Thursday, April 28, 2011

Damodaran, The Little Book of Valuation

Aswath Damodaran, professor of finance at NYU’s Stern School of Business, has written extensively on valuation. In The Little Book of Valuation (Wiley, 2011) he makes the process accessible to any individual investor who can—to quote one of his “rules for the road”—convert stories to numbers.

The math in this book is elementary; for the most part it requires no more than a junior high school education or, barring that, a calculator. Naturally, the concepts are more sophisticated.

Damodaran begins by differentiating between intrinsic and relative valuation. Intrinsic valuation looks inward, to the properties of cash flows (e.g., high/low, stable/volatile). Relative valuation looks outward, to how the market prices similar assets. There’s no compelling reason to use a single model and discard the other. “In truth, you can improve your odds by investing in stocks that are undervalued not only on an intrinsic basis but also on a relative one.” (p. 5)

Frequently the outputs of the two models are quite different. The explanation for this disparity lies in their “different views of market efficiency or inefficiency. In discounted cash flow valuation, we assume that markets make mistakes, that they correct these mistakes over time, and that these mistakes can often occur across entire sectors or even the entire market. In relative valuation, we assume that while markets make mistakes on individual stocks, they are correct on average.” (p. 78) Any investor who went through the bust should realize how tenuous relative valuation can be. An Internet company that was undervalued in relation to its radically overvalued sector could still be, and probably was, intrinsically overvalued.

After explaining the essential steps involved in statically valuing stocks according to each model, the author introduces a more dynamic “cradle to grave” scenario. Companies have life cycles, and there are valuation issues at every phase in these cycles. For instance, how do you value young companies that may be losing money and whose survival is not assured? How do you value companies that are suffering from growing pains? Even mature companies, which might seem easy to value, can present challenges. “The biggest challenge in valuing mature companies is complacency. When valuing these companies, investors are often lulled into believing that the numbers from the past … are reasonable estimates of what existing assets will continue to generate in the future.” (p. 128) And what about companies in decline, which can still be profitable investments?

Finally, the author addresses special situations in valuation—financial service companies, cyclical and commodity companies, and companies with intangible assets. All this in a 5” x 7” book of 230 pages.

For the investor who wants to use fundamental analysis to help unearth opportunities in the market The Little Book of Valuation is a gem. Damodaran provides the reader with the essential tools of valuation without overtaxing his brain. Even more important, he challenges (and helps) the reader to go beyond the formulaic and ask the kinds of questions that can make all the difference between an essentially useless valuation and one that is a truly valuable input to an investment decision. Hats off to Damodaran and to the “little book” series.

Wednesday, April 27, 2011

Greiner, Ben Graham Was a Quant

Ben Graham Was a Quant: Raising the IQ of the Intelligent Investor by Steven P. Greiner (Wiley, 2011) is, as intimated by the subtitle, a dense book. Unless the reader is familiar with the principles of quantitative analysis he will have to expend both time and mental energy even though the book contains virtually no math. But the effort is well worth it for anyone who wants to manage his own portfolio or who aspires to become a professional portfolio manager.

At its core Greiner’s book analyzes factors, how to build models from factors, and how to build portfolios from models. Leading up to this analysis are discussions of alpha and beta, risk, and modeling pitfalls. The two final chapters contain ruminations on assorted conceptual topics and a look back at the past and into the future.

As is my wont, I’m going to pull out a few ideas I considered particularly thought-provoking.

Greiner accepts that (1) the stock market is a complex chaotic system, (2) Soros’s reflexivity paradigm is essentially correct, and (3) the GARCH model fits the basic return distribution particularly well. If these three statements are true, the notion of mean reversion is probably, well, meaningless. “One often hears people in finance and asset managers speak of regression to the mean or mean reversion when discussing stock valuation or bond spreads. Unfortunately, in congruence with chaos theory, the notion of stock returns is more accurately termed antipersistent, meaning that there really is no mean to return to, but that, after moving in one direction, the process will soon revert. Additionally, one can readily decipher stock returns as changing direction more easily than one can say where it will revert to. … Investors do not and cannot know the actual average value of any given stock.” (p. 263)

Likewise, quants cannot know when random extinction-level events (ELE), a term Greiner prefers over “black swans,” will occur. “Quants generally are very aware of the unpredictable nature of random unforeseen events, and they do not waste their time trying to predict them. They spend their time building models to predict normal events with known causes that are predictable.” (p. 36)

Along the same lines, Greiner maintains that asset allocation did not fail the investor during the financial crisis. “There are two main categories of risk: market risk and security risk, also called systemic and idiosyncratic risk. Proper asset allocation and diversification results in minimizing idiosyncratic risk because only this kind of risk is diversifiable. … [I]n the credit crisis, when all stocks correlated highly as they do in down markets, … the total risk composed of market and security-specific risk changed their contribution percentages, so that market risk increased and security-specific risk, which is diversifiable, decreased. However, the asset allocation did its job by mitigating the security-specific idiosyncratic risk.” (p. 257)

Finally, let’s look at a topic dear to every investor’s heart: the search for alpha. Greiner outlines eight rules of thumb for deciding when an alpha signal is truly being generated by some factor. Here are three: (1) It must come from real economic variables, (2) The signal must be strong enough to overcome trading costs, and (3) It should not be misconstrued as a risk factor. What does it mean to misconstrue an alpha factor as a risk factor? Once again, let me quote Greiner: “It is safe to say that if a factor is not a risk factor, and it explains the return or the variance of return to some extent, it must be an alpha factor. … A great example is a 12-month past-earnings growth. Though returns are colinear with this earnings growth, they are poor predictors of future returns. This is because many investors will have bid up the pricing of stocks that have shown historically good earnings growth concurrently with earnings announcements. However, 12-month past-earnings growth fails miserably at being a forecaster of future return. … In this case, 12-month past-earnings growth is probably a risk factor because it regresses well with future return statistically, but offers little in the way of alpha.” (pp. 23-24)

Ben Graham Was a Quant may not be a page turner, but I think it would be an important addition to the library of anyone who is interested in building portfolio models—and not just value portfolio models.

