Duhigg, The Power of Habit

A new year is right around the corner, and with it will come the usual host of resolutions—sadly, rarely kept. To be more precise, more than 40% of Americans make New Year’s resolutions and just 8% achieve their goals. Sometimes the goals they set are too daunting, sometimes too vague. And, perhaps the biggest problem with the whole resolution business is that people focus on goals rather than processes.

In 2012 Charles Duhigg, a Pulitzer Prize-winning journalist for The New York Times, wrote The Power of Habit, which spent 62 weeks on the paper’s best seller lists and was named one of the best books of the year by The Wall Street Journal and the Financial Times. It is now being reissued with an afterword by the author.

I reviewed the book when it first came out and thought I would write a new post now that I have the reissued edition. But then I reread my original piece and decided that I probably couldn’t improve on it. So instead I’ll republish it here.

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“All our life, so far as it has definite form, is but a mass of habits,” William James wrote in 1892. Well, that might be a bit of an overstatement: a researcher in 2006 knocked that “mass” down to “over 40 percent.” Whatever the percentage, we are creatures of habit. In The Power of Habit: Why We Do What We Do and How to Change It (Random House, 2012) Charles Duhigg explores the work that neurologists, psychologists, sociologists, and marketers have done over the past two decades to figure out how habits work and how they change. It’s a fascinating tale.

So what is a habit anyway and why are habits so important? After we figure out a sequence of actions and practice it sufficiently (Duhigg uses the example of backing out of the driveway), our brain converts that sequence into an automatic routine, a habit, and stores it in our basal ganglia. We no longer have to think about backing out of the driveway; our brain is free to think about something else or to quiet itself. “Habits, scientists say, emerge because the brain is constantly looking for ways to save effort. Left to its own devices, the brain will try to make almost any routine into a habit, because habits allow our minds to ramp down more often.” The brain becomes more efficient; we can devote our mental energy to “inventing spears, irrigation systems, and, eventually, airplanes and video games.” (p. 28)

Most habits are innocuous enough; they don’t make a major difference in our lives. But some habits do, and not always for the better. Moreover, no matter what we do, those bad habits never really disappear; “they’re encoded into the structures of our brain.” The good news is that although old habits never die, they can be “ignored, changed, or replaced.” (pp. 29-30) How? Quite simply, at least in theory: by changing the habit loop of cue, routine, reward.

Ad men figured this out early on. Claude Hopkins, for instance, was responsible for making Pepsodent a sensation at a time when hardly any Americans brushed their teeth; “when the government started drafting men for World War I, so many recruits had rotting teeth that officials said poor dental hygiene was a national security risk.” (p. 39) A decade after the first Pepsodent campaign, more than half the American population brushed their teeth daily and flashed that Pepsodent smile. And they presumably believed that they no longer had that dingy film on their teeth that they could feel when they ran their tongue across their teeth, the cue that Hopkins devised to entice them to brush in the first place. (In fact, the toothpaste did nothing to remove the film, but then ads have never been known for their truthfulness.) So a simple habit loop was formed: cue (tooth film), routine (brushing), reward (beautiful teeth).

What if you already have a habit that you want to change? In that case, “you must keep the old cue, and deliver the old reward, but insert a new routine.” (p. 60) As one of the developers of habit reversal training said, “It seems ridiculously simple, but once you’re aware of how your habit works, once you recognize the cues and rewards, you’re halfway to changing it.” (p. 70) Some people need a support group to reinforce their belief in change, others are fine on their own.

Changing some habits makes very little impact on other parts of a person’s life; keystone habits, by contrast, have ripple effects. They “start a process that, over time, transforms everything.” (p. 87) “They help other habits to flourish by creating new structures, and they establish cultures where change becomes contagious.” (p. 94) Duhigg recalls Paul O’Neill’s fixation with safety when he became CEO of the troubled Alcoa and how “O’Neill’s plan for getting to zero injuries entailed the most radical realignment in Alcoa’s history.” (p. 91)

Keystone habits, which admittedly are difficult to identify and put into practice, create widespread changes because of the principle of small wins. “A huge body of research has shown that small wins have enormous power, an influence disproportionate to the accomplishments of the victories themselves. ‘Small wins are a steady application of a small advantage,’ one Cornell professor wrote in 1984. ‘Once a small win has been accomplished, forces are set in motion that favor another small win.’ Small wins fuel transformative changes by leveraging tiny advantages into patterns that convince people that bigger achievements are within reach.” (p. 96)

One example of what seems for many people to be a keystone habit is exercising. “Typically, people who exercise start eating better and becoming more productive at work. They smoke less and show more patience with colleagues and family. They use their credit cards less frequently and say they feel less stressed. It’s not completely clear why. But for many people, exercise is a keystone habit that triggers widespread change.” (p. 93)

Duhigg extends his analysis to willpower, how retailers predict (and manipulate) habits, how movements happen, and the neurology of free will. But let me stop here and make a couple of off-the-cuff, not especially profound observations.

Traders often repeat the same mistakes over and over, acting on triggers that have served them poorly time and time again even as they continue to expect a tidy profit as a reward. Not only is this insanity, the problem is that they’ve developed a powerfully destructive habit loop. They need to figure out a new routine—and in this case, I believe, contrary to habit reversal theory, either a new, non-monetary reward or a more probabilistic view of the reward.

Beginning traders sometimes feel compelled to swing a big line, and normally they lose big. Just think how many accounts have been blown out. Small wins are powerful levers (and don’t have the downside risk of using too much leverage). “Levers, not leverage”—it has a nice ring to it!

The Power of Habit is chock full of fascinating information—from Michael Phelps’s training regimen to how Target “targets” pregnant women as potential big-time spenders without seeming intrusive. I thoroughly enjoyed it and learned from it. Who can ask for much more? Now on to that next small win. (If you’re intrigued with this topic, you can follow it up with Peter Sims, Little Bets: How Breakthrough Ideas Emerge from Small Discoveries. I admit I haven’t read it yet.)

Amazon associates program is back!

As you may recall, for some time my book reviews looked a lot jazzier than they do now. Each review had a picture of the book’s cover, compliments of Amazon. And if you clicked on the picture and actually bought the book, I got a small referral fee—and it cost you nothing extra. Win, win. Then came the brouhaha over Connecticut sales tax and Amazon shut down the associates program in the state. Now it’s back. Actually, it’s been back for some time, but I just found out about its reincarnation.

I’ve never junked up this blog with ads, but I feel differently about the Amazon program. First of all, it improves the look of the blog. Second, I get a few bucks each month if you have a U.S. Amazon account and either buy a book I reviewed by clicking on its image or if you use the search box on the right-hand side bar and buy anything your heart desires from Amazon. It can be a book, a phone or tablet, towels, skis, pet supplies—you name it. Amazon will thank me each month with a small deposit to my checking account. And I will have another incentive to keep on blogging.

Right now Amazon is running a promotion for a 30-day free trial to Amazon Prime. Here’s the link.

Join Amazon Prime - Watch Over 40,000 Movies

Happy holidays

Faerber, All About Value Investing

I’m not sure why value investing has become such a popular topic. I have reviewed at least half a dozen books on value investing and, to the best of my recollection, not a single one on momentum investing. “Momentum” is a dirty word, associated with burst bubbles, even as it remains a popular strategy with many professional investors. By contrast, value, a concept with an impeccable pedigree, is often touted as an all-seasons strategy, one that doesn’t require keen timing skills and that allows the retail investor to sleep well at night.

Esmé Faerber, a professor of business and accounting at Rosemont College and the author of three previous “All About” investing books, adds to the growing literature with All About Value Investing: The Easy Way to Get Started(McGraw-Hill, 2014). As the subtitle indicates, this book is written for beginners. More experienced value investors should turn to such recent works as Quantitative Value by Gray and Carlisle, The Art of Value Investing by Heins and Tilson, The Manual of Ideas by Mihaljevic, Damodaran’s Investment Valuation, or even his The Little Book of Valuation.

Value investing is neither easy nor mechanical. Faerber takes the reader through the basics: the balance sheet, income statement, and statement of changes in cash. She explains how ratio analysis “uses a company’s financial information to predict whether it will meet its future projections of earnings.” (p. 130) The investor/analyst can use five groups of ratios: liquidity, activity, profitability, leverage, and common-stock related ratios. The value investor also has to assess qualitative factors, such as the company’s competitiveness and the quality of its management.

For those who don’t want to go through this kind of company-by-company analysis, Faerber explains the use of mutual funds, closed-end funds, and ETFs. She rounds out the book with chapters on bonds, preferred stock, and options, rights, and warrants.

All About Value Investing offers a glimpse into a respected style of investing, perhaps enough to whet the reader’s appetite to delve further.

Pike and Gregory, Why Stocks Go Up and Down

William Pike and Patrick Gregory, who have taught investment courses at the college and professional level, have done the would-be retail investor (and even some experienced investors) a great service by writing Why Stocks Go Up and Down, now in its fourth edition. Naturally, the question posed by the book’s title remains unanswered (and fundamentally unanswerable except at the most obvious level of supply and demand). Instead, the authors direct their attention to the various ways a company can raise capital and the metrics that can be used to assess a company’s financial well-being.

This book starts at the very beginning, with the formation of a private company, and explains the ways the company funds itself and some ratios its investors keep an eye on. It then moves on to the IPO process, explaining primary offerings, secondary offerings, public offerings, private placements, and follow-on offerings.

If the company wants to raise additional funds it might consider issuing bonds. The authors ease the reader into this often ill-understood field before proceeding to more advanced topics, such as “call” and “refunding” provisions and covenants. They also describe convertible bonds, preferred stock, convertible preferred stock, and hybrid preferred securities. By the end of this discussion the reader will probably know more about bonds than 75% of retail investors do.

