you need to do it. You put yourself in a temporary state of bliss, calmness—and lethargy.” (p. 44)
So how do you actually accomplish your dream? First, it is important that your dream is feasible. Dreaming that next year you’ll turn a $10,000 portfolio into a $1 million portfolio is not feasible, so you should just let that dream go and move on to something more realistic.
Oettingen introduces a tool with the acronym WOOP to move people from dream to accomplishment. The “W” stands for a wish or concern you might have, “something that is challenging but that you think is possible for you to achieve in a given period of time.” (p. 104) The first “O” is the outcome: “What is the best thing that you associate with fulfilling your wish or solving your concern?” Moving beyond the standard recommendations of positive thinking, the author introduces the second “O,” the obstacle. “Find the most critical, internal obstacle that prevents you from fulfilling your wish or solving your concern.” (p. 105) Finally, the “P” represents the plan. “What can you do to overcome or circumvent your obstacle? Name one thought or action you can take—the most effective one—and hold it in your mind. Then think about when and where the obstacle will next occur. Form an if-then plan: ‘If obstacle x occurs (when and where), then I will perform behavior y.’ Repeat this if-then plan to yourself one more time.” (p. 106)
“And that’s it. You’re done.”
Before I say I’m done, here’s an amusing anecdote about dreams that aren’t feasible from Joan Didion’s Blue Nights. In her seventies, thin and frail, she was told to gain weight and devote a minimum of three hours a week to physical therapy. She writes:
“I find, … somewhat to my surprise, that I actively like physical therapy. I keep regular appointments at a Columbia Presbyterian sports medicine facility at Sixtieth and Madison. I am impressed by the strength and general tone of the other patients who turn up during the same hour. I study their balance, their proficiency with the various devices recommended by the therapist. The more I watch, the more encouraged I am: this stuff really works, I tell myself. The thought makes me cheerful, optimistic. I wonder how many appointments it will take to reach the apparently effortless control already achieved by my fellow patients. Only during my third week of physical therapy do I learn that these particular fellow patients are in fact the New York Yankees, loosening up between game days.” (p. 78)
Gabriele Oettingen, a professor of psychology at New York University and the University of Hamburg, has done extensive research on the power—and impotence—of positive thinking. Her findings in Rethinking Positive Thinking: Inside the New Science of Motivation (Current/Penguin, 2014) undercut the view that positive thinking can transform dreams into reality. Instead, “the obstacles that we think most impede us from realizing our deepest wishes can actually hasten their fulfillment.” (p. 8)
Positive thinking can sometimes be perilous, especially when it comes in the form of collective positive thinking. The author analyzed articles in the financial pages of USA Today dating from the beginnings of the financial crisis during 2007-2009. Using a computer program that extracted all words that dealt with the future or that carried a positive valence as well as all words that were negative or dealt with the past, they created a “future positive” index. They then used this index to explore whether positive thinking in the media correlated with movements in the Dow. Contrarians won’t be surprised to learn that they “found a clear correlation: the more positive newspaper reporting was in a given week, the more the Dow declined in the week and month that followed.” A similar finding: “the more positive the inaugural address for a given presidential term, the lower the GDP and the higher the unemployment rates were in the following presidential term.” (p. 25)
Returning to individual self-sabotaging, Oettingen found that dreaming, or positive fantasizing about something, relaxes us. It even lowers our blood pressure. That’s a problem. “In dreaming it, you undercut the energy you need to do it. You put yourself in a temporary state of bliss, calmness—and lethargy.” (p. 44)
So how do you actually accomplish your dream? First, it is important that your dream is feasible. Dreaming that next year you’ll turn a $10,000 portfolio into a $1 million portfolio is not feasible, so you should just let that dream go and move on to something more realistic.
Oettingen introduces a tool with the acronym WOOP to move people from dream to accomplishment. The “W” stands for a wish or concern you might have, “something that is challenging but that you think is possible for you to achieve in a given period of time.” (p. 104) The first “O” is the outcome: “What is the best thing that you associate with fulfilling your wish or solving your concern?” Moving beyond the standard recommendations of positive thinking, the author introduces the second “O,” the obstacle. “Find the most critical, internal obstacle that prevents you from fulfilling your wish or solving your concern.” (p. 105) Finally, the “P” represents the plan. “What can you do to overcome or circumvent your obstacle? Name one thought or action you can take—the most effective one—and hold it in your mind. Then think about when and where the obstacle will next occur. Form an if-then plan: ‘If obstacle x occurs (when and where), then I will perform behavior y.’ Repeat this if-then plan to yourself one more time.” (p. 106)
“And that’s it. You’re done.”
Before I say I’m done, here’s an amusing anecdote about dreams that aren’t feasible from Joan Didion’s Blue Nights. In her seventies, thin and frail, she was told to gain weight and devote a minimum of three hours a week to physical therapy. She writes:
“I find, … somewhat to my surprise, that I actively like physical therapy. I keep regular appointments at a Columbia Presbyterian sports medicine facility at Sixtieth and Madison. I am impressed by the strength and general tone of the other patients who turn up during the same hour. I study their balance, their proficiency with the various devices recommended by the therapist. The more I watch, the more encouraged I am: this stuff really works, I tell myself. The thought makes me cheerful, optimistic. I wonder how many appointments it will take to reach the apparently effortless control already achieved by my fellow patients. Only during my third week of physical therapy do I learn that these particular fellow patients are in fact the New York Yankees, loosening up between game days.” (p. 78)
Saturday, December 27, 2014
Perfection and Coyote cosmology
I’m not prone to sermonizing in this blog—or anywhere else for that matter, but I was inspired by a wonderful short piece, "Coyote," in the current issue of The New Yorker. I’ve provided a link to the essay because I’m about to take all the fun out of it, and that’s not fair to either you or Rebecca Solnit, the author.
The worldview, religious or philosophical, that most of us have been steeped in draws a sharp distinction between the perfect and the imperfect. We are, as we are often told, imperfect creatures who nonetheless strive to be perfect, and in our failure we suffer all the attendant anxiety and guilt. In some versions we are doomed, in others we can be saved. Whatever the version, we can’t make ourselves perfect no matter how hard we try. We bear the burden of always being imperfect. We make mistakes, we disappoint others, we disappoint ourselves.
Or, in Solnit’s much more vivid prose, “The angel with the flaming sword kept us out of Eden because we talked to snakes and made a bad choice about fruit snacks. Everything that followed was an affliction and a curse. Redemption was required, because perfection was the standard by which everything would be measured, and against which everything would fall short.”
What if, in keeping with Coyote cosmology, we simply scrap the notion of perfection? What if everything is just better or worse and nothing is perfect? Wouldn’t that make life much more manageable? Wouldn’t we actually stand a chance of becoming better if we didn’t beat ourselves up every time we stumbled and fell short of some self-sabotaging notion of perfection?
Let me pause here to say that those who regard this suggestion as heresy should pretend they never read it. I’m not interested in engaging in theological debate. I’m writing, after all, for those of us who inhabit what is usually considered to be the house of mammon, though I hope we’re also trying to be good stewards of this earth.
The message is this. In 2015, strive to be good, better, and, if you swim in a small enough pond, best, but never perfect. Perfection is a mirage. End of sermon. No amen necessary.
The worldview, religious or philosophical, that most of us have been steeped in draws a sharp distinction between the perfect and the imperfect. We are, as we are often told, imperfect creatures who nonetheless strive to be perfect, and in our failure we suffer all the attendant anxiety and guilt. In some versions we are doomed, in others we can be saved. Whatever the version, we can’t make ourselves perfect no matter how hard we try. We bear the burden of always being imperfect. We make mistakes, we disappoint others, we disappoint ourselves.
Or, in Solnit’s much more vivid prose, “The angel with the flaming sword kept us out of Eden because we talked to snakes and made a bad choice about fruit snacks. Everything that followed was an affliction and a curse. Redemption was required, because perfection was the standard by which everything would be measured, and against which everything would fall short.”
What if, in keeping with Coyote cosmology, we simply scrap the notion of perfection? What if everything is just better or worse and nothing is perfect? Wouldn’t that make life much more manageable? Wouldn’t we actually stand a chance of becoming better if we didn’t beat ourselves up every time we stumbled and fell short of some self-sabotaging notion of perfection?
Let me pause here to say that those who regard this suggestion as heresy should pretend they never read it. I’m not interested in engaging in theological debate. I’m writing, after all, for those of us who inhabit what is usually considered to be the house of mammon, though I hope we’re also trying to be good stewards of this earth.
The message is this. In 2015, strive to be good, better, and, if you swim in a small enough pond, best, but never perfect. Perfection is a mirage. End of sermon. No amen necessary.
Thursday, December 25, 2014
Happy holidays
Do you have time on your hands? Do you find doing the same thing over and over again therapeutic? Do you have a book you wish you had never bought and that even your local library doesn't want for its book sale--and that you're willing to trash? Well, here's the perfect winter project. Directions at SL.
Wednesday, December 24, 2014
Franco, Understanding Bitcoin
Although it seems that everybody and his brother have weighed in on the merits of Bitcoin, I suspect that few have more than a superficial knowledge of how it actually works. Pedro Franco aims to change that state of affairs with his in-depth study, Understanding Bitcoin: Cryptography, Engineering, and Economics (Wiley, 2015). Most of the book is easily accessible to anyone with a rudimentary grasp of financial transactions. It doesn’t even require a lot of mental effort to follow the general thrust of the author’s lengthy account of Bitcoin cryptography.
I have no doubt that money will increasingly be digitized and that paper bills and coins will be a thing of the past. The main question is whether decentralized cryptocurrencies can ever replace, in whole or in part, fiat currencies or whether fiat currencies will morph into some form of cryptocurrencies themselves.
As it stands now, critics argue that Bitcoin is not a currency because it does not serve the three functions of money—medium of exchange, store of value, and unit of account. But does it have to fulfill all three functions or can the three functions of money be unbundled? “A consensus seems to be emerging among economists that Bitcoin is a good medium of exchange, a risky store of value and a poor unit of account.” (p. 22)
We know that the price of bitcoins is extraordinarily volatile, making them a poor store of value. Bitcoin is also wanting as a unit of account: merchants don’t quote prices in bitcoins because the Bitcoin economy is tiny and, again, the price of bitcoins isn’t stable. Even as a medium of exchange, which is touted as its strength, Bitcoin is not without its problems. For instance, it is illiquid compared to fiat currencies, transactions take several minutes on average to be confirmed, and it could face scalability pressures.
But even if Bitcoin or one of its competitors/successors never becomes a generally accepted currency, the technology that underlies it could have other applications. For instance, the blockchain at the heart of Bitcoin could be used to register the ownership and transfer of any digital asset, such as digital bonds or shares, or even physical assets such as cars. And off-chain transactions could be used for frequent micropayments—such as paying for online newspaper articles read or for data consumption at WiFi hotspots.
Franco offers a balanced account of the pros and cons of Bitcoin as well as a clear description of how it works. All in all, the book was an enlightening read.
I have no doubt that money will increasingly be digitized and that paper bills and coins will be a thing of the past. The main question is whether decentralized cryptocurrencies can ever replace, in whole or in part, fiat currencies or whether fiat currencies will morph into some form of cryptocurrencies themselves.
As it stands now, critics argue that Bitcoin is not a currency because it does not serve the three functions of money—medium of exchange, store of value, and unit of account. But does it have to fulfill all three functions or can the three functions of money be unbundled? “A consensus seems to be emerging among economists that Bitcoin is a good medium of exchange, a risky store of value and a poor unit of account.” (p. 22)
We know that the price of bitcoins is extraordinarily volatile, making them a poor store of value. Bitcoin is also wanting as a unit of account: merchants don’t quote prices in bitcoins because the Bitcoin economy is tiny and, again, the price of bitcoins isn’t stable. Even as a medium of exchange, which is touted as its strength, Bitcoin is not without its problems. For instance, it is illiquid compared to fiat currencies, transactions take several minutes on average to be confirmed, and it could face scalability pressures.
But even if Bitcoin or one of its competitors/successors never becomes a generally accepted currency, the technology that underlies it could have other applications. For instance, the blockchain at the heart of Bitcoin could be used to register the ownership and transfer of any digital asset, such as digital bonds or shares, or even physical assets such as cars. And off-chain transactions could be used for frequent micropayments—such as paying for online newspaper articles read or for data consumption at WiFi hotspots.
Franco offers a balanced account of the pros and cons of Bitcoin as well as a clear description of how it works. All in all, the book was an enlightening read.
Monday, December 22, 2014
Ahuja, The Alpha Masters
Maneet Ahuja’s 2012 book The Alpha Masters: Unlocking the Genius of the World’s Top Hedge Funds is now available in paperback. Somehow I missed the book when it first appeared, so in the spirit of “better late than never” I decided to write a few words about it here.
Most of the characters in this book are familiar: Ray Dalio of Bridgewater Associates, Tim Wong and Pierre Lagrange of Man Group/AHL, John Paulson of Paulson & Co., Marc Lasry and Sonia Gardner of Avenue Capital Group, David Tepper of Appaloosa Management, William A. Ackman of Pershing Square Capital Management, Daniel Loeb of Third Point, James Chanos of Kynikos Associates, and Boaz Weinstein of Saba Capital Management. Adding to the luminaries, Mohammed El-Erian wrote the foreword and Myron Scholes the afterword.
Many of their stories are familiar as well. So why does this book remain a compelling read?
It introduces us to a very bright, hardworking, resilient group of people. We see how their research leads them to formulate hypotheses, how they translate these hypotheses into market positions, how they push their advantage, and how they bounce back when their hypotheses don’t pan out.
In chapter after chapter we begin to see what it takes to be an alpha master (or, as Scholes would have it with a nod to Ohm’s law, an omega master, “where omega is the varying amounts of resistance in the market”). It matters not where you start or what niche you carve out for yourself. But it matters enormously that you mold your fund to fit your own interests and expertise, that your research is relentless and subject to constant testing and potential revision, that you understand (and respect) risk. It matters that you can see things in available data that other people don’t, that you or your team have a set of skills that can offer a fresh perspective when weighing potential investments.
If your goal is to become a master investor/trader, this book may inspire you to work harder and smarter than you ever thought necessary.
Most of the characters in this book are familiar: Ray Dalio of Bridgewater Associates, Tim Wong and Pierre Lagrange of Man Group/AHL, John Paulson of Paulson & Co., Marc Lasry and Sonia Gardner of Avenue Capital Group, David Tepper of Appaloosa Management, William A. Ackman of Pershing Square Capital Management, Daniel Loeb of Third Point, James Chanos of Kynikos Associates, and Boaz Weinstein of Saba Capital Management. Adding to the luminaries, Mohammed El-Erian wrote the foreword and Myron Scholes the afterword.
Many of their stories are familiar as well. So why does this book remain a compelling read?
It introduces us to a very bright, hardworking, resilient group of people. We see how their research leads them to formulate hypotheses, how they translate these hypotheses into market positions, how they push their advantage, and how they bounce back when their hypotheses don’t pan out.
In chapter after chapter we begin to see what it takes to be an alpha master (or, as Scholes would have it with a nod to Ohm’s law, an omega master, “where omega is the varying amounts of resistance in the market”). It matters not where you start or what niche you carve out for yourself. But it matters enormously that you mold your fund to fit your own interests and expertise, that your research is relentless and subject to constant testing and potential revision, that you understand (and respect) risk. It matters that you can see things in available data that other people don’t, that you or your team have a set of skills that can offer a fresh perspective when weighing potential investments.
