Happy New Year

Have a very happy, prosperous 2011!

Lien, The Little Book of Currency Trading

I am not a forex trader, nor do I aspire to become one. Nonetheless, I am interested in currencies, so I decided to read Kathy Lien’s The Little Book of Currency Trading: How to Make Big Profits in the World of Forex (Wiley, 2011). This is the sixteenth volume in Wiley’s “little book” series.

Lien covers a lot of ground, from the basics of forex trading to one of her favorite trade setups, from trade management to identifying scams, from having a trading plan and a contingency plan to the top ten mistakes traders make (including, my personal favorite, becoming a demo billionaire). Often she proceeds by way of analogy. For instance, she highlights the difference between a trader and an investor by analyzing the behavior of those New York City taxi cab drivers who pay medallion owners a fixed sum per week for the right to drive a 12-hour night shift: some speed down city streets looking for as many “lower value” fares as possible, others wait patiently at JFK for the few “higher value” fares.

Since readers are always searching for ways to make outsized gains in the markets, I’m going to accommodate today. Well, that’s a gross overstatement. More accurately, I am going to share two practical suggestions that Lien makes on “how to make big profits in the world of forex.”

First, she describes her Double Bollinger Band Method, where the bands are set to one and two standard deviations above and below the 20-period moving average. These double bands, Lien argues, “can be used for identifying whether the currency is in a range or trend, if and when a trend has exhausted, where to find value within the trend, and how to get into a new trend.” (p. 108) I’m not going to steal her thunder. I assume that anyone who is savvy in technical analysis can hypothesize the outline of some of her tactics, if not their details.

Second, she disputes the common claim that traders must maintain at least a 2 to 1 reward to risk ratio. “An overly ideal risk to reward ratio encourages traders to try and take more from the market than is being offered and may encourage scalpers to use excessively tight stops.” (p. 100) Instead, she advocates trading with a negative edge, entering with a double lot and scaling out in two steps. Why adopt a mathematically inferior strategy which needs to be successful at least 60 to 70 percent of the time? Because, she writes, “it is psychologically more palatable, and trading at its core is always more psychological than it is logical.” (p. 103)

The Little Book of Currency Trading emphasizes the practical over the theoretical. Although it’s written for forex traders and investors, much of it is applicable to traders and investors in other markets as well. It’s a quick, lively read; it’s informative and concrete. It may not be a classic, but it’s definitely worth a look.

Digging out, very slowly

The to-do list that started to be checked off before dawn: There are huge sand dunes around my car, except they’re white. And then there’s the area where Delta, the geriatric basset hound, stretches her legs and relieves herself. Not to mention the walkway to the heating oil and propane tanks. I leave the driveway to the professional, who plows when he’s finished his “important” clients. After which, if I don’t shovel, the driveway remains impassable. And it’s a very long driveway. Well, you get the idea.

Unlike many people in my Connecticut town, I didn’t lose power. Which was a godsend, because no electricity also means no heat and no water. Unfortunately the cable connection was down more than it was up, so it was a frustrating day.

The best I can offer you today is a link to a Harvard Business Review blog post by Tony Schwartz from August: "Six Keys to Being Excellent at Anything." It doesn’t break new ground, but it might inspire some New Year’s resolutions.

Santa reading “The Holy Grail of Trading”

In case you didn’t notice, the page is blank.

The happiest of holidays to all my readers.

Durbin, All About Derivatives

All About Derivatives (McGraw-Hill, 2011, a fully revised second edition) is a curious book, and I don’t say that unkindly. It’s just odd that in a book in the “All About” series, touted as “the easy way to get started,” you find such a lengthy discussion of options pricing. But then Michael Durbin is, among other things, a financial technology consultant specializing in high-frequency trading of financial derivatives, and he has helped numerous Wall Street firms develop derivative pricing and trading systems.

The structure of this book is straightforward. After an overview chapter, the author devotes a chapter each to forwards, futures, swaps, options, and credit derivatives. He then looks at using derivatives to manage risk, pricing the various derivatives, hedging a derivatives position, and derivatives and the 2008 financial meltdown. In three appendices he investigates interest, swap conventions, and binominal option pricing.

Even though this book would be a fine introduction to the subject of derivatives, it often goes beyond the elementary. For instance, Durbin points out the subtle pricing differences between warrants and options. Moreover, the book is laced with interesting tidbits. I didn’t know, for example, that Enron issued a series of credit-sensitive notes in 1998 that offered a coupon rate inversely tied to its credit rating.

For options traders who want to delve a little more deeply into pricing models, Durbin offers a gentle account in the text, coupled with a more mathematical description in an appendix. He explains why Black-Scholes cannot be used to determine the value of every type of option. Yes, it was meant to apply to European-style options, and there are other choices for American-style call options. But, he writes, “for American puts, Black-Scholes is simply not a choice. You must use a binomial tree method because an analytical method for pricing an American put option simply does not exist. An analytical solution is one in which you plug factors into a function and get a result. A nonanalytical method is more of a brute-force or trial-and-error approach, which the tree method really is.” It seems that the absence of an analytical solution to pricing American-style puts is an example of a “free boundary” problem. “These things,” Durbin continues, “are hard, like trying to predict precisely where water will flow when poured from a bucket onto a flat surface.” (p. 172)

All About Derivatives is a survey of a world that nearly everybody caught a glimpse of after 2008, but Durbin gives it structure and some mathematical clarity. It is a how-it-works book, not a how-to book. The trader in search of a quick buck will be disappointed. I was not.