The third part of the book deals with accounting principles necessary to understand a company’s fundamentals. Although the authors explain such concepts as depreciation, cost versus expense, capitalizing assets, and write-offs, their major focus is cash flow. And wisely so, since it is the key metric for many valuational models.

Finally, the authors relate a company’s stock price to its fundamentals, describing a set of commonly used ratios, including price/earnings, price/cash-flow, and price/sales.

Everyone who buys even a single share of stock should be familiar with the material covered in this book. It provides a necessary foundation for becoming an informed investor. Pike and Gregory are to be commended for writing what they describe as “the book you need to understand other investment books.” Or, as I would suggest, the book you need to read (or some of the stuff you need to know) before you commit hard-earned dollars to the markets.

Best books of 2013

Readers often urge me to highlight books I reviewed over the course of the year that I found particularly worthwhile. It’s a holiday tradition on practically every site that either sells or reviews books. So, despite the fact that putting a book on a “best” list is a subjective and intrinsically flawed process, here goes. This year I have chosen six books, presented here in alphabetical order by author.

Fitschen, Keith. Building Reliable Trading Systems (Wiley)

Gray, Wesley R. and Tobias E. Carlisle. Quantitative Value (Wiley)

Li, Junheng. Tiger Woman on Wall Street (McGraw-Hill)

Mihaljevic, John. The Manual of Ideas (Wiley)

Paul, Jim and Brendan Moynihan. What I Learned Losing a Million Dollars (Columbia University Press)

Weatherall, James Owen. The Physics of Wall Street (Houghton Mifflin Harcourt)

Roach, Unbalanced

Stephen Roach, formerly chairman and chief economist of Morgan Stanley Asia and now a senior fellow at Yale, is singularly well equipped to analyze the complex economic relationship between China and the United States. Unbalanced: The Codependency of America and China, forthcoming from Yale University Press, explores the evolution of this relationship, its current fragility, and future opportunities.

Codependency is a psychological term for a relationship disorder, probably most commonly associated with the relationship between an alcoholic and his family and friends. Roach extends it to economics. “The relationship between the U.S. and Chinese economies, with the world’s ultimate consumer locked in a tight embrace with the world’s ultimate producer, exemplifies this syndrome—not just in the cross-border transfer of goods but also in the exchange of financial capital. Two large, dynamic economies, both plagued with unbalanced and unstable tendencies, have become very needy in what they ask and expect of each other. This relationship obviously brings important benefits but there are serious risks. Psychologists warn that codependency ultimately leads to identity crisis, denial of responsibility, and the tendency to blame others for problems. China and the United States manifest most aspects of that mutual pathology.” (p. 250)

Although Roach focuses on codependency, he stresses that “there are no bilateral fixes to multilateral problems.” (p. 127) America’s current account deficit and trade imbalance, for instance, are not “made in China” and hence there is no Chinese “fix” for our economic woes. In 2012 the U.S. “ran deficits with 102 countries—up from 98 in 2011 and 88 in 2010.” (p. 126) China is “the hub of a massive, integrated, pan-regional export machine—in effect, a proxy for a large collection of tightly connected Asian economies that provide low-cost goods to a savings-short U.S. economy. … While China may be the final stop in this chain of production, assembly, and distribution, it is far from the only cog in the global trade machine that the U.S. has come to rely on.” (p. 140)

A theoretical sidebar for those who believe that David Ricardo’s work on comparative advantage and international specialization provides the intellectual underpinning for what Roach calls Globalization 2.0. Roach argues that, although Ricardian trade theory remains a pillar of economic theory and practice, it is not directly relevant to today’s world and that “the simple Ricardian models of exchange between producer and consumer economies [are] largely obsolete.” (p. 117)

Even though the U.S.-Chinese codependency cannot be viewed in isolation, the fact remains that “they suffer similar maladies: they are the most unbalanced major economies in the world today.” And, Roach warns, “no unbalanced economy is ultimately sustainable.” (p. 213) Both countries must undergo structural change. The U.S. should reduce its personal consumption share of GDP (currently at a record high of around 71%); China should reduce its combined share of exports and investments (more than 70% of GDP).

Structural reforms will face stiff resistance in both countries. In China “the national mantra of ‘reforms and opening up’ has been almost exclusively directed at strengthening China’s producer culture.” And the U.S. seems unwilling to stem the excesses of personal spending and false prosperity; consumerism is seen as personifying the American self-image. (p. 216)

Despite the extraordinary difficulties, “rebalancing is the only solution for unstable codependency.” It will “require a coherent framework of action—what might even be called a strategy. China excels at that—America abhors anything that even hints of a plan.” The endgame, as Roach admits, “is anyone’s guess. … [T]he strategic thinking and economic management skills of both the United States and China could ultimately determine whether this transition is both stable and peaceful.” (p. xiii)

Roach offers specific recommendations on how to move toward a stable relationship between the Next China and the Next America. Policy makers should pay heed.

Sander, All About Low Volatility Investing

A 2011 study in the Financial Analysts Journal highlighted, and sought to explain, the seemingly anomalous long-term success of low-volatility and low-beta stock portfolios. The success of these portfolios is anomalous because their high average returns and small drawdowns “run counter to the fundamental principle that risk is compensated with higher expected return.” Over the 41 years between January 1968 and December 2008 a dollar invested in the lowest-volatility portfolio, assuming no transaction costs, increased to $59.55 whereas a dollar invested in the highest-volatility portfolio was worth a mere 58 cents by the end. In real terms, the former produced a gain of $10.12, the latter a loss of more than 90 cents (or 90%). The authors of the study argued that low volatility portfolios outperformed because “exploiting [the anomaly] involves holding stocks with more or less similar long-term returns (which does not help a typical investment manager’s excess returns) but with different risks, which only increases tracking error. So, even though irrational investors happily overpay for high risk and shun low risk, investment managers are generally not incentivized to exploit such mispricing.” And, they concluded, “so long as most of the investing world sticks with standard benchmarks,” the advantage will go to low volatility investors.

Critics will be quick to point out that volatility and risk are not the same. That’s true, of course, but let’s not get tripped up over theoretical distinctions, however important. The fact remains that, for whatever reason—and some would point to the tough uphill climb after large drawdowns, low-volatility low-beta investing has outperformed handily.

Peter Sander’s new book (he has written 39!), All About Low Volatility Investing: The Easy Way to Get Started (McGraw-Hill, 2014), introduces investors to this strategy. He wants it to be accessible to math-phobes and stresses that “informed common sense will help you more than [quantitative models] in making the right decisions.” (p. 84) But the reality is that you can’t write about volatility without describing it statistically. So Sander succumbs even as he maintains that investors need to know concepts and relationships, not formulas. It’s about the thought process, he claims, not the actual measurement.

The second part of the book moves beyond the somewhat tortured “what” of volatility to the “how” of becoming a low volatility investor.

Sander begins at the level of portfolio construction. He suggests building a three-tiered portfolio comprised of foundational, rotational, and opportunistic investments. Low-volatility investments belong to the foundational portion of the portfolio, along with such long-term investments as real estate, trusts, and collectibles. Rotational investments are those that take advantage of business cycles such as sector-specific ETFs. Opportunistic investments/trades include high beta stocks and options. The weightings of these categories of investments will depend on how conservative or aggressive the investor is. A sample tiered portfolio would consist of classic low volatility stocks (30%), low volatility funds (30%), real estate income (10%), inflation hedge (10%), sector funds (5%), inverse/low correlated (5%), strategy funds (5%), and “hot stuff” (5%).

The investor, of course, still has to figure out what stocks and funds to buy to fill out his tiered portfolio. Sander gives some pointers on what to screen for; he suggests that among the core indicators of low volatility are dividends, beta, size, and growth. When all else fails, look at a chart, especially one with Bollinger bands.

Sander’s book is elementary, but for investors intrigued with low volatility investing it’s a decent starting point.

Mauldin & Tepper, Code Red

Extraordinary measures for extraordinary circumstances. But have the central banks overplayed their hands? How, and how quickly, will they be able to scale back their operations? As you might surmise from the book’s title—Code Red: How to Protect Your Savings from the Coming Crisis, John Mauldin and Jonathan Tepper are skeptics.

A little more than half of this book is devoted to explaining (and decrying) current policies. The book is written in laymen’s terms. The authors have, as they say, “written Code Red with cab drivers in mind.” (p. 251) Well, that may be a bit of a stretch. But the prose is engaging, so even if you’re familiar with its macroeconomic themes it’s a good, sometimes ghoulishly funny read.

Then comes chapter eight, entitled “What Will Happen When It All Goes Wrong.” “In theory,” the authors write, “the Fed could reverse its Code Red policies in a second. However, the problems with undoing Code Red policies are all political and practical, not technical.” (p. 210) They foresee a scenario in which the Fed becomes technically insolvent as its starts to wind down its Code Red policies; in fact, they “pretty much guarantee” this outcome. (p. 214) The Fed is leveraged some 59-to-1, having borrowed more than $3.24 trillion and with only $55 billion of equity. Since it pays out its net income every year to the U.S. Treasury, it has no built-up equity. Hence the prediction of a technical insolvency. But, the authors ask rhetorically, “if the Fed is borrowing money from the government and not the other way around, how long do you think the Fed could keep its independence?” (p. 215)

They also suggest that the Fed will be forced to pay ever higher rates of interest on the large excess reserves banks are holding. These banks will then lend out the money again, multiplying it 10 times. “Money growth would surge and create very high levels of inflation.” (p. 220)

How should an investor manage through the bubbles, booms, and busts that central banks create? Enter the investor’s old friend, diversification. The chapter on diversification is introduced with a great quotation from Ray Dalio: “He who lives by the crystal ball will eat shattered glass,” perhaps written in connection with Bridgewater’s All-Weather funds. The authors recommend that the investor build his own all-weather portfolio. To help the investor along, they include a chapter on “commodities, gold, and other real assets.”

