Weis, Trades About to Happen

If you like drawing lines on charts you’ll find a soul mate in David H. Weis, author of Trades About to Happen: A Modern Adaptation of the Wyckoff Method (Wiley, 2013). As he writes, “I cannot stress enough the importance of drawing lines all over your charts. … They define the angle of advance or decline within a price trend, alert one to when a market has reached an overbought or oversold point within a trend, frame trading ranges, depict prices coiling to a point of equilibrium (apex), and help forecast where to expect support or resistance on corrections.” (p. 27)

Weis has long been considered an expert on the Wyckoff trading method as well as on Elliott Waves. Technical traders may know him from his Weis Wave indicator.

In Trades About to Happen Weis, like Wyckoff, touts skill in tape reading as the key to trading profitability. His charts include only price and volume—with, of course, the mandatory lines (support and resistance levels, trend lines, and channels). Most of his charts, by the way, are bar charts, although in his analysis of Wyckoff’s methodology he includes volume-figure charts and, later on, more traditional point-and-figure and renko charts.

To read the tape is to read a fascinating story, a story of supply and demand, of shifting sentiment. It is not simply to read a succession of letters (or bars), as some bastardized forms of tape reading would have us believe. As Wyckoff himself wrote in Studies in Tape Reading (p. 95), “Successful tape reading is a study of Force; it requires ability to judge which side has the greatest pulling power and one must have the courage to go with that side. There are critical points which occur in each swing, just as in the life of a business or individual. At these junctures it seems as though a feather’s weight on either side would determine the immediate trend. Anyone who can spot these points has much to win and little to lose.”

Weis explores key tape reading concepts such as springs, upthrusts, and absorption. In fact, he claims that “You can make a living by trading springs and upthrusts.” For those not familiar with the terminology, a spring is “a washout (penetration) of a trading range or support level that fails to follow through and leads to an upward reversal.” (p. 73) An upthrust is a failed upside breakout. Both the spring and the upthrust offer trading opportunities “at the danger point where the risk is the least” (p. 95), although Weis considers the upthrust a trickier trade. After all, many breakouts are spectacularly successful.

Trades About to Happen is a carefully crafted book with an abundance of detail. It’s essentially a textbook (without all those annoying qualities of so many textbooks) for the would-be tape reader. Traders who are floundering in a sea of indicators would do well to learn some of the tales the tape tells. And learn to use their own judgment.

Piros & Pinto, Economics for Investment Decision Makers

If your command of economics is either rusty or fuzzy but you don’t have the time to sit through three or four semester courses, Economics for Investment Decision Makers: Micro, Macro, and International Economics (Wiley, 2013) might be just the ticket. This 700+-page book by Christopher D. Piros and Jerald E. Pinto is part of the CFA Institute Investment Series. You don’t have to aspire to become a certified financial analyst to benefit from the book. It’s a good foundational text for every investor.

The book is divided into twelve chapters: (1) demand and supply analysis: introduction, (2) demand and supply analysis: consumer demand, (3) demand and supply analysis: the firm, (4) the firm and market structures, (5) aggregate output, prices, and economic growth, (6)understanding business cycles, (7) monetary and fiscal policy, (8) international trade and capital flows, (9) currency exchange rates, (10) currency exchange rates: determination and forecasting, (11) economic growth and the investment decision, and (12) economics of regulation.

My hunch is that, of the topics covered in this book, investors probably know the least about currency exchange rates. Yes, they know that it can be more or less expensive to travel to Europe or to buy a Japanese-manufactured car depending on the strength of the dollar against the euro or the yen—though even here it should be noted that “Many studies find long lags, perhaps lasting several years, between (1) the onset of the exchange rate change and (2) the adjustment in traded goods prices in response to the change in the exchange rate, and then (3) the eventual effect of the change in traded goods prices on import and export demand.” (p. 613)

Perhaps they even think they understand the basic principles of the carry trade. But can they answer these two questions about carry trade strategies? (1)Carry trades can be profitable when: A. covered interest rate parity does not hold. B. uncovered interest rate parity does not hold. C. the international Fisher effect does not hold. (2) Over time, the return distribution of the fund’s FX carry trades is most likely to resemble: A. a normal distribution with fat tails. B. a distribution with fat tails and a negative skew. C. a distribution with thin tails and a positive skew. (“B” is the correct answer to both.)