Schreiber and Stroik, All About Dividend Investing

What’s all the fuss over dividends? Do they really make that big a difference? In All About Dividend Investing, 2d ed. (McGraw-Hill, 2011) Don Schreiber, Jr. and Gary E. Stroik argue that they make a huge difference. In a classic dividend story they compare the portfolios of twins who were each given $10,000 in 1944 to invest in companies that made up the Dow Jones Industrial Average. The twin who spent his dividends each year had a portfolio worth $767,000 in 2009; he spent more than $370,000 in dividend income from 1944 through 2009.The conscientious twin reinvested his dividends until he retired in 1984 and needed his dividend income to help support his lifestyle. By the end of 2009 his portfolio was worth more than $4.7 million, and since 1984 he had collected more than $1.7 in dividends. So the first twin realized a little over $1 million from his initial gift; the second, about $6.5 million.

Dividend stocks are often recommended in down cycles. In the particular cycle the authors picked (or cherry-picked) $100,000 invested in the DJIA Index in 1966 would have declined to $90,275 by 1981. Had a person reinvested dividends, thereby acquiring more shares as prices were falling, the account would have been worth $186,661 in 1981. And had he taken his dividends in cash, he would have received $64,978 over those years; instead of losing $10,000 he would have netted about $50,000.

In bull markets dividend-paying stocks may underperform the more speculative non-dividend-paying growth stocks (in 1999 the NASDAQ gained 85% while the DJIA advanced only 25%). But with dividends reinvested the return would have increased substantially. An investment of $100,000 in the DJIA in 1982 would have been worth $1,302,760 at the end of 1999; with dividends reinvested, the value would have been $2,056,109.

The authors are writing for the relatively uninformed investor. They offer basic advice on how to screen for stock candidates and how to rank them. They outline alternatives to individual stocks such as folios, ETFs, and mutual funds. They explain simple risk management techniques and write about the current tax treatment of various kinds of dividends.

All About Dividend Investing is a good book for investors who are planning for their retirement needs, although it may not take the place of a financial planner. It offers a model portfolio: 70% dividend payers, 14% tactical choices, 14% noncorrelators, and 2% cash. Within the dividend payers segment the allocation is equally divided into five slices: value, growth, quality, yield, and overall best. But then the reader has to get down to work to find the right stocks to plug into these slices. Otherwise, he can use what he learned to find the right advisor for his needs.

Dion, The Ultimate Guide to Trading ETFs

The Ultimate Guide to Trading ETFs: How to Profit from the Hottest Sectors in the Hottest Markets All the Time by Don Dion and Carolyn Dion (Wiley, 2011) is a workmanlike account of the benefits and pitfalls of investing in ETFs, many of which have been amply documented in the financial press and on blogs. The authors, however, give structure to the tidbits that the investor can pick up from other sources. The result is (contrary to the subtitle) a well-organized, balanced book that should serve the ETF investor well.

Although most investors know the advantages of ETFs over mutual funds, they are undoubtedly less aware of some of their potential disadvantages. The authors begin with the basics: appropriateness, liquidity, and concentration. Consider liquidity, for instance. The authors explain that ETFs have both primary and secondary liquidity. Primary liquidity refers to the liquidity of the fund’s underlying basket of securities whereas secondary liquidity refers to demand for the ETF itself. If either primary or secondary liquidity is lacking or dries up, the ETF “will tend to trade at a noticeable premium or discount” to its NAV. (p. 9)

Domestic, international, and derivative-based ETFs each come with their own sets of complications. International ETFs can become disconnected from their underlying equities because of time-zone differences; futures-based funds can trade at significant premiums to their NAV when position limits are imposed or threatened.

I appreciate a book that exposes the underbellies of trading vehicles since too many investors have a decent investing idea (hedge a winter’s supply of heating oil with an ETF, circumvent the short-selling restriction in an IRA by buying short ETFs, increase leverage with the 2X and 3X ETFs, gain exposure to an individual country with an ETF) without truly understanding the product they are using to execute their idea. How closely does it track the underlying? Is it best used for short-term trading or investing?

The authors stress again and again that the investor has to educate himself. For example, “there is a world of difference between … iPath Dow Jones-UBS Platinum Subindex Total Return ETN (PGM), which is based on platinum futures contracts, and ETFS Physical Platinum Shares (PPLT), which is backed by a physical stockpile of platinum. The word ‘platinum’ is the only thing these two funds have in common. The ways they provide exposure to that market are diametrically opposed.” (p. 152)

The book also has useful appendixes. One ranks all U.S.-listed ETFs and ETNs (as of April 30, 2010) on a scale of 1 to 5, a scale which is intended to be a guide to their complexity. A second is a tax guide for ETF investors. Yet another appendix offers sample portfolios for various trader/investor types.

The Ultimate Guide to Trading ETFs is not a revolutionary book. But any ETF investor who is not familiar with all of the material included in it is bound to stumble.

Waltzek, Wealth Building Strategies in Energy, Metals, and Other Markets

I have many vices, but listening to talk radio (Internet or otherwise) is not among them. Reading Chris Waltzek’s Wealth Building Strategies in Energy, Metals, and Other Markets (Wiley, 2010) doesn’t tempt me to change my mind. Waltzek is the host of Goldseek.com Radio, a weekly two-hour broadcast. He has thousands of enthusiastic followers, some of whom have written glowing reviews of this book on Amazon.

Well, it’s certainly different from the run-of-the-mill investment book. Where else can you read about survivalist techniques to ensure against food shortages and rationing, commonplace in times of rampant inflation? If you really want to know, “a home-based safety net can be purchased for less than $5 per week, by simply adding a few canned items and/or a 5 lb. bag of rice to the grocery store shopping cart on each visit.” (p. 79) And then there’s the home garden, which I happen to have but never viewed as a key to survival in the event of runaway inflation. Waltzek even explains how to grow potatoes which, “pound for pound of yield, … requires 75 percent less garden space than does grain or rice.” An interesting statistic, but how many home gardeners grow grain or rice? Perhaps more telling, “Since potato tubers grow underground, unlike tomatoes, corn, and so on, hungry neighbors are far less inclined to borrow a meal without express written permission.” (pp. 79-80) He also recommends replacing credit cards with a cash emergency fund, best kept in a fireproof home safe in the event of a prolonged bank holiday.