If as the Fed unwinds its portfolio the investor is confronted with an inflationary environment, he should own stock in companies that have pricing power. These are companies that have, in Warren Buffett ‘s words, moats around them. Types of moats are: intangible assets, the network effect, low-cost producer, high switching costs, and efficient scale. Taking just one example to illustrate each kind of moat, we have: Disney, MasterCard, Walmart, Oracle, and pipelines.

Mauldin is, as he writes, “long on humanity but short government,” (p. 340) a bias that’s evident throughout the book. Despite this bias (or, others would argue, because of it) Code Red is a worthwhile read.

Wasik, Keynes’s Way to Wealth

John Maynard Keynes was not only a renowned economist, he was an investor. He managed his own money as well as that of King’s College, his friends and family, and insurance companies. As John C. Bogle writes in his introduction to the book, “His spectacular success showed not only his passion for making money, but his growing aversion to losing it. As someone who had gained two fortunes through his trading prowess and lost them through his hubris, Keynes is a stellar example of how an investor can learn, fall on his face more than once, and still come out ahead.” (p. xxxiv)

John S. Wasik explores this investing journey in Keynes’s Way to Wealth: Timeless Investment Lessons from the Great Economist (McGraw-Hill, 2014). Let me start with the rewards of the journey: what Keynes did with his wealth. He bought art as well as rare books and manuscripts. The Keynes collection of rare books, bequeathed to King’s College in 1946, is, according to the college’s web site, “especially strong in editions of Hume, Newton and Locke, and in sixteenth and seventeenth century literature. About 1300 books in this collection have been catalogued on the online catalogue. … Keynes’s collection of manuscripts by Newton, Bentham, John Stuart Mill, etc., is housed in the Modern Archive Centre.” A man after my own heart, but with a bigger budget.

Keynes was a speculator. According to his own definition, “The essential characteristic of speculation … is superior knowledge. We do not mean by this the investment’s actual future yield … we mean the expected probability of the yield. The probability depends upon the degree of knowledge in a sense, therefore it’s subjective. If we regard speculation as a reasoned effort to gauge the future from present known data, it may be said to form the reins of all intelligent investing.” (p. 8)

In 1920 he set up an investing syndicate to trade currencies, both long and short. Initially, he was successful, but then in the space of four weeks the syndicate’s entire capital was wiped out. With the help of a “birthday present” from his father and a loan from a financier Keynes got back in the game and by the end of 1922 was able to repay all of his investors and then some. At that point he decided to add even more volatile commodities to his trading portfolio. “When it came to commodities, Keynes was an absolute data wonk. His documenting of commodity price supplies and fluctuations fills nearly 400 pages of Volume 12 of his collected writings.” (p. 26)

His commodities trading seemed to go well for some time, but then came the stock market crash of 1929 and the attendant collapse in demand for commodities. He lost some 80 percent of his net worth.

“Although Keynes was well known for his arrogance and his air of intellectual superiority, the humbling experience of having nearly lost two fortunes changed his thinking on the best way to invest. The macro view of trying to guess where the economy was moving, and to link currency and commodity trades to those hunches, had failed in a big way. His new focus on confidence, sentiment, and psychology made all of his extensive research into prices, supply/demand ratios, and monetary movement seem irrelevant.” (pp. 48-49)

Keynes became a bottom-up investor, holding concentrated positions in companies that he was familiar with and in whose management he “thoroughly believe[d].” (p. 116) He used leverage; from 1929 to 1945 it “amplified his winnings” (and of course his losses as well), “multiplying his net wealth by a factor of 52.” (p. 118)

As for asset allocation, he was a tactical investor. As he wrote in 1938, “the whole art is to vary the emphasis and the center of gravity of one’s portfolio according to circumstances.” (p. 115) But for the most part he now focused on the long-term profitability of companies. His investment philosophy rested on three principles: (1) “a careful selection of a few investments (or a few types of investment) having regard to their cheapness in relation to their probable actual and potential intrinsic value over a period of years ahead and in relation to alternative investments at the time; (2) a steadfast holding of these in fairly large units through thick and thin, perhaps for several years, until they have fulfilled their promise or it is evident that they were purchased on a mistake; (3) a balanced investment position, i.e., a variety of risks in spite of individual holdings being large, and if possible opposed risks (e.g., a holding of gold shares amongst other equities, since they are likely to move in the opposite directions when there are general fluctuations).” (pp. 111-12)

His principles have certainly had lasting power; they underlie some of the most successful investment portfolios today.

Mallory, The Part-Time Trader

Don’t quit your day job. Instead, Ryan Mallory suggests, join the world of The Part-Time Trader (Wiley, 2014). Mallory himself started as a part-time trader while working in corporate America and then transitioned to being a full-time trader. He also cofounded SharePlanner, a finance trading site that gives real-time trade setups, ideas, and analysis to day traders, swing traders, and position traders—most of them part-timers.

In this book Mallory recounts his time as a dissatisfied “company man” who “added a heap of stress” to his life by trading at work. He himself proceeded by trial and error but eventually came up with a number of “best practices.” He describes how to balance job and trading, how to set up a “workplace trading desk,” how to fly beneath the radar and (critically) maintain monitor privacy. He explains why your best friend is the person who works in IT and how to trade when traveling. He admonishes part-time traders not to be too social.

I assume his advice is sound, although I was never in his position. For most of my working life my Simon Legree boss (me) would never have tolerated such distracting behavior.

In fairness to Mallory, he emphasizes that “you are being paid to perform a set of responsibilities and you should do them well. That goes without saying. … Essentially, what is true about the job that you hold should be the opposite of how you trade. Time-consuming job responsibilities means a trading strategy that requires you to be more hands off with your trading. Less time sensitivity and a job where you have the ability to work at your own pace without daily deadlines or a micromanaging boss allows you to customize a trading strategy that allows for higher-frequency trading.” (pp. 62-63)

Those who are trying to juggle the demands of a full-time job and part-time trading will undoubtedly find useful tips in this book. Mallory is writing from experience.

Ehlers, Cycle Analytics for Traders

John F. Ehlers is probably best known for his MESA (maximum entropy spectral analysis) technical indicators, developed over thirty years ago. He has continued his research in this field and brings traders up to date with his latest book, Cycle Analytics for Traders: Advanced Technical Trading Concepts (Wiley, 2013).

Two types of traders should read this book: those who want to know why things work and those who are looking for new and improved indicators. Since I belong to the former category, I’ll quickly dispense with what probably interests most technical traders—indicators. The book comes with a PIN code to access and copy the EasyLanguage computer code found in the book, some of which is quite lengthy and would be exceedingly tedious to retype. Among the indicators whose code is provided are the decycler, decycler oscillator, band-pass filter, Hurst coefficient, roofing filter, modified (and adaptive) stochastic, modified (and adaptive) RSI, autocorrelation, autocorrelation periodogram, spectral estimate, even better sinewave indicator, convolution, and Hilbert transformer. There is code to compute the dominant cycle using the dual differentiator method, the phase accumulation method, and the homodyne method. There are also indicators for SwamiCharts. (If you don’t know what SwamiCharts are, a quick Google search will fill you in.)

As for the why. Ehlers is careful to explain the principles and the math behind these indicators. But he does more. He reflects on the very nature of the markets themselves. I was particularly struck by his thoughts on the drunkard’s walk hypothesis.

Ehlers begins with the claim embraced by proponents of the efficient markets model that price fully reflects available information. This claim “has been assumed to imply that successive price changes are independent of each other” and that “successive changes are identically distributed. Together, these two hypotheses constitute the random walk model. This model says that the conditional and marginal probability distributions of an independent random variable are identical. In addition, it says that the probability density function must be the same for all time. This model is clearly flawed. If the mean return is constant over time then the return is independent of any information available at a given time.” (p. 70)

In its stead Ehlers proposes a constrained random walk model. I can’t summarize it properly here, but let me highlight a few points that may serve as guideposts. First, “the equation governing the distribution of the displacement of the random walker from his starting point” is the partial differential equation known as the diffusion equation. It can be illustrated by a smoke plume leaving a smokestack, which is akin to the way a trend carries itself through the market. Second, Ehlers modifies the random walk model to allow the coin toss (which determines whether the drunkard takes one step to the left or the right) “to determine the persistence of motion. In other words, with probability p the drunkard makes his next step in the same direction as the last one, and with probability 1-p he makes a move in the opposite direction. … The interesting feature of the modified drunkard’s walk is that as the distance between the point and the time between steps decreases, one no longer obtains the diffusion equation,” but rather a different partial differential equation, the telegrapher’s equation.

The drunkard’s walk solution can thus describe two market conditions. “The first condition, where the probability is evenly divided between stepping to the right or the left, results in the trend mode, described by the diffusion equation. The second condition, where the probability of motion direction is skewed, results in the cycle mode, described by the telegrapher’s equation.” (p. 72)

I trust that this review, however sketchy, indicates that Ehlers’ book would be a very valuable addition to any trader’s library. It encapsulates decades of thoughtful work.

Wilcox & Fabozzi, Financial Advice and Investment Decisions

Financial Advice and Investment Decisions: A Manifesto for Change by Jarrod W. Wilcox and Frank J. Fabozzi (Wiley, 2013) is meant as a wake-up call for individual investors (and, presumably, their financial advisers as well). The book is comprised of thirteen chapters and four appendices. The chapters cover such topics as the extended balance sheet approach to financial planning, properties of mostly efficient markets, growing discretionary wealth, coping with uncertain knowledge, controlling investing behavioral biases, tax efficient investing, matching investment vehicles to needs, active vs. passive strategies, performance measurement, and organizational investment. The final chapter looks at causal feedback loops in society that are affected by financial decision making.