If your response to these questions and answers is not “of course,” you will probably learn a lot from this book. It’s not bedtime reading, but I suspect the time invested in studying it will pay off.

There’s also a workbook that goes along with this text, but I haven’t seen it.

Martin, The Risk Takers

Individual traders are often told that they should view their activity as a business. But what exactly does this mean? After all, one business after the other fails; presumably these aren’t the best models. Renee and Don Martin, successful entrepreneurs themselves, come to the rescue with The Risk Takers: 16 Women and Men Share Their Entrepreneurial Strategies for Success (Vanguard Press, 2010). No, it’s not a new book, but I hadn’t read it and I suspect most of you haven’t either.

With two exceptions, the entrepreneurs founded their companies—Curves, Alvarado Construction, Kinko’s, Liz Lange Maternity, Geek Squad, The Corcoran Group, World Wide Technology, Build-A-Bear Workshop, John Paul Mitchell Systems, Spanx, Amy’s Kitchen, Trilogy, Invacare, Tova, The WW Group (Weight Watchers), and (the author’s own) The Cal-Surance Companies.

Many—actually, probably most—of the entrepreneurs were dreadful students. Many went from rags to riches, sometimes back to rags again before they ultimately triumphed, but I won’t recount any of these personal journeys. Rather, I’m going to pull out a few quotations that may have applicability to the trading business, although I’ll point out how some of them can steer the trader wrong.

“Risk taking is also about embracing change. …change takes you out of your comfort zone, but how else can a business grow? ‘I think people like me learn to like feeling uncomfortable…. In fact, we get comfortable with being uncomfortable.’” (p. 46)

The successful entrepreneur never stops reinventing his company to adapt to changes. “I have an appreciation for challenges…. You either go through a challenge or you’re stopped by it. There’s always opportunity at the end. If you give up, obviously, there’s no chance of ever having any hope of reaching that end where the prize is.” (p. 178)

“Not dreaming big enough is one of the biggest mistakes entrepreneurs make.” (p. 193) Yes, but risking too much is also one of the biggest trading mistakes. There should always be a significant gap between the risk actually taken and the dreams of major success.

“Successful people do all the things unsuccessful people don’t want to do. They’ll knock on ten doors, and even when every one is slammed in their face, they’re just as excited on door number 11—or door number 582.” (p. 223) In trading, however, by door number 582 you’d better understand that your trading system is broken; in fact, you’re probably broke yourself.

“Clearly, you either shy away from competition or you thrive on it. I’ve always loved competition and excellence. I’ve always said, ‘Show me a good loser, and I’ll show you a loser.’ I don’t always come in first, but I sure as heck try to get there.” (pp. 310-11) Losing is, of course, part of any trading business.

And finally, a few sentences about Barbara Corcoran that encapsulate several of the book’s themes: “Barbara had spotted a trend and pounced.” Even though both her competitors and her own advisors thought she was on the wrong track by paying so much attention to the West Side, which had historically lagged behind in property values, “she trusted her gut and did it anyway. In effect, she was positioning her company to hit ’em where they ain’t.” (pp. 143-44) Scrap the “trusted her gut” phrase. The Corcoran Group had done extensive market research that predicted a surge in demand for apartments on the West Side. She trusted the data.

Halvorson & Higgins, Focus

People can be roughly divided into two camps, Heidi Grant Halvorson and E. Tory Higgins argue in Focus: Use Different Ways of Seeing the World to Power Success and Influence (Hudson Street Press, 2013). Essentially, they’re offering a modification of the across-the-board findings of behavioral economics. Some people, they maintain, focus on the win; others, on avoiding the loss. That is, most people have a dominant motivational focus—either promotion or prevention.