It is within this “build the bunker” framework that Waltzek recommends investing in precious metals (especially silver) and energy. “Thanks to Fed monetary gamesmanship the greenback has relinquished 99 percent of its purchasing power since the unconstitutional Federal Reserve seized control of the national money supply.” (p. 47) The United States is following a monetary path similar to Voltaire’s France and risking Voltaire’s doomsday prediction: “Paper money eventually returns to its intrinsic value—zero.”

Waltzek also devotes considerable space to the housing crisis and offers rules of thumb that “every home hunter needs while stalking real estate prey” in 2012. And for those not familiar with Sun Tzu’s The Art of War and the uninspired Sun Tzu’s Art of War for Traders and Investors, Waltzek provides a few summary points.

“Standing on the shoulders of the great philosopher and mathematician, Vilfredo Pareto, as well as Taleb and Mandelbrot,” the author presents his major theoretical contribution: the Pareto-Waltzek Hypothesis. It comes in the form of two rules. First, “although prices typically gyrate in a random manner, eventually all markets enter protracted trends.” (p. 10) And second, “all primary market movements (trends) are the result of at least one fundamental event, the significance of which is rarely recognized at the time.” (p. 13) Punkt.

If you are anti-government and anti-Fed, and if you think it’s essential to prepare for a financial Armageddon, you may like this book. If you really want to learn about commodity investment strategies, much better alternatives are available.

Bogle, Don’t Count on It!

Don’t Count on It!: Reflections on Investment Illusions, Capitalism, “Mutual” Funds, Indexing, Entrepreneurship, Idealism, and Heroes (Wiley, 2011) is an anthology of recent writings and speeches by John C. Bogle, the venerable founder of Vanguard. It is a substantial book, over 600 pages long, and, as its subtitle indicates, covers a range of topics. Here I’m going to confine myself to two. I’ll begin by exploring three principles that underlie Bogle’s well-known case for low cost passive index funds. Then I’ll jump to the lecture he gave to the Risk Management Association in October 2007: “Black Monday and Black Swans.”

Why, according to Bogle, is it preferable to invest in broad index funds rather than actively manage a portfolio? First, “the past is not prologue” (p. xxiii) or, put another way, “historic stock market returns have absolutely nothing in common with actuarial tables.” Bogle continues, quoting Keynes: “’It is dangerous to apply to the future inductive arguments based on past experience [that’s the bad news] unless one can distinguish the broad reasons for what it was’ [that’s the good news]. For there are just two broad reasons that explain equity returns . . . (1) economics and (2) emotions.” (p. 7) The math here is blissfully elementary. Add earnings growth and dividend yield to get investment return. Calculate the percentage increase in the P/E ratio to get the speculative return. Add investment return and speculative return to get total return. “In the short run,” Bogle writes, “speculative return drives the market. In the long run, investment return is all that matters.” (p. 66)

Second, actual investor returns and theoretical market returns are miles apart. About 98 percent of the theoretical return of $212,000 on a $1,000 investment 50 years ago would have gone up in smoke as a result of inflation, intermediation costs, and taxes (and here Bogle assumes a hit of only 2% for taxes). We end up not with $212,000 but a mere $4,300.

Third, we should respect the power of reversion to the mean: “reversion to the mean is the rule, not only for stock sectors, for individual equity funds, and for investment strategies that mix asset classes, it is also the rule for the returns provided by the stock market itself.” (p. 65) A chart showing the investment real return of $1 versus the market real return (1900-2009) nicely illustrates this point.

Now on to Bogle’s lecture given on the twentieth anniversary of Black Monday (October 19, 1987). In this lecture Bogle reviewed the literature on risk and uncertainty: Popper, Knight, Mandelbrot, Keynes, and Minsky. Elaborating on Minsky’s prediction that the financial economy would come to overwhelm the productive economy, Bogle said: “When investors—individual and institutional alike—engage in far more trading—inevitably with one another—than is necessary for market efficiency and ample liquidity, they become, collectively, their own worst enemies. While the owners of business enjoy the dividend yields and earnings growth that our capitalistic system creates, those who play in the financial markets capture those investment gains only after the costs of financial intermediation are deducted. Thus, while investing in American business is a winner’s game, beating the stock market—for all of us as a group—is a zero-sum game before those costs are deducted. After intermediation costs are deducted, beating the market becomes, by definition, a loser’s game.” (pp. 177-78)

In this lecture he also pointed to the staggering growth of the financial sector. Financials accounted for only about 5 percent of the earnings of the S&P 500 25 years ago; in 2007 that figure was 27%. Adding in the likes of GE Capital and the auto-financing arms of GM and Ford, he figured that financial earnings probably exceeded one-third of S&P 500 annual earnings. This growth was spurred by the explosion in intermediation costs and the boom in complex financial instruments.

By October 2007 banks were beginning to cut the values of their mortgage-backed portfolios, a clear sign that systemic risks were rising. But how, Bogle asked, “can it be that risk premiums on stocks are at less than one-half the historic average?” He quoted Alan Greenspan, who said in 2005: “History has not dealt kindly with the aftermath of protracted periods of low risk premiums.” (pp. 182-83) Indeed.

Don’t Count on It! is a wise book. As most traders and investors remain convinced that they can beat the market, it’s always sobering to hear a compelling voice from the other side.

Rotblut, Better Good Than Lucky

It seems that Lefty Gomez, who played for the Yankees in the 1930s, gets credit for having said “I’d rather be lucky than good.” Charles Rotblut turns this around in his book title: Better Good Than Lucky: How Savvy Investors Create Fortune with the Risk-Reward Ratio (W&A Publishing, 2010). His central tenet is that being a successful investor is about making good decisions, not about being lucky.