Tuesday, April 26, 2011

Knuth, Trading between the Lines

Trading books often target segmented markets. There are books for system designers and books for those who believe that discretion is the better part of valor, for hedgehogs and foxes, for analysts and traders in need of analysis themselves. Elaine Knuth’s Trading between the Lines: Pattern Recognition and Visualization of Markets (Bloomberg/Wiley, 2011) is the first book I’ve encountered that explains trading in a way that former literature majors can understand. As the author writes in the preface, “Each pattern … is first explained (framed) in a metaphor that fits the idea of the pattern. When reading about the lightning bolt pattern, for example, we first think about what conditions create lightning in the real world, and then within the context of this metaphor the pattern is described. Or when reading about the Icarus pattern, we first learn about what led up to the mythological flight of Icarus. Beyond being simply a pattern name and description, the use of metaphor helps us better understand the concept behind a pattern.” (p. ix) Steering us in this process by way of epigraphs at the beginning of each chapter are the indomitable Don Quixote and his sidekick Sancho Panza. The author justifies her choice, but I nonetheless find the “sane madman” and the “wise fool” disconcerting guides.

It would be easy but foolhardy to say that Knuth simply gives fancy new names to old patterns. She views the market somewhat differently from the norm, so even where a pattern seems familiar the reader is better off letting the author spin her tale and not assume that he already knows the ending.

We encounter such patterns as the knock on the door, the snake, Adam and Eve (similar to but not borrowed from Alan Farley’s short-term pattern), the Titan constellation, and the valley of the kings. These patterns are amply illustrated with charts of stocks and commodities. Unlike most charts that appear in trading books, which are truly “textbook,” Knuth’s charts are truer to life, which means that they are sometimes messy and more difficult to interpret. As the author writes, “A pattern in isolation tells only part of the unfolding story of price action. Trading a classic textbook description of a breakout while ignoring the internals or granularity of price behavior and information around the breakout can (and often does) lead us into chasing one false breakout after another. What distinguishes a real opportunity from a false one may be in the small but essential characteristics of the developing pattern.” (p. 47)

The patterns described in this book are intended to help the trader anticipate change rather than react to it. In part this means that we have to learn to recognize tipping points in market cycles—bear bottoms and bull tops. Although Knuth writes about breakout patterns and continuation patterns in some detail, perhaps the greatest strength of the book lies in her analysis of reversal patterns.

Trading between the Lines is not for the novice who wants a crash course in pattern trading. It is too nuanced. For the trader with a modicum of experience, however, it offers a fresh perspective and new insights. And since the author was a financial journalist before becoming a commodity trading advisor, the book moves along at a rather pleasant clip.

Monday, April 25, 2011

Elder, The New Sell & Sell Short

Most traders have read Alexander Elder’s Trading for a Living, originally published in 1993. Elder has, of course, written other popular books such as Come into My Trading Room (2002) and Entries and Exits (2006). His latest work, The New Sell & Sell Short: How to Take Profits, Cut Losses, and Benefit from Price Declines (Wiley, 2011) is an expanded second edition of his 2008 book. It comes with a built-in study guide: three sets of questions and answers. Although it is a paperback, the charts and graphs are printed in color and the stock is of high quality.

The first part of the book covers Elder’s signature contributions to the trading literature: psychology, risk management, and record-keeping. It is brief because we’ve been there before, but Elder does describe some new ways to keep records—an ongoing project because he believes that “the single most important factor in your success or failure is the quality of your records.” (p. 341)

Part two tackles the all-important question of how to exit a (long) trade. Elder offers three alternative scenarios: sell at a target above the market, be prepared to sell below the market using a protective stop, and “sell before the stock hits either a target or a stop—because market conditions have changed and you no longer want to hold it.” (p. 59)

Elder then moves on to shorting stocks, futures, and forex; he also has a section on writing options. Finally, he points out some lessons of the 2007-2009 bear market.

I debated what specifics to share in this post because I realize that my readership is diverse. Some are new to the game and have never shorted a stock in their lives, others have extensive experience on both sides of the market. Here are two tidbits that should be of interest to readers at all stages of their trading careers. Both deal with stop placement—the first an initial stop (compliments of Nic Grove), the second a trailing stop (the creation of Kerry Lovvorn).

Elder explains that “the worst misconception about stops is that one should place them on long positions immediately below the latest low. … The level immediately below the latest low is where amateurs cut and run, while professionals tend to buy.” (p. 102) An alternative is to have an even tighter stop on stocks that have reached a defined level of support. “Nic suggested looking for the low where most people would place their stops and then examine the bars that bracketed that low on each side. He would then place his stop a little below the lower of those two bars.” (pp. 116-17)

The volatility-drop trailing stop is designed to be used once the trade’s target has been hit but the market is moving “in a way that seems to have potential for an additional reward.” The trader who wants to keep part of his position on might proceed along the following lines. “Suppose I use Autoenvelope to set my price target when I enter the trade. The normal width of the envelope is 2.7 standard deviations. If I want to switch to a trailing stop once that target is reached, I will place it one standard deviation tighter—at 1.7 standard deviations. As long as the move continues along the border of a normal envelope, I’ll stay with it, but as soon as the price closes inside of the tighter channel, I’ll be out.” (p. 125)

The New Sell & Sell Short is appropriate for traders and investors who are relative novices (definitely not rank amateurs). It explains how to exploit the asymmetry of markets; the path up and the path down are not, contrary to Heraclitus, one and the same. And, as we have come to expect from Elder, it stresses how to do this while keeping risk manageable.

Wednesday, April 20, 2011

Byers, The Blind Spot

William Byers, a retired math and statistics professor, explores the subjective and ambiguous side of the so-called exact sciences in The Blind Spot: Science and the Crisis of Uncertainty (Princeton University Press, 2011). All well and good, you may say, but what does this book have to do with trading and investing in the financial markets?

Byers makes the obvious link—that financial firms, with their quant packages, marketed the illusion of certainty. “What was being sold was the faith that the complex, human, world of economics and finance could be made over in the image of science, could be made objective and predictable.” (pp. 61-62)

But the obvious is rarely the interesting. As Byers blurs the lines between art and science, the human and the “pure,” even knowing and the known, he offers insights into the processes of learning, creating, and discovering. These processes are as vital for traders as they are for scientists.

For those who blithely assume that our eyes are up to the task of seeing what is, let’s start with the book’s title. “The physiological blind spot is the place in the visual field that corresponds to the lack of light-detecting photoreceptor cells on the optic disc of the retina where the optic nerve passes through it. Since there are no cells to detect light on the optic disc, a part of the field of vision is not perceived. The brain fills in with surrounding detail and with information from the other eye, so the blind spot is not normally perceived.” (p. 2)

We are constantly being confronted with metaphorical blind spots. For instance, there are inherent limits on what can be known using concepts and symbols. The mind is not simply some kind of computing device, fixed and unchanging, and the world is neither static nor stable. It is always changing in a way that defies certain prediction, and it includes entities/processes that remain ungraspable, at least by reason.