The authors believe that investors have to up their game. First, they should prepare for economic dislocations. Structural factors contributing to our current high unemployment, for example, are “likely to get worse over the longer term”; moreover, “the most important processes involved are strongly nonlinear in their progress.” (p. 255) So people should save to compensate for possible future unemployment or underemployment. Second, odds are that they will live longer, which again means they will need more savings. As the authors write, “[T]echnology is rapidly improving and will likely substitute for not only traditional healthcare but insurance practices. What happens when moderate amounts of life extension become an optional consumption good rather than insurable events? Better start saving.”(p. 258)

Some of the themes of this book have been covered elsewhere (although usually not within a single volume), but other material is new—at least to this reader. Wilcox, for instance, offers a surplus growth model (akin to a neglected model devised by Mark Rubinstein in 1976) which applies the Kelly optimal growth model “not to the investment portfolio” but to “the surplus wealth that could be lost without failing to meet financial obligations.” (p. 85) This intriguing model is described briefly but with some mathematical precision. It maximizes the expected log return of discretionary wealth. “Using only two terms of a Taylor series, and approximating, this amount[s] to maximizing LE – LE²V/2 where L is leverage, E is the expected portfolio return, and V is portfolio return variance.” (pp. 102-103)

On another front, trying to capture the essence of “mostly efficient markets,” the authors write: “If market cycles operated as smooth outcomes of simple feedback loops, they would be subject to anticipation by intelligent speculators, thereby losing their force. In practice, however, the behavior of multiple linked feedback loops is not only complex, but its character may be disguised by frictions—thresholds that must be exceeded before action is taken—that make their operation spasmodic. … Because of the resulting lumpy nature of the actual purchases, the sources of system risk that develop across multiple investors and investments are often obscured. This kind of emergent behavior, whether in terms of small movements of a single security or cataclysms over most of the world’s financial system, can be better understood if we think of its operation through a network of investors.” (p. 51) The authors illustrate properties of investor networks—and network contagion--with simple grid diagrams.

This book is written for the serious retail investor who wants more than the usual financial advice pap. It doesn’t offer stock tips or even the standard fundamental/technical words of wisdom. Instead, it provides a framework within which to make intelligent investment decisions. And a good framework is worth a thousand stock tips.

Howard, The Mortgage Wars

Just when you thought you knew everything there was to know about the meltdown of the mortgage market, along comes The Mortgage Wars: Inside Fannie Mae, Big-Money Politics, and the Collapse of the American Dream (McGraw-Hill, 2014). Timothy Howard, former CFO of Fannie Mae, was in the trenches until the end of 2004. At that time he left Fannie Mae, “along with Fannie Mae’s chairman and CEO Frank Raines, in the wake of allegations by the company’s regulator that [they] had deliberately falsified its financial reports.” A civil case lasting over eight years ensued, with Raines and the author named as individual defendants. The defendants filed motions for summary judgment in their favor, which was granted in the fall of 2012. Thus vindicated, Howard was finally free to tell his side of the story. And a fascinating story it is. Here’s some background.

Fannie Mae was set up in 1938 as a government-owned national mortgage association. In 1954 it became a mixed-ownership corporation, with the U.S. Treasury holding nonvoting preferred stock that was meant to be gradually retired so that Fannie Mae would become a wholly privately owned company. In 1968, as the national debt was approaching $100 billion, “a threshold President Lyndon Johnson desperately did not wish to exceed,” and as “pressures were growing to include Fannie Mae’s then $2.5 billion in borrowings in the debt totals,” it was rechartered. Fannie Mae was split in two—a stockholder-owned company and a new agency, Ginnie Mae. Two years later Congress created the Federal Home Loan Mortgage Corporation (FHLMC), owned and regulated by the Federal Home Loan Banks. “The act did have one noticeable shortcoming: it did not produce a pronounceable acronym for its new offspring. The closest phonetic equivalent to FHLMC, ‘Flummox,’ was out of the question as a nickname. It became known as ‘Freddie Mac’ instead.” (pp. 21-22)

Fannie Mae may have become a shareholder-owned company, but it enjoyed benefits that both created the perception of a special relationship with the U.S. government and lowered the cost or increased the marketability of the company’s securities. As such, it “faced criticism and pressures from three main sources: free-market advocates, actual and potential competitors, and the two principal bank regulators, the Federal Reserve and the Treasury.” (p. 32) But, despite calls for Fannie Mae to sever all ties with the government and become a stand-alone entity, internal studies concluded that such a step would be suicidal. Fannie Mae remained a GSE.

Fannie Mae’s real challenge was interest rate risk. In 1985, when its credit losses were $170 million, it tightened its underwriting standards; by 1993 management “could credibly claim in Congress and elsewhere that [its] management of mortgage credit risk was second to none.” (p. 46)

Criticism, however, was unrelenting—and from a host of powerful adversaries. For instance, “Greenspan and Summers both viewed the GSEs’ federal charters as the antithesis of the free-market principles they cherished. Their shared ideology led them to advocate tighter restrictions on the government-sponsored enterprises while simultaneously seeking to relax regulations on banks—which they considered to be free market entities in spite of the fact that they benefited from federal deposit insurance and a regulator, the Fed, willing to lower their cost of funds by dropping market interest rates whenever they got into difficulty (as banks periodically did).” (p. 105)

The attacks on Fannie Mae only intensified. Howard describes in vivid detail the campaign against the GSEs, as “seemingly credible sources, including the Wall Street Journal,” argued “with … frequency and fervor that the risky GSE’s must be replaced by far safer private-market alternatives.” (p. 148) The private-label mortgage-backed securities market began to flourish. We know where that took us.

Here I’ve merely offered a glimpse into some of the early events and players (there were many) that prompted the mortgage wars and eventually the housing market meltdown and the nationalization of a Fannie Mae that had lost its way. Howard takes the story through to its end, detailing the chain of events with the passion of an aggrieved insider and the precision of a number cruncher. He adds considerably to our understanding of what went wrong and offers suggestions about how we can prevent a reoccurrence. The Mortgage Wars should be required reading for politicians, regulators, and bankers—and all of us who are tasked with keeping them in check.

Durenard, Professional Automated Trading

I’m in over my head with Eugene A. Durenard’s Professional Automated Trading: Theory and Practice (Wiley, 2013), so consider this post more of a notice than a review.

Durenard describes how to set up a framework to research and select trading models and to implement them in a real-time low-latency environment. The book “requires readers to have some knowledge of certain mathematical techniques (calculus, statistics, optimization, transition graphs, and basic operations research), certain functional and object-oriented programming techniques (mostly LISP and Java), and certain programming design patterns (mostly dealing with concurrency and multithreading).”

Durenard focuses on the design of trading strategies as trading agents, the goal being to build “robust trading systems that can gracefully withstand changes of regime.” He introduces swarm systems, which are “aggregate agents that embed various types of switching mechanisms.”

The assumption underlying Durenard’s framework is that markets are complex adaptive systems best understood, and exploited, by an aggregate adaptive agent. This agent has a collection of nonadaptive strategies at his disposal. The agent “is endowed with criteria to choose a subset of behaviors that is expected to produce a positive performance over the next foreseeable future. This is the behavior that the agent implements in real trading. As time unfolds, the agent learns from experience to choose its behavior more effectively. Effectiveness means that as the market goes through various cycles of regime changes, the performance during those change periods does not degrade.”

Durenard draws on concepts from evolutionary theory and learning to endow trading systems with opportunism, robustness, and flexibility. Learning is important because a swarm system needs not only behaviors that have proved effective in the past but also a degree of innovation. The innovation problem is “an active area” of Durenard’s current research.

This book is divided into four parts: strategy design and testing, evolving strategies, optimizing execution, and practical implementation. It offers its fair share of code to help the reader along—unfortunately, not this grossly under-qualified reader.

Birinyi, The Master Trader

Even though he is sometimes derided for being a perma-bull (or in his words, “a redundant bull” [p. 62]), Laszlo Birinyi has a long, proven track record which has earned him the title “a legend.” So the publication of The Master Trader: Birinyi’s Secrets to Understanding the Market (Wiley, 2013) is something of an event.

Birinyi’s investing style is difficult to categorize. He is no fan of technical analysis: “it is not predictive, it is not consistent, and it is not analysis.” (p. 1) And yet his money flows indicator is often included in technical analysis packages. No, no, he argues, money flows are not a technical indicator. “They are the ultimate fundamental input.”(p. 72)

In addition to money flows analysis, which looks at every trade (and, most importantly, the size of every trade) in every stock, Birinyi also uses anecdotal data to inform his trading. Magazines and newspapers, he contends, are “databases in disguise.” (p. 80) He also keeps track of the attitudes of commentators and economists.