“Promotion focus is about maximizing gains and avoiding missed opportunities. … Prevention focus, on the other hand, is about minimizing losses, to keep things working.” (p. 3) “Promotion motivation is … about filling your life with positives: love and admiration, but also accomplishment, advancement, and growth. Promotion goals are ones that we would ideally like to achieve…. When we do obtain whatever positive thing we’ve been seeking, we feel the high-energy, cheerfulness-related emotions: happiness, joy, and excitement. … Prevention motivation, on the other hand, is about … doing what’s necessary to maintain a satisfactory life: keeping safe, doing what’s right. Prevention goals are ones that we feel we ought to achieve—ones we think of as duties, obligations, or responsibilities. … When we do successfully maintain safety and security, we feel the low-energy, quiescence-related emotions: calm, relaxation, and relief.” (p. 5)

The authors are quick to point out that people may have different dominant motivations in different areas of their lives. A person may, for instance, be promotion focused when it comes to his job but prevention focused when dealing with his investments. Moreover, certain activities themselves have promotion or prevention qualities. Think of playing the lottery (I don’t) vs. getting a flu shot (I do).

Promotion-focused folks are the optimistic, can-do types. Mind you, they’re also the ones that can get themselves and the world into serious trouble. We have only to think of rogue traders. By contrast, those who are prevention focused have a maybe-it-won’t-work-out mentality and hence are vigilant. Think of Andy Grove’s famous quotation: “Success breeds complacency. Complacency breeds failure. Only the paranoid survive.”

Put another way, the promotion-focused “really get going when they feel they are doing well. … The prevention-focused, on the other hand, really hop to it when things aren’t going so well. The possibility of failure enhances their motivation, and their performance, too.” (p. 24)

Businesses need both types of people; they “need to excel at innovation and maintenance, at speed and accuracy.” (p. 47) Moreover, they need to convince both types of people to buy their products. Businesses, in the authors’ words, must create a motivational fit for both their employees and their customers.

Focus touches on many aspects of our lives, including decision-making, parenting, and marital relations (mixed-motivation marriages, by the way, tend to be the most successful). Although the book’s thesis is pretty straightforward, the authors give it a lot of color. All in all, a worthwhile read.

Greiner, Investment Risk and Uncertainty

Steven Greiner, the author of Ben Graham Was a Quant, which I reviewed two years ago, is back with a new book, Investment Risk and Uncertainty: Advanced Risk Awareness Techniques for the Intelligent Investor (Wiley, 2013). I suppose Greiner could more accurately be described as editor instead of author; although he has written many of the chapters, either alone or with co-authors, he has also enlisted the expertise of his colleagues at FactSet and FactSet’s risk vendors.

The subtitle may describe the intended audience as “the intelligent investor,” but this book is really directed at the quantitatively savvy investment professional. Few retail investors, intelligent or not, will either have or require the high-level risk modeling and management skills described in this book.

For those who run large portfolios or who otherwise need to know about a broad spectrum of risk management issues, tools, and practical solutions, Greiner’s book is both comprehensive and comprehensible. It is divided into three unequal parts, with the third and shortest highlighting products available from FactSet and fleshing out the many references to FactSet that occur throughout the first two parts.

The first part draws key theoretical distinctions and provides an overview of the field. Its seven chapters include discussions of exposed versus experienced risk, definitions of tractable risk, an introduction to asset class specifics, commodities and currencies, options and interest rate derivatives, measuring asset association and dependence, and risk model construction. The second part zeroes in on fixed income and deals with a range of topics, from interest rate risk and spread risk to portfolio risk measures and portfolio optimization.