The financial markets may not be a microcosm of the world, but they share its qualities of uncertainty, unpredictability, and constant change. The tasks required of a person trying to understand the markets are similar to those of the scientist trying to understand the world.

The very act of understanding “demands placing something in a context. It implies having a ‘feel’ for the situation in which the concept arises, not to mention the ability to use the concept in novel situations or solve problems not previously encountered. … Understanding is a process without end. At a certain stage in the process, one can say, ‘I understand randomness.’ But in reality you can always understand it better, understand it differently. “ (pp. 8-9)

In order to understand what is—not superficially but more deeply and creatively, it is necessary to embrace ambiguity and cognitive dissonance because “ambiguity is the way things are. … When there is ambiguity, there is one situation but two perfectly good ways of looking at it. To make matters worse, these two points of view are in conflict and may even be incompatible with each other. This incompatibility makes situations of ambiguity uncomfortable, irritating, even anxiety provoking—it evokes a tension that might even feel intolerable.” (pp. 70-71)

Ambiguity should not be resolved by opting for one alternative and rejecting the other. Continuing the ocular theme, Byers writes that “one metaphor for ambiguity is binocular vision. When you cover up one eye and view a scene through the other, the scene you see is flat, two-dimensional. When you look at the same scene with two eyes, each eye registers a slightly different scene. These are the incompatible points of view. The brain reconciles these two views by creating a new way to see the situation. This is accomplished by introducing a new dimension—depth.” (p. 72)

Byers’ book is itself ambiguous, and in a good way, since “ambiguity is … the ultimate attempt to grasp the ungraspable.” (p. 163) Ambiguity is also the fundamental state of the world, or perhaps I should say it is the fundamental process of the world: the world is better characterized as becoming than as being. In an ambiguous world control is an illusion, as is infallibility. But we are offered something far more enticing: “the world of the uncertain is the world of creative possibilities.” (p. 185)

Philosophers of science will read The Blind Spot as a serious effort to recast the process of science and the world it tries to grasp. But this book has ramifications outside the world of science. It argues against rigid thinking, complicated ideas (as opposed to complex ideas), and reductionism. It encourages metaphor, wonder, and unity. It is a rich book.

Tuesday, April 19, 2011

Augen, Microsoft Excel for Stock and Option Traders

Jeff Augen’s books are always challenging, as he intends them to be. Microsoft Excel for Stock and Option Traders: Build Your Own Analytical Tools for Higher Returns (FT Press, 2011) is no exception. Admittedly, my own skill levels are modest: I’m reasonably comfortable with standard Excel functions but am regularly foiled by VBA, despite the author’s claim that it is relatively easy to learn. Is it worth the effort to keep building databases and pounding away at VBA?

Augen would answer with a resounding yes: “investors who limit themselves to traditional off-the-shelf indicators will always lose money to sophisticated traders armed with more powerful tools. The days of buying and selling stocks when moving averages cross or when an oscillator reaches one side of a channel are over.” (p. 58) Moreover, he argues, “the capability gap between private and institutional investors increases as the trading time frame decreases.” Charting patterns designed around the behavior of human investors “have little relevance in a time frame that has come to be dominated by high-speed algorithmic trading.” (p. 156)

Although Augen hasn’t abandoned short-term trading (for instance, he illustrates the often complex but sometimes revelatory relationship between implied volatility and stock price on a 5-minute AAPL chart as well as on daily index charts), most of the data referenced in this book are end-of-day.

Ideally, the trader trying to gain a statistical edge has both a database program such as Access and a spreadsheet program such as Excel. But with the dramatic increase in the capacity of Excel (Excel 2010 worksheets can contain over 1,000,000 rows and 16,384 columns) many traders can get by, at least initially, with Excel alone.

Augen’s book presupposes a working knowledge of Excel. In the chapter entitled “The Basics” he shows how to manage date formats, perform volatility calculations, create ratios that simulate candlestick bars, construct summary tables with VBA, unearth statistical correlations, and draw polynomial trendlines on Excel charts.

In the chapter on advanced topics Augen explains in some detail how to develop and test hypotheses—for instance, whether sharp downward corrections in AMZN are followed by a relatively strong rally. For those who are inexperienced in backtesting with Excel, this chapter is exceedingly useful. It illustrates how to go about quantifying such qualitative terms as “sharp” and “relatively strong,” how to build complex statements from the inside out, and how to automate the process. It will save the would-be backtester countless hours of frustration. Even the column descriptions for a sample experiment should make this clear.

(click to enlarge)

Unfortunately, as far as I can ascertain, there is no accompanying web site where the reader can grab the Excel and VBA coding printed in the book. The reader who wants to crib some of Augen’s work will have to retype—very carefully.

Monday, April 18, 2011

Michalowski, Attacking Currency Trends

Greg Michalowski is a believer in the K.I.S.S. principle—not “Keep It Simple, Stupid” but “Keep It Simple to be Successful.” (p. 100) In Attacking Currency Trends: How to Anticipate and Trade Big Moves in the Forex Markets (Wiley, 2011) he applies this principle to currency trading, but it works equally well in the futures markets. (For equities traders life is somewhat trickier.)

In its barest outlines Michalowski’s book is indeed simple. He shares his mission statement—to make the most money with the least amount of risk—and his game plan—trade the trends and keep fear to a minimum. But we shouldn’t confuse simplicity with simplemindedness. Underlying both the mission statement and the game plan are genuine insights into markets and trader psychology. His five rules for attacking the trend offer even more focused trading wisdom.

Retail traders don’t trade trends well; this seems to be a documented fact. Their failure is due in part to an inability to anticipate trends and get on board and in part to an inability to hang on for the ride. Using unambiguous tools to get on board will help cure the first problem. The second is tougher to deal with since it is more psychological: “a trader fears the success he has on his trade will be taken away.” (p. 93) Alas, we know that sometimes the trader who hangs on really does give up all his profits, so his fear is not irrational. But if he succumbs to it on a regular basis he will abrogate his chance to book profits far in excess of his risk. He needs a trade management strategy that overrides his fear.

Michalowski offers tips that he believes can transform the losing retail currency trader, who bags a pip here or there only to lose considerably more on the next trade, into a successful trend trader. In this post I am going to focus on a single rule, be picky about your tools.