If your goal is to become a master investor/trader, this book may inspire you to work harder and smarter than you ever thought necessary.
Wednesday, December 17, 2014
Sears, The Indomitable Investor, 2d ed.
Steven M. Sears, probably best known for his options column in Barron’s, wrote The Indomitable Investor: Why a Few Succeed in the Stock Market When Everyone Else Fails in 2012. Wiley recently issued a second edition with a new preface. Although I reviewed it when it first came out, it’s time for another look.
Sears focuses on the “make or break” things most investors blithely ignore, such as risk and when/how to sell. With respect to the latter, he writes: “Selling is Wall Street’s essence just as surely as buying is Main Street’s. … If you don’t learn to be a disciplined seller, you risk losing more money than you make. … Selling is not about timing the stock market. It is about managing the risk of your own investment portfolio, and tempering your decisions.” (pp. 23, 24) There’s no single right philosophy of selling, although Bernard Baruch’s timeless advice to “sell while the stock still is rising or, if you have made a mistake, to admit it immediately and take your loss” (p. 35) remains a good place to start.
At home in both the stock and options markets, Sears contrasts the two, saying that “the options market is driven by fear” and “the stock market is driven by greed.” He admits that “this is an oversimplification—but not by much.” (p. 89) The SKEW Index, an option-based indicator that measures the risk of 30-day S&P 500 returns two or more standard deviations below the mean, can be a useful guide for the risk-conscious stock investor. “When the SKEW Index is at 100, it means that the probability of a steep stock market decline is minimal. When it rises above 100, the odds of a sharp decline increase.” (p. 90) Its all-time low was on March 21, 1991, as the recession that had begun in July 1990 was winding down. Its all-time high—146.88—was in October 1998 during the Russian debt crisis and the unexpected Fed move to lower interest rates. It was also high in March 2006, shortly before the housing bubble burst. Using the SKEW Index in conjunction with the VIX can be especially helpful.
Sears also describes an alternative approach to asset allocation, relying on the work of Mark Taborsky, then at PIMCO. This was a strategy that Mohammed El-Erian’s Harvard team tried to execute but found very difficult to quantify and optimize. As El-Erian outlined the strategy in When Markets Collide, “The ideal situation is to come up with a small set (three to five) of distinct (and ideally orthogonal) risk factors that command a risk premium. The next step is to assess the stability of the factors and how they can be best captured through the use of tradable instruments.” (p. 233) Instead of relying on historical asset class performance patterns and assuming that markets are mean reverting, Taborsky explained, PIMCO looked at factors such as risk, volatility, correlation, interest rates, or even time.
These short takeaways from The Indomitable Investor offer only a glimpse into the richness of Sears’s book. Investors who are serious about managing their money and who want to be among the few who succeed can learn a great deal from Sears.
Sears focuses on the “make or break” things most investors blithely ignore, such as risk and when/how to sell. With respect to the latter, he writes: “Selling is Wall Street’s essence just as surely as buying is Main Street’s. … If you don’t learn to be a disciplined seller, you risk losing more money than you make. … Selling is not about timing the stock market. It is about managing the risk of your own investment portfolio, and tempering your decisions.” (pp. 23, 24) There’s no single right philosophy of selling, although Bernard Baruch’s timeless advice to “sell while the stock still is rising or, if you have made a mistake, to admit it immediately and take your loss” (p. 35) remains a good place to start.
At home in both the stock and options markets, Sears contrasts the two, saying that “the options market is driven by fear” and “the stock market is driven by greed.” He admits that “this is an oversimplification—but not by much.” (p. 89) The SKEW Index, an option-based indicator that measures the risk of 30-day S&P 500 returns two or more standard deviations below the mean, can be a useful guide for the risk-conscious stock investor. “When the SKEW Index is at 100, it means that the probability of a steep stock market decline is minimal. When it rises above 100, the odds of a sharp decline increase.” (p. 90) Its all-time low was on March 21, 1991, as the recession that had begun in July 1990 was winding down. Its all-time high—146.88—was in October 1998 during the Russian debt crisis and the unexpected Fed move to lower interest rates. It was also high in March 2006, shortly before the housing bubble burst. Using the SKEW Index in conjunction with the VIX can be especially helpful.
Sears also describes an alternative approach to asset allocation, relying on the work of Mark Taborsky, then at PIMCO. This was a strategy that Mohammed El-Erian’s Harvard team tried to execute but found very difficult to quantify and optimize. As El-Erian outlined the strategy in When Markets Collide, “The ideal situation is to come up with a small set (three to five) of distinct (and ideally orthogonal) risk factors that command a risk premium. The next step is to assess the stability of the factors and how they can be best captured through the use of tradable instruments.” (p. 233) Instead of relying on historical asset class performance patterns and assuming that markets are mean reverting, Taborsky explained, PIMCO looked at factors such as risk, volatility, correlation, interest rates, or even time.
These short takeaways from The Indomitable Investor offer only a glimpse into the richness of Sears’s book. Investors who are serious about managing their money and who want to be among the few who succeed can learn a great deal from Sears.
Monday, December 15, 2014
Davis, Being Right or Making Money
Ned Davis started his eponymous investment research company in 1980. Thirty-four years later NDR employs nearly 50 researchers and has a client base of more than 1,200. It is widely respected for its objective analysis and its timing models.
The third edition of Being Right or Making Money (Wiley, 2014) showcases the firm’s guiding principles and some of its research. Although I have neither the first (1991) nor the second (2000) edition of this book, I think we can safely discard the idea that the 2014 edition is merely an update. The simple fact that the second edition was 150 pages long and the new edition runs some 231 pages is probably sufficient to disavow anyone of that notion. Chapters that deal with current topics, such as a potential bear market in 2014 and the game-changing nature of U.S. energy independence, are another tip-off.
What has remained the linchpin of all three editions is Ned Davis’s own investment philosophy. Even here there has been one major change: “the evolution of my belief that the most successful money managers are risk averse.” (p. xv)
Davis maintains that the four keys to making money in a business characterized by making mistakes are objective indicators, discipline, flexibility, and risk management. There is, of course, a dynamic tension between discipline (“remaining faithful to [one’s] systems through good and bad times”) and flexibility (the ability to change one’s mind when the evidence shifts). Davis readily admits that “there are periods, historically, in which model indicators tend to fail or stay wrong against a major move.” (p. 35) Risk management-–in the simplest terms, being willing to take small losses but avoiding big losses—helps to resolve this tension. And hence “the bottom line at Ned Davis Research is that our timing models, at every stage of development, are designed with one thought foremost in mind, and that is controlling big mistakes.” (p. 36)
Three chapters of this book are devoted to model building. The first describes the process of model building; the next two offer a stock market model and a simple model for bonds.
In building a timing model, the investor should first make sure he has clean data. He must then investigate “which data series, out of the innumerable possible sets out there, are the most useful or relevant for asset-allocation and market-timing purposes. Some data is best suited for aggressive, short-term trading, while other data is best suited for long-term asset allocation and risk control. Finding out what is useful is the biggest challenge the investor faces….” (p. 42)
NDR employs both internal and external indicators in its timing models. Internal indicators include such things as the slope of a moving average, breadth-thrust, and momentum. External indicators include interest rates as well as sentiment and valuation. Numerous charts illustrate indicators NDR has found useful in its models.
The final three chapters of the book—the first by Ned Davis, the second by Alejandra Grindal, and the final one by John LaForge—are examples of the kind of research NDR does. They are chock full of graphs, some comparing data that might not seem to be obviously connected such as the U.S. petroleum trade deficit and the goods deficit with China.
Being Right or Making Money is a tribute to the kind of research that can help the investor make money, even if he’s not always right.
The third edition of Being Right or Making Money (Wiley, 2014) showcases the firm’s guiding principles and some of its research. Although I have neither the first (1991) nor the second (2000) edition of this book, I think we can safely discard the idea that the 2014 edition is merely an update. The simple fact that the second edition was 150 pages long and the new edition runs some 231 pages is probably sufficient to disavow anyone of that notion. Chapters that deal with current topics, such as a potential bear market in 2014 and the game-changing nature of U.S. energy independence, are another tip-off.
What has remained the linchpin of all three editions is Ned Davis’s own investment philosophy. Even here there has been one major change: “the evolution of my belief that the most successful money managers are risk averse.” (p. xv)
Davis maintains that the four keys to making money in a business characterized by making mistakes are objective indicators, discipline, flexibility, and risk management. There is, of course, a dynamic tension between discipline (“remaining faithful to [one’s] systems through good and bad times”) and flexibility (the ability to change one’s mind when the evidence shifts). Davis readily admits that “there are periods, historically, in which model indicators tend to fail or stay wrong against a major move.” (p. 35) Risk management-–in the simplest terms, being willing to take small losses but avoiding big losses—helps to resolve this tension. And hence “the bottom line at Ned Davis Research is that our timing models, at every stage of development, are designed with one thought foremost in mind, and that is controlling big mistakes.” (p. 36)
Three chapters of this book are devoted to model building. The first describes the process of model building; the next two offer a stock market model and a simple model for bonds.
In building a timing model, the investor should first make sure he has clean data. He must then investigate “which data series, out of the innumerable possible sets out there, are the most useful or relevant for asset-allocation and market-timing purposes. Some data is best suited for aggressive, short-term trading, while other data is best suited for long-term asset allocation and risk control. Finding out what is useful is the biggest challenge the investor faces….” (p. 42)
NDR employs both internal and external indicators in its timing models. Internal indicators include such things as the slope of a moving average, breadth-thrust, and momentum. External indicators include interest rates as well as sentiment and valuation. Numerous charts illustrate indicators NDR has found useful in its models.
The final three chapters of the book—the first by Ned Davis, the second by Alejandra Grindal, and the final one by John LaForge—are examples of the kind of research NDR does. They are chock full of graphs, some comparing data that might not seem to be obviously connected such as the U.S. petroleum trade deficit and the goods deficit with China.
Being Right or Making Money is a tribute to the kind of research that can help the investor make money, even if he’s not always right.
Wednesday, December 10, 2014
Smith, Catching Lightning in a Bottle
Winthrop H. Smith, Jr., the son and namesake of one of the founders of Merrill Lynch (the Smith in Merrill Lynch, Pierce, Fenner and Smith) and himself a 28-year veteran of Mother Merrill until he resigned in 2001, has written a compelling history of the firm. Catching Lightning in a Bottle: How Merrill Lynch Revolutionized the Financial World (Wiley, 2014) starts with the rise of the ambitiously charming 5’4” Charles E. Merrill and the man he chose to be his partner after he went out on his own, the big-framed, skeptical, sometimes bullying Edmund Lynch.
The relationship between the partners was often fractious. Managers “remembered the two locked in sulfurous glares, faced off like the Monitor and the Merrimac, Lynch’s forehead knotted in fury, Merrill’s blue eyes turned into ice fields. The debates were bare-knuckled, and both were capable of extended, loud, and imaginative invective. At the root of these disagreements were fundamentally different approaches to life. Merrill was the visionary, Lynch the realist—but only Merrill recognized that a business needed both.” (p. 73)
Initially, the brokerage business was secondary to the investment banking business at Merrill, Lynch & Co. The firm’s bread and butter was underwriting stock issuances in expanding chain stores such as McCrory’s, Kresge’s, Penney’s, Kinney Shoes, and eventually Safeway.
After Lynch died in 1938, the company began to shift direction. At the urging of Win Smith, a partner of the ailing brokerage firm E. A. Pierce, Merrill merged the two firms. This “would be the realization of Merrill’s dream of a ‘department store of finance’ operated in the chain-store mold—a high volume of transactions with a small return on each to maintain profitability.” (p. 139)
Americans didn’t trust brokers; their main complaint was that brokers churned accounts in order to generate commissions. Merrill Lynch decided to offer a new model, where brokers were paid a straight salary, “with annual bonuses to reward special contributions to the firm.” … “This approach,” Smith notes, “lasted into the 1970s when competitive pressure forced the firm to change its method of compensation back to a commission-based one.” (p. 143)
The new Merrill model embraced ideas that were radical at the time: the customer’s interest would come first, the firm would advertise extensively, it would publish an annual report, its brokers wouldn’t give investment advice unless asked for it. But, despite efforts to cut costs and boost sales, in the early 1940s the brokerage firm was flailing financially. “The firm had an average income per transaction of $10.17 and an average cost of $14.29. According to Merrill, ‘When you figure that one of our clients, the Carnation Milk Company, can content the cow, milk it, pasteurize the milk, put the milk in the can, put a label on it, put it in a box, advertise it, and ship it all over the world, and sell the can of milk for five cents, then you realize how perfectly frantic these figures make me feel.’” (p. 158)
Smith recounts the subsequent successes of Merrill, and exposes its warts, with the fondness of an insider and the objectivity of a reporter. His anger about the course the firm took after Stan O’Neal became CEO (and after he resigned) is, however, barely contained.
Merrill is now 100 years old and no longer an independent legal entity. It, like so many Wall Street firms, was hijacked by a leader who did not understand the company’s principles and “unique culture” that had “allowed it to grow and prosper and survive in many challenging environments.” (p. 515)
Catching Lightning in a Bottle is not only an account of what was but a call for what should be. It’s a first-rate read.
The relationship between the partners was often fractious. Managers “remembered the two locked in sulfurous glares, faced off like the Monitor and the Merrimac, Lynch’s forehead knotted in fury, Merrill’s blue eyes turned into ice fields. The debates were bare-knuckled, and both were capable of extended, loud, and imaginative invective. At the root of these disagreements were fundamentally different approaches to life. Merrill was the visionary, Lynch the realist—but only Merrill recognized that a business needed both.” (p. 73)
Initially, the brokerage business was secondary to the investment banking business at Merrill, Lynch & Co. The firm’s bread and butter was underwriting stock issuances in expanding chain stores such as McCrory’s, Kresge’s, Penney’s, Kinney Shoes, and eventually Safeway.
After Lynch died in 1938, the company began to shift direction. At the urging of Win Smith, a partner of the ailing brokerage firm E. A. Pierce, Merrill merged the two firms. This “would be the realization of Merrill’s dream of a ‘department store of finance’ operated in the chain-store mold—a high volume of transactions with a small return on each to maintain profitability.” (p. 139)
Americans didn’t trust brokers; their main complaint was that brokers churned accounts in order to generate commissions. Merrill Lynch decided to offer a new model, where brokers were paid a straight salary, “with annual bonuses to reward special contributions to the firm.” … “This approach,” Smith notes, “lasted into the 1970s when competitive pressure forced the firm to change its method of compensation back to a commission-based one.” (p. 143)
The new Merrill model embraced ideas that were radical at the time: the customer’s interest would come first, the firm would advertise extensively, it would publish an annual report, its brokers wouldn’t give investment advice unless asked for it. But, despite efforts to cut costs and boost sales, in the early 1940s the brokerage firm was flailing financially. “The firm had an average income per transaction of $10.17 and an average cost of $14.29. According to Merrill, ‘When you figure that one of our clients, the Carnation Milk Company, can content the cow, milk it, pasteurize the milk, put the milk in the can, put a label on it, put it in a box, advertise it, and ship it all over the world, and sell the can of milk for five cents, then you realize how perfectly frantic these figures make me feel.’” (p. 158)
Smith recounts the subsequent successes of Merrill, and exposes its warts, with the fondness of an insider and the objectivity of a reporter. His anger about the course the firm took after Stan O’Neal became CEO (and after he resigned) is, however, barely contained.