In this slight book Rotblut introduces the beginning investor (as well as the investor who is trying to rejigger his portfolio in a more thoughtful way) to the rationale for value investing and to some of its basic principles.

“One reason,” he writes, “why stock prices rose too much in the 1920s and the 1990s—as well as other periods—was that forecasts were given more weight than valuations.” (p. 9) Analyst forecasts usually have about as much predictive value as the divination that comes from reading entrails. “Placing an emphasis on valuation provides a margin of safety against making mistakes.” (p. 10)

Rotblut takes the reader through the fundamentals of corporate analysis: business models, the balance sheet, income statement, and cash flow statement. He then cuts to the chase and offers what he considers the two most profitable measures of valuation (price-to-book and price-to-earnings) and “a sanity check to ensure you are not overpaying for a stock” (discounted cash flow).

Book value, the theoretical value of a company’s net assets or equity, is according to many studies the best valuation measure of a stock’s performance because “no quality company should sell for a price equivalent to or less than its theoretical liquidation value.” (p. 123) But the P/E multiple should not be ignored, since a high P/E increases the possibility of downside risk whereas a low P/E increases the potential for upside reward. DCF, a mathematical model that calculates the current worth of a company’s future cash flows and that is most often invoked to calculate a stock’s price target, should be used not “to determine a stock’s worth, but whether a stock is undervalued or overvalued relative to its projected future cash flows.” (p. 166) As rules of thumb Rotblut recommends looking for stocks trading at a P/B multiple of 2.0 or lower, a P/E of 12 or lower, and a discount of 10% or more to their DCF-calculated value.

Better Good Than Lucky is an entry-level book. In addition to its discussion of value investing it explains where to get investment advice, how to apply modern portfolio theory, and how to own stocks and still sleep at night. Rotblut, by the way, makes one recommendation that should be followed by everyone, quite independent of investment style: keeping an investing journal, writing down the reasons you bought each stock as well as the factors that would cause you to sell it.

Investors who want a meaty book would be better served with John Price’s The Conscious Investor. But for those who want a quick and easy introduction to value investing, Rotblut’s Better Good Than Lucky is an excellent choice.

Statman, What Investors Really Want

Meir Statman’s What Investors Really Want: Discover What Drives Investor Behavior and Make Smarter Financial Decisions (McGraw-Hill, 2011) is a book that every investor should read. Statman is an academic, but he writes like a best-selling author. He uses the findings of behavioral finance, in which he himself has done extensive research, to expose the mistakes we make and to offer advice that ranges from the “ka-ching” practical to the rabbinical.

For those who are acquainted with the mainstays of behavioral finance literature, let me assure you that there’s a lot of new material in this book. Even where Statman covers familiar ground, he does it in such a winning way that he often unlocks something that was hitherto unknown, or repressed.

He uses the World’s Work, a magazine published a century ago, as well as Internet ads to illustrate his points. He retells stories about such characters as the notoriously stingy Russell Sage; he writes about herding from China to Finland, from librarians to institutional investors. He explores the rationalization that allows investors to find it easier to sell losers in December than in November: “What is framed as a loss in November is framed as a gain, in the form of a tax deduction, in the following December.” (pp. 142-43)

Statman also ventures into world of values because ultimately, he argues, “investments are about life beyond money.” He explores socially responsible investing, our demand for fairness, and our investments in our children and families.

All in all, this is a rich book—and a book that might make you richer in a multitude of ways.

Standard & Poor’s 500 Guide, 2011 Edition

This is a very big paperback—8 ½” x 11”, more than 1000 pages, and weighing in at about 4.5 lbs. With so much information available online, why would anyone need this book? I can think of several compelling reasons.

First, a personal preference: I enjoy flipping through pages, making serendipitous discoveries. I don’t have the same kind of experience online since I normally am looking for something specific, not just seeing what comes my way.

Second, the two pages devoted to each company in the S&P 500 are jam-packed with data, including ten years of company financials (per share data, income statement analysis, and balance sheet and other financial data), five years of revenue and earnings per share, and the five most recent dividend payments. The summary of the company’s business is also more analytical than the run-of-the-mill online fare.

Third, and taking up almost half of the space allocated to each company, is proprietary S&P information, ranging from analysts’ reports to the famous five-star system of investment recommendations. The analysts’ reports, I should note, are not especially timely; some date back to July and the most recent are from October. The book seems to have gone to press in late October; most of the closing prices are from October 22.

Other data include S&P’s qualitative risk assessment, its quantitative evaluation, and each company’s relative strength rank. There is also a price chart from June 2007 through October 2010 overlaid with S&P proprietary metrics.

For the reader who cannot live without stock screens, the book provides lists of companies with five consecutive years of earnings increases, stocks with A+ rankings, rapid growth stocks, and fast-rising dividends.

The book is somewhat unwieldy to handle (it’s definitely best read on a desk, which I personally find awkward), but this is a small price to pay for the amount of information available.

Marr & Reynard, Investing in Emerging Markets

British financial journalists Julian Marr and Cherry Reynard take the reader around the world in 246 pages. Investing in Emerging Markets: The BRIC Economies and Beyond (Wiley, 2010) is an engaging book, well researched and well written. For Americans, it is also refreshing to have a British perspective because so much of the research on emerging markets is done in London. I follow the economy of one country (which fluctuates between emerging and submerging) fairly closely and am constantly being referred in its press to “the analysts in London.”

The authors begin with a sophisticated introduction to the emerging markets, asking such questions as whether globalization and decoupling can possibly occur simultaneously. They analyze the notion of a commodities supercycle (noting in a different context that “in investment, certainty is the rarest commodity of all”). (p. 80) They weigh the benefits and risks of sovereign wealth funds.