Technical tools must meet three requirements: “they must be trend defining, risk defining, and unambiguous.” (p. 108) Of these three, the author considers the last to be most in need of explanation. “What I define as an unambiguous tool is one that gives a clear bullish or bearish bias. The tool should not give an oversold or overbought condition. It should not give an 80-percent correlation clue.” (p. 109) Indicators such as the relative strength index and stochastic oscillator have no place in Michalowski’s game plan. “If a market is said to be overbought, there is nothing to say that the price cannot get even more overbought. If this can happen, where is the stop loss? Where is the position closed out? There is no price for the stop. It is more of a guess. Guesses tend to increase fear over time. Successful traders look to steer clear of fear, not increase it.” (p. 109)

The author suggests using three tools; it’s the Goldilocks number. These three tools should be “universally used and simple. … Traders who create their own proprietary technical tools don’t get the fact that the market is simple, and as such it focuses on the most obvious, most of the time.” (p. 114)

What kinds of tools meet Michalowski’s criteria? He himself uses moving averages, trend lines and remembered lines, and Fibonacci retracements. These tools enable the trader to define significant borderlines (essentially, lines where the bias is bullish on one side and bearish on the other), which are always low-risk trading levels for entries and also become targets along the trend highway.

Michalowski explains at some length how to use these tools to anticipate trend moves, take the plunge, and get the most out of the trade. We often hear that trading is simple but not easy. Attacking Currency Trends, by exploring the simple, makes it a tad easier—perhaps even more profitable—for the retail trader.

Friday, April 15, 2011

McTague, Crapshoot Investing

On May 6, 2010, I sat in front of my computer absolutely stunned as the flash crash unfolded before my very eyes. As soon as it was available I downloaded the recording of Ben Lichtenstein’s live squawk broadcast so I would never forget the gut-wrenching terror I felt. Jim McTague’s Crapshoot Investing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market into a Casino (FT Press, 2011) explains the constellation of events that made the flash crash possible. It’s a gripping tale.

Of the many themes in the book I decided to write about two—liquidity and internalization. (And please stifle your yawns, they’re vitally important.)

High-frequency traders claim that they provide liquidity to the markets and hence dampen volatility. We know that their activities have inflated volume. Since some of the exchanges give “sub-pennies-per-share” rebates to HFT firms, it behooves them to boost volume. “Buy and sell tens of millions of shares a day, and that fraction of a cent adds up to substantial profit.” But is this in fact no more than what a white paper referred to as hot-potato trading? “If two guys trade 1,000 shares back and forth a million times, that’s a billion shares. Did a billion shares actually trade, or did the thousand shares change hands a million times between two guys playing hot potato?” (p. 22) Upshot: volume and liquidity are not interchangeable terms.

When Waddell & Reed tried to hedge a $7 billion position in U.S. equities by selling short $4.1 billion worth of E-Minis (75,000 contracts) on the fateful day of May 6, volume didn’t seem to be a problem. But it wasn’t what it seemed: it “appeared to be larger than it was because HFT firms using 15,000 accounts were trading E-Mini contracts back and forth, several thousand times a second, to generate rebates.” And “what Waddell & Reed could not possibly know that day was that buy-side liquidity in the E-Mini had fallen by 55%, from $6 billion to $2.65 billion, by the early afternoon.” There was “an appearance of deep liquidity where, in fact, it was thinner than spring ice.” (p. 69)

HFT firms may juice volume, but they do not robotically provide liquidity, independent of market conditions. Instead, “the high-frequency trader was playing the markets the way card counters play blackjack, … providing liquidity if a market for a particular security is staked in his favor and backing off at other times.” (p. 163) On the afternoon of May 6, high-frequency traders “stopped providing liquidity and began competing for it, and that drove the price of the E-Mini S&P 500 future even lower.” (p. 219)

And yet it would be unfair to single out HFT firms as the main culprits in the flash crash. Consider the 200 brokerage houses that regularly transact customer orders in house. “Internalization on most days accounts for nearly 100% of all retail trades. The practice … is a huge profit maker for the firms. They attempt to match one customer’s buy or sell order with the buy or sell order of another customer. If the firm can’t find a trade that reflects the market’s best bid and best offer, it sends it to an executing broker. The executing broker generally takes the opposite side of the customer order because retail customers generally buy high and sell low, so it’s easy to make money off of them. In the rare instance when an executing broker demurs, he sends the trade to a dark pool—usually one owned by his firm. If the dark pool can’t execute the trade, it is deemed exhaust and sent to one of the stock exchanges.” (p. 223)

On May 6, “spooked by the wave of selling” and wanting to “get rid of their own inventories of stock, not accumulate more,” some brokerage firms internalized buy orders but sent sell orders onto the stock exchanges. (p. 224) This move naturally intensified the pressure for liquidity on the exchanges.

McTague’s book might not be as intense as Lichtenstein’s audio, and even though he has a chapter entitled “The Real Culprits” it’s not quite a detective story. Any time regulators are among the cast of characters the plot tends to flag a bit, for me at least. But it’s a tale told by a seasoned reporter (Washington Editor for Barron’s), full of insights and indignation, signifying more than we might want to admit for the future trajectory of the financial markets.

Thursday, April 14, 2011

Cohen and Malburg, Surviving the Bond Bear Market

You own bonds because asset allocators say you should. You have some experience in the bond market, but you’re not a bond guru. Since times have been good, you haven’t had to lie awake at night thinking about how to manage your bond portfolio. But what if the market turns ugly? In Surviving the Bond Bear Market: Bondland’s Nuclear Winter (Wiley, 2011) Marilyn Cohen and Chris Malburg present some doomsday scenarios and, more important, action plans that you can follow to insulate your bond portfolio. Along the way we track the progress of the brothers-in-law El Greedo and Neo Fyte.

In anticipation of a bond market crash—and the authors list both warning signs and manifestations of the bond market’s nuclear winter—the bond investor can cushion the shock by rebalancing his portfolio. The recommended allocation is 15% to constant maturing Treasurys and fixed-to-float bonds, 30% to LEAPS and ETFs that are short Treasurys, 30% to a short-duration laddered portfolio, and 25% to cash.

But rebalancing is only the first step, and it assumes an inflationary environment. What would happen if we got hit with deflation instead of inflation? An extended deflationary spiral, the authors believe, is a tail-risk event, but the investor should make contingency plans just in case. “Should the deflationary forces begin to swell, the most profitable bond trade is to buy zero-coupon long-term Treasury STRIPS—but only for those who can take the risk. For those who prefer to avoid such a gamble, buy long-term U.S. Treasury bonds that pay coupons.” (p. 52)

Many of the strategies outlined in this book require significant capital. For instance, in an emergency triage of their bond portfolio El Greedo and Neo Fyte get out of nearly $5 million in problem positions. Small investors can’t make such targeted decisions, especially since most are invested in managed bond funds, which the authors consider particularly vulnerable. So what’s the small investor to do? The authors recommend replacing these funds with specialized funds, such as bond unit investment trusts and floating rate funds. Or, if the bond market starts to tank, allocating some of the portfolio to inverse bond ETFs.