And this is just the beginning. It quickly becomes clear that what he’s advocating involves a lot of work. Birinyi concedes the point but counters: “consider a portfolio of $100,000 which hopes to make 10 percent or $10,000. Working as a teacher or administrator or chef, how long would it take to accumulate $10,000? Three months, half a year? Why should you make it on Wall Street in only three days or six weeks?” (p. 196)

Birinyi’s firm crunches numbers relentlessly to analyze, among other things, market cycles, sector rotation, small vs. large stocks, growth vs. value, market sentiment, and the impact of the Fed. As he writes (though in connection with a suggested reading list), “you can never know too much about too many things on Wall Street.” (p. 281) Of course, what you know is more important than how much you know. Birinyi quotes Roland Grimm, former manager of the Yale Endowment, who said, “You have to be careful regarding the railroad analyst who knows how many ties there are between New York and Washington and not when to sell Penn Central.” (p. 244) Moreover, “sometimes too much data is actually a handicap as it incorporates different circumstances. Risk measures, as one example, before the advent of options were a totally different environment.” (p. 248)

In recent years Birinyi’s firm has “found portfolio enhancing opportunities in short-term trading by ignoring or omitting historical data.” And yet, “despite our efforts, we have not been able to develop metrics for shorter periods and have no confidence in others’ efforts to do so either. There is one exception—the next day—and even then only in certain circumstances.” (p. 250)

As for gaps, remember the old rule that large gaps have to be closed? Well, the new rule says that these gaps close only about 25% of the time. Within this number, however, there are tendencies even if no definite answers. “[I]n a world of computerized trading, models, and other mechanized inputs, gaps may provide a significant opportunity for human judgment.” (p. 275)

Times change, markets change, traders and market analysts come and go. But some things remain constant. Over the long haul careful, extensive analytic research combined with keen human judgment will triumph. Laszlo Birinyi’s career illustrates this constancy. The Master Trader details the principles, the studies, and the grunt work that contributed to his investing success over the decades.

Atkeson & Houghton, Win By Not Losing

Nicholas Atkeson and Andrew Houghton, founding partners of Delta Investment Management, have written what, in the words of the lengthy subtitle, is a disciplined approach to building and protecting your wealth in the stock market by managing your risk. Win By Not Losing (McGraw-Hill, 2013) is a mix of stories about some not-so-famous investors (in fact, a few are identified simply by their first names) and an introduction to tactical investing.

The authors contend that “stock prices are influenced by oddities in human behavior that often cause security pricing to be predictable.” (p. 120) They support their contention by sharing some of their observations from the trading floor of an investment bank. Earnings momentum, for instance, can be both predictable and profitable: “the cycle of exceeding analysts’ estimates is often predictable in light of the pressures on analysts to be overly conservative.” (p. 121) And one study found that “over the 60 trading days after an earnings announcement, a long position in stocks with unexpected earnings in the highest decile, combined with a short position in stocks in the lowest decile, yields an annualized ‘abnormal’ return of about 25 percent before transaction costs.” (p. 122)

It’s all very well and good to analyze individual stocks, but the overall market environment should be of paramount concern to the investor. The authors suggest that a person should be a tactical equity investor if he believes that “there is a reasonable probability the stock market will experience a period of severe depreciation during your investment horizon” and/or “there is a reasonable probability the stock market will not experience sufficient appreciation during your investment horizon to meet your investment objectives.” (p. 177)

The authors note that the risk-conscious tactical investor has a fairly narrow window in which to make decisions because “evaluations of market risk levels tend to be most accurate over a week to a month.” (p. 180) They recommend entering the stock market when “the perceived market risk is moderate and declining.” (p. 196) Their own favorite indicator is the 75-day simple moving average applied to a group of roughly 3,600 stocks. “When the majority of stocks in the market are trading above their 75-day moving average, the market is bullish. When the majority of stocks are trading under this level, the market is bearish.” (p. 199) (They publish a free weekly Market Sentiment Indicator report on their website; it also appears in Barron’s.)

One of the authors’ recommendations is that an investor should be aggressive when participating in up markets. One way to accomplish this is to boost the beta of the portfolio. If investors “were willing to accept portfolio volatility equal to the market, they could then increase their expected volatility during times they are invested in equities, as the higher in-the-market volatility would be offset by the lower out-of-the equity market volatility. These investors could raise the in-the-market portfolio beta to a level at which the average of in-the-market and out-of-the-market volatility is equal to the market volatility on its own.” (p. 206)

Winning By Not Losing is not for the rank novice, but anyone with some experience in the stock market, especially the person who wants to move beyond a buy and hold strategy, can find useful tidbits in this book.

Li, Tiger Woman on Wall Street

Junheng Li has written a smart, compelling book. Tiger Woman on Wall Street: Winning Business Strategies from Shanghai to New York and Back (McGraw-Hill, 2014) moves seamlessly between autobiography and analysis to create a finely chiseled portrait of the often shadowy Chinese business world. It’s an important read for anyone interested in investing in China—or in companies that have a Chinese presence.

Li grew up in Shanghai under the early tutelage of a harsh (what Westerners would call abusive) tiger dad. He forced her, for instance, to kneel on a washer board for more than an hour while he drilled her on the multiplication tables and slapped her when she gave the wrong answer or was slow to reply. She was three years old at the time. But, as she writes, “His high standards for me were just part of his language of love that got lost in translation.” (p. 10)

Li left Shanghai in 1996 to attend Middlebury College and subsequently to pursue a career as a Wall Street analyst. She now runs the independent equity research firm JL Warren Capital, aimed at plugging the gap between the business reality in China and American investors. If this book is any indication, the firm is doing a first-rate job.

The depth of analysis that Li offers is something that no individual investor could possibly match. She has both keen analytical skills and a familiarity with the Chinese business environment (as well as many useful contacts in China). So investors should take her caveats to heart. Consider, for example, the fact that most private Chinese companies “spend a far lower portion of their revenue on R&D than American peers in the same sector.” The reason? “In industries where innovation drives growth and market share, such as technology and healthcare, China’s culture of lawlessness hinders innovation. If you create something commercially compelling, it is nearly guaranteed that others will copy it and undercut your pricing.” (p. 148)

Trying to assess the value of a business in China is a major challenge. Sometimes companies fudge their numbers. Even when they are honest in their reports (and most publicly traded companies by now are), normal valuational methods often don’t apply. “Most value investors depend on what’s called a ‘mid-cycle analysis’ to assess the normalized earnings power before ascribing a value to a business. … To get that estimate, analysts look at the successive peaks and troughs in a company’s earnings and adjust them to a moving average. But for both Chinese companies and China’s economy, mid-cycle references do not exist. Since the introduction of the market reform in 1979, the Chinese economy has only gone up, never down. Whenever the economy showed signs of slowing down, the government stepped in with fiscal stimulus and expansionary monetary policy.” (pp. 188-89)

Chinese corruption is a well-known fact. Li believes that “a big portion of government-led infrastructure spending in 2008 trickled out in the form of bribery, embezzlement, and kickbacks, all of which went to the connected and enfranchised. Interestingly, shortly after Beijing released its massive stimulus package, Macau casino stocks began to soar, led by those companies with the most exposure to VIP gamblers from the mainland.” (p. 155)

I’ve just scratched the surface of the material that Li covers in this book. Tiger Woman on Wall Street offers carefully honed analysis even as it tugs at your heartstrings. I would say that it’s one of the best investing books of 2013 (except that it has a 2014 copyright).

Hirsch, Stock Trader’s Almanac 2014

This year’s Stock Trader’s Almanac, its forty-seventh annual edition, has a new look, at least on the outside. Although it is still spiral bound, it now sports a maroon soft cover with gold embossed lettering and golden spirals.

The inside remains pretty much the same, with a calendar section, a directory of trading patterns and databank, and a strategy planning and (somewhat abbreviated) 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 63 years), and the January barometer since 1950 in graphic form. 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.

As we all know, 2014 is a midterm election year, but what does this mean for investors? Jeffrey A. Hirsch, co-editor of the Almanac, writes that “midterm elections have a history of being a bottom picker’s paradise. In the last 13 quadrennial cycles since 1961, 9 of the 16 bear markets bottomed in the midterm year. … [T]his has provided excellent buying opportunities. … From the midterm low to the pre-election year high, the Dow has gained nearly 50% on average since 1914.” Hirsch anticipates “a good hunk of the next major downturn to transpire in 2014” with a low in the DJIA 12,000 range likely.

We are now in the market’s “magical” quarter where gains over the years have been the greatest and the most consistent. If we take the S&P 500 as our benchmark, it has delivered an average return of 4.0% in the fourth quarter (1949-2012). Compare that to 2.3% for the first quarter, 1.6% for the second, and 0.6% for the third. Looking at the fourth quarter in the context of the presidential cycle, post-election results have averaged 3.1%, midterm a whopping 8.0%, pre-election 3.0%, and election a meager 1.9%.

For those traders who are interested in intra-day trends, the Almanac divides the trading day into half-hour segments and tracks the percentage of time the Dow closed higher in a given half hour than it did in the previous half hour. The positive half-hour segments between 1987 and May 2013 began at 10, 11, 11:30, 12:30, 1, 1:30, 3, 3:30, and the close, with the strongest performances coming from the close, 3 p.m., and 10 a.m. On a daily basis, since 1990 Tuesday has produced the strongest gains although, since the March 2009 bottom, Thursday has taken over the honors.

Investors who appreciate the power of seasonals and who believe that past is prologue will, as usual, relish this Almanac.

Runciman, The Confidence Trap

As we seem to lurch from one self-inflicted crisis in Washington to the next some people begin to despair. Is American democracy itself on the brink? Is democracy inherently flawed? In The Confidence Trap: A History of Democracy in Crisis from World War I to the Present (Princeton University Press, 2013) David Runciman highlights the tension between “the onward march of democracy” and the “constant drumbeat of intellectual anxiety.” Today, as the established democracies face four fundamental challenges—war, public finance, environmental threat, and the existence of a plausible competitor—“it is not clear,” Runciman writes, that they “are doing well in meeting any of them.”

Democracies have certain advantages over their rivals. For instance, they are better at surviving crises. At the same time, they seem unable to learn how to avoid crises. “It is some consolation in a democracy to know that nothing bad lasts for long,” but “consolation can produce its own kind of complacency. Knowing that they are safe from the worst effects of hubris can make democracies reckless—what’s the worst that could happen?—as well as sluggish—why not wait for the system to correct itself? That is why the crises keep coming.”