Merrill is now 100 years old and no longer an independent legal entity. It, like so many Wall Street firms, was hijacked by a leader who did not understand the company’s principles and “unique culture” that had “allowed it to grow and prosper and survive in many challenging environments.” (p. 515)
Catching Lightning in a Bottle is not only an account of what was but a call for what should be. It’s a first-rate read.
Monday, December 8, 2014
Dayton, Trade Mindfully
It’s impossible for me to write a reliable review of this book because so far I have merely read it and haven’t done it. And, as Gary Dayton stresses, it is not enough to read Trade Mindfully: Achieve Your Optimum Trading Performance with Mindfulness and Cutting Edge Psychology (Wiley, 2015). You actually have to do the exercises and practice trading mindfully. I can say, however, that I found Dayton’s book sufficiently intriguing that I’ve put it aside for a second, more interactive read.
Dayton, a clinical psychologist, sets a course for traders to follow that will, in the best case scenario, prevent them from being hijacked by their emotions. This is not to say that traders will be able to eliminate or control those emotions that undercut their trading success. In fact, trying to suppress, control, or eliminate feelings and thoughts usually only makes them worse.
Emotions are not only a necessary part of trading; they add to the quality of trading decisions. They are “a crucial component necessary in making decisions, especially in controlling and correcting reward-related and punishment-related behavior because these kinds of decisions always involve emotion.” Studies show, for instance, that people with frontal lobe damage cannot adapt their behavior to changing patterns of rewards. “[A]fter the experiment was over, the [brain-damaged] participants could accurately describe the tests, how the tests had changed, and also how they were incorrectly responding to the changes, signifying that they fully comprehended the tests, at least on an intellectual level. They could not, however, explain the dissociation between what they knew and what they did.” (p. 84)
So, the trader must provide room for emotions yet not permit them to wreak havoc on his trading. The key to walking what seems to be a fine line is, Dayton argues, mindfulness. As he writes, the “three characteristics of mindfulness—a heightened clarity of the market environment, focus on the here and now, and an understanding that thoughts and feelings are merely temporary events and not necessarily reality—can help the trader take action in the direction of what matters most in a given trade, as well as what matters most to him or her as a trader.” (p. 106)
Normally we fuse with our thoughts and emotions. That is, “thoughts and feelings are generated automatically by the mind and we don’t have much say over what thoughts and feelings occur. … The environment and the situations we are in highly influence what the mind tells us. … When fused, we uncritically believe the mind and become entangled in its story. This causes us to lose contact with the present. … When fused with our thoughts and feelings, we lose focus with the trading task at hand. … The mind can be remarkably shameless in the stories it will tell. When we are fused, we can’t tell the difference between what is truly useful and what is not.” (pp. 152-54)
The remedy for fusion is defusion, “the ability to accept thoughts exactly as they are for what they are (just words and feelings), not what they represent themselves to be (e.g., the truth).” For instance, ‘I am going to have a loss’ is a fused thought; its defused alternative is ‘I am having the thought that I am going to have a loss.’ “Letting thoughts go is possible by developing the skill of defusion.” (p. 158)
Trading is a stressful business, even if you’re an old hand at it. Will the stress of trading take a toll on our lives? Not necessarily, research shows. Premature death seems to be linked not to stress itself but to the perception that stress is harmful to our health. A study of 28,000 adults showed that people who experienced high levels of stress and who believed that it affected their health had a 43% increased chance of premature death. Those highly stressed people who did not believe that their stress was harmful to their health had the lowest risk of dying, even lower than people with low stress. My hunch is that in the first group were an outsize number of people who acted on their perceptions by engaging in harmful allegedly stress-reducing behavior, thus sabotaging themselves, and that in the second group were a good number of highly successful (and, yes, stressed) people who tend to live longer than folks lower down on the socioeconomic ladder. Whatever the case, believing may not necessarily make it so, but beliefs do shape actions and outcomes, for better or worse.
Dayton makes a strong case for mindfully accepting and defusing unwanted thoughts and feelings so that attention can remain on the task at hand. With practice, the mindful trader will be able focus on his trade rather than on, for instance, his fear that he’s going to lose money. The fear won’t go away, but it will no longer be the force that guides his actions.
The final part of the book, “Maximizing Your Trading Performance,” moves from the psychology of negative emotions and erratic behaviors to the positive psychology that can help enhance performance. Central to performance psychology is the Before-During-After process. “Preparing for trading in a high-quality way, taking our preparation into trading to maximize our trading abilities, and assessing our trading performance and results with the intent to improve our preparation and execution is the royal road to developing, advancing, and enhancing our trading.” (p. 273)
Dayton, a clinical psychologist, sets a course for traders to follow that will, in the best case scenario, prevent them from being hijacked by their emotions. This is not to say that traders will be able to eliminate or control those emotions that undercut their trading success. In fact, trying to suppress, control, or eliminate feelings and thoughts usually only makes them worse.
Emotions are not only a necessary part of trading; they add to the quality of trading decisions. They are “a crucial component necessary in making decisions, especially in controlling and correcting reward-related and punishment-related behavior because these kinds of decisions always involve emotion.” Studies show, for instance, that people with frontal lobe damage cannot adapt their behavior to changing patterns of rewards. “[A]fter the experiment was over, the [brain-damaged] participants could accurately describe the tests, how the tests had changed, and also how they were incorrectly responding to the changes, signifying that they fully comprehended the tests, at least on an intellectual level. They could not, however, explain the dissociation between what they knew and what they did.” (p. 84)
So, the trader must provide room for emotions yet not permit them to wreak havoc on his trading. The key to walking what seems to be a fine line is, Dayton argues, mindfulness. As he writes, the “three characteristics of mindfulness—a heightened clarity of the market environment, focus on the here and now, and an understanding that thoughts and feelings are merely temporary events and not necessarily reality—can help the trader take action in the direction of what matters most in a given trade, as well as what matters most to him or her as a trader.” (p. 106)
Normally we fuse with our thoughts and emotions. That is, “thoughts and feelings are generated automatically by the mind and we don’t have much say over what thoughts and feelings occur. … The environment and the situations we are in highly influence what the mind tells us. … When fused, we uncritically believe the mind and become entangled in its story. This causes us to lose contact with the present. … When fused with our thoughts and feelings, we lose focus with the trading task at hand. … The mind can be remarkably shameless in the stories it will tell. When we are fused, we can’t tell the difference between what is truly useful and what is not.” (pp. 152-54)
The remedy for fusion is defusion, “the ability to accept thoughts exactly as they are for what they are (just words and feelings), not what they represent themselves to be (e.g., the truth).” For instance, ‘I am going to have a loss’ is a fused thought; its defused alternative is ‘I am having the thought that I am going to have a loss.’ “Letting thoughts go is possible by developing the skill of defusion.” (p. 158)
Trading is a stressful business, even if you’re an old hand at it. Will the stress of trading take a toll on our lives? Not necessarily, research shows. Premature death seems to be linked not to stress itself but to the perception that stress is harmful to our health. A study of 28,000 adults showed that people who experienced high levels of stress and who believed that it affected their health had a 43% increased chance of premature death. Those highly stressed people who did not believe that their stress was harmful to their health had the lowest risk of dying, even lower than people with low stress. My hunch is that in the first group were an outsize number of people who acted on their perceptions by engaging in harmful allegedly stress-reducing behavior, thus sabotaging themselves, and that in the second group were a good number of highly successful (and, yes, stressed) people who tend to live longer than folks lower down on the socioeconomic ladder. Whatever the case, believing may not necessarily make it so, but beliefs do shape actions and outcomes, for better or worse.
Dayton makes a strong case for mindfully accepting and defusing unwanted thoughts and feelings so that attention can remain on the task at hand. With practice, the mindful trader will be able focus on his trade rather than on, for instance, his fear that he’s going to lose money. The fear won’t go away, but it will no longer be the force that guides his actions.
The final part of the book, “Maximizing Your Trading Performance,” moves from the psychology of negative emotions and erratic behaviors to the positive psychology that can help enhance performance. Central to performance psychology is the Before-During-After process. “Preparing for trading in a high-quality way, taking our preparation into trading to maximize our trading abilities, and assessing our trading performance and results with the intent to improve our preparation and execution is the royal road to developing, advancing, and enhancing our trading.” (p. 273)
Friday, December 5, 2014
Gutsche, Better and Faster
Jeremy Gutsche’s Better and Faster: The Proven Path to Unstoppable Ideas (Crown Business, 2015) joins the crowded field of books on innovation. Gutsche, the founder of the Trend Hunter site, an online community for people to share business ideas, has not written the definitive book on the subject, but some of his own ideas are definitely worth sharing.
The guiding metaphor of the book pits the hunter against the farmer. Once the farmer (and Gutsche’s farmer is, of course, a stylized construct) figures out how to produce a harvest, each year he repeats the chain of decisions that led to the last harvest. He is complacent and wants to protect the status quo. The hunter, by contrast, is insatiable, curious, and willing to destroy. In Gutsche’s world the farmer is likely to become irrelevant or worse—think Smith-Corona or Blockbuster—while the hunter forges ahead.
Okay, so let’s say you’ve vowed to be a hunter. What should you hunt for? Gutsche lays out six patterns of opportunity: convergence, divergence, cyclicality, redirection, reduction, and acceleration. Described in their simplest terms, convergence combines multiple products, services, or trends. Divergence opposes or breaks free from the mainstream. Cyclicality focuses on predictably recurring opportunities. Redirection channels the power of a trend instead of fighting it; for instance, redirection can refocus or reprioritize. Reduction simplifies or focuses an idea. Acceleration identifies a critical feature and dramatically enhances that element.
What I have laid out in one paragraph Gutsche spends over a hundred pages on, describing the patterns in more detail and giving multiple examples. I would hope that traders and investors could come up with their own examples of patterns of opportunity.
We’ve now reached the point in Gutsche’s book that, “armed with a knowledge of the patterns of opportunity and having awakened your inner hunter, you’re now better prepared to spot and hit those opportunities to find better ideas, faster.”
The first step is to narrow your focus to “zero-in on the opportunities that are just big enough to be profitable, but not so large and obvious that your competitors can already spot them.” (p. 161) Then find a cluster of products, services, or concepts that follow a similar idea. The third step is to search the perimeter for slightly related ideas and the fourth, to push your boundaries. Five, collect and cluster what you find, and then throw away your first clusters because “the human mind is great at finding trends and patterns by creating shortcuts or by falling prey to stereotypes, schemas, and bias. We try to lighten our mental load by referencing what we’ve seen before and what we know works.” (p. 168) Finally, use the six patterns to re-cluster your insights.
There you have it, folks, a game plan for better, faster ideas. It might just work.
The guiding metaphor of the book pits the hunter against the farmer. Once the farmer (and Gutsche’s farmer is, of course, a stylized construct) figures out how to produce a harvest, each year he repeats the chain of decisions that led to the last harvest. He is complacent and wants to protect the status quo. The hunter, by contrast, is insatiable, curious, and willing to destroy. In Gutsche’s world the farmer is likely to become irrelevant or worse—think Smith-Corona or Blockbuster—while the hunter forges ahead.
Okay, so let’s say you’ve vowed to be a hunter. What should you hunt for? Gutsche lays out six patterns of opportunity: convergence, divergence, cyclicality, redirection, reduction, and acceleration. Described in their simplest terms, convergence combines multiple products, services, or trends. Divergence opposes or breaks free from the mainstream. Cyclicality focuses on predictably recurring opportunities. Redirection channels the power of a trend instead of fighting it; for instance, redirection can refocus or reprioritize. Reduction simplifies or focuses an idea. Acceleration identifies a critical feature and dramatically enhances that element.
What I have laid out in one paragraph Gutsche spends over a hundred pages on, describing the patterns in more detail and giving multiple examples. I would hope that traders and investors could come up with their own examples of patterns of opportunity.
We’ve now reached the point in Gutsche’s book that, “armed with a knowledge of the patterns of opportunity and having awakened your inner hunter, you’re now better prepared to spot and hit those opportunities to find better ideas, faster.”
The first step is to narrow your focus to “zero-in on the opportunities that are just big enough to be profitable, but not so large and obvious that your competitors can already spot them.” (p. 161) Then find a cluster of products, services, or concepts that follow a similar idea. The third step is to search the perimeter for slightly related ideas and the fourth, to push your boundaries. Five, collect and cluster what you find, and then throw away your first clusters because “the human mind is great at finding trends and patterns by creating shortcuts or by falling prey to stereotypes, schemas, and bias. We try to lighten our mental load by referencing what we’ve seen before and what we know works.” (p. 168) Finally, use the six patterns to re-cluster your insights.
There you have it, folks, a game plan for better, faster ideas. It might just work.
Wednesday, December 3, 2014
Greyserman and Kaminski, Trend Following with Managed Futures
Trend Following with Managed Futures: The Search for Crisis Alpha (Wiley, 2014) by Alex Greyserman and Kathryn M. Kaminski is an academically rigorous book with a practical bent. Although on the surface it appears to have a narrow focus, in reality it covers a broad spectrum of important but often overlooked investing concepts. Even readers who have no real interest in managed futures can learn a great deal from it, especially if they have some familiarity with financial statistics.
The authors start with an 800-year historical perspective and then discuss trend following basics, theoretical foundations, trend following as an alternative asset class, benchmarking and style analysis, and trend following in an investment portfolio.
Here I’ll simply highlight a couple of ideas that are central to the book’s thesis.
Let’s start with the notion of crisis alpha. “Crisis alpha opportunities are profits that are gained by exploiting the persistent trends that occur across markets during times of crisis.” (p. 145) Viewed in the context of the adaptive market hypothesis set forth by Andrew Lo in 2004, “for both behavioral and institutional reasons, market crisis represents a time when market participants become synchronized in their actions creating trends in markets. It is only the select (few) most adaptable market players who are able to take advantage of these ‘crisis alpha’ opportunities.” (p. 73)
A key concept of the book is divergent risk taking. “Convergent risk takers believe that the world is well structured, stable, and somewhat dependable. Divergent risk takers profess their own ignorance to the true structure of potential risks/benefits with some level of skepticism for what is or is not dependable.” (p. 95) Investing in equity markets is a convergent risk-taking activity; investors “believe in both the existence of an equity risk premium over the long run driven by fundamental value and the efficiency of financial markets. … In distribution, this is also true. Equity returns are positive in expectation, yet negatively skewed with fat left tails.” By contrast, trend following is an obvious financial example of divergent risk taking. “Trend followers do not believe in anything but opportunity. … When they see a trend they follow it, they give no consideration to fundamentals. In fact, the distribution of trend following is positive in expectation with positive skewness.” (p. 97) That is, “Convergent trading systems generally focus on many smaller gains with the occasional extreme loss. Divergent trading approaches focus on smaller losses with the occasional extreme gains.” (p. 98)
Using the market divergence index (MDI), “a simple aggregate measure of ‘trendiness’ in prices taking into account the level of volatility (or noise) in the price series” (p. 109), the authors show, using six agriculture markets with substantial price histories, that market divergence is stationary—that is, that “occasional ‘trendiness’ in markets is a stable characteristic of markets over the long run.” (p. 115)
Some of the authors’ findings are things we already believed to be true but had no compelling grounds for believing. Their work provides us with the requisite quantitative underpinning.