Moving on to the BRIC economies, the authors brush aside ideas designed to rationalize grouping the four economies together that “cross the line from the simplified to the simplistic.” Their view is more dynamic. “Suffice to say that the quartet are the flagships of the three main emerging markets regions of Asia, Emerging Europe and Latin America and their importance to global trade over the coming decades is hard to overstate—not least in the way they interact with each other.” (p. 83)

The bulk of the book focuses on individual emerging market economies, including those better described as the “emerged” emerging markets (Hong Kong, Singapore, South Korea, and Taiwan), with a very brief look at the frontier markets. The general format for the more developed economies is a brief economic history followed by a section making the investment case for the country. Sometimes the investment case is weak. Take Argentina, for instance, which “provides a salutary lesson in how not to manage an economy.” (p. 194)

The authors draw insights from a number of emerging markets experts, many of whom highlight the dangers of investing in emerging markets. Throughout the book the authors raise “the spectre of possibilities such as water shortages in China [and] advances in technology derailing demand for certain commodities.” They also quote the risk list of a CIO (abbreviated here): “What happens when interest rates start to rise? … How is the ‘Axis of overspending’ going to finance their projected deficits? Is China the savior of the global economy or its Achilles’ heel?” (p. 222)

Investing in Emerging Markets is a thoughtful, balanced book which offers an overview of regional and country-specific economies. Naturally, anyone thinking about investing in an individual country should seek out far more information than the authors can provide here. Their summaries are but stepping off points. At least they are solid; readers have been given the wherewithal to avoid both slippery slopes and quicksand.

Kiev, Hedge Fund Masters, a second look

I wrote briefly about this book last year but decided to return to it. Ari Kiev, who died just over a year ago, was best known in the trading world as an author and as a coach to traders at Steve Cohen’s SAC Capital Advisors in the early 1990s. Hedge Fund Masters addresses the kinds of traders he coached.

I took notes on Kiev's book when I first read it, and I’m going to select four self-therapeutic passages from them for this post. I suspect that most of my notes are quotations, but I don’t think it’s important to check their accuracy, though I will provide page references.

* * *

By establishing a vision, you have promised to achieve something. The promise means you are giving yourself permission to begin to act in the realm of the impossible, to create all kinds of openings. In that one promise, you begin to abandon self-doubt and the need for approval. This way of being in the world lets loose huge reserves of energy and creates enormous possibilities. Yet none of this can happen until you take the first step forward in pursuit of a goal with no guarantee of outcome. (p. 218)

Living in the gap makes you vulnerable. Once you’re out there, on the cutting edge, you’ll suffer breakdowns as well as breakthroughs. Although it will not always be comfortable, living in the gap between where you are and where you want to be will make your days far more interesting and action packed than if you traded with the intention of avoiding pain and discomfort. (p. 229)

It is useful to note when an activity becomes tedious, dull, and routine and leads to withdrawal and avoidance. This is the time to consider whether you are facing obstacles and are retreating behind your survival needs or whether these feelings signify that you have reached your goal and now need to raise the stakes. (p. 236)

The development of mastery is, in a sense, an existential and experiential methodology, directed at what is and what can be. You invent your own future through commitment to a goal, identifying what is necessary to produce specific results, and learning how to handle the unknown. (p. 247)

McGuire, Hard Money

As the number of books on investing in gold continues to proliferate, Shayne McGuire’s Hard Money: Taking Gold to a Higher Investment Level (Wiley, 2010) stands out in several ways. Most importantly, the author methodically builds a case for gold by analyzing five drivers of potential price appreciation. They are: the increasing likelihood of fiscal crises in major economies of the world, the return of inflation, a small allocation shift into gold by institutional funds, the rise of China, and gold’s potential return to being the dominant financial asset in the global monetary system.

In the second part of the book McGuire describes in some detail the kinds of elements that might be included in a precious metals portfolio as a subset of an overall portfolio—stocks, ETFs, physical metals. He explains how to buy coins, including rare coins. All in all, a good practical guide for the investor.

Here are a couple of points that struck me as worth sharing.

McGuire argues that gold can be viewed as the “youngest major investment asset class” because “it is only since the early 1970s that it started being broadly perceived as an investment.” Before the collapse of the Bretton Woods monetary system in 1971, gold was money; currencies were “receipts that represented and were exchangeable for hard money.” Therefore it makes no sense to evaluate gold as an investment prior to the 1970s. As McGuire writes, “Evaluating it as an investment over this time period would be like examining the return on investment of a dollar bill: Both moved in lockstep by government decree.” (pp. 68-69) Yes, gold would rise in value in response to an economic shock, often triggered by war. But “even during these periods of financial stress, nobody was investing in gold. People were hiding in and accumulating savings in gold, the way they hide in cash to move away from volatile financial markets and keep savings accounts in dollars today. In the past, investing generally involved taking risks by moving away from gold, which was always seen as money. Today is the opposite. For any fund manager, buying gold today means investing, taking risk.” (p. 69)

Although McGuire contemplates the possibility of $10K gold, he warns the reader of the genuine economic concerns that underlie allegations of gold market manipulation by financial authorities. The problem for financial authorities is that “a gold investment wave can suck resources out of the broader economy,” especially bonds, resulting in a spike in interest rates, “and ultimately deflation and another banking system crisis.” (p. 85) We have only to think back to 1933 and FDR’s confiscation of gold.

One final cautionary note from the author. He writes: “Although there are reasons why a gold boom could endure for some time, I think a gold portfolio is something that I, personally, would not maintain as a permanent portfolio in my overall diversified portfolio of assets. I think of it as a portfolio to be maintained in these extraordinary times….” (p. 145)

Katsenelson, The Little Book of Sideways Markets

Vitaliy N. Katsenelson’s The Little Book of Sideways Markets: How to Make Money in Markets That Go Nowhere (Wiley, 2011) is thoroughly enjoyable, not so much for the message as for the thoughtful and often entertaining way in which it is delivered. It is part of the “Little Book Big Profits” series that began with Joel Greenblatt’s The Little Book That Beats the Market in 2005 (recently updated) and now includes fifteen titles.