The bond market winter won’t last forever; one day green shoots will begin to appear again. The authors spend about a quarter of the book explaining how to recognize the incipient signs of recovery and how to rebalance into bond market prosperity. So, despite its title, the book pretty well covers an entire cycle in the bond market.

Spreadsheets dot the book, all created in an Excel workbook that is available to purchasers of the book for free download. It “allows you to consolidate all of your bond brokerage accounts in a single analytical spreadsheet system [and] provides a variety of essential bond information presented in easy-to-understand formats, language, and reports.” (p. xiv) The appendix to the book explains how to use it.

Wednesday, April 13, 2011

Marston, Portfolio Design

Richard Marston’s Portfolio Design: A Modern Approach to Asset Allocation (Wiley, 2011) was written for sophisticated investment advisors, especially those with high-net-worth or institutional clients. Marston, a professor at the Wharton School, has taught asset allocation to over 5000 financial advisors as part of Wharton’s Certified Investment Management Analyst program.

The book is thoroughly researched and precisely written, which means that even intellectually curious individual investors with a decent-sized portfolio could profit from it. There’s no quant hurdle since it presupposes only a passing familiarity with statistics (basically, correlation and standard deviation). The book is chock full of parsed data, particularly useful for those who ascribe to some version of buy-and-hold or the endowment model of investing. Marston is no market timer.

We encounter the usual suspects in asset allocation: small-cap vs. large-cap stocks, value and growth investing, foreign stocks, emerging markets, bonds, hedge funds, venture capital and private equity, real estate, and commodities. In two chapters the author also offers some spending rules for foundations and retirees.

Let’s look at a couple of specific cases. First, does international diversification significantly boost the returns of a portfolio? Let’s say that an investor has a 70/30 portfolio and that foreign stocks are 40% of the total stock allocation (28% of the overall portfolio allocation). U.S. stocks are represented by the Russell 3000 all-cap stock index, foreign stocks by the MSCI EAFE index. From January 1979 (when the Russell data began) to December 2009 the Sharpe ratios of the U.S.-only portfolio and the portfolio with EAFE are identical, so alpha is zero. If the same time period is considered but emerging markets have a one-third weight in the foreign-stock portion of the portfolio after the EM index was launched in 1990, the risk-adjusted return is 0.3% above that of the U.S.-only portfolio. Not exactly a show stopper.

Summarizing these findings as well as findings from earlier in the book, Marston writes: “The results above suggest that we will have to search more widely for assets to enhance portfolio performance. Diversifying into a range of investment-grade bonds does not add much to portfolio performance. Neither does diversifying the U.S. stock portfolio into small caps and mid caps. It’s true that international stocks do enhance portfolio performance, but less than they did in earlier sample periods. We need alternative investments to improve portfolio performance.” (p. 150)

So, moving on to alternative investments, what about a passive investment in commodities (as measured by the GSCI or DJ UBS)? To make a long story short, “in the recent period, in particular, [Feb 1991-Jun 2009] there is only a weak case for diversifying a portfolio with a passive investment in commodities. Despite having a very low beta, it’s not a miracle drug for the portfolio.” (p. 249)

Managed futures are best compared to hedge funds; “after all, an investor in managed futures funds does not even know whether he or she is long in commodities.” (pp. 252-53) Even here, managed futures indexes have underperformed comparable hedge fund indexes. Still and all, they generate enough alpha that “managed futures should be considered as a possible strategy in a hedge fund portfolio.” (p. 253)

It’s positively obscene to reduce such a rich book to a one-line conclusion, and I’m sure the author would violently disagree, but here goes anyway. Talent trumps indexes. If you can pay for genuine talent, especially in the area of alternative investments, your portfolio may well outperform. If you can’t, agonizing over how to diversify your portfolio (and sticking with that decision over the long haul) may not be worth the mental effort. Without “meddling,” whether through rebalancing or market timing, your diversified portfolio will probably offer only middling improvements in your returns in the long run. But if you yourself are genuinely talented and not just overconfident, whether you are managing your own account or other people’s money, Marston’s book belongs in your library. He’s done the meticulous research you can build on.

Tuesday, April 12, 2011

Bigalow, Profitable Candlestick Trading, 2d ed.

Ten years after the first edition of the highly acclaimed Profitable Candlestick Trading: Pinpointing Market Opportunities to Maximize Profits appeared, Stephen W. Bigalow is back with a “new and improved” second edition. It is a thorough, clear presentation of reversal and continuation patterns, some familiar to those who have read Steve Nison’s work, others less well known.

As a catalogue the book excels. But it is far more than a catalogue. Combining candlesticks with stochastics and volume (and occasionally other technical “tells” such as trend lines and moving averages), the author takes the reader through some profitable trades and explains how many false signals can be eliminated. He outlines trading programs and describes the ways in which candlesticks can be used to improve Elliott Wave analysis.

What are some of the patterns that have performed particularly well in the last ten years? Bigalow singles out two for special mention.

First, the left/right combo, which triggers a long entry when a doji (or series of dojis) in the oversold condition is followed by a bullish engulfing signal. To the downside a doji (or series of dojis) followed by a bearish engulfing bar is expected to produce a very strong price movement.

The second pattern is the belt hold. Let me quote Bigalow’s description. “The Bullish Belt Hold is a long white candle that has gapped down in a downtrend. From its opening point, it moved higher for the rest of the day. … The Bearish Belt Hold is just the opposite. It is formed with a severe gap away from the existing uptrend. It opens at its high and immediately backs off for the rest of the day. … The longer the body of the Belt Hold, the more significant the reversal.” (p. 78)

Bigalow also ventures beyond candlesticks with the T-line (where “T” stands for “trigger”), a not so fancy name for the 8-period exponential moving average. One of Bigalow’s earliest private students devised buy and sell rules using candlesticks, stochastics, and this moving average. “His research indicated that a Candlestick buy signal in the oversold condition, followed by a close above the T-line, produced an extremely high-probability result. The uptrend would remain in progress until the appearance of a Candlestick sell signal and a close below the T-line.” (p. 320)

Bigalow makes no attempt to systematize candlestick trading, so the reader who wants to have an idea of the kinds of results that can be achieved has to do his own backtesting. With most software packages that’s easy enough.

Overall, traders and investors who are interested in incorporating candlestick analysis into their playbooks have a first-class guide in Profitable Candlestick Trading. Will you end up like the man in one of Bigalow’s epigraphs, a Yiddish proverb? “With money in your pocket, you are wise and you are handsome and you sing well too.” Not simply by reading this book. Alas, as always, the real work begins when you have finished it.