Greiner’s book does not lend itself to short excerpts, but I’ll try nonetheless. First, an abbreviated list of the “many statistics used today to identify, measure, monitor, and mitigate risk”: tracking error, portfolio variance, portfolio standard deviation, dollar value at risk (at various confidence intervals and horizons), percent value at risk (at various confidence intervals and horizons), information ratio, Sharpe ratio, systematic risk, and idiosyncratic risk. (p. 68)

And, since we read so much about tracking error (TE), “the most ubiquitous equity risk measure,” it might be worth calling attention to one of its obvious shortcomings. TE “calculates the standard deviation of the distribution of portfolio returns versus the benchmark returns. … It says nothing, however, about what the mean of returns is, so it’s possible for two portfolios to have two different mean returns and have the same tracking error. In fact, one portfolio could outperform its benchmark and another could underperform its benchmark and yet both portfolios could have the same tracking error.” This “yardstick” that was “invented to beat the heads of asset managers with” (p. 63) may thus not be a particularly meaningful stand-alone risk measure.

Wethey, Decide

We are constantly making decisions, operating for the most part on autopilot. But then there are the decisions that are part and parcel of how we manage our ambitions and achieve our goals. These kinds of decisions, the ones that require dealing with opportunities and problems, are the focus of David Wethey’s Decide: Better Ways of Making Better Decisions (Kogan Page, 2013). Wethey’s own life decisions include a career first as an ad man and now as a client-side consultant. He also writes the blog Making Better Decisions, Better.

Much of Wethey’s analysis is set within a business context, where teamwork and “buy-ins” are critical. But five of his six rules for making an important decision in the right way, and then managing it, are applicable to the individual trader and investor as well. To wit, (1) “Every important decision is a journey, not a single step.” (2) “You must ask the right questions at the outset to make sure you are operating within the correct frame.” (3) “Plotting scenarios is how you come to the right decision, and for that you need the best possible intelligence.” (4) “Execution is critical. A great decision badly executed will fail.” (5) “Learning and feedback are fundamental, because decision making is a constant activity—every decision you take will inform every other decision you have to make in the future.” (p. 94)

Wethey conducted some fascinating interviews for his book to learn how people actually make decisions—decisions about everything from war and sports to love and buying a consumer product. Among his findings (from the literature as well as his own research), “the best option is often the one with the second-best upside and the least-damaging downside (a bit like a wine list, when you want to balance hospitality with frugality!).” Or two problems are often better than one; if you can’t make a decision about issue A, move down your “to do” list and tackle problem B, then, “refreshed and motivated by your winning performance,” go back to A.

Smart decision making is not a purely rational process; it “has to be a mixture of good thinking and harnessing the power of the subconscious brain.” The subconscious is dominant when the time available to decide is short. But unless, like a soldier or firefighter, you’re meticulously trained to make snap decisions or (my example), like Warren Buffett, you can make a decision quickly because you’ve spent years studying business metrics, faster is not necessarily better. In fact, where a fast decision is an early decision, it can be downright insidious.

Wethey’s exploration of, among other things, decision traps, the role of luck in decision outcomes, and how we capitalize on or waste opportunities is bracketed by a Theodore Roosevelt quotation and his own final words. “In any moment of decision, the best thing you can do is the right thing. The worst thing you can do is nothing.” And “Decide! Success comes from making decisions, not putting them off, or fudging them.” (p. 278)

I decided to spend part of my weekend reading this book and consider my decision to have been a good one.

Balenthiran, The 17.6 Year Stock Market Cycle

Kent Balenthiran’s The 17.6 Year Stock Market Cycle: Connecting the Panics of 1929, 1987, 2000 and 2007 (Harriman House, 2013) is a difficult book to review. The problem is that in this 91-page book the author sets forth a single historical and predictive hypothesis. In its broad strokes the 17.6-year historical hypothesis is not new, as Balenthiran readily admits. I myself have encountered it numerous times. The author provides more granularity, however, which makes his work both more original and more prone to predictive error.

The profile of a bull market cycle resembles an Elliott Wave sequence, although Balenthiran notes that, in contrast to Elliott Waves, his cycle “has distinct phases of fixed time and direction” and “is not trying to determine by how much the stock market may increase or decrease in that time.” (p. 30) Nonetheless, his bull market cycle has an initial leg up lasting four to five years, a sharp correction lasting one to two years, another rally lasting four to five years, a mild mid-cycle correction, and finally a major bull market top. In his stylized version, the rough 4-5 and 1-2 figures get turned into more exact numbers: 4.4 and 2.2 years.