For traders and investors who want to be challenged intellectually but not overwhelmed, this book is an illuminating read. And, let me repeat, it’s not just for those who invest in managed futures.
The authors start with an 800-year historical perspective and then discuss trend following basics, theoretical foundations, trend following as an alternative asset class, benchmarking and style analysis, and trend following in an investment portfolio.
Here I’ll simply highlight a couple of ideas that are central to the book’s thesis.
Let’s start with the notion of crisis alpha. “Crisis alpha opportunities are profits that are gained by exploiting the persistent trends that occur across markets during times of crisis.” (p. 145) Viewed in the context of the adaptive market hypothesis set forth by Andrew Lo in 2004, “for both behavioral and institutional reasons, market crisis represents a time when market participants become synchronized in their actions creating trends in markets. It is only the select (few) most adaptable market players who are able to take advantage of these ‘crisis alpha’ opportunities.” (p. 73)
A key concept of the book is divergent risk taking. “Convergent risk takers believe that the world is well structured, stable, and somewhat dependable. Divergent risk takers profess their own ignorance to the true structure of potential risks/benefits with some level of skepticism for what is or is not dependable.” (p. 95) Investing in equity markets is a convergent risk-taking activity; investors “believe in both the existence of an equity risk premium over the long run driven by fundamental value and the efficiency of financial markets. … In distribution, this is also true. Equity returns are positive in expectation, yet negatively skewed with fat left tails.” By contrast, trend following is an obvious financial example of divergent risk taking. “Trend followers do not believe in anything but opportunity. … When they see a trend they follow it, they give no consideration to fundamentals. In fact, the distribution of trend following is positive in expectation with positive skewness.” (p. 97) That is, “Convergent trading systems generally focus on many smaller gains with the occasional extreme loss. Divergent trading approaches focus on smaller losses with the occasional extreme gains.” (p. 98)
Using the market divergence index (MDI), “a simple aggregate measure of ‘trendiness’ in prices taking into account the level of volatility (or noise) in the price series” (p. 109), the authors show, using six agriculture markets with substantial price histories, that market divergence is stationary—that is, that “occasional ‘trendiness’ in markets is a stable characteristic of markets over the long run.” (p. 115)
Some of the authors’ findings are things we already believed to be true but had no compelling grounds for believing. Their work provides us with the requisite quantitative underpinning.
For traders and investors who want to be challenged intellectually but not overwhelmed, this book is an illuminating read. And, let me repeat, it’s not just for those who invest in managed futures.
Monday, December 1, 2014
Natenberg, Option Volatility and Pricing,2d ed.
Many moons ago, when I was a residential college dean at Yale, one of my tasks was to write recommendations for law school applicants. It seemed that everybody applied to Harvard Law, no matter how mediocre their academic record. So I devised a system that would preserve my credibility and, at the same time, do the best for my students. I wrote two recommendations for each of my so-so students—one for schools that might actually admit them and another for schools that would never consider them. It wasn’t that the first letter was good and the second bad; rather the first letter was good and the second merely descriptive. For the most promising students I often wrote a very short letter, essentially saying that unless the admissions committee was a bunch of dimwits they simply had to accept X or Y. The system worked exceedingly well. The right students got into the right schools and everybody seemed to be satisfied.
Why this stroll down memory lane? Because once again I feel that brevity is in order. My message here is simple: everyone who trades options as stand-alone instruments or who uses options to hedge stock or futures positions should own a copy of Sheldon Natenberg’s Option Volatility and Pricing: Advanced Trading Strategies and Techniques (McGraw-Hill, 2015). Even those who have a copy of the first edition published twenty years ago should pony up for the second edition because it has been considerably updated, revised, and expanded.
Yes, the subtitle says that it is an advanced book and it definitely is. For instance, it deals with such topics as volatility skews and binomial option pricing. But it is written for the trader, not the academic, and it’s math-lite (though heavy on the Greeks, including higher-order sensitivities such as vanna, color, and zomma). Moreover, it proceeds step by step, starting with the basic building blocks, some presented in a way quite different from the usual fare. For instance, Natenberg constructs parity graphs of complex positions using slopes. The reader who’s brand new to options trading will really have to stretch, but it’s a book he can grow with.
The upshot: If you buy only one book on options (which I don't recommend), this should be the one. It’s a textbook, a reference book, and a guide for the perplexed. If, by the way, you're still perplexed after reading Option Volatility and Pricing, a companion workbook will be coming out sometime next year.
Why this stroll down memory lane? Because once again I feel that brevity is in order. My message here is simple: everyone who trades options as stand-alone instruments or who uses options to hedge stock or futures positions should own a copy of Sheldon Natenberg’s Option Volatility and Pricing: Advanced Trading Strategies and Techniques (McGraw-Hill, 2015). Even those who have a copy of the first edition published twenty years ago should pony up for the second edition because it has been considerably updated, revised, and expanded.
Yes, the subtitle says that it is an advanced book and it definitely is. For instance, it deals with such topics as volatility skews and binomial option pricing. But it is written for the trader, not the academic, and it’s math-lite (though heavy on the Greeks, including higher-order sensitivities such as vanna, color, and zomma). Moreover, it proceeds step by step, starting with the basic building blocks, some presented in a way quite different from the usual fare. For instance, Natenberg constructs parity graphs of complex positions using slopes. The reader who’s brand new to options trading will really have to stretch, but it’s a book he can grow with.
The upshot: If you buy only one book on options (which I don't recommend), this should be the one. It’s a textbook, a reference book, and a guide for the perplexed. If, by the way, you're still perplexed after reading Option Volatility and Pricing, a companion workbook will be coming out sometime next year.
Thursday, November 27, 2014
Happy Thanksgiving
I have mixed feelings about the wild turkeys that visit. They have been known to peck at the ground-level windows of my house with such vehemence that I could easily envisage a flock of turkeys promenading around the living room. But my heart went out to the turkey I watched being murdered by a coyote a couple of weeks back--right outside of my vegetable garden.
I'm thankful I wasn't that turkey. And no, I'm not having turkey for dinner today.
Wednesday, November 26, 2014
Pugliese, How to Beat the Market Makers at Their Own Game
How to Beat the Market Makers at Their Own Game: Uncovering the Mysteries of Day Trading (Wiley, 2014) is not the most compelling advertisement for Cyber Trading University, of which the author, Fausto Pugliese, is the founder and president. It’s by turns simplistic and obscure, repetitious and “gappy.” Traders may be able to make money following Pugliese’s advice; as the rather gruesome saying goes, there’s more than one way to skin a cat. I’m criticizing the way book is written, not the message—although I admit to finding the message troubling at several points.
So let’s turn to the message, without further value judgments.
Achieving success as an active trader means making “$200 on our trades each day.” All you have to do to make your “day’s pay” is to purchase 1,000 shares of the right stock and sell it for “just $.20 more per share than you paid for it.” (p. 50)
But how can the trader identify the right stock? Pugliese lists nine rules: (1) stay away from stocks that are higher than $30 a share, (2) avoid brand-name stocks, (3) steer clear of stocks with insufficient tier depth, (4) stay away from stocks with low trading volumes, (5) avoid stocks with high trading volumes, (6) pass up stocks with very few active market makers, (7) keep your spread to a minimum, (8) follow the stock trend both in pre-market and during the day to get a sense of direction, and (9) look for market maker traps.
Once the trader has created a list of tradable stocks and found the ax for each, “the only thing left for you to learn is when to buy a stock and when to sell it.” (p. 101) The answer is simple: the trader has to pay attention to support and resistance levels.
That’s it. “Once you hit $200, you have earned your day’s pay and can retire for the day.” (p. 123)
Well, actually that’s not quite it because Pugliese has ten trading rules of the road, including no overnights and no dollar cost averaging.
He concludes by inviting the reader to visit his educational site for “even more information on furthering your trading career.” (p. 187)
So let’s turn to the message, without further value judgments.
Achieving success as an active trader means making “$200 on our trades each day.” All you have to do to make your “day’s pay” is to purchase 1,000 shares of the right stock and sell it for “just $.20 more per share than you paid for it.” (p. 50)
But how can the trader identify the right stock? Pugliese lists nine rules: (1) stay away from stocks that are higher than $30 a share, (2) avoid brand-name stocks, (3) steer clear of stocks with insufficient tier depth, (4) stay away from stocks with low trading volumes, (5) avoid stocks with high trading volumes, (6) pass up stocks with very few active market makers, (7) keep your spread to a minimum, (8) follow the stock trend both in pre-market and during the day to get a sense of direction, and (9) look for market maker traps.
Once the trader has created a list of tradable stocks and found the ax for each, “the only thing left for you to learn is when to buy a stock and when to sell it.” (p. 101) The answer is simple: the trader has to pay attention to support and resistance levels.
That’s it. “Once you hit $200, you have earned your day’s pay and can retire for the day.” (p. 123)
Well, actually that’s not quite it because Pugliese has ten trading rules of the road, including no overnights and no dollar cost averaging.
He concludes by inviting the reader to visit his educational site for “even more information on furthering your trading career.” (p. 187)
Monday, November 24, 2014
Nations, The Complete Book of Option Spreads and Combinations
If you trade options, you’d do well to have Scott Nations’ Complete Book of Option Spreads and Combinations (Wiley, 2014) in your reference library. It’s an intermediate-level book that explains the structure of more spreads than most people will ever trade but that they should understand nonetheless. A case in point: a conversion or a reversal, a combination that is rarely executed as a package but that “a smart retail trader might end up having on.” (p. 209) It’s better to know in advance what this position is and how to deal with it.
There’s an abundance of information available online about option spreads and combinations, and Nations of necessity covers much of the same territory. But he proceeds more analytically, and he deals with issues that most online descriptions ignore, such as ways to mitigate wide bid/ask spreads. Take, for instance, the long call condor. Nations looks at an AAPL call condor that, using midpoint pricing, costs 18.87 and that, buying on the ask and selling on the bid would cost 0.63 more. What if we were to replace the in-the-money call spread “with something that’s out-of-the-money and has bid/ask spreads similar to the bid/ask spreads of these other out-of-the-money options?” That is, what if we sold a put spread with the same strikes instead of buying that call spread—and again sold at the bid and bought at the ask? Instead of paying a 0.63 penalty, we now pay only 0.27. This “new, magical structure” is an iron condor. (pp. 201-202)
In eleven chapters this book deals with vertical spreads, covered calls, covered puts, calendar spreads, straddles, strangles, collars, risk reversal, butterflies, condors and iron condors, and conversion/ reversal. Every strategy is encapsulated in cheat sheets and, more importantly, is illustrated with examples, complete with tables and figures. Here, for instance, is the graph of a vertical spread he analyzes, which includes the probability of profitability—something he explains how to calculate on the previous page.
Unlike Nations’ previous book, Options Math for Traders, this one is math-lite. He confines his discussion of option pricing to a single chapter and refers the reader to his website Option Math to download a free spreadsheet that calculates theoretical option values using the Black-Scholes model and inputs supplied by the user.
But it provides an excellent conceptual framework for understanding spreads and combinations. With the help of this book the reader can progress from being a trader who uses options to an options trader.
There’s an abundance of information available online about option spreads and combinations, and Nations of necessity covers much of the same territory. But he proceeds more analytically, and he deals with issues that most online descriptions ignore, such as ways to mitigate wide bid/ask spreads. Take, for instance, the long call condor. Nations looks at an AAPL call condor that, using midpoint pricing, costs 18.87 and that, buying on the ask and selling on the bid would cost 0.63 more. What if we were to replace the in-the-money call spread “with something that’s out-of-the-money and has bid/ask spreads similar to the bid/ask spreads of these other out-of-the-money options?” That is, what if we sold a put spread with the same strikes instead of buying that call spread—and again sold at the bid and bought at the ask? Instead of paying a 0.63 penalty, we now pay only 0.27. This “new, magical structure” is an iron condor. (pp. 201-202)
In eleven chapters this book deals with vertical spreads, covered calls, covered puts, calendar spreads, straddles, strangles, collars, risk reversal, butterflies, condors and iron condors, and conversion/ reversal. Every strategy is encapsulated in cheat sheets and, more importantly, is illustrated with examples, complete with tables and figures. Here, for instance, is the graph of a vertical spread he analyzes, which includes the probability of profitability—something he explains how to calculate on the previous page.
Unlike Nations’ previous book, Options Math for Traders, this one is math-lite. He confines his discussion of option pricing to a single chapter and refers the reader to his website Option Math to download a free spreadsheet that calculates theoretical option values using the Black-Scholes model and inputs supplied by the user.
But it provides an excellent conceptual framework for understanding spreads and combinations. With the help of this book the reader can progress from being a trader who uses options to an options trader.
Wednesday, November 19, 2014
The Best Business Writing 2014
For three years now Columbia Journalism Review Books has been publishing what the book’s editors (in this case Dean Starkman, Martha M. Hamilton, and Ryan Chittum) consider to be the best business writing of the year. This year’s collection contains 31 articles on topics ranging from the criminal—“Dead End on Silk Road” and “London’s Laundry Business” (and no, it’s not about laundering clothes but rather dirty money and dirty reputations)—to the political—“Washington’s Robust Market for Attacks, Half-Truths” and “He Who Makes the Rules.” There are articles on taxation—“Amazon’s (Not So) Secret War on Taxes” and “How the NFL Fleeces Taxpayers"—as well as on unhealthy business—“Merchants of Meth: How Big Pharma Keeps the Cooks in Business” and “The Extraordinary Science of Addictive Junk Food.” The section on creative destruction has five articles, that on frenzied finance has seven. And there is, of course, the requisite set of articles on Silicon Valley.
I’m not sure how many of these articles made their way into books. I know that Kevin Roose’s “One Percent Jokes and Plutocrats in Drag: What I Saw When I Crashed a Wall Street Secret Society” was recycled in his Young Money.
This is not the kind of book that lends itself to a review, but I thought I’d share the gist of Jia Lynn Yang’s article “Maximizing Shareholder Value: The Goal That Changed Corporate America.”
We take it for granted today that a company’s primary purpose is to maximize shareholder value, but that wasn’t always the case. “Rather, it was introduced by a handful of free-market academics in the 1970s and then picked up by business leaders and the media until it became an oft-repeated mantra in the corporate world.” (p. 162)
“In the decades after World War II, as the U.S. economy boomed, the interests of companies, shareholders, society, and workers appeared to be in tune. … Even until 1981, the Business Roundtable trade group understood the need to balance these different stakeholders. ‘Corporations have a responsibility, first of all, to make available to the public quality goods and services at fair prices, thereby earning a profit that attracts investment to continue and enhance the enterprise, provide jobs, and build the economy. ... The long-term viability of the corporation depends upon its responsibility to the society of which it is a part. And the well-being of society depends upon profitable and responsible business enterprises." (p. 164)
Today those words sound positively utopian. We have succumbed to Milton Friedman’s infamous 1970 remark that the only “social responsibility of business is to increase its profits.” (p. 165) This shift in objectives, Yang contends, “helped spawn the rise of executive pay tied to share prices—and thus the huge rise in stock-option pay. As a result, average annual executive pay has quadrupled since the early 1970s.” (p. 165)
I found a different set of figures from the Economic Policy Institute, a union-oriented organization: that “from 1978 to 2013, CEO compensation, inflation-adjusted, increased 937 percent, a rise more than double stock market growth and substantially greater than the painfully slow 10.2 percent growth in a typical worker’s compensation over the same period. The CEO-to-worker compensation ratio was 20-to-1 in 1965 and 29.9-to-1 in 1978, grew to 122.6-to-1 in 1995, peaked at 383.4-to-1 in 2000, and was 295.9-to-1 in 2013.”