Starting with Tocqueville as “the indispensable guide to the ongoing relationship between democracy and crisis,” Runciman examines seven crises: 1918 (false dawn), 1933 (fear itself), 1947 (trying again), 1962 (on the brink), 1974 (crisis of confidence), 1989 (the end of history), and 2008 (back to the future).

Throughout Runciman illustrates versions of what he calls the confidence trap. For instance, it is too soon to act and it is never too soon to act. This tension was manifest in the opposing views of Sarkozy and Merkel during the Euro crisis: Sarkozy urged immediate action, Merkel believed that it was important not to be rushed.

Politicians can point to history as a rationalization for their bad behavior. “American democracy had survived its near-death experience in 1933. It had survived everything that had been thrown at it since. It had proved its adaptability and its resilience. There is less incentive for politicians to compromise if they believe the system can withstand most forms of confrontation.” (p. 284)

“This,” Runciman writes, “is the confidence trap. Democracies are adaptable. Because they are adaptable, they build up long-term problems, comforted by the knowledge that they will adapt to meet them. Debt accumulates; retrenchment is deferred. Democracies are also competitive, which means that politicians will blame each other for their failure to tackle the long-term problems. However, they do it in a way that gives the lie to the urgency, because if it were truly urgent, then they would compromise to fix it. Instead they squabble. … So democracy becomes a game of chicken. When things get really bad, we will adapt. Until they get really bad, we need not adapt, because democracies are ultimately adaptable. … Games of chicken are harmless, until they go wrong, at which point they become lethal.” (p. 285)

Scaremongers argue that profligate spending is pushing the U.S. to the point of a full-scale default. Not so, Runciman replies. “The institutional constraints on sustained fiscal irresponsibility would kick in before then. The real problem is not that the United States will knowingly walk off a cliff. It is that no one knows where the edge of the cliff is, or which of the intermediate ridges along the way—the lesser ‘fiscal cliffs’—pose real danger.” … The U.S. may “get itself into more trouble than it realizes because it will be unable to tell apart the point when deferring retrenchment keeps its options open from the point when deferring retrenchment closes them down. Credible systems, like credible banks, can find they lose credibility quickly and unexpectedly.” (pp. 312-13)

Runciman uses dialectical tension to strike an appropriate balance between optimism and pessimism. He opts not to assume that we will eventually encounter the crisis that overwhelms us. He refuses to see politics as inherently tragic; democracy “is too inadvertently comical for that.” (p. 324) At the same time, he believes that democracy is a series of mismatches, that it displays a repeated pattern of crisis and recovery. “The long-term strength of democracy comes from its short-term restlessness; it is also at risk of being undermined by its short-term restlessness.” Put in the most general of terms, “democracies succeed because they fail and they fail because they succeed. There is no way around this.” (p. 304)

Katsman, Retirement GPS

Aaron Katsman’s Retirement GPS: How to Navigate Your Way to a Secure Financial Future with Global Investing (McGraw-Hill, 2013) offers a look at how to invest in foreign stocks and bonds. Even if you don’t agree with the author’s recommendation that 50% of a retirement portfolio be allocated to international stocks and bonds (being more tactically inclined, I personally am uneasy with such fixed allocations), you can still profit from some of his tips.

The GPS portfolio is based on macro events and macro trends. In deciding whether to invest in a particular country, Katsman asks such questions as whether it has a stable political climate, economic freedom, a young population and a growing middle class, a projected GDP growth with lower inflation for the following year, and a diversified economy. The countries that shine right now in these respects are the Asian Tigers (Hong Kong, South Korea, Taiwan, and Singapore), Australia, ASEAN (Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam), Colombia, Peru, Israel, and Turkey.

As to investing in global bonds, Katsman points out that over 15 years (ending in 2011) a hedged global bond portfolio, one which tries to neutralize the impact of currency swings, had returns very similar to those on U.S. bonds but with less volatility. Mind you, the cost of currency hedging can be quite steep.

Most investors are probably reasonably familiar with global stocks and how to access them. International bonds are more of a mystery. The retail global bond investor has three basic alternatives: individual bonds, bond funds, and ETFs. Unless an investor has a very large portfolio, the first alternative is not practical. So on to alternative two. The investor who opts for a mutual fund will be subject to fees that can eat into returns. Moreover, unlike individual bonds, there is no guarantee of principal in a bond fund. And, of course, it’s important to monitor the fund manager. As for ETFs, passive emerging market or global bond funds are flawed because passive investment simply does not work in fixed income, especially in emerging markets; “most of the bonds in the index are not available to be bought.” (p. 128)

Katsman’s book meanders into some unexpected byways, such as crowd funding, that probably wouldn’t figure in most portfolios. And he veers away from the main theme of the book when he advocates for financial advisors (yes, he is one of them). But even if this book lacks the rigor of most mainstream investing books and leaves many questions unanswered, it offers some useful advice. The reader can fill in the gaps elsewhere.

Yanofsky, The Outer Limits of Reason

If you’re looking for a refreshing break from the usual investing/trading fare, let me recommend Noson S. Yanofsky’s The Outer Limits of Reason: What Science, Mathematics, and Logic Cannot Tell Us (MIT Press, 2013). Written for the layman, it explores the realm of the unsolvable, unprovable, and unknowable. Some (perhaps even most) of the material will be familiar, but Yanofsky offers a compelling synthesis of various “outer limits” problems.

Some computing challenges are staggering—that is, practically unsolvable, even if not theoretically impossible. For instance, Euler may have solved the seven bridges of Königsberg problem with sheer brain power, but solving the traveling salesman problem for 100 cities—assuming that our computer can check a million routes in a second—would take 2.9 * 10¹⁴² centuries! Splitting a hundred numbers into two sets to see if the sum of one part equals half the sum of all the elements would take a mere 401,969,368,413,314 centuries. And trying to predict with any degree of precision an event in a chaotic system, or a complex adaptive system, is a pretty hopeless undertaking; it’s not even a question of time or computer power. (Just ask any trader.)

Many problems, such as the halting problem or the tiling problem, are undecidable—at least by computer logic. Often these problems suffer from some form of self-referential limitation. Think of time-travel paradoxes, Russell’s paradox, Gödel’s first incompleteness theorem or my personal stroll-down-memory-lane favorite (I guess because, when I was first introduced to logic, I learned a new word in the process) the heterological paradox. In fact, Yanofsky writes, “the universe is the ultimate self-referential system; the universe uses scientists to study itself.” (p. 343)

Other problems stem from the chasm between the describable and the indescribable—the former countably infinite, the latter (presumably) uncountably infinite. That is, “there is no longest word or longest novel, because there is no limit to the longest formula, and so on. This makes language infinite. However, it can be alphabetized or counted, which makes language countably infinite. … It is plausible to say that there is an uncountably infinite number of phenemona that can occur. This is stated without proof because I cannot quantify all phenomena. To quantify them, I would have to describe them and I cannot do that without language.” (p. 175)

Yanofsky doesn’t break new ground in this book, but he offers a “one-stop” emporium for those who enjoy pondering the limits of reason. I had a grand time reading it.

Mihaljevic, The Manual of Ideas

John Mihaljevic is a managing editor of the prestigious monthly journal for value-oriented investors The Manual of Ideas. Hence the title of as well as a major resource for this book, The Manual of Ideas: The Proven Framework for Finding the Best Value Investments (Wiley, 2013).

Even if you yawn at the very thought of yet another book on value investing you owe it to yourself to give this manual a try. It is a serious, thoroughly researched work that draws on interviews with top value investors, quantitative screens, and good old-fashioned qualitative analysis. It offers not only principles but actionable advice. And it reads well. In brief, its value far exceeds its price ($25.99 hardcover on Amazon).

The book covers a range of value investing styles and opportunities: deep value, sum-of-the-parts value, Greenblatt’s approach, jockey stocks (i.e., investing in companies with great management), following superinvestors, small- and micro-cap stocks, special situations, equity stubs, and international.

Let’s say that you want to track superinvestors. Mihaljevic offers some caveats when it comes to choosing whom to follow. These caveats should be fairly obvious, but investors often overlook them when looking for investment ideas, so they’re worth repeating. For instance, you should take into account portfolio turnover. Since a fund has to file a 13F-HR only quarterly and there is on top of that a 45-day filing delay, “the higher the turnover of a superinvestor’s portfolio the higher the chance that an investor is considering selling an equity by the time we consider buying it.” And if a superinvestor engages in a lot of short selling, “we cannot be sure whether a long position represents a high-conviction call on the merits of a specific investment or whether it simply represents the long side of a pair trade.” (pp. 161-62)

Mihaljevic lists some of his favorite superinvestors along with their CIK (Central Index Key) numbers, used when searching SEC filings. He also gives tips on how to track a handful of top investors who do not file 13F-HR forms with the SEC.

Those who are interested in investing in small cap stocks will find useful screens and, more importantly, ways to go beyond these “crude tools for finding interesting ideas.” (p. 197) The book offers, for instance, methods for deciding whether a fallen angel will fly again and for uncovering hidden inflection points. It encourages investors to ask whether a company passed the right screen for the wrong reason, whether the financial statements raise any red flags, who has been buying and selling the shares, what management’s attitude is toward outside shareholders, and where the shares are relative to their historical range.