The bear market cycle is more complex. It starts with a bear market crash lasting approximately two years, is followed by a rally lasting four to five years, a second bear market crash lasting around two years (often, he claims, the lowest low), a two-year bear market rally, a major bear market low (not necessarily the lowest low), a final bear market low, and finally the end of the bear market cycle.

So, what can we expect? The current bear market should end in 2018, with the final low coming this year. This low is “not likely to be lower than that seen in 2009, but ideally below the 2011 high.” (p. 57) This may be a good entry point for the new bull market even though it comes five years before the start of the next long-cycle bull market.

Perhaps this is what all the money sitting on the sidelines is waiting for

Narang, Inside the Black Box, 2d ed.

I never read the first edition of Rishi K. Narang’s Inside the Black Box: A Simple Guide to Quantitative and High-Frequency Trading, so I was delighted when Wiley published a second edition this year and I finally got the chance to find out what’s really “inside the black box.” It turns out that it’s not something mysterious but rather something that every trader should aspire to, whether his eventual trading box is black or translucent. In brief, this book is not just for those who want to know what quants do (though it does an excellent job of describing their role in the investment community) but for everyone whose trading is informed by more than dart throwing or gut reactions.

At its most basic, a quant trading strategy consists of an alpha model, a risk model, and a transaction cost model, all of which “feed into a portfolio construction model, which in turn interacts with the execution model.” (p. 17) Necessary to build and run these models are data and research.

Let’s assume that you are a retail trader. To make things really simple, I’m going to further assume that you don’t have to worry about portfolio construction but rather are using a small portion of your overall portfolio to trade a single instrument. First, you need a model, either testable (if a hypothesis) or adaptive (if the result of data mining), of when to buy and when to sell that will give you an edge. Second, you need to set up some rules that will improve the quality and consistency of your returns and that will prevent you from losing your shirt. Third, you have to figure out what broker to use and on what time frame to trade so that transaction costs don’t swamp potential profits. And finally, you have to figure out how to execute your trades—what kind of an order to use, whether it is automatically generated based on an algorithm or entered by hand, whether to scale in and out, etc.

In brief, at least in outline every retail trader, even the discretionary trader, should do what the quants do. For starters, focused, scientifically driven research. Narang’s book provides something of a road map that everyone can use. The non-quant retail trader won’t go as far as the professional quant; to analogize, faced with a map of the U.S. he might decide to start in Connecticut and end in Pennsylvania whereas the quant might go from Connecticut to Nevada (I couldn’t resist the Las Vegas image). Without the road map, however, he might end up drowning in the ocean or speeding down to Florida only to be swallowed up by a sink hole.

Narang divides his book into four parts: the quant universe, inside the black box, a practical guide for investors in quantitative strategies, and (new to this edition) high-speed and high-frequency trading. The text is highly readable. No math is required, only, I would suggest, an interest in scientific inquiry and a curiosity about the world that the mathematical elite inhabit. Inside the Black Box is an enlightening and potentially enriching read.

Baker and Filbeck, Alternative Investments

Alternative Investments: Instruments, Performance, Benchmarks, and Strategies, edited by H. Kent Baker and Greg Filbeck (Wiley, 2013), is the latest addition to the Kolb Series in Finance. The books in this series, all hefty (this one is over 600 pages), are collections of papers by both academics and practitioners.

The editors have organized Alternative Investments around the standard offerings: real estate, private equity, commodities and managed futures, and hedge funds. In twenty-eight chapters the book’s contributors take the reader on a journey that touches on a wide range of topics, from the introductory to the arcane. The retail investor or the investing professional relatively new to the game can learn about the role of alternative investments in strategic asset allocation and investing in commodities. For the more academically and statistically oriented reader there is an analysis that uses multivariate cointegration techniques to ascertain whether “investors in REITs receive a return consistent with the direct real estate market.” The quick answer: the two tend toward a long-term equilibrium but financial markets lead movements in the real estate market.