This isn’t the place to parse economic data. Suffice it to say that CEOs are making much more, workers are treading water, and shareholder value is rising. Goals are no longer balanced.
I’m not sure how many of these articles made their way into books. I know that Kevin Roose’s “One Percent Jokes and Plutocrats in Drag: What I Saw When I Crashed a Wall Street Secret Society” was recycled in his Young Money.
This is not the kind of book that lends itself to a review, but I thought I’d share the gist of Jia Lynn Yang’s article “Maximizing Shareholder Value: The Goal That Changed Corporate America.”
We take it for granted today that a company’s primary purpose is to maximize shareholder value, but that wasn’t always the case. “Rather, it was introduced by a handful of free-market academics in the 1970s and then picked up by business leaders and the media until it became an oft-repeated mantra in the corporate world.” (p. 162)
“In the decades after World War II, as the U.S. economy boomed, the interests of companies, shareholders, society, and workers appeared to be in tune. … Even until 1981, the Business Roundtable trade group understood the need to balance these different stakeholders. ‘Corporations have a responsibility, first of all, to make available to the public quality goods and services at fair prices, thereby earning a profit that attracts investment to continue and enhance the enterprise, provide jobs, and build the economy. ... The long-term viability of the corporation depends upon its responsibility to the society of which it is a part. And the well-being of society depends upon profitable and responsible business enterprises." (p. 164)
Today those words sound positively utopian. We have succumbed to Milton Friedman’s infamous 1970 remark that the only “social responsibility of business is to increase its profits.” (p. 165) This shift in objectives, Yang contends, “helped spawn the rise of executive pay tied to share prices—and thus the huge rise in stock-option pay. As a result, average annual executive pay has quadrupled since the early 1970s.” (p. 165)
I found a different set of figures from the Economic Policy Institute, a union-oriented organization: that “from 1978 to 2013, CEO compensation, inflation-adjusted, increased 937 percent, a rise more than double stock market growth and substantially greater than the painfully slow 10.2 percent growth in a typical worker’s compensation over the same period. The CEO-to-worker compensation ratio was 20-to-1 in 1965 and 29.9-to-1 in 1978, grew to 122.6-to-1 in 1995, peaked at 383.4-to-1 in 2000, and was 295.9-to-1 in 2013.”
This isn’t the place to parse economic data. Suffice it to say that CEOs are making much more, workers are treading water, and shareholder value is rising. Goals are no longer balanced.
Monday, November 17, 2014
Doug Kass on the Market
For over 15 years Doug Kass, president of Seabreeze Partners Management, has been a contributor to TheStreet.com and has by his own estimate written over 30 million words in more than 50,000 columns (typically at least 15 a day). He makes the rest of us look incredibly lazy.
In this his first book, Doug Kass on the Market: A Life on TheStreet (Wiley, 2014), Kass, with the help of his editor Daniel Robinson, offers a selection of these columns. They document the thinking of a conservative short seller (or, the stuffed animal the cover portrays him holding, a teddy bear) over a range of market conditions.
The book is divided into nine sections: where it began, short-selling, lessons learned, the great decession: subprime and credit/debt crisis, recovery, against the grain, Wall Street personalities, Buffett watch, and surprises. There’s some overlap, and some understandable repetition, but Kass covers a lot of territory in more than 500 pages.
I was most interested in his investing advice. Let me share a few of his pearls of wisdom here.
“Regardless of one’s modus operandi (fundamental, technical, or a combination of both), logic of argument and power of dissection are the two most important ingredients in delivering superior investment returns. Common sense, which is not so common, runs a close third.” (p. 51)
“Under a normally trending (and upwardly sloping) market (and dependent upon my degree of confidence), I would have as much as 67% (when fully invested) of my portfolio in investment holdings (with a majority of longs), and I would have as much as 33% of my portfolio in trading rentals (again, a majority of longs).”
In a range-bound market, “I would be more inclined to trade stocks…. In this case, I might only be as much as 40% committed to investments and perhaps as much as 60% in opportunistic rentals, with a mix of both longs and shorts.”
In a downwardly sloped market, “in theory, my portfolio … would be dominated by shorts, but, in reality, it’s not practical, as the asymmetric risk/reward of short sales would reduce the overall commitment to shorts even in a correcting market phase.” (p. 94)
“Avoid illiquid and heavily shorted stocks. If you don’t, eventually a short squeeze will be the outcome, and there will be heavy losses with it.
“Trade around your short positions, and ladder your shorts with the timing of expected catalysts (in terms of the calendar) to ensure superior performance and participation in market downdrafts.” (p. 17)
Since I devote this blog almost exclusively to books on trading and investing, I’m always interested in what other people read. In 2011 Doug Kass described The Most Important Thing by Howard Marks as “a tour de force, … the single-best investment primer I have read” since Graham and Dodd’s Security Analysis (1934) and Graham’s The Intelligent Investor (1949). I wasn’t so effusive in my review.
Fans of Warren Buffett will undoubtedly turn immediately to the section that describes Kass’s trip to Omaha to ask questions as a “credentialed bear,” one who wrote a column in 2008 explaining his rationale for being short Berkshire stock. They won’t be disappointed.
The final section of the book is devoted to his annual list of possible surprises for the coming year, a practice he started in 2002. I don’t know why anyone would ever want to go through this exercise since, as Woody Allen said (and as Kass quotes him), “I’m astounded by people who want to ‘know’ the universe when it’s hard enough to find your way around Chinatown.” (p. 428) Predicting the future is harder yet. To Kass’s credit, he lays everything out—the prescient as well as the dead wrong.
In this his first book, Doug Kass on the Market: A Life on TheStreet (Wiley, 2014), Kass, with the help of his editor Daniel Robinson, offers a selection of these columns. They document the thinking of a conservative short seller (or, the stuffed animal the cover portrays him holding, a teddy bear) over a range of market conditions.
The book is divided into nine sections: where it began, short-selling, lessons learned, the great decession: subprime and credit/debt crisis, recovery, against the grain, Wall Street personalities, Buffett watch, and surprises. There’s some overlap, and some understandable repetition, but Kass covers a lot of territory in more than 500 pages.
I was most interested in his investing advice. Let me share a few of his pearls of wisdom here.
“Regardless of one’s modus operandi (fundamental, technical, or a combination of both), logic of argument and power of dissection are the two most important ingredients in delivering superior investment returns. Common sense, which is not so common, runs a close third.” (p. 51)
“Under a normally trending (and upwardly sloping) market (and dependent upon my degree of confidence), I would have as much as 67% (when fully invested) of my portfolio in investment holdings (with a majority of longs), and I would have as much as 33% of my portfolio in trading rentals (again, a majority of longs).”
In a range-bound market, “I would be more inclined to trade stocks…. In this case, I might only be as much as 40% committed to investments and perhaps as much as 60% in opportunistic rentals, with a mix of both longs and shorts.”
In a downwardly sloped market, “in theory, my portfolio … would be dominated by shorts, but, in reality, it’s not practical, as the asymmetric risk/reward of short sales would reduce the overall commitment to shorts even in a correcting market phase.” (p. 94)
“Avoid illiquid and heavily shorted stocks. If you don’t, eventually a short squeeze will be the outcome, and there will be heavy losses with it.
“Trade around your short positions, and ladder your shorts with the timing of expected catalysts (in terms of the calendar) to ensure superior performance and participation in market downdrafts.” (p. 17)
Since I devote this blog almost exclusively to books on trading and investing, I’m always interested in what other people read. In 2011 Doug Kass described The Most Important Thing by Howard Marks as “a tour de force, … the single-best investment primer I have read” since Graham and Dodd’s Security Analysis (1934) and Graham’s The Intelligent Investor (1949). I wasn’t so effusive in my review.
Fans of Warren Buffett will undoubtedly turn immediately to the section that describes Kass’s trip to Omaha to ask questions as a “credentialed bear,” one who wrote a column in 2008 explaining his rationale for being short Berkshire stock. They won’t be disappointed.
The final section of the book is devoted to his annual list of possible surprises for the coming year, a practice he started in 2002. I don’t know why anyone would ever want to go through this exercise since, as Woody Allen said (and as Kass quotes him), “I’m astounded by people who want to ‘know’ the universe when it’s hard enough to find your way around Chinatown.” (p. 428) Predicting the future is harder yet. To Kass’s credit, he lays everything out—the prescient as well as the dead wrong.
Wednesday, November 12, 2014
Pilon, The Monopolists
I have fond memories of spending countless youthful hours on a neighbor’s screened-in porch playing Monopoly. When life intervened—to go home for lunch or at the end of the day—and the game wasn’t yet finished, the board remained set up, ready for us to pick up where we had left off. And so, when I saw that a new book on Monopoly was coming out in February, 2015, I rushed to read the advance galleys. I was amply rewarded for my time, although I must admit that something of a pall was cast over my memories.
Mary Pilon’s The Monopolists: Obsession, Fury, and the Scandal Behind the World’s Favorite Board Game (Bloomsbury) is a well-crafted tale of how Monopoly came to be and how the wrong person was given (actually, falsely claimed) credit for creating it.
Under the best of circumstances attribution is a tricky business. For instance, every school child is taught that Thomas Edison invented the light bulb, and yet he was only the most famous in a string of inventors who contributed to electric lighting. Volta developed the first practical method of generating electricity in 1800, Humphrey Davy invented the electric arc lamp in 1802, Warren de la Rue developed a platinum filament light bulb in 1840, Joseph Swan came up with a light bulb that used carbonized paper filaments in 1850, and Henry Woodward and Matthew Evans filed a patent in 1874 for an electric lamp with carbon rods. They sold their patent to Edison in 1879, the same year in which he filed a patent for an electric lamp with a carbon filament. And, of course, Edison did not work alone; he had a large team of researchers. It is more accurate, therefore, to say that Thomas Edison and his team invented the first commercially practical incandescent light.
In the case of Monopoly, the journey from first iteration to wildly popular board game was more incremental. But one thing we can now say with certainty. Charles Darrow, the unemployed salesman whose alleged invention—or so the official story went—rescued both Parker Brothers and Darrow from financial collapse, did not create the game. He simply reaped its benefits.
In the beginning was a woman, Elizabeth Magie, a follower of the anti-monopolist Henry George. During the day she worked in the Dead Letter Office, in the evening she pursued literary and theatrical ambitions and dabbled in invention. At the age of 26, for instance, she patented a gadget that improved on typewriter technology. She also taught classes about George’s single tax theory. Wanting to expand her audience for George’s theory, she came up with a board game, which she called the Landlord’s Game. “It is a practical demonstration of the present system of land-grabbing with all its usual outcomes and consequences,” she wrote in 1902. “[S]omewhat surprisingly, Lizzie created two sets of rules: an anti-monopolist set in which all were rewarded when wealth was created, and a monopolist set in which the goal was to create monopolies and crush opponents.” (p.33) We know, of course, which set of rules the public came to embrace.
The Landlord’s Game became popular, mainly among east coast, left-wing intellectuals. It was played at the Wharton School and Columbia and by the late 1920s was a sensation in the fraternity scene at Williams College. One of the students who played the game at Williams produced his own version of it, calling it Finance. He couldn’t find buyers for his game, but before he abandoned the project altogether he taught the game to some Quaker friends, “who would modify it and change its course in the most unlikely way.” (p. 79)
A group of Quakers moved to Atlantic City to “establish a healthy, fresh-air community, complete with modest accommodations and prayer lodges.” (p. 80) Well, you can pretty well guess the next stage in the game’s development, though I’d wager to say that you don’t know why Baltic Avenue is less valuable than Marvin Gardens or that ‘Marvin Gardens’ turned out to be a tell-tale copying error (the correct spelling was ‘Marven’).
Unfortunately it’s a short step from the innocent Quaker innovators to the dark side of the game’s history.
Pilon, a staff reporter at The New York Times, does a brilliant job of exposing questionable corporate mores and individual dishonesty and greed. The heroes of the book, such as Ralph Anspach—who uncovered the provenance of Monopoly while engaged in costly litigation over his Anti-Monopoly board game decades later, struggled; the villains thrived. The game, of course, continues. It no longer, however, comes with a printed copy of Darrow’s rags to riches story.
Mary Pilon’s The Monopolists: Obsession, Fury, and the Scandal Behind the World’s Favorite Board Game (Bloomsbury) is a well-crafted tale of how Monopoly came to be and how the wrong person was given (actually, falsely claimed) credit for creating it.
Under the best of circumstances attribution is a tricky business. For instance, every school child is taught that Thomas Edison invented the light bulb, and yet he was only the most famous in a string of inventors who contributed to electric lighting. Volta developed the first practical method of generating electricity in 1800, Humphrey Davy invented the electric arc lamp in 1802, Warren de la Rue developed a platinum filament light bulb in 1840, Joseph Swan came up with a light bulb that used carbonized paper filaments in 1850, and Henry Woodward and Matthew Evans filed a patent in 1874 for an electric lamp with carbon rods. They sold their patent to Edison in 1879, the same year in which he filed a patent for an electric lamp with a carbon filament. And, of course, Edison did not work alone; he had a large team of researchers. It is more accurate, therefore, to say that Thomas Edison and his team invented the first commercially practical incandescent light.
In the case of Monopoly, the journey from first iteration to wildly popular board game was more incremental. But one thing we can now say with certainty. Charles Darrow, the unemployed salesman whose alleged invention—or so the official story went—rescued both Parker Brothers and Darrow from financial collapse, did not create the game. He simply reaped its benefits.
In the beginning was a woman, Elizabeth Magie, a follower of the anti-monopolist Henry George. During the day she worked in the Dead Letter Office, in the evening she pursued literary and theatrical ambitions and dabbled in invention. At the age of 26, for instance, she patented a gadget that improved on typewriter technology. She also taught classes about George’s single tax theory. Wanting to expand her audience for George’s theory, she came up with a board game, which she called the Landlord’s Game. “It is a practical demonstration of the present system of land-grabbing with all its usual outcomes and consequences,” she wrote in 1902. “[S]omewhat surprisingly, Lizzie created two sets of rules: an anti-monopolist set in which all were rewarded when wealth was created, and a monopolist set in which the goal was to create monopolies and crush opponents.” (p.33) We know, of course, which set of rules the public came to embrace.
The Landlord’s Game became popular, mainly among east coast, left-wing intellectuals. It was played at the Wharton School and Columbia and by the late 1920s was a sensation in the fraternity scene at Williams College. One of the students who played the game at Williams produced his own version of it, calling it Finance. He couldn’t find buyers for his game, but before he abandoned the project altogether he taught the game to some Quaker friends, “who would modify it and change its course in the most unlikely way.” (p. 79)
A group of Quakers moved to Atlantic City to “establish a healthy, fresh-air community, complete with modest accommodations and prayer lodges.” (p. 80) Well, you can pretty well guess the next stage in the game’s development, though I’d wager to say that you don’t know why Baltic Avenue is less valuable than Marvin Gardens or that ‘Marvin Gardens’ turned out to be a tell-tale copying error (the correct spelling was ‘Marven’).
Unfortunately it’s a short step from the innocent Quaker innovators to the dark side of the game’s history.