Monday, April 11, 2011

Koppel, Investing and the Irrational Mind

Robert Koppel’s Investing and the Irrational Mind: Rethink Risk, Outwit Optimism, and Seize Opportunities Others Miss (McGraw-Hill, 2011) is not a groundbreaking book, but it’s a darned good read. An engaging, well-crafted page turner which I finished in one sitting. Koppel interweaves findings from behavioral finance and neurology as well as insights from top traders to distinguish between expert/winning traders and novice/losing traders and to hint at how to join the ranks of the former.

In lieu of an “aerial” review of this book, I’m going to share a few points that I found particularly intriguing. I’m sure they reflect my somewhat idiosyncratic interests; others would most likely come away with an entirely different list. There is certainly a lot to choose from.

First, a scary finding from the field of neuroeconomics: that “after two repetitions of a stimulus, the brain automatically expects a third.” Of the many potentially damaging implications Koppel highlights one: “It is no wonder that after two profitable trades, we take it for granted that the next investment will be a sure winner.” (p. 89)

Second, a new word (at least for me): “Pareidolia is a psychological phenomenon involving a vague image or sound that is perceived as being significant. Familiar examples include seeing images of animals in clouds, seeing the man in the moon, and hearing hidden messages on records. It can also involve the subjective perception of instructions embedded in price charts when no such information is really there.” (p. 149

Third, writing about the illusion of control Koppel reports that this illusion “has been observed in games of chance, such as shooting craps, where players tend to throw harder for high numbers and softer for low numbers.” The illusion of control is detrimental to trading profits. For this reason, Koppel recalls, “It used to be a rule of thumb among trading executives, when they were looking to hire proprietary traders, to seek out individuals with successful histories in music, tennis, golf, or basketball. In general, these individuals were trained to think in subtleties, allowing themselves to let go and move with the flow. The need for control usually would not intrude on their performance. As a group, they were unlike former hockey players or football stars, who ached for control. Taking the bull by its horns, they were determined to fight on, no matter what the obstacle.” (p. 165)

Fourth, in a section entitled “Sometimes You Really Should Just Do It,” the author draws on the work of Daniel Gilbert, who studied the performance of golfers. In one study “subjects practiced putting golf balls, and got better as they continued to play. Their game play kept getting better, that is, until they were offered a cash reward for the next shot, and which point their performance fell sharply, as though off of a cliff.” Why the precipitous decline in performance? Part of the reason is that “we pay close attention to what we’re doing when what we’re doing matters, and though close attention is helpful when our task is novel or complex, it is positively destructive when our task is simple and well practiced.” (p. 211)

Finally, Koppel reports on a paper entitled “Exploring the Nature of Trader Intuition,” published in the Swiss Finance Institute’s research paper series and available for download at, among other places, the Social Science Research Network. It suggests that trading success is more a function of being able to read the minds of others (specifically, the ability to attribute to others mental states different from one’s own, an ability known as Theory of Mind [ToM]) than of mathematical ability. Apparently “forthcoming research out of Europe suggests that we may even have certain neurons for interpreting ToM when we can see people and different types of neurons for when we don’t have ‘a visual’ on the person—for example, interpreting through symbols, as we do when we are watching markets and charts.” (p. 218) It seems that science is vindicating the insights of some of the early traders. I wrote a post some time back (Wyckoff on reading the mind of the market) that speaks to this point.

Koppel has done an excellent job of synthesizing a broad spectrum of literature on the ways (and the reasons) we trip ourselves up. He doesn’t have a remedy for all the psychological failings that hurt our bottom line, but he offers some guidelines and even more clues. I personally like clues. They spark our imagination and, as we track them down, may let us carve a more productive space from which to trade.

Friday, April 8, 2011

Coming attractions

Here are some of the titles that I’ll be reviewing in the next couple of weeks:

Koppel. Investing and the Irrational Mind
Bigalow. Profitable Candlestick Trading
Michalowski. Attacking Currency Trends
Cohen & Malburg. Surviving the Bond Bear Market
Marston. Portfolio Design
Elder. The New Sell & Sell Short
Byers. The Blind Spot
Knuth. Trading Between the Lines

So stay tuned.

The secret of success

From this month’s Despair, inc. calendar: What is the secret? Pretend you’ve already achieved it—then offer to sell the secret to others.

Sound familiar?

Thursday, April 7, 2011

Arnett, Global Securities Markets

It’s unclear to me who the intended audience is for Global Securities Markets: Navigating the World’s Exchanges and OTC Markets (Wiley, 2011) by George W. Arnett III. The flap describes the book as a complete Global Investing 101 course (in about 150 pages), but this is definitely not the case. The author, a lawyer, is primarily concerned with the legal structures, regulatory environments, and safeguards of financial markets. Contrary to the book’s title, the U.S. financial system receives the most extensive coverage.

Rather than write about market structure (exchanges and their associated depositories), the history of U.S. regulation, or issues surrounding margin, derivatives, short selling, and prime brokerage—all topics covered in Arnett’s book, I decided to share an interesting case study of how money can move around the world despite governmental constraints.

In 2003 Hugo Chavez imposed currency controls to restrict the flow of U.S. dollars into and out of Venezuela. A Venezuelan national or company that wanted U.S. dollars had to apply to a government agency under the jurisdiction of the Ministry of Finance. The process was lengthy and cumbersome and the kinds and sizes of approvable transactions were limited. Naturally, enterprising souls found a way to introduce “a parallel unofficial exchange regime.” (p. 129) Enter the process of permuta (swap). It’s far more expensive (6.5 to 7 bolivars to the U.S. dollar as opposed to the official change rate of 2.15 to 1), but it gets the job done. Here’s how it works.