Some of the asset classes described in this book are not readily available to the retail investor. Take mezzanine capital, for instance. “Seasoned investors in alternative assets have come to realize its resilience as an asset class capable of generating stable noncorrelated returns across a wide variety of prevailing market conditions. … However, the bespoke nature of mezzanine instruments combined with their term structure mean that mezzanine capital is an illiquid asset class. For this reason, mezzanine debt is … best invested in by using either a dedicated closed-end blind pool fund or a specialist credit fund.” (p. 279) In brief, probably not for “the rest of us.” But, in case you’re interested, KeyBanc puts out a quarterly mezzanine debt newsletter.

To my mind the strongest part of the book is the one that deals with real estate. It includes seven chapters: “REITs and the Private Real Estate Market,” “Commercial Real Estate,” “Real Estate Investment Trusts,” “Mortgage-Backed Securities,” “Mezzanine Debt and Preferred Equity in Real Estate,” “Real Estate Appraisal and Valuation,” and “Performance of Real Estate Portfolios.” Now that real estate is no longer a dirty word, it is high time (never say “too late”) for serious investors to learn more about the nitty-gritty of investing in real estate. No, not flipping condos, but how the pros do it. It’s a complicated field, but it remains a potentially lucrative alternative investment. Even if you’re simply buying a REIT, you should know more than most investors probably do.

Students and investment professionals would do well to read the whole book. The retail investor can pick and choose. Whatever your method, you will be well rewarded.

Siegel, Predictive Analytics

Predictive analytics intrudes on our lives every day. Amazon recommends products (sometimes, admittedly, bizarre—I’ve received ads for headlights, guitars, and baby diapers), Stop and Shop sends targeted grocery coupons, and the same politician crafts different ads for Republicans and Democrats. Eric Siegel takes the reader into this powerful, potentially troubling world in Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Wiley, 2013).

The glut of data is growing by “an estimated 2.5 quintillion bytes per day (that’s a 1 with 18 zeroes after it). … As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is what’s discovered therein.” (pp. 26-27) Enter predictive analytics, “technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions.” (p. 37)

I’m going to look at a single use of predictive analytics, how it has been used in data-driven black box trading. For this purpose Siegel turned to John Elder, now head of the largest predictive analytics services firm in North America, who claims that “Wall Street is the hardest data mining problem.” (p. 74) Early in his career, while still a graduate student at the University of Virginia, Elder reverse engineered a black-box trading system that claimed 70% accuracy with its predictions on whether the S&P 500 would go up or down the following day. It turned out that the so-called predictions “were based in part on a three-day average calculated across yesterday, today … and tomorrow. The scientists had probably intended to incorporate a three-day average leading up to today, but had inadvertently shifted the window by a day. Oops. … Any prediction it would generate today could not incorporate the very thing it was designed to foresee—tomorrow’s stock price.” (p. 77)

After he finished his dissertation and became a postdoc, Elder created a trading system that detected a slight but repeatable pattern among the overwhelming market noise. He risked everything he had on his system.

“Going live with black box trading is really exciting and really scary,” says John. “It’s a roller coaster that never stops. The coaster takes on all these thrilling ups and downs, but with a very real chance it could go off the rails.”

As with baseball, he points out, slumps aren’t slumps at all—they’re inevitable statistical certainties. Each one leaves you wondering, “Is this falling feeling part of a safe ride, or is something broken?” A key component to his system was a cleverly designed means to detect real quality, a measure of system integrity that revealed whether recent success had been truly deserved or had come about just due to dumb luck.

John’s system was a phenomenal success, increasing his assets at a rate of 40% a year. Investors started signing up until finally the fund was managing a few hundred million dollars. But “after nearly a decade, the key measure of system integrity began to decline. John was adamant that they were running on fumes, so with little ceremony the entire fund was wound down…. [A]ll the investors came out ahead.” (p. 83)

I’m sharing this excerpt with the hope that someone can explain to me how one might go about measuring system integrity, at least in principle. Either post a comment or e-mail me. You’ll find my e-mail address by clicking on “View my complete profile” under “About Me,” which, as you probably know, is anything but complete.