Katsenelson’s hypothesis is that we will likely be in a sideways market, personified by the cowardly lion, “whose bursts of occasional bravery lead to stock appreciation but are ultimately overrun by fear that leads to a descent,” until about 2020. (p. 3) His reasoning is that we are experiencing earnings growth but continuing P/E compression: the gains we get from earnings growth are wiped out by a decline in P/E ratios. Even though there can be a lot of cyclical volatility, over the long haul stock prices will stagnate. Until the 12-month trailing P/E falls “significantly below the historical average of 15” (by mid-2010 stocks were trading at more than 19 times 2010 earnings) the sideways market will continue. (p. 27)

If this hypothesis is borne out, buy and hold (never a great idea in any environment) absolutely must be replaced with buy and sell. “A disciplined sell process injects a healthy dose of Darwinism … into the portfolio, weeding out the weakest stocks—the ones that have deteriorated fundamentals or diminished margin of safety—in favor of stronger ones.” (p. 164) That is, once the reasons you bought the stock (valuation, quality, and growth) have disappeared, sell and move on.

Katsenelson takes his reader step by step into the mind of the value investor by relating, in a fictional addendum to Fiddler on the Roof, the story of Tevye’s purchase of Golde, the cow. He also describes his own big-time gambling evening (he was willing to lose a maximum of $40) and that of a half-drunken, rowdy fellow blackjack player to stress the importance of process. He then moves on to the fundamental principles of active value investing.

What differentiates this book from so many others on value investing is that it describes, sometimes through the use of case studies, the thinking of a value investor. Not just his models or his metrics but his assessments. Katsenelson is an empiricist who weighs facts, looks for contraindications, and makes decisions. He makes value investing come alive.

This may be a little book, but it’s packed with insights for both novices and experienced investors. And it is a delight to read.

Shaffer, Profiting in Economic Storms

So you woke up feeling pretty good this morning? Well, Daniel S. Shaffer is out to ruin your mood. In Profiting in Economic Storms: A Historic Guide to Surviving Depression, Deflation, Hyperinflation, and Market Bubbles (Wiley, 2010) he foresees a deflationary depression coming between 2012 and 2014. He bases his doomsday forecast on cycle theory, invoking both natural cycles (especially sunspot cycles) and investment cycles. But he warns that “your investment strategy should include disruptions by regulators or politicians that purposely disrupt the natural order of the markets.” (p. 156)

Shaffer pads his book with rather pedestrian discussions of trading psychology, the reliability of economic releases, accounting irregularities, modern portfolio theory, fallen civilizations, the history of the U.S. banking system, and famous market manias. Shaffer is a Fed and Bernanke basher who suggests that “the Federal Reserve should not be in existence in its current form by 2013.” (p. 121)

Unfortunately, Shaffer adds nothing substantive to cycle research. He pays homage to Welles Wilder’s Delta Society, Elliott wave theory, Fibonacci sequences, and Terry Laundry’s T Theory and includes a few charts to illustrate their applications. How he himself arrived at a projected 40-year cycle low of about 3,500 on the Dow Jones Industrial Average, probably in 2013, remains something of a mystery. Nor is it clear why “hyperinflation has a high potential of showing up around 2020.” (p. 201)

Investors should always be on their toes. Listening to one self-styled prophet will probably provide little actionable information.

Fisher, Debunkery

Ken Fisher’s Debunkery: Learn It, Do It, and Profit From It—Seeing Through Wall Street’s Money-Killing Myths (Wiley, 2011) is a welcome antidote to the intellectual pap, often laced with arsenic, that is regularly dished up on CNBC and in financial planning books.

The reader need not and should not agree with Fisher on every point. Nor should he merely store away talking points for cocktail parties or potential zings for his financial planner. Instead, this book should set the investor on a course of independent thinking, during which he honors Santayana’s oft-quoted statement that “skepticism is the chastity of the intellect, and it is shameful to surrender it too soon or to the first comer.”

Fisher debunks fifty myths, ranging from “retirees must be conservative” to “when the VIX is high, it’s time to buy,” from “so goes January” to “pray for budget surpluses,” from “stocks love lower taxes” to “consumers are king.” Here I’ll share two of his “debunkeries” as well as his thoughts on the usefulness of history.

Bunk 12: “Stop-losses stop losses!” Wrong, claims Fisher. “It would be more accurate to call them ‘stop-gains.’ In the long term and on average they’re a provable money loser.” (p. 51) The reason that stop-losses don’t work is that stock prices aren’t serially correlated: “What happened yesterday doesn’t have a lick of impact on what happens today or tomorrow.” He continues: “If stock price movements dictated later movements, you could just buy stocks that have gone up a bunch. But you know, instinctively, that doesn’t work. Sometimes a stock that’s up a lot keeps going up, sometimes it goes down, or sometimes it bounces along sideways. You know that. So why don’t people understand that correctly on the downside?” It should be clear that Fisher is no believer in momentum investing. As he writes, “momentum investors don’t do better on average than any other school of investors. In fact, they mostly do worse. Name five legendary ones. Or even one!” (p. 52)