The Venezuelan national or company takes the first step by depositing bolivars in the bank account of a local broker-dealer and using the deposited funds to buy a bond denominated in bolivars. The broker-dealer transfers this bond to an offshore entity that typically it has set up itself for the purpose of permuta. The favorite sites are Panama, the Netherlands Antilles, the Cayman Islands, and the British Virgin Islands. In the next step of the transaction the bolivar-denominated bond is swapped for a U.S. dollar-denominated bond held at a second offshore company, and this dollar-denominated bond is sent to the original client. The second offshore entity, which usually has an account at a U.S. bank or broker-dealer, then buys the bond from the client at a predetermined price and wires the proceeds to the client’s U.S. account. And, finally, it sells the Bolivar-denominated bond into the U.S. market. (p. 130)

The process is lawful even if not transparent. At least, it is normally lawful. An exception may arise if the second offshore entity conducts its activity in a U.S. account. “If the sale of the U.S. dollar-denominated bonds is to effect a permuta transaction whereby a U.S. dollar-denominated instrument is converted into U.S. dollars for the express purpose of moving funds from one place to another on behalf of a third party without any market risk to the participants, then the offshore company, if not licensed in the U.S. to provide money transfer services, may be acting as an unlicensed money transmitter under U.S. regulations.” (pp. 131-32)

Although financial firms can help foreign nationals and companies convert their money, even if the task sometimes requires activity bordering on skullduggery, many countries, including the United States, draw a line in the sand when it comes to helping foreign clients evade taxes in their home country. Recently, for instance, the Argentine government cracked down on transactions to and from tax havens. It was trying to stop the flow of so-called blue money and black money, neither reported for tax purposes, to offshore accounts. The tax evaders cannot turn to U.S. firms for help in masking their identities as their money wends its way to a proscribed tax haven. As Arnett writes, “A U.S. financial firm could run afoul of U.S. law if it knowingly assists Argentinian nationals to evade taxes through the knowing facilitation of intermediary transfers. In 2005 the U.S. Supreme Court decided a case called United States v. Pasquantino that established that a plot to defraud a foreign government of tax revenues (in this case, Canadian customs duties on alcohol) that has a U.S. nexus (use of the telephone in the United States) is a federal crime. The ruling overturned established law that one country would not look to enforce the tax laws of another country.” (pp. 139-40)

Wednesday, April 6, 2011

Gutmann, The Very Latest E-Mini Trading,2d ed.

Michael J. Gutmann, a frequent contributor to Futures Magazine, straddles the worlds of discretionary and automated trading. His trade entry setups, though well structured, are discretionary whereas his trade management system is more automated. In The Very Latest E-Mini Trading: Using Market Anticipation to Trade Electronic Futures, 2d ed. (2010) he explains both why he has adopted a hybrid system and what the ingredients of his system are.

Let’s start with the automated side of trading, which is designed to prevent the trader from taking profits prematurely. As Gutmann writes, “We can talk all we want about the importance of trading with the trend and achieving winning runners, but it seems that without some external, automatic mechanism as a guide … , we just can’t not take certain profits. Perhaps what’s important is to recognize this fact and then find the right tools to deal with it.” (p. 247)

Gutmann, using NinjaTrader, employs a three-tiered strategy for trading ES—an initial 10 tick stop loss for all targets, two defined targets (4 and 6 ticks), and a third target that will be trailed with Invivo.Stops. If the market accommodates, the trade will be managed mechanically. There are, however, two occasions on which the trader can override the trailing stop. First, if indicators (the author is particularly fond of his statistical MACD) point to a reversal, the trade can be closed manually before the stop-loss triggers. Second, if the market is trending strongly, the stop may be moved farther away than the software would dictate.

In placing trades as well as in managing them Gutmann stresses the importance of market architecture. What kind of a day is it? Is it, to use the terminology of market profile theory, a non-trend, normal, neutral, double-distribution, or trend day? Where is price relative to the session’s first hour price range or to the point of control? What is volume (Gutmann relies on his cumulative ticks indicator) telling us? Are there any discernible price patterns? What time of day is it?

Answering these questions helps the trader anticipate price movement. And anticipation, the author argues, is essential to success. “Anticipating the market rather than chasing it means using orders set ahead of the market (Limit or Stop Market) to open positions, and at prices that are predefined by the day’s architecture of price action.” (p. 262)

Gutmann packs his book with trade examples complete with charts, which is great. Unfortunately, since he is not a wordsmith, he uses acronyms to identify his trade setups and market conditions. For instance, MML is momentum move with ledge, BOP is breakout pullback, IB RE is initial balance range extension, and RBS is resistance becomes support. For me, at least, it was something of a chore to remember the acronyms; I often had to refer back to the earlier text.

The Very Latest E-Mini Trading is not a book for those who want instant gratification. On the contrary, it demonstrates the necessity of experience, analysis, trial and error, creativity, testing, more experience, more analysis—and the beat goes on. But there is a lot of useful material in this book to help the trader along the way. The developmental and statistical work Gutmann himself undertook will save the trader time (I particularly appreciate his trade management directed graphs), the sample playbook is an excellent guide, and the discussion of market architecture brings home the importance of context. It may not be the easiest book to read, but then who ever said that learning to trade well was easy?

Tuesday, April 5, 2011

Masonson, All About Market Timing, 2d ed.

“If you were in a leaking boat,” Leslie N. Masonson writes, “you’d have three choices: 1. Stay in the boat and stop the leak = Go short. 2. Get out of the boat = Switch to cash. 3. Go down with the ship = Buy-and-hold.” (p. 60) In this second edition of All About Market Timing: The Easy Way to Get Started (McGraw-Hill, 2011) Masonson explains why market timing is superior to buy-and-hold and describes some timing strategies that have been profitable in the past.

Most people, I assume, would prefer market timing to buy-and-hold—if it really were a viable strategy. The main argument against timing is that it can’t be done. The investor will end up being out of the market on the best days, in on the worst days, and poorer for his efforts. Better just sit there, say the critics, take your lumps in bear markets, and trust that the market will eventually power ahead, taking you along with it. Unfortunately the market can be very slow to recuperate from downdrafts, as the author documents in several tables.

Masonson presents five familiar market timing strategies: the best six months, presidential cycles combined with seasonality, simple moving averages, the Value Line 3 and 4 percent, and the Nasdaq Composite 6 percent. These strategies are best pursued using ETFs rather than individual stocks or mutual funds.

Performance summaries for each of these strategies (and variations on them—for instance, using daily versus weekly data, leveraging, and tweaking the seasonal approach) are included. Some of the summaries are updated through 2010, and some come with equity curves for the more visually oriented.

Where the performance of a particular strategy has degraded over time, Masonson offers an alternative. The Value Line 4% strategy, which triggers a buy signal when the Value Line Composite Index rises 4% from its last market low and a sell signal when it declines 4% from its last market top, performed well for quite a spell but then turned in mediocre results (although it still beat buy-and-hold). Between January 28, 2000 and January 12, 2001 the weekly strategy signaled 15 trades, of which 14 were losers; the daily strategy over roughly the same time period experienced 18 losers out of 20 trades. A 3% weekly strategy would have outperformed dramatically. Of course, this is 20/20 hindsight, and we don’t know how well a 3% strategy will deliver in the future.

In the book’s final chapter Masonson highlights some market timing newsletters, web sites, and advisors. Most of these are by subscription only—no free lunch, it seems, in the market timing world.