Pilon, a staff reporter at The New York Times, does a brilliant job of exposing questionable corporate mores and individual dishonesty and greed. The heroes of the book, such as Ralph Anspach—who uncovered the provenance of Monopoly while engaged in costly litigation over his Anti-Monopoly board game decades later, struggled; the villains thrived. The game, of course, continues. It no longer, however, comes with a printed copy of Darrow’s rags to riches story.
Monday, November 10, 2014
Brandes on Value
Brandes on Value: The Independent Investor (McGraw-Hill) is a paean to the “practicality and universal application of Graham-and-Dodd principles.” Charles H. Brandes became a convert to value investing through a most unlikely encounter. In 1971, three years out of college and a broker/analyst in San Diego, he was taking his turn keeping an eye out for the admittedly rare walk-in brokerage customer “when an elderly, unassuming man walked through the door.” That man was Benjamin Graham—yes, the Benjamin Graham. Graham was spending his winters in La Jolla and wanted to open an account so he could buy a stock he had been tracking for months. Well, one thing led to another, and soon enough Brandes was hooked. In 1974, a year that most investors would have considered inauspicious but Graham called “an excellent time to launch a venture of this sort,” Brandes opened his own firm. Forty years later he remains convinced that “the fundamentals of value investing [make] total practical sense for long-term investors.” (p. xiv)
Here I’ll highlight three concepts that are basic to Brandes’ framework: investing versus speculation, value philosophy, and risk.
Brandes expands on Graham’s distinction between investing and speculation. In The Intelligent Investor Graham wrote: “An investment operation is one which, upon thorough analysis, promises safety of principal and an adequate return. Operations not meeting these requirements are speculative.” Brandes adds two more criteria that define speculation: “any contemplated holding period shorter than a normal business cycle (typically three to five years)” and “any purchase based solely on anticipated market movements.” (p. 26)
Value investors agonize over—and disagree about—what characteristics a company must have to be considered a value play. Brandes simplifies the selection process, condensing “the most significant precepts of the value philosophy into a four-step test that you can quickly apply to any company that catches your eye”: “1. No losses were sustained within the past five years. 2. Total debt is less than 100 percent of total tangible equity. 3. Share price is less than book value per share. 4. Earnings yield is at least twice the yield on long-term (20-year) AAA bonds.” (p. 71)
There’s some wiggle room in using these guidelines. As Brandes writes, “Utilities, which are usually buffered from economic influences, may allow a little more leniency on the debt-to-equity or annual earnings growth tests, while for a potentially more volatile technology-based business, these would be two must-pass criteria before we would even consider it.” (p. 73) Moreover, lest one think that value investing can be reduced to a straightforward four-step process, the professional value investor will typically subject any company in which he is interested to much more detailed analysis.
Finally, let’s look at Brandes’ understanding of risk. He rails against conflating volatility with risk. Risk is just what the average investor thinks it is—the possibility of losing money. He argues that “working with equities is not about reading the beta or standard deviation and diversifying away the alpha potential. It means doing some homework, stepping up, and taking on some additional volatility risk that could turn out to be an excellent value opportunity.” (p. 217)
Risk in its true sense cannot be measured in the way that volatility and similar mathematical notions can. But it follows a general pattern. Investors lose money when they overpay, when they sell at a loss (that is, when they didn’t wait patiently for the stock to turn around), when the company itself deteriorated, and when they strayed from fundamental investing discipline and lost focus. Note that only one of these reasons for a loss of capital is outside the control of the investor. In the investing world, where uncertainty is said to reign supreme, that definitely shifts the balance of power.
Here I’ll highlight three concepts that are basic to Brandes’ framework: investing versus speculation, value philosophy, and risk.
Brandes expands on Graham’s distinction between investing and speculation. In The Intelligent Investor Graham wrote: “An investment operation is one which, upon thorough analysis, promises safety of principal and an adequate return. Operations not meeting these requirements are speculative.” Brandes adds two more criteria that define speculation: “any contemplated holding period shorter than a normal business cycle (typically three to five years)” and “any purchase based solely on anticipated market movements.” (p. 26)
Value investors agonize over—and disagree about—what characteristics a company must have to be considered a value play. Brandes simplifies the selection process, condensing “the most significant precepts of the value philosophy into a four-step test that you can quickly apply to any company that catches your eye”: “1. No losses were sustained within the past five years. 2. Total debt is less than 100 percent of total tangible equity. 3. Share price is less than book value per share. 4. Earnings yield is at least twice the yield on long-term (20-year) AAA bonds.” (p. 71)
There’s some wiggle room in using these guidelines. As Brandes writes, “Utilities, which are usually buffered from economic influences, may allow a little more leniency on the debt-to-equity or annual earnings growth tests, while for a potentially more volatile technology-based business, these would be two must-pass criteria before we would even consider it.” (p. 73) Moreover, lest one think that value investing can be reduced to a straightforward four-step process, the professional value investor will typically subject any company in which he is interested to much more detailed analysis.
Finally, let’s look at Brandes’ understanding of risk. He rails against conflating volatility with risk. Risk is just what the average investor thinks it is—the possibility of losing money. He argues that “working with equities is not about reading the beta or standard deviation and diversifying away the alpha potential. It means doing some homework, stepping up, and taking on some additional volatility risk that could turn out to be an excellent value opportunity.” (p. 217)
Risk in its true sense cannot be measured in the way that volatility and similar mathematical notions can. But it follows a general pattern. Investors lose money when they overpay, when they sell at a loss (that is, when they didn’t wait patiently for the stock to turn around), when the company itself deteriorated, and when they strayed from fundamental investing discipline and lost focus. Note that only one of these reasons for a loss of capital is outside the control of the investor. In the investing world, where uncertainty is said to reign supreme, that definitely shifts the balance of power.
Wednesday, November 5, 2014
Hirsch, Stock Trader’s Almanac 2015
The Stock Trader’s Almanac is now in its forty-eighth edition. It remains a must for traders who use seasonal factors to time the market.
The spiral bound, navy-covered almanac opens flat for easy access to its data or for jotting down notes. The format remains essentially the same, with a calendar section, a directory of trading patterns and databank, and a strategy planning and record keeping section. The calendar section has on facing pages historical data on market performance (verso) and a week’s worth of calendar entries (recto). January’s verso pages, for example, give the month’s vital statistics, January’s first five days as an early warning system, the January barometer (which has had only seven significant errors in 64 years), and the January barometer in graphic form since 1950. Each trading day’s entry on the recto pages includes the probability, based on a 21-year lookback period, that the Dow, S&P, and Nasdaq will rise. Particularly favorable days (based on the performance of the S&P) are flagged with a bull icon; particularly unfavorable trading days get a bear icon. A witch icon appears on options expiration days. At the bottom of each entry is an apt quotation. There’s about a five-square-inch space in which to write. New this year is a three-page section in which “some of the best minds on Wall Street” offer their outlooks for 2015.
The Stock Trader’s Almanac pays particular attention to the presidential cycle, and it bodes well for 2015. Pre-presidential election years are the best performers in the cycle. “There hasn’t been a down year in the third year of a presidential term since war-torn 1939, Dow off 2.9%. The only severe loss in a pre-presidential election year going back 100 years occurred in 1931 during the Depression.” (p. 20)
The presidential cycle isn’t the only thing 2015 has going for it. “The fifth year of the decade is also the best year of the decennial pattern by a long shot with only one loss in the past 13 decades.” (p. 6)
Enjoy it while it lasts, since Jeffrey Hirsch expects a bear market after 2015, “taking the market 30-40% lower into 2017-2018 into the range of Dow 11,500-13,500.”
What other seasonals are powerful? The best six months strategy still works. “Investing in the Dow Jones Industrial Average between November 1st and April 30th each year and then switching into fixed income for the other six months has produced reliable returns with reduced risk since 1950.” In 64 years the Dow gained 17432 points during these months and lost 1066 points during May through October. The S&P gained 1790 points in the same best six months versus 75.5 points in the worst six. And applying a simple MACD timing indicator nearly triples these results.
The first months of quarters are the most bullish, and the first trading day of the month outshines all others combined. You read me right: “Over the last 17 years the Dow Jones Industrial Average has gained more points on the first trading days of all months than all other days combined. While the Dow has gained 8868.89 points between September 2, 1997 (7622.42) and May 16, 2014 (1649.31), it is incredible that 5468.22 points were gained on the first trading days of these 201 months. The remaining 4003 trading days combined gained 3400.67 points during the period. This averages out to gains of 27.21 points on first days, in contrast to just 0.85 points on all others.” (p. 86) By the way, 2014 did not continue this tradition; during the first trading days of the first five months it lost 562.06 points (-135.31, -326.05, -153.68, 74.95, and -21.97).
This almanac is chock full of data that will delight those traders who believe that past is prologue. Even those who are skeptical have to pay attention to data that seasonal traders rely on and that therefore tend to move markets.
The spiral bound, navy-covered almanac opens flat for easy access to its data or for jotting down notes. The format remains essentially the same, with a calendar section, a directory of trading patterns and databank, and a strategy planning and record keeping section. The calendar section has on facing pages historical data on market performance (verso) and a week’s worth of calendar entries (recto). January’s verso pages, for example, give the month’s vital statistics, January’s first five days as an early warning system, the January barometer (which has had only seven significant errors in 64 years), and the January barometer in graphic form since 1950. Each trading day’s entry on the recto pages includes the probability, based on a 21-year lookback period, that the Dow, S&P, and Nasdaq will rise. Particularly favorable days (based on the performance of the S&P) are flagged with a bull icon; particularly unfavorable trading days get a bear icon. A witch icon appears on options expiration days. At the bottom of each entry is an apt quotation. There’s about a five-square-inch space in which to write. New this year is a three-page section in which “some of the best minds on Wall Street” offer their outlooks for 2015.
The Stock Trader’s Almanac pays particular attention to the presidential cycle, and it bodes well for 2015. Pre-presidential election years are the best performers in the cycle. “There hasn’t been a down year in the third year of a presidential term since war-torn 1939, Dow off 2.9%. The only severe loss in a pre-presidential election year going back 100 years occurred in 1931 during the Depression.” (p. 20)
The presidential cycle isn’t the only thing 2015 has going for it. “The fifth year of the decade is also the best year of the decennial pattern by a long shot with only one loss in the past 13 decades.” (p. 6)
Enjoy it while it lasts, since Jeffrey Hirsch expects a bear market after 2015, “taking the market 30-40% lower into 2017-2018 into the range of Dow 11,500-13,500.”
What other seasonals are powerful? The best six months strategy still works. “Investing in the Dow Jones Industrial Average between November 1st and April 30th each year and then switching into fixed income for the other six months has produced reliable returns with reduced risk since 1950.” In 64 years the Dow gained 17432 points during these months and lost 1066 points during May through October. The S&P gained 1790 points in the same best six months versus 75.5 points in the worst six. And applying a simple MACD timing indicator nearly triples these results.
The first months of quarters are the most bullish, and the first trading day of the month outshines all others combined. You read me right: “Over the last 17 years the Dow Jones Industrial Average has gained more points on the first trading days of all months than all other days combined. While the Dow has gained 8868.89 points between September 2, 1997 (7622.42) and May 16, 2014 (1649.31), it is incredible that 5468.22 points were gained on the first trading days of these 201 months. The remaining 4003 trading days combined gained 3400.67 points during the period. This averages out to gains of 27.21 points on first days, in contrast to just 0.85 points on all others.” (p. 86) By the way, 2014 did not continue this tradition; during the first trading days of the first five months it lost 562.06 points (-135.31, -326.05, -153.68, 74.95, and -21.97).
This almanac is chock full of data that will delight those traders who believe that past is prologue. Even those who are skeptical have to pay attention to data that seasonal traders rely on and that therefore tend to move markets.
Monday, November 3, 2014
Ervolini, Managing Equity Portfolios
Active portfolio managers are judged by the outcomes of their investing strategies, such as risk adjusted returns. More often than not, these returns come up short when measured against standard benchmarks. Understandably, investors ask why they should pay management fees for subpar active management when they could park their money in passive index funds at a significantly lower cost.
In Managing Equity Portfolios: A Behavioral Approach to Improving Skills and Investment Processes (MIT Press, 2014) Michael A. Ervolini, CEO of Cabot Research, offers the beleaguered portfolio manager some suggestions on how to go about improving. That such a book is deemed necessary is somewhat worrisome. Retail investors and traders, whose portfolios are dwarfed by their institutional brethren’s and who don’t collect hefty salaries for managing their own money, have been deluged with works offering much of the same advice—beware of behavioral traps, focus on process rather than outcome, keep a trading journal. Fortunately, since Cabot Research provides “innovative analytics to help money managers improve portfolio performance,” the book also highlights some of the metrics that all traders and investors can use to assess and improve their own performance.
Instead of rehashing the findings of behavioral finance, which I’ve written about on numerous occasions, I’ll focus on the book’s main organizing principle and some of its attendant metrics.
Investing, stripped to its bare essentials, involves three skills: buying, selling, and position sizing. “Familiar as these terms are,” the author writes, “few professionals know with any degree of confidence how much of their portfolio alpha comes from just the buying.” Or the selling, or the position sizing. “Not knowing how effective each skill is means that any attempt to improve is, at best, based on a hunch.” The author advocates adopting an analytical framework that regards performance as “a portfolio of decisions, rather than holdings. … The goal is to rigorously measure skills, process, and behaviors so that managers can do more of what they do well and have the necessary information to make small refinements that have a high likelihood of helping them improve.” (p. 158)
How should a money manager proceed? First, he has to collect data—the more granular the better. “For example, when making adds to existing positions, you might jot down answers to the following questions: Is the position currently a winner or loser? Prior to the add, is it small, mid-sized, or large relative to your typical full weight? How is it performing relative to the two or three basic attributes you use to gauge a stock’s alpha potential … ? How are you feeling—optimistic, pessimistic, confident, fearful, etc.?”
The manager must then analyze the data. “For example, to look deeper into your adds to winning positions, you might create a graph with an x-axis indicating time and two distinct y-axes, the one on the left indicating cumulative return, and the one on the right indicating the size of the adds.” (p. 236) And finally, he must draw up an improvement plan.
Ervolini walks the reader through a few ways to analyze buy, sell, and position sizing decisions. Sell decisions can be critiqued through the lens of holding time—whether positions harvested early are helping or hurting performance. As for buying or adding to positions, you can analyze whether your “high conviction” purchases are outperforming those in which you have less confidence.
The upshot is that you can only know your strengths and weaknesses if you find a way to measure your investing behavior—a way that is, the author recommends, simple (otherwise you won’t do it) and granular (otherwise the results will be too general to be useful). Separate out your trading activities, and here, I would suggest, you can include such things as order type and fill, response to market volatility, source of investment idea, etc. You never know what kinds of analytics might be helpful until you start collecting data and mining the results for performance gold.
In Managing Equity Portfolios: A Behavioral Approach to Improving Skills and Investment Processes (MIT Press, 2014) Michael A. Ervolini, CEO of Cabot Research, offers the beleaguered portfolio manager some suggestions on how to go about improving. That such a book is deemed necessary is somewhat worrisome. Retail investors and traders, whose portfolios are dwarfed by their institutional brethren’s and who don’t collect hefty salaries for managing their own money, have been deluged with works offering much of the same advice—beware of behavioral traps, focus on process rather than outcome, keep a trading journal. Fortunately, since Cabot Research provides “innovative analytics to help money managers improve portfolio performance,” the book also highlights some of the metrics that all traders and investors can use to assess and improve their own performance.