For those with nerves of steel, an appreciation of the often destructive power of leverage, and a keen sense of risk management, equity stubs “can be one of the most rewarding pieces of a portfolio.” (p. 239) Successful investing in equity stubs requires sound judgment and experience. Even then, “due to the lopsided payoff in leveraged equities, the probability of winning on any one investment may be well under 50 percent.” (p. 264) For those determined to pursue this area of value investing, Mihaljevic suggests that “industry-wide sell-offs represent better hunting grounds for potential opportunities than do company-specific crises.” (p. 265)

An “intra-text” note from this reviewer who watched, and thoroughly enjoyed, the documentary “Note By Note: The Making of Steinway L1037”: As readers probably know, John Paulson recently bought Steinway, which Mihaljevic describes as a classic case of a company that “saw no urgency to unlock shareholder value.” Although “the renowned piano maker … also owns a band instruments business and valuable real estate in New York, … investors who bought Steinway shares based on a sum-of-the-parts appraisal would have witnessed years of inaction on monetizing real estate.” (p. 61) Well, if it takes about a year to make a piano, perhaps we can understand the frustratingly snail-like pace of Steinway’s board.

The Manual of Ideas is a book I can highly recommend to retail and institutional investors alike or, to slice the investing world another way, to beginners as well as old-hands. It has something to say to every investor, even those who don’t consider themselves true value investors.

Focardi, Fabozzi, and Bali, Mathematical Methods for Finance

Mathematical Methods for Finance: Tools for Asset and Risk Management by Sergio M. Focardi, Frank J. Fabozzi, and Turan G. Bali (Wiley, 2013) may have chapter titles that sound like a math department’s course offerings, but this book is no substitute for actually taking the courses. The reader is not about to learn differential calculus in 30 pages or matrix algebra in 26 pages. And the two concluding chapters on stochastic calculus are definitely not for those who opted to round out their college schedules with the history of art instead of math. The authors may claim that “there is no prerequisite mathematical knowledge for reading this book,” but without some pretty extensive math background (or an extraordinary ability to grasp mathematical concepts intuitively) the reader’s understanding of the text will be minimal. Prospective readers looking for a crash course should understand that they won’t go from 0 to 60 in 300 pages.

Since the authors are trying to cast a wide net they explain key concepts in each field. For instance, the differential calculus chapter discusses the notion of limit, the essentials of limit theorems, the common definitions linking relevant conditions to limits of functions and sequences, the concept of continuity and total variation, differentiation and commonly used rules for computing first-order derivatives, computing second-order and higher-order derivatives, the chain rule, and the Taylor series expansion. The reader whose grasp of calculus is firm, or the reader who just needs a quick refresher course, will then learn a couple of applications of derivatives in bond portfolio management.

For many who would like to understand the quantitative side of modern finance this book serves as a daunting to-do list. Probability in finance, for example, is not the kind of probability used by poker players (and taught in beginning probability courses). Poker players don’t have to worry about fat tails and Hermite polynomials, quants do. Poker players can win big without ever having seen an integral, quants can lose millions/billions for their firms if they don’t understand integrals inside out.

Even though the book spends far more time on mathematical concepts than on applications, Mathematical Methods for Finance is still a good reference book for those who want to move from the math of the academy to the math of Wall Street. A primer, however, it’s not.

Greenblatt, Breakthrough Strategies for Predicting Any Market,2d ed.

The first edition of Jeff Greenblatt’s Breakthrough Strategies for Predicting Any Market: Charting Elliott Wave, Lucas, Fibonacci, Gann, and Time for Profit appeared in 2007. Since that time Greenblatt came to embrace the work of W. D. Gann. He also found that Alan Andrews’ median lines served as “an excellent GPS system in order to understand how trends evolve.” The second edition (Wiley, 2013) thus includes new chapters on Gann, Andrews, and median channels. It also addresses market sentiment/psychology.

Greenblatt is the director of Lucas Wave International and editor of The Fibonacci Forecaster. And who was Lucas, you might ask. (Well, at least I did.) Edouard Lucas (1842-1891) was a French mathematician who invented the famous (some might say infamous) Tower of Hanoi puzzle. He also studied number sequences, most notably the Fibonacci sequence. The closely related number sequence (2, 1, 3, 4, 7, 11, 18, 29, …) is named after Lucas.

But back to the book.

Breakthrough Strategies focuses on chart reading, the idea being to wean traders away from a reliance on lagging indicators and to introduce them instead to the kind of pattern analysis/recognition that can serve as a forecasting tool. By pattern recognition Greenblatt doesn’t mean simply finding double tops or ascending triangles. He is looking for quantifiable patterns. He counts bars in search of cycles, squares time and price, calculates Fibonacci retracements and extensions.

He takes the reader chart by chart (some of them pretty difficult to decipher amid all the lines and numbers) to illustrate the various techniques he uses. The idea is to build up a repertoire of methods that are objective, not subjective. Of course, in trading nothing is purely objective. Just because a Gann calculation agrees with some Fibonacci level doesn’t mean that the trader has an objective signal. An Andrews channel in conjunction with another Fibonacci level might offer up a competing signal. Moreover, even when all the stars align the results may be disappointing, as Greenblatt readily admits.

So who can profit from this book? Certainly not a beginning trader; it’s far too complex for someone just getting his feet wet. Not the minimalist who likes clean charts. And, of course, not the person who thinks that all this old stuff is so much voodoo. Greenblatt is unlikely to win converts to his cause with this book. But for the trader who is using any of these strategies and is looking for a way to complement them (especially for those who might contemplate adding Gann to their quiver), Greenblatt’s book is a helpful guide.

Markowitz, Risk-Return Analysis, vol. 1

Harry M. Markowitz, now in his mid-80s, has embarked on a four-volume series entitled Risk-Return Analysis, of which this volume, The Theory and Practice of Rational Investing (McGraw-Hill, 2013), is the first.

Most of us grew up with modern portfolio theory, first enunciated in a 1952 journal article and later proclaimed to be the beginning of modern finance. Brokerage firms provided clients with graphs showing optimal portfolios that offered the highest expected return for a given level of risk, achieved largely through diversification, and investors who wanted to sound knowledgeable threw around the phrase “the efficient frontier”. Modern portfolio theory seemed to work pretty well for decades. But then came the financial crisis, and critic after critic began sounding the death knell for MPT.

Markowitz’s response is masterful. He doesn’t launch a frontal attack on his critics. (Well, here and there he does let loose. For instance, on p. 72 he writes that “the persistence of the Great Confusion—that MV [mean-variance] analysis is applicable in practice only when return distributions are Gaussian or utility functions quadratic—is as if geography textbooks of 1550 still described the Earth as flat.”) Instead, for the most part he invites them to understand just what it is he is saying (which is different from what they are criticizing). This exercise involves a lot more than catch phrases and graphs. Moreover, he explains where and how his own thinking has evolved over the decades.

The result is a book that every finance professional should own. Serious retail investors who are not afraid of a little statistically related math will also be rewarded intellectually, perhaps financially as well. But, casual reader beware, this book is not one that I would describe as a good read.

The book is divided into five chapters: the expected utility maxim, mean-variance approximations to expected utility, mean-variance approximations to the geometric mean, alternative measures of risk, and the likelihood of various return distributions.

Perhaps the most fundamental mistaken notion about MPT that Markowitz has sought to dispel over the years, the one that he addressed in the passage I quoted above, is that mean-variance analysis should not be used if distributions are not normal. Markowitz explains that this criticism is misguided because he bases his “support for mean-variance analysis on mean-variance approximations to expected utility.” (p. 34)

Why, some might ask, “if one believes that action should be in accordance with the maximize EU rule, … seek to approximately maximize it via a mean-variance analysis? Why not just maximize expected utility?” (p. 41) One very important reason is that “the only inputs required for a mean-variance analysis are the means, variances, and covariances of the securities or asset classes of the analysis.” The formula for the expected return of a portfolio, according to this analysis, “is true whether or not returns are normally distributed, or even symmetrical, and whether or not the return distributions have ‘fat tails’….” (pp. 42-43)

In this book Markowitz also assesses competing risk measures (variance, mean absolute deviation, semivariance, value at risk, and conditional value at risk). His findings are provocative and, I’m sure, will elicit fervent rebuttals from proponents of these risk measures.

The Theory and Practice of Rational Investing is an important work, inviting academics and finance professionals to take a second look (or perhaps a first genuine look) at modern portfolio theory and thereby more fully understand its foundations, tenets, and consequences.

Conrick and Hanson, Vertical Option Spreads

What can two guys from North Dakota tell us about vertical option spreads that we don’t already know? Even if we disregard the tongue-in-cheek geographical slur (and I feel comfortable making it because for a few years I had family ties to North Dakota), the question is misdirected. Vertical Option Spreads: A Study of the 1.8 Standard Deviation Inflection Point by Charles Conrick IV and Scott Hanson (Wiley, 2013) is more about developing a probabilistic trading strategy than about the nuts and bolts of vertical spreads. Which makes it a more interesting book than its generic title would indicate. There are also bonanzas for those who buy the book: a 180-day free trial of Oracle’s pricey Crystal Ball (an Excel add-in for predictive modeling, forecasting, simulation, and optimization) and the authors’ “Amazing Spreadsheet.” In this book they explain in detail how to use both.

Using S&P weekly returns from 1928 to 1989 and its ETF tracker SPY, the authors discovered a window of opportunity. “The area between plus or minus 1.0 and 2.0 standard deviations from the mean return is, in effect, an exact negative of what the normal distribution would predict!” (p. 107) Between plus 1.0 and minus 1.0 standard deviations from the mean there are about 13.2% more data points, between plus or minus 1.0 and 2.0 standard deviations 13.2% fewer data points.

Armed with this statistical information and Crystal Ball’s tools, the authors devised a profitable trading strategy using weekly SPY credit spreads and iron condors. Even though the strategy handily beats the index, it is not wildly profitable, which lends credibility to it.