All About Market Timing is an introductory text, but it’s an excellent place to start to weigh the pros and cons of trying to time the market.

Monday, April 4, 2011

Dormeier, Investing with Volume Analysis

In addition to his “real” job managing money, Buff Pelz Dormeier develops technical indicators. He shares some of the fruits of his—and his noteworthy predecessors’—labor in Investing with Volume Analysis: Identify, Follow, and Profit from Trends (FT Press, 2011).

When I started reading this book I suspected that it would be like so many others: long on generalities and short on actionable ideas. The first hundred pages or so do indeed deal with general relationships between price and volume, and some of the material is familiar. But even the familiar material is often presented in an unusual way. Here’s one example.

Newton’s second law of motion, reinterpreted to apply to financial markets, analyzes “how much volume (force) is required to move a security (the object) a given distance (price change) at a given speed (acceleration/momentum). … Richard Wyckoff referred to this principle as the law of effort versus result, which asserts that the effort must be in proportion to the results.” (p. 47) As a corollary of this law, “if more volume (force) is required to produce less price change (acceleration), then the stock is becoming overly bought or sold.” (p. 85)

In apparent contradiction to Wyckoff’s law of effort is the rule of trend volume, according to which “more volume substantiates a stronger trend.” (p. 85) Can these two principles be reconciled? Dormeier suggests that they can, once we bring the notions of strong hands and weak hands into the equation. His discussion is too detailed to summarize here, but it is premised on how strong hands and weak hands play the game. As he writes, “Strong hands buy out of an expectation of capital appreciation. Weak hands buy out of greed and the fear of missing out on an opportunity. Weak hands sell from the fear of losing capital. Strong hands sell to reinvest in better opportunities (which does not have to be other equities).” (p. 87)

Dormeier really hits his stride when he turns “general volume principles into indicators with numerical values.” (p. 113) These indicators have a dual mandate—to lead price and to confirm price. But they don’t all work the same way; they are “tools, each of which is designed to explain a distinct piece of the volume puzzle.” (p. 117)

The author differentiates seven types of volume indicators; put otherwise, “volume indicators provide information in seven different ways.” The types (or ways) are: pure volume, volume accumulation based on interday price change, volume accumulation based on intraday price change, volume-price range indicators, price accumulation based on volume, tick volume, and volume-adjusted price indicators. He devotes brief chapters to each of these types of indicators, acknowledging their creators, describing their construction, and judging their usefulness. Perhaps the most bizarre are the price-volume charts created in the 1950s by Benjamin Crocker; they form “lines that resemble a toddler’s drawings on an Etch-a-Sketch.” (p. 124)

Dormeier’s own contributions lie in the realm of volume-weighted price indicators. Most notably, volume-weighted moving averages, volume-weighted MACD, the trend thrust indicator, and the volume price confirmation indicator. He has also devised a trailing stop that combines the VPCI with Bollinger Bands. And, to resolve the “significant disconnect between the relationship of the price index to the index’s volume totals,” (p. 227) he introduces the reader to cap-weighted volume. He explains how to construct each of these indicators.

The returns for Dormeier’s indicators are impressive. The only problem is that he developed them some time ago and tested most of them on data from the 1990s and the early 2000s. He did not update the backtests for this book, so I have no idea what kinds of results they would have produced over the last five years or even the last year.

Some people argue that volume analysis is really a thing of the past now that we have high-frequency trading adding substantially to volume totals. The author thinks not. “Non-directional trading,” he writes, “does not directly affect volume analysis” (p. 302) and the secular growth in volume will have virtually no impact on short- and intermediate-term volume analysis.

Investing with Volume Analysis is an important work for anyone who wants to incorporate volume indicators into a trading system or systems. Dormeier explains the theory, offers indicators for testing, and even describes some interesting ways to segment market data for purposes of testing. For those who think that volume bars at the bottom of the chart say everything there is to say on the subject, this book will be an eye opener.

Friday, April 1, 2011

Bennett, Day Trading Grain Futures

At the core of David Bennett’s Day Trading Grain Futures: A Practical Guide to Trading for a Living (Harriman House, 2009) is a single breakout strategy. It’s a strategy that incorporates not only entry rules but also position sizing, risk management, and exit rules. In page after page, chart after chart, the author drills the reader on his strategy and its fine points—and how to use Interactive Brokers platform to execute the trades. (Since the IB platform is ever evolving, this book should not be used as a TWS manual.) The result is one of the clearest examples I’ve encountered of how a trader plies his craft.

Bennett is an Australian resident who fights time zones to trade the U.S. grain markets—corn, beans, and wheat. The market session for the grains is from 9:30 to 13:15 CST, which means that show time in Australia is after midnight. Bennett interrupts his sleep to make at most a single trade.

As a breakout trader, the author stalks support and resistance ranges. One end of the range is the breakout level. The other end of the range has to be determined by a rule. In the case of a long trade, it is “the low of the last candle which had a lower low and lower high than its immediately preceding candle.” (p. 51) The range (r) is used to set a stop loss and profit target—for example, a stop at somewhere between 0.5r and 1r and a profit target between 1.5r and 3r.

As a day (or night) trader who values his sleep, Bennett enters not only a stop order and a profit taking order; in case neither one triggers, he also enters a “good after time” order to make sure he is flat at the end of the session. Of course, these three orders have to be grouped (one cancels all). So, if he drifts off to sleep, his orders are resting in the market or at his broker; he will either be stopped out, reach his profit target, or the trade will be closed just before the end of the session.

Bennett devised an Excel spreadsheet calculator (which he sells on his web site but which even I could easily recreate). Once the user has entered the stop factor (say, 0.5), the profit factor and the entry price, the spreadsheet automatically calculates the stop and the target levels as well as the potential profit and the trade risk in dollars. And, assuming that the trader uses a fixed risk model, the spreadsheet will calculate the maximum number of contracts the trader should buy or sell. There’s more data in the spreadsheet, most notably the daily limit for the traded product and the required margin, but you get the idea. As Bennett explains, “Once a trading session starts, … I don’t want to be in a position of writing down ranges, calculating stop and target levels by hand, or manually working out how many contracts I can take.” (p. 63)

Some might view Bennett’s trading plan as overly simplistic, but I don’t think the author would consider this to be a valid criticism. As he writes, “The trading style presented in this book is not sophisticated, but it is nevertheless built from strong bricks.” Moreover, he continues, “Trading is the constant repetition of a relatively simple process, striving for perfect implementation. It is a case of doing the same, simple thing really well, day after day after day.” (p. 146) Day Trading Grain Futures is an exemplary account of this approach to trading.