Instead of rehashing the findings of behavioral finance, which I’ve written about on numerous occasions, I’ll focus on the book’s main organizing principle and some of its attendant metrics.
Investing, stripped to its bare essentials, involves three skills: buying, selling, and position sizing. “Familiar as these terms are,” the author writes, “few professionals know with any degree of confidence how much of their portfolio alpha comes from just the buying.” Or the selling, or the position sizing. “Not knowing how effective each skill is means that any attempt to improve is, at best, based on a hunch.” The author advocates adopting an analytical framework that regards performance as “a portfolio of decisions, rather than holdings. … The goal is to rigorously measure skills, process, and behaviors so that managers can do more of what they do well and have the necessary information to make small refinements that have a high likelihood of helping them improve.” (p. 158)
How should a money manager proceed? First, he has to collect data—the more granular the better. “For example, when making adds to existing positions, you might jot down answers to the following questions: Is the position currently a winner or loser? Prior to the add, is it small, mid-sized, or large relative to your typical full weight? How is it performing relative to the two or three basic attributes you use to gauge a stock’s alpha potential … ? How are you feeling—optimistic, pessimistic, confident, fearful, etc.?”
The manager must then analyze the data. “For example, to look deeper into your adds to winning positions, you might create a graph with an x-axis indicating time and two distinct y-axes, the one on the left indicating cumulative return, and the one on the right indicating the size of the adds.” (p. 236) And finally, he must draw up an improvement plan.
Ervolini walks the reader through a few ways to analyze buy, sell, and position sizing decisions. Sell decisions can be critiqued through the lens of holding time—whether positions harvested early are helping or hurting performance. As for buying or adding to positions, you can analyze whether your “high conviction” purchases are outperforming those in which you have less confidence.
The upshot is that you can only know your strengths and weaknesses if you find a way to measure your investing behavior—a way that is, the author recommends, simple (otherwise you won’t do it) and granular (otherwise the results will be too general to be useful). Separate out your trading activities, and here, I would suggest, you can include such things as order type and fill, response to market volatility, source of investment idea, etc. You never know what kinds of analytics might be helpful until you start collecting data and mining the results for performance gold.
Wednesday, October 29, 2014
Ashton, How to Fly a Horse
Kevin Ashton is a creative guy, best known for his coined phrase “the Internet of Things” although, more substantively, he led pioneering work on RFID. Now he can add to his credits a wonderful book, How to Fly a Horse: The Secret History of Creation, Invention, and Discovery (Doubleday, to be released in January 2015).
The title refers to Wilbur Wright’s comparison of an object being buffeted by wind when it glides to an untrained horse, “darting hither and thither in the most erratic manner.” Wright continues: “Yet this is the style of steed that men must learn to manage before flying can become an everyday sport. The bird has learned this art of equilibrium, and learned it so thoroughly that its skill is not apparent to our sight. We only learn to appreciate it when we try to imitate it.” Or, as Ashton writes, “when we try to fly a horse.” (pp. 58-59)
Ashton introduces us to creative people from many walks of life. “Taken together, the stories reveal a pattern for how humans make new things, one that is both encouraging and challenging. The encouraging part is that there is no magic moment of creation. Creators spend almost all their time creating, persevering, despite doubt, failure, ridicule, and rejection until they succeed in making something new and useful. There are no tricks, shortcuts, or get-creative-quick schemes. The process is ordinary, even if the outcome is not. Creating is not magic but work.” (p. 15)
Ashton debunks some of the myths of creation—for instance, that creators are geniuses or that creators stand on the shoulders of giants. I was especially taken with his analysis of the latter myth. In 1676 Newton famously wrote: “If I have seen further it is by standing on the shoulders of giants.” Robert Merton traced the chain of custody of this phrase. Newton got it from George Herbert, who got it from Robert Hooke, who got it from Robert Burton, who got it from the Spanish theologian Diego de Estella, who probably got it from John of Salisbury, who got it from Bernard of Chartres, 1130. “We do not know from whom Bernard of Chartres got it.” In brief, Newton’s line was “close to a cliché at the time he wrote it.” (p. 120)
But, Ashton argues, “if everybody sees further because they are standing on the shoulders of giants, then there are no giants, just a tower of people, each one standing on the shoulders of another. … We do not see farther because of giants. We see farther because of generations.” (p. 121)
He uses Rosalind Franklin’s research in crystallography (and, most famously, her DNA photography and analysis) to illustrate this point—and to highlight the contributions of a chain of women to science. Since women are still underrepresented, and underpaid, in STEM research—as well as in finance, and since women’s “innate abilities” are often challenged (think of Larry Summers’ infamous hypothesis), I’ll devote a big chunk of this post to Ashton’s discussion of women in science.
“When Rosalind Franklin started analyzing DNA using X-ray crystallography, she was inheriting a technique pioneered by Dorothy Hodgkin, who was inspired by Polly Porter, who was a protégé of Florence Bascom, who broke ground for all women in science, following work by William Bragg, who was inspired by Max von Laue, who followed Wilhelm Röntgen, who followed William Crookes, who followed Heinrich Geissler, who followed Robert Boyle.” And, he continues, “Today, the whole world stands on Rosalind Franklin’s shoulders.” (p. 126)
The women who were critical in laying the groundwork for the discovery of DNA were relegated to “a relative backwater” of science—crystallography—and had to overcome demeaning obstacles to be able to study even that field. Florence Bascom, the first woman to earn a Ph.D. from Johns Hopkins, “had to take her classes there sitting behind a screen so that she would ‘not distract the men.’” (p. 123)
Polly Porter’s parents forbade her to go to school because they didn’t believe women should be educated. She got jobs reorganizing a collection of ancient Roman marble, dusting the laboratory of a crystallographer, and—after the family moved to the United States—cataloguing stones at the Smithsonian and then at Bryn Mawr. It was there that “Florence Bascom discovered her and appealed to Mary Garrett, a suffragist and railroad heiress, for funds so she could study.” In 1914 Bragg won the Nobel Prize, and “crystallography moved from the margins of geology to the foundation of science.” At this point Bascom recommended Porter for a laboratory job with a mineralogist at Heidelberg. She arrived in June 1914, a month before World War I began. “Porter succeeded at her work of learning the art of crystallography despite the difficulties of the war and the depression and distraction of Goldschmidt, and three years later, she earned a science degree from Oxford. She stayed at Oxford, conducting research into, and teaching undergraduates about, the crystals that were her passion until she retired, in 1959. One of her most enduring acts was to inspire and encourage a woman who would become one of the world’s greatest crystallographers and Rosalind Franklin’s mentor: Dorothy Hodgkin.” (p. 124)
James Watson and Francis Crick did not stand on the shoulders of Rosalind Franklin; they stole her work. Franklin took pictures of DNA and analyzed them by hand using a complex mathematical equation. “While [she] was concluding this work, her King’s College colleague Maurice Wilkins showed her data and pictures to James Watson and Francis Crick, without her consent or knowledge. Watson and Crick leapt to the conclusion Franklin was diligently proving—that the structure of DNA was a double helix—published it, then shared their Nobel Prize with their secret source, Wilkins.” (p. 116)
They were not the only men to win Nobel Prizes in science for discoveries made in whole or part by women. “It was the same when Marietta Blau, an unpaid woman working at the University of Vienna, developed a technique for photographing atomic particles. Blau could not get a paid position anywhere, even though her work was a major advance in particle physics. C. F. Powell, a man who ‘adopted and improved’ her techniques, was awarded the Nobel Prize in 1950. Agnes Pockels was denied a college education because she was a woman, taught herself science from her brother’s textbooks, created a laboratory in her kitchen, and used it to make fundamental discoveries about the chemistry of liquids. Her work was ‘adopted’ by Irving Langmuis, who won a Nobel Prize for it in 1932.” (p. 117) And Lise Meitner “discovered nuclear fission only to see her collaborator Otto Hahn receive the 1944 Nobel Prize for her work.” (p. 115)
Even Marie Curie was humiliated by the male establishment. “Harvard University refused to award her an honorary degree because, in the words of Charles Eliot, then president emeritus, ‘Credit does not entirely belong to her.’ Eliot assumed that her husband, Pierre, did all her work; so did almost all her male peers. They had no such problems assuming that credit ‘entirely belonged to’ any of the men they wanted to honor.” (p. 114)
Ashton’s work is wide ranging. He writes about the connection between motivation and creation, bringing up Woody Allen’s aversion to the evaluation of others—in particular, the Academy Awards.
He reminds us that “the only thing we do before we begin is fail to begin. … In the beginning, all that matters is how much clay you throw on the wheel. Go for as many hours as you can. Repeat every day possible until you die.” (p. 165)
He warns of the destructive addiction of interruption. “Every five minutes our mind itches for interruption: to stretch, get coffee, check e-mail, pet the dog. We indulge an urge for research, and before we know it we have Googled three links away from where we started and are reminding ourselves of the name of Bill Cosby’s wife in The Cosby Show (it was Clair) or learning what sound a giraffe makes (giraffes are generally quiet, but they sometimes cough, bellow, snort, bleat, moo, and mew.)” (p. 166)
“We may not write symphonies or discover laws of science, but new is in all of us,” Ashton concludes. We just have to begin, persevere, be our own harshest critic, correct our mistakes, work some more, face adversity, work even more, be rejected, continue working…. We can find inspiration in the stories told in this book, but ‘work’ remains the operative word.
The title refers to Wilbur Wright’s comparison of an object being buffeted by wind when it glides to an untrained horse, “darting hither and thither in the most erratic manner.” Wright continues: “Yet this is the style of steed that men must learn to manage before flying can become an everyday sport. The bird has learned this art of equilibrium, and learned it so thoroughly that its skill is not apparent to our sight. We only learn to appreciate it when we try to imitate it.” Or, as Ashton writes, “when we try to fly a horse.” (pp. 58-59)
Ashton introduces us to creative people from many walks of life. “Taken together, the stories reveal a pattern for how humans make new things, one that is both encouraging and challenging. The encouraging part is that there is no magic moment of creation. Creators spend almost all their time creating, persevering, despite doubt, failure, ridicule, and rejection until they succeed in making something new and useful. There are no tricks, shortcuts, or get-creative-quick schemes. The process is ordinary, even if the outcome is not. Creating is not magic but work.” (p. 15)
Ashton debunks some of the myths of creation—for instance, that creators are geniuses or that creators stand on the shoulders of giants. I was especially taken with his analysis of the latter myth. In 1676 Newton famously wrote: “If I have seen further it is by standing on the shoulders of giants.” Robert Merton traced the chain of custody of this phrase. Newton got it from George Herbert, who got it from Robert Hooke, who got it from Robert Burton, who got it from the Spanish theologian Diego de Estella, who probably got it from John of Salisbury, who got it from Bernard of Chartres, 1130. “We do not know from whom Bernard of Chartres got it.” In brief, Newton’s line was “close to a cliché at the time he wrote it.” (p. 120)
But, Ashton argues, “if everybody sees further because they are standing on the shoulders of giants, then there are no giants, just a tower of people, each one standing on the shoulders of another. … We do not see farther because of giants. We see farther because of generations.” (p. 121)
He uses Rosalind Franklin’s research in crystallography (and, most famously, her DNA photography and analysis) to illustrate this point—and to highlight the contributions of a chain of women to science. Since women are still underrepresented, and underpaid, in STEM research—as well as in finance, and since women’s “innate abilities” are often challenged (think of Larry Summers’ infamous hypothesis), I’ll devote a big chunk of this post to Ashton’s discussion of women in science.
“When Rosalind Franklin started analyzing DNA using X-ray crystallography, she was inheriting a technique pioneered by Dorothy Hodgkin, who was inspired by Polly Porter, who was a protégé of Florence Bascom, who broke ground for all women in science, following work by William Bragg, who was inspired by Max von Laue, who followed Wilhelm Röntgen, who followed William Crookes, who followed Heinrich Geissler, who followed Robert Boyle.” And, he continues, “Today, the whole world stands on Rosalind Franklin’s shoulders.” (p. 126)
The women who were critical in laying the groundwork for the discovery of DNA were relegated to “a relative backwater” of science—crystallography—and had to overcome demeaning obstacles to be able to study even that field. Florence Bascom, the first woman to earn a Ph.D. from Johns Hopkins, “had to take her classes there sitting behind a screen so that she would ‘not distract the men.’” (p. 123)
Polly Porter’s parents forbade her to go to school because they didn’t believe women should be educated. She got jobs reorganizing a collection of ancient Roman marble, dusting the laboratory of a crystallographer, and—after the family moved to the United States—cataloguing stones at the Smithsonian and then at Bryn Mawr. It was there that “Florence Bascom discovered her and appealed to Mary Garrett, a suffragist and railroad heiress, for funds so she could study.” In 1914 Bragg won the Nobel Prize, and “crystallography moved from the margins of geology to the foundation of science.” At this point Bascom recommended Porter for a laboratory job with a mineralogist at Heidelberg. She arrived in June 1914, a month before World War I began. “Porter succeeded at her work of learning the art of crystallography despite the difficulties of the war and the depression and distraction of Goldschmidt, and three years later, she earned a science degree from Oxford. She stayed at Oxford, conducting research into, and teaching undergraduates about, the crystals that were her passion until she retired, in 1959. One of her most enduring acts was to inspire and encourage a woman who would become one of the world’s greatest crystallographers and Rosalind Franklin’s mentor: Dorothy Hodgkin.” (p. 124)
James Watson and Francis Crick did not stand on the shoulders of Rosalind Franklin; they stole her work. Franklin took pictures of DNA and analyzed them by hand using a complex mathematical equation. “While [she] was concluding this work, her King’s College colleague Maurice Wilkins showed her data and pictures to James Watson and Francis Crick, without her consent or knowledge. Watson and Crick leapt to the conclusion Franklin was diligently proving—that the structure of DNA was a double helix—published it, then shared their Nobel Prize with their secret source, Wilkins.” (p. 116)
They were not the only men to win Nobel Prizes in science for discoveries made in whole or part by women. “It was the same when Marietta Blau, an unpaid woman working at the University of Vienna, developed a technique for photographing atomic particles. Blau could not get a paid position anywhere, even though her work was a major advance in particle physics. C. F. Powell, a man who ‘adopted and improved’ her techniques, was awarded the Nobel Prize in 1950. Agnes Pockels was denied a college education because she was a woman, taught herself science from her brother’s textbooks, created a laboratory in her kitchen, and used it to make fundamental discoveries about the chemistry of liquids. Her work was ‘adopted’ by Irving Langmuis, who won a Nobel Prize for it in 1932.” (p. 117) And Lise Meitner “discovered nuclear fission only to see her collaborator Otto Hahn receive the 1944 Nobel Prize for her work.” (p. 115)
Even Marie Curie was humiliated by the male establishment. “Harvard University refused to award her an honorary degree because, in the words of Charles Eliot, then president emeritus, ‘Credit does not entirely belong to her.’ Eliot assumed that her husband, Pierre, did all her work; so did almost all her male peers. They had no such problems assuming that credit ‘entirely belonged to’ any of the men they wanted to honor.” (p. 114)
Ashton’s work is wide ranging. He writes about the connection between motivation and creation, bringing up Woody Allen’s aversion to the evaluation of others—in particular, the Academy Awards.
