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 dot.com 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.

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.

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.

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.

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.

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.

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.