Despite having probability on their side, the authors are not pure system traders. For example, if there is an upcoming Fed meeting they may trade further out than normal or just stay out of the market until after the announcement. “There is no reason to get into a trade just because you feel compelled to do so. Use good judgment, and make sure all the edges are in place.” (p. 234)

Some of the authors’ trading practices are questionable, which means that this is not the best book for someone who is just starting out in options. There are better places to learn how and when to open and close trades, what brokers to use, and how to manage risk. But for someone who is trying to exploit “improbabilities,” it is a good case study. That you get to play with Crystal Ball for 180 days is icing on the cake.

Graham and Emid, Investing in Frontier Markets

Whatever your take on the global markets, especially viewed against the backdrop of Federal Reserve policy, you need to understand the range of products that are available. Investing in Frontier Markets: Opportunity, Risk and Role in an Investment Portfolio (Wiley, 2013) by Gavin Graham and Al Emid introduces readers to one of the least understood asset classes.

For starters, it’s important to define emerging markets as a whole and then to isolate the frontier markets subset. Emerging markets are defined as those countries with a GDP per capita of less than $12,476 that are included in the MSCI Emerging Markets Index. Frontier markets “are investable but have lower market capitalization and liquidity, or more investment restrictions than the more established emerging markets, or both.” (p. 3) Forty countries are included in both the MSCI and S&P frontier market indices—eleven from sub-Saharan Africa, five from Asia, ten from Eastern Europe, six from Latin America, and eight from the Middle East and North Africa. To give a sense of what countries are considered frontier markets, the Asian representatives are Bangladesh, Kazakhstan, Pakistan, Sri Lanka, and Vietnam. The Latin American countries are Argentina, Colombia, Ecuador, Jamaica, Panama, and Trinidad and Tobago.

Why invest in frontier markets? The key benefits, the authors contend, are “diversification, a low correlation with developed markets and the strong likelihood of frontier markets mirroring the development path followed by longer-established emerging markets, thus delivering strong returns to investors with long-term horizons.” (p. 2)

There are reasons to be cautious about investing in frontier markets, however, most notably their recent returns. In the five years ending August 2012 frontier markets have significantly underperformed emerging markets: -9.83% per annum versus -0.07% per annum. Over a ten-year period they returned 8.33%, whereas emerging markets returned 15.35%.

Frontier markets also exhibit high volatility, in part because “there are no, or very few, … institutional investors to offset capital flows generated by individuals and foreign investors.” (p. 75) But high volatility does not imply high portfolio risk because “frontier markets not only have low correlation with developed and emerging markets but very low correlations with each other.” (p. 74)

Let’s say that you would like to invest in frontier markets. What’s the best way to go about it? There are (in order of popularity) global frontier market funds, ADRs, individual equities in multinational companies with major exposure to frontier markets, single-country funds, sector funds, regional funds, and ETFs. The authors recommend using an actively managed global fund with a reasonable expense ratio (2.1%-2.3% per annum). The largest is the Templeton Frontier Markets Fund. Its U.S. version launched in October 2008 and returned 13.45% per annum from inception to the end of 2012 after deducting a 2.15% management expense ratio; during this same period the MSCI Frontier Markets Index had a negative return of 4.98% per annum. Two other outperforming funds are the Harding Loevner Frontier Emerging Markets Fund and the HSBC GIF Frontier Markets Fund. This outperformance is easy to understand. “Given the extremely concentrated and illiquid nature of the frontier market equities that passive investments such as ETFs have to invest in, it is unsurprising that active managers have beaten the indexes. They are inefficient markets where active managers find it much easier to add alpha by virtue of research and taking positions away from the index weightings.” (p. 221)

The most obvious audience for Investing in Frontier Markets is financial advisors who have to explain to clients the pros and cons, the ins and outs, of adding this asset class to their portfolios. They will definitely be better informed after reading this book.

Lack, Bonds Are Not Forever

As you might guess from its title, Bonds Are Not Forever: The Crisis Facing Fixed Income Investors (Wiley, 2013) is an admonition about investing in bonds under current conditions. Simon A. Lack, who dealt with the fixed income market for many years at J.P. Morgan, is not a bond basher in general. Indeed, bonds have been a good place to be. “Bonds outperformed stocks during the first decade of the millennium, and the buyer of a 30-Year Treasury bond at the peak in yields in 1981 also outperformed equities during the subsequent 30 years.” (p. 189) Now, however, it’s time for bondholders to pull up stakes and move on.

Even though many others have sounded the alarm on bonds, Lack offers a historical framework, anecdotes (at times amusing and at other times scary), and compelling analysis in support of his position.

Here I’ll focus on two related reasons that bondholders should bail. First, “nominal yields that are close to and below inflation ensure that the investor will get back less purchasing power than he gave up when he bought the bonds. Figure in taxes and it’s worse. Moreover, real rates on government and investment-grade credit are unlikely to provide the 2 to 3 percent cushion above inflation that ought to be the minimum requirement of lenders.” (p. 190) Second, “even earning a return on bonds that beats inflation after taxes doesn’t ensure a secure future for those planning their retirement.” (p. 191)

Most people assume that beating inflation means beating the CPI. But there is a disconnect between the CPI and consumers’ daily purchasing experience. As Lack writes, the folks at the BLS “don’t measure what we care about because it’s too hard; they measure what they can, and we mistakenly think they’re counting what counts to us.” (p. 185) For instance, we think they are measuring the cost of owning a home, aka the bottomless pit, but in fact they’re measuring what the home would rent for. Moreover, they construct their index by asking homeowners how much they think their home would rent for, as if homeowners were the ultimate real estate experts. The BLS disregards such things as mortgage rates, property taxes, insurance, and maintenance and measures only utility bills. (Even here, if you heat with natural gas you win; with heating oil, you lose.)

And then there’s the problem of the “hedonic quality adjustment” in the CPI. The BLS doesn’t measure the cost of a constant standard of living but the cost of constant utility. For instance, “if your standard of living includes being able to afford the latest iPad, and the latest iPad costs what the older version did, you don’t feel as if your standard of living has improved. The BLS would record an increase in your utility (because you bought more iPad for $500 than used to be possible), but you’ve simply bought the latest iPad.” (p. 179)

In brief, people who simply keep up with the CPI “will experience a steadily declining standard of living. You’ll have last year’s utility when you really want this year’s to maintain your relative standard of living.” (p. 185)

Where should a bondholder go? Equities are the obvious alternative; holding some cash adds stability to a long-only portfolio. Lack provides two tables to guide the investor, one that shows the percentage of stocks needed to earn an equivalent treasury bond return and another that compares drawdowns in cash and stocks versus bonds.

Even if you’ve heard this song before, Lack offers interesting embellishments. In my opinion the book is worth reading just for the anecdotes. Did you know, for instance, that until 1986 brokers from the British brokerage firm Mullins were required to wear top hat and tails every day on the trading floor? Of course, there’s a lot more to Bonds Are Not Forever than curiosities. It is an insider’s view of what outsiders should know and, as such, should be required reading for every retail bond investor.

Maxwell, Sometimes You Win—Sometimes You Learn

We’ve all read innumerable times that we learn more from failure than from success. Well, that’s not quite accurate. The sentence should probably read: “Failure provides a better opportunity for learning than does success.” Not all people—in fact, probably few people, take advantage of the opportunity that failure offers.

John C. Maxwell, a prolific author of self-help books, wants to increase the number of learners. Sometimes You Win—Sometimes You Learn: Life’s Greatest Lessons Are Gained from Our Losses (Center Street/Hachette, October 2013) explains how to turn failure into learning. John Wooden wrote the foreword to the book, based on its outline, a few months before he died.

Losses are tough, there’s no getting around this fact. They cause us to become emotionally stuck and mentally defeated, they create a gap between knowing and doing, they never leave us the same. They hurt, but when we don’t learn from them they really hurt.

Maxwell approaches learning from multiple perspectives: the foundation of learning, the focus of learning, the motivation of learning, the pathway of learning, the catalyst of learning, the price of learning, and the value of learning. His final chapter is entitled “Winning Isn’t Everything, But Learning Is.” He incorporates anecdotes, insights from others, and apposite quotations such as Bill Gates’s famous line: “Success is a lousy teacher. It makes smart people think they can’t lose.”

Here is one point that traders should appreciate (and act on): don’t let a bad experience become a worse experience. Maxwell recalls ABC’s Wide World of Sports, which used to open with a narrator intoning “the thrill of victory … the agony of defeat.” To illustrate the latter, Maxwell writes, “it always showed a ski jumper heading down ramp, and then suddenly going off course, spinning, crashing through the supporting structure, and then bouncing on the ground. It looked like a horrendous crash. What most people didn’t know was that the skier’s fall wasn’t an accident. He chose to fall rather than to finish the jump. An experienced jumper, he realized that the ramp had become icy, and he was picking up so much speed that if he completed the jump, he would probably land far beyond the sloped landing area and hit level ground, which might have killed him.” (pp. 133-34) By comparison a losing trade, even one not cut short, seems tame indeed. But the same principle applies.

Traders who want to be successful should commit to a regimen of unlearning things that aren’t working. This is a difficult task because, as a leadership coach wrote, “When you are frightened, you calcify your attitudes and beliefs—you resort to the familiar and close your mind. New learning is impossible, and effectiveness is impaired. … Unlearning is prerequisite for growth. … To unlearn, you: 1) admit that an old practice, belief, or attitude is not solving the current problem and that doing more of it won’t lead to desired outcomes; 2) open your mind …; 4) commit to terminating the old way forever; and 5) practice and perfect the new way.” (p. 151)

Maxwell’s book is a good read. Translating learning into acting is, of course, a big step, involving the cultivation of good habits. But we can’t afford not to try. Nobel Peace Prize winner Fridtjof Nansen’s encouraging words might help: “Have you not succeeded? Continue! Have you succeeded? Continue!” (p. 167)