He reminds us that “the only thing we do before we begin is fail to begin. … In the beginning, all that matters is how much clay you throw on the wheel. Go for as many hours as you can. Repeat every day possible until you die.” (p. 165)
He warns of the destructive addiction of interruption. “Every five minutes our mind itches for interruption: to stretch, get coffee, check e-mail, pet the dog. We indulge an urge for research, and before we know it we have Googled three links away from where we started and are reminding ourselves of the name of Bill Cosby’s wife in The Cosby Show (it was Clair) or learning what sound a giraffe makes (giraffes are generally quiet, but they sometimes cough, bellow, snort, bleat, moo, and mew.)” (p. 166)
“We may not write symphonies or discover laws of science, but new is in all of us,” Ashton concludes. We just have to begin, persevere, be our own harshest critic, correct our mistakes, work some more, face adversity, work even more, be rejected, continue working…. We can find inspiration in the stories told in this book, but ‘work’ remains the operative word.
Monday, October 27, 2014
Antonacci, Dual Momentum Investing
In 2012 Gary Antonacci won the Wagner Award for his paper “Risk Premia Harvesting Through Dual Momentum”; the year before he was the runner-up with “Optimal Momentum Investing.” Now, with Dual Momentum Investing (McGraw-Hill) he has given the investing world a first-rate book-length analysis of the two kinds of momentum and how to combine them to beat the market.
For those who think momentum investing is “so 90’s,” Wesley Gray, coauthor of Quantitative Value, sets them straight. In his laudatory preface to the book he quotes Eugene Fama, who, despite the apparent challenge to his efficient market hypothesis, admitted that “momentum is pervasive.” But why is it pervasive, and how can investors capture the momentum anomaly?
Antonacci focuses on the second question but does address the first in a short chapter “Rational and Not-So-Rational Explanations of Momentum.” Let me start there. The rational explanation for why momentum works is that “high momentum profits are compensation for assuming greater amounts of risk.” The “not-so-rational” explanation is that “investors behave unexpectedly and irrationally in systematic and predictable ways.” (p. 36) In a nutshell, “herding/anchoring/ confirmation bias and the disposition effect complement each other and can lead to a unified, behaviorally based concept of momentum-inducing behavior.” (p. 43) If behavioral finance is more or less correct, “momentum lets us profit from human behavioral biases instead of being subject to them in adverse ways.” (p. 44)
All well and good, the reader might say. But we are all familiar with the adage that the trend is your friend--until it ends. How can the investor profit from momentum instead of being swept away by it?
Antonacci has thoroughly researched this question. Most important, he distinguishes between relative and absolute momentum. Relative strength “compares an asset to its peers in order to predict future performance. In academic research, relative momentum is often the same as cross-sectional momentum, which involves sectioning a universe of individual assets into equal segments and comparing the performance of the strongest segments (‘winners’) to the performance of the weakest (‘losers’).” By contrast, when viewed on an absolute or longitudinal basis, “an asset’s own past predicts its future.” (p. 84) Absolute momentum is “a bet on the continuing serial correlation of returns, or, in cowboy terms, absolute momentum says, ‘A horse is easiest to ride in the direction it’s already going.’” (p. 85)
The major weakness of relative momentum investing is that “relative strength does little to reduce downside exposure. Relative momentum may even increase downside volatility.” (p. 84) Absolute momentum, by contrast, not only provides greater downside portfolio protection than relative momentum; it even provides more downside protection than low volatility portfolios do “while preserving more upside market potential. It can also do this without the tracking error, sector concentration, and high turnover issues associated with low volatility portfolios.” (p. 88)
Antonacci’s recommendation is a deceptively simple one: “use absolute and relative together in order to gain the advantages of both. The way we do that is by first using relative momentum to select the best-performing asset over the preceding 12 months. We then apply absolute momentum as a trend-following filter by seeing if the excess return of our selected asset has been positive or negative over the preceding year. If it has been positive, that means its trend is up and we proceed to use that asset. If our asset’s excess return over the past year has been negative, then its trend is down and we invest instead in short- to intermediate-term fixed-income instruments until the trend turns positive.” (p. 89)
This is a dynamic approach to asset allocation, using only stocks and bonds for reasons that the author explains. The model (Global Equity Momentum--GEM) switches between the S&P 500 and the ACWI ex-U.S. based on relative strength momentum and uses aggregate bonds as a safe haven during bear markets based on absolute momentum signals taken from the S&P 500.
Between 1974 and 2013 GEM had an annual return of 17.43%, which soundly trumped relative momentum (14.41%), absolute momentum (12.66%), ACWI (8.85%) and ACWI + AGG (8.59%). Its annual Sharpe ratio was 0.87, in contrast to 0.52, 0.57, 0.22, and 0.28. And its maximum drawdown was 22.72%, as opposed to 53.06%, 23.76%, 60.21%, and 45.74%. “GEM benefited from absolute momentum in 1982, 2001, and 2009, when relative momentum offered no advantage over the market. On the other hand, GEM benefited most from relative momentum in 1986 through 1988 and 2004 through 2007 when stocks were strong and absolute momentum provided no advantage over the market.” (p. 105)
Although GEM is a simple long-term model, it is powerful. Antonacci’s extensive research and his clear-headed thinking have led to a book that every investor should read. The academically oriented reader will be grateful for his occasional excursions into the weeds, his carefully laid-out data, and his lengthy bibliography. The practically oriented investor will find a road map for moving ahead and staying out of really big trouble. And those who enjoy an infusion of humor will laugh at his mini-essay “All Aboard!” that wraps up the main text of book. This one’s a keeper!
For those who think momentum investing is “so 90’s,” Wesley Gray, coauthor of Quantitative Value, sets them straight. In his laudatory preface to the book he quotes Eugene Fama, who, despite the apparent challenge to his efficient market hypothesis, admitted that “momentum is pervasive.” But why is it pervasive, and how can investors capture the momentum anomaly?
Antonacci focuses on the second question but does address the first in a short chapter “Rational and Not-So-Rational Explanations of Momentum.” Let me start there. The rational explanation for why momentum works is that “high momentum profits are compensation for assuming greater amounts of risk.” The “not-so-rational” explanation is that “investors behave unexpectedly and irrationally in systematic and predictable ways.” (p. 36) In a nutshell, “herding/anchoring/ confirmation bias and the disposition effect complement each other and can lead to a unified, behaviorally based concept of momentum-inducing behavior.” (p. 43) If behavioral finance is more or less correct, “momentum lets us profit from human behavioral biases instead of being subject to them in adverse ways.” (p. 44)
All well and good, the reader might say. But we are all familiar with the adage that the trend is your friend--until it ends. How can the investor profit from momentum instead of being swept away by it?
Antonacci has thoroughly researched this question. Most important, he distinguishes between relative and absolute momentum. Relative strength “compares an asset to its peers in order to predict future performance. In academic research, relative momentum is often the same as cross-sectional momentum, which involves sectioning a universe of individual assets into equal segments and comparing the performance of the strongest segments (‘winners’) to the performance of the weakest (‘losers’).” By contrast, when viewed on an absolute or longitudinal basis, “an asset’s own past predicts its future.” (p. 84) Absolute momentum is “a bet on the continuing serial correlation of returns, or, in cowboy terms, absolute momentum says, ‘A horse is easiest to ride in the direction it’s already going.’” (p. 85)
The major weakness of relative momentum investing is that “relative strength does little to reduce downside exposure. Relative momentum may even increase downside volatility.” (p. 84) Absolute momentum, by contrast, not only provides greater downside portfolio protection than relative momentum; it even provides more downside protection than low volatility portfolios do “while preserving more upside market potential. It can also do this without the tracking error, sector concentration, and high turnover issues associated with low volatility portfolios.” (p. 88)
Antonacci’s recommendation is a deceptively simple one: “use absolute and relative together in order to gain the advantages of both. The way we do that is by first using relative momentum to select the best-performing asset over the preceding 12 months. We then apply absolute momentum as a trend-following filter by seeing if the excess return of our selected asset has been positive or negative over the preceding year. If it has been positive, that means its trend is up and we proceed to use that asset. If our asset’s excess return over the past year has been negative, then its trend is down and we invest instead in short- to intermediate-term fixed-income instruments until the trend turns positive.” (p. 89)
This is a dynamic approach to asset allocation, using only stocks and bonds for reasons that the author explains. The model (Global Equity Momentum--GEM) switches between the S&P 500 and the ACWI ex-U.S. based on relative strength momentum and uses aggregate bonds as a safe haven during bear markets based on absolute momentum signals taken from the S&P 500.
Between 1974 and 2013 GEM had an annual return of 17.43%, which soundly trumped relative momentum (14.41%), absolute momentum (12.66%), ACWI (8.85%) and ACWI + AGG (8.59%). Its annual Sharpe ratio was 0.87, in contrast to 0.52, 0.57, 0.22, and 0.28. And its maximum drawdown was 22.72%, as opposed to 53.06%, 23.76%, 60.21%, and 45.74%. “GEM benefited from absolute momentum in 1982, 2001, and 2009, when relative momentum offered no advantage over the market. On the other hand, GEM benefited most from relative momentum in 1986 through 1988 and 2004 through 2007 when stocks were strong and absolute momentum provided no advantage over the market.” (p. 105)
Although GEM is a simple long-term model, it is powerful. Antonacci’s extensive research and his clear-headed thinking have led to a book that every investor should read. The academically oriented reader will be grateful for his occasional excursions into the weeds, his carefully laid-out data, and his lengthy bibliography. The practically oriented investor will find a road map for moving ahead and staying out of really big trouble. And those who enjoy an infusion of humor will laugh at his mini-essay “All Aboard!” that wraps up the main text of book. This one’s a keeper!
Wednesday, October 22, 2014
Two perspectives on failure: How Google Works and Fail Better
Failure has become one of the hottest themes for graduation speeches, blog posts, and self-help books. It is often worn as a badge of honor. But, let’s face it, failing is painful, sometimes even fatal. So how, and under what circumstances, can there be value in falling short?
Let me start with a section from How Google Works by Eric Schmidt and Jonathan Rosenberg (Grand Central Publishing, 2014) entitled “Fail well.” They recall Google Wave, “a technological marvel but a major flop.” It failed well because it created some valuable technology that migrated to Google+ and Gmail. “As Larry says, if you are thinking big enough it is very hard to fail completely. There is usually something very valuable left over.”
We have all heard and have come to believe that a good failure is a fast one, “but one of the hallmarks of an innovative company is that it gives good ideas plenty of time to gestate.” How can we reconcile short-term successes or failures with long-term goals? “The key is to iterate very quickly and to establish metrics that help you judge if, with each iteration, you are getting closer to success. Small failures should be expected and allowed, since they often can shed light on the right way to proceed. But when the failures mount and there is no apparent path to success (or, as Regina Dugan and Kaigham Gabriel put it, when achieving success requires ‘multiple miracles in a row’), it is probably time to call it a day.” (p. 188)
In Fail Better: Design Smart Mistakes and Succeed Sooner (Harvard Business Review Press, 2014) Anjali Sastry and Kara Penn offer techniques for managing projects from their launch through their iteration to build and refine, and finally to embedding the learning.
(For those like me who thrive on the tangential, the book’s title comes from Samuel Beckett’s Worstward Ho—“Try again. Fail again. Fail better.” As the authors note, “Cast as a mantra that turns failure into success, the phrase caught on with tennis players, tech entrepreneurs, and many more, infusing it with an optimism that no literary critic would credit to ‘the twentieth century’s most depressing writer.’” [p. 15])
Fail Better is of course a business book that assumes a team trying to implement a project, so not all of its recommendations are applicable to lone traders and investors. For today’s post I decided to continue with the theme of managing time frames since I think everyone struggles with this issue.
The authors suggest that “we need a systematic method for managing our innovation projects because what looks like a failure at one time scale could actually be a success at another, if you manage things well. Or, it could go the other way: you may scrape together some quick apparent wins and declare an early victory, yet later discover that things are actually worse, when negative side effects subsequently emerge.” (pp. 215-16)
Why, the authors ask, do we get timing wrong so often? Perhaps the major reason is that “people tend to underestimate the effects of nonlinear rates of change. Consequently, they are blindsided by effects that appear to come out of nowhere but are actually the result of compounding processes playing out within the system. A similar tendency is at work when people assume that the future will be similar to the recent past: the normal human tendency is to guess that the future will continue current trends. … For anything that’s cyclical or exponentially growing or declining, this heuristic ensures that you will at some point be wrong—and that you will be dead wrong at those crux moments when rates of change are greatest (peaks and troughs in cyclical markets, for example).” (p. 228)
Both of these books are good reads, and I’ve shortchanged them by zeroing in on a single topic. But I hope that the passages I’ve quoted will inspire you to find ways to fail well in your trading and investing.
Let me start with a section from How Google Works by Eric Schmidt and Jonathan Rosenberg (Grand Central Publishing, 2014) entitled “Fail well.” They recall Google Wave, “a technological marvel but a major flop.” It failed well because it created some valuable technology that migrated to Google+ and Gmail. “As Larry says, if you are thinking big enough it is very hard to fail completely. There is usually something very valuable left over.”
We have all heard and have come to believe that a good failure is a fast one, “but one of the hallmarks of an innovative company is that it gives good ideas plenty of time to gestate.” How can we reconcile short-term successes or failures with long-term goals? “The key is to iterate very quickly and to establish metrics that help you judge if, with each iteration, you are getting closer to success. Small failures should be expected and allowed, since they often can shed light on the right way to proceed. But when the failures mount and there is no apparent path to success (or, as Regina Dugan and Kaigham Gabriel put it, when achieving success requires ‘multiple miracles in a row’), it is probably time to call it a day.” (p. 188)
In Fail Better: Design Smart Mistakes and Succeed Sooner (Harvard Business Review Press, 2014) Anjali Sastry and Kara Penn offer techniques for managing projects from their launch through their iteration to build and refine, and finally to embedding the learning.
(For those like me who thrive on the tangential, the book’s title comes from Samuel Beckett’s Worstward Ho—“Try again. Fail again. Fail better.” As the authors note, “Cast as a mantra that turns failure into success, the phrase caught on with tennis players, tech entrepreneurs, and many more, infusing it with an optimism that no literary critic would credit to ‘the twentieth century’s most depressing writer.’” [p. 15])
Fail Better is of course a business book that assumes a team trying to implement a project, so not all of its recommendations are applicable to lone traders and investors. For today’s post I decided to continue with the theme of managing time frames since I think everyone struggles with this issue.
The authors suggest that “we need a systematic method for managing our innovation projects because what looks like a failure at one time scale could actually be a success at another, if you manage things well. Or, it could go the other way: you may scrape together some quick apparent wins and declare an early victory, yet later discover that things are actually worse, when negative side effects subsequently emerge.” (pp. 215-16)
Why, the authors ask, do we get timing wrong so often? Perhaps the major reason is that “people tend to underestimate the effects of nonlinear rates of change. Consequently, they are blindsided by effects that appear to come out of nowhere but are actually the result of compounding processes playing out within the system. A similar tendency is at work when people assume that the future will be similar to the recent past: the normal human tendency is to guess that the future will continue current trends. … For anything that’s cyclical or exponentially growing or declining, this heuristic ensures that you will at some point be wrong—and that you will be dead wrong at those crux moments when rates of change are greatest (peaks and troughs in cyclical markets, for example).” (p. 228)
Both of these books are good reads, and I’ve shortchanged them by zeroing in on a single topic. But I hope that the passages I’ve quoted will inspire you to find ways to fail well in your trading and investing.
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