Bunk 19: “Beta measures risk.” No, Fisher contends, “it measures prior risk. … It doesn’t measure anything about the present or future.” (p. 75) Fisher’s argument again hinges on his claim that price action is non-serially correlated “by definition.” And if price can say nothing about the future that’s exploitable, how could volatility (which is based solely on price action) be useful, academics be damned? It can’t—at least not in the sense that a low-beta stock implies low risk going forward and a high-beta stock implies high risk. But if used in a contrarian way in specific circumstances beta can be a profitable guide. In V-shaped recoveries “those categories that hold up better than the market during the beginning of a bear that then fall the most in back of a bear market (making them high-beta) bounce most in the early stage of the new bull.” Put another way, “Those categories with the best returns after the bottom had the biggest beta at the bottom. They had more volatility to the bottom and more volatility than the market in the new bull! But the way our brains work, we tend to think: When it’s down, it’s ‘volatile,’ but when it’s up, it’s ‘good’!” (p. 77)

Although Fisher readily accepts the notion that past performance is no guarantee of future results and, as we have seen, rails against those who seek patterns in past price action (or volatility) to shed light on future price action (or volatility), he nonetheless believes that history is the “investors’ lab.” Investing, he writes, is not a craft; becoming a master craftsman does not give you an edge. Instead, investors should model themselves on scientists. “In science, you develop a hypothesis, test, confirm, and retest—continuously. It’s a non-stop query session. While investors don’t have a traditional lab like biologists or chemists, they do have history.” (p. 135) By history he means the kind of stuff that happens in the real world and that is easily researched, such as whether gold is a safe haven and whether high unemployment is a stock killer. In this sense, “history is one important tool for shaping forward-looking expectations” (p. 136) and improving the probabilities of profitable investing results.

Debunkery may not be a core library holding, but it’s a fast, often provocative read.

Keeping a trade alive

Perhaps we can all learn something from, or at least be inspired by, this amazing play.

A critique of Granger causality

Continuing the journey that I began with "causation" and continued in "Granger causality and cointegration," today I’m pitting the recipient of a MacArthur “genius” grant against a Nobel Prize winner. Nancy Cartwright, a philosopher of science (no, not the voice of Bart Simpson), claims that the argument structure of Granger causality is “exceedingly simple.” But, she continues, “the premises are concomitantly exceedingly strong.” That is, “every possible source of variation of every kind must be controlled if a valid conclusion is to be drawn.” (Hunting Causes and Using Them [Cambridge University Press, 2007], p. 29)

Her critique is straightforward though stylistically dense. First, we must “suppose that for populations picked out by the right descriptions K_i, if X and Y are probabilistically dependent and X precedes Y then X causes Y. If any population P contains such a K_i as a subpopulation, then X causes Y in P in the sense that for some individuals in P, X will cause Y (in the ‘long run’). …

“The argument is deductive because of the way the K_i are supposed to be characterized. Begin from the assumption that if X and Y are probabilistically dependent in a population that must be because of the causal principles operating in that population. (Without this kind of assumption it will never be possible to establish any connection between probabilities and causality.) The trick then is to characterize the K_i in just the right way to eliminate all possible accounts of dependency between X and Y other than that X causes Y (there is no correlation in K_i between X and any ‘other’ causes of Y, there is no ‘selection bias’, etc.). Given that K_i is specified in this way, if X and Y are probabilistically dependent in population K_i, there is no possibility left other than the hypothesis that X causes Y.” That is, everything that has occurred up to the time of the putative cause must be held fixed.

“Of course the epistemic problems are enormous. How are we to know what to include in K_i? … Knowledge of just the right kind is thought to be rare in the social sciences…. Granger causality solves the problem of our ignorance about just what to put in the descriptions K_i by putting in everything that happens previous to X. That of course is literally impossible so in the end very specific decisions about the nature of the K’s must be made for any application.” (p. 30)

If we say that X Granger-causes Y, we have to know that “all other sources of probabilistic dependence have been randomized over or controlled for” and that “we are studying systems where all dependencies are due to causal connections.” (pp. 33-34) This is most likely impossible.

Which takes us back to Logic 101. If the premises of a deductive argument are true the conclusion must be true. If we aren’t sure whether the premises of the argument are true but are willing to assign a 90% probability of their being true, it is “reasonable to assign a probability of 90 percent to the conclusion.” But, Cartwright continues, that “is very different from the case where we are fairly certain, may even take ourselves to know, nine out of ten of the premises, but have strong reason to deny the tenth. In that case the method can make us no more certain of the conclusion than we are of that doubtful premise. Deductions can take us from truths to truths but once there is one false premise, they cannot do anything at all.” (p. 34)

Cartwright’s critique ultimately hinges on her characterization of Granger causality as a deductive scheme that clinches causal inferences rather than merely inductively vouches for them. Kevin Hoover grants her claim that “many arguments take the form of clinchers, conditional on background assumptions.” But, he counters, “she is wrong to imply that advocates of these forms of argument are insensitive to the tentativeness and the fallibility of those strong background assumptions. Such sensitivity means that arguments that take the form of clinchers are, in reality, always practically vouchers.” (review of Cartwright’s book) In another piece (“RCTs and the Gold Standard”) Hoover repeats his contention, arguing that all methods—clinchers and vouchers—“require good judgment to draw relevant conclusions—and a great deal of it. Since judgment cannot be eliminated, we had best get on with managing it. This however requires judgment!”

To my mind Cartwright’s criticism stands unscathed. There is a philosophical chasm between “X Granger-causes Y” and “In my judgment X Granger-causes Y.” The former is intended to be viewed probabilistically; the latter introduces elements of subjectivity and uncertainty.

* * * *

Now that you’ve eaten your brussel sprouts, tomorrow you’ll get dessert—a very short non-financial YouTube video that you’ve probably already seen but then again maybe you haven’t.

Price, The Conscious Investor

John Price, author of The Conscious Investor: Profiting from the Timeless Value Approach (Wiley, 2011), began his career as a research mathematician and for thirty-five years taught math, physics, and finance at universities around the world. He then morphed into an entrepreneur, developing stock screening software that emulates Warren Buffett’s investing strategies. And, as is evident from this book, he didn’t neglect his writing skills. He proceeds with the analytical precision of a mathematician but with the facility and clarity of a careful wordsmith.

Price describes over twenty methods of valuation. He explains the circumstances in which each method is most appropriate. He also evaluates each method’s strengths and weaknesses.



Here I am going to confine myself to describing the screen that underlies Price’s own investing system. He focuses on earnings forecasts, offering objective methods in place of the strategies of analysts, which are tainted with behavioral biases. Critically, he screens to find companies that are actually amenable to growth forecasts. They share three characteristics. “The first two, stable growth in earnings and stable return on equity, are based on histories of financial data taken from the financial statements. The third one, strong economic moat, is based on the ability of the company to protect itself from competitors.” (p. 292) Since many readers will be familiar with Warren Buffett’s notion of moats, I will discuss only the first two characteristics and how to measure them.

Price developed a proprietary function called STAEGR which “measures the stability or consistency of the growth of historical earnings per share from year to year, expressed as a percentage in the range of 0 to 100 percent. … STAEGR of 100 percent signifies complete stability, meaning that the data is changing by exactly the same percentage each year. The function has the feature of adjusting for data that could overly distort the result, such as one-off extreme data points, negative data, and data near zero. It also puts more emphasis on recent data.” This function is “independent of the actual growth. This means that whether a company has high or low stability of earnings is independent of whether the earnings are growing or contracting. In this way the two measures, stability and growth, complement each other in describing qualities of historical earnings.” (p. 294)

In measuring the stability of return on equity, Price assumes the clean surplus relationship which, on a per-share basis, states that the initial book value + dividends per share + earnings per share = the resulting book value. Under that assumption, “whenever return on equity is constant, … the growth rate of earnings each year is approximately equal to return on equity times the dividend retention rate. … [I]f a company pays no dividends, the growth rate of earnings and return on equity will match very closely.” (p. 297) Price does not contend that return on equity implies information about the growth of earnings since return on equity is defined in terms of earnings. Rather, he suggests that stability in return on equity and the payout ratio enable the analyst to estimate stability in the growth in earnings.

Once he screens for stability functions he then calculates margins of safety for forecasts of earnings, P/E ratios, and dividend payout ratios. I have no space here to describe his techniques. Suffice it to say that he has developed methods by which to “decrease the size and frequency of negative earnings surprises in a consistent manner for large databases of companies.” (p. 318)

The Conscious Investor serves two important functions. First, it critically assesses a range of valuation methods. Second, it is an accessible case study in the application of quantitative methods to fundamental analysis. Perhaps I should add a third: it seems that Price’s techniques are actually profitable in the real world. Using the conscious investor system, to which he sells subscriptions for a fairly hefty fee, he booked audited returns of 19.45% per year over the course of five years versus the 2.82% actual return of the S&P 500 index.

And the winners are . . .

A reader suggested that I do what practically every bookseller or newspaper book review section does: highlight the best of 2010. I thought about this suggestion, I even tried compiling a list. And I threw up my hands. There’s no need to follow my tortuous mental processes.

Instead, I decided to redefine this task. Challenging my Internet-compromised memory, I set out to recall a few books that I’ve reviewed since I launched this blog that have made a difference to the way I think. They are also books that I’ve returned to over time. Without further ado, here they are in alphabetical order.


John B. Abbink, Alternative Assets & Strategic Allocation. Another Yale philosophy Ph.D. gone astray, but intriguingly so.

Steven Drobny, Inside the House of Money. The interview with Jim Leitner is one that I keep going back to.

Scott E. Page. The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. A brilliant book, with lots of ramifications for the markets.

Andrew Redleaf and Richard Vigilante. Panic. Among other things, distinguishing between the scientific scruples of academicians and the savvy of investors.

Josh Waitzkin. The Art of Learning. A book everyone should read.

This list reflects my intellectual predilections, with a bit of a tilt toward hedge fund thinking. But as I review the list these are all books I feel comfortable recommending.

Happy Thanksgiving

Carr, The Shallows

I don’t know about you, but I can certainly identify with Nicholas Carr’s problem. He writes: “Over the last few years I’ve had an uncomfortable sense that someone, or something, has been tinkering with my brain, remapping the neural circuitry, reprogramming the memory. My mind isn’t going—so far as I can tell—but it’s changing. I’m not thinking the way I used to think. … [When reading] my concentration starts to drift after a page or two. I get fidgety, lose the thread, begin looking for something else to do. I feel like I’m always dragging my wayward brain back to the text. The deep reading that used to come naturally has become a struggle.” In The Shallows: What the Internet Is Doing to Our Brains (W. W. Norton & Company, 2010) Carr makes a compelling case that, despite its usefulness and in part because of its addictiveness, the Internet is making us shallower thinkers.

Neuroscience has taught us that the brain is very plastic. But “for all the mental flexibility [neuroplasticity] grants us, it can end up locking us into ‘rigid’ behaviors.” That is, plastic is not the same as elastic. Repeated mental activity can alter our neural circuitry. The mental skills we exercise increasingly take up more brain map space; the circuits of those we neglect can weaken or dissolve. With concerted effort we can rebuild skills we’ve lost, but by and large the vital paths in our brain are the paths of least resistance. Many of these paths take us straight to Google.

As Carr writes: “The influx of competing messages that we receive whenever we go online not only overloads our working memory; it makes it much harder for our frontal lobes to concentrate our attention on any one thing. The process of memory consolidation can’t even get started. And, thanks once again to the plasticity of our neuronal pathways, the more we use the Web, the more we train our brain to be distracted—to process information very quickly and very efficiently but without sustained attention. That helps explain why many of us find it hard to concentrate even when we’re away from our computers. Our brains become adept at forgetting, inept at remembering. Our growing dependence on the Web’s information stores may in fact be the product of a self-perpetuating, self-amplifying loop. As our use of the Web makes it harder for us to lock information into our biological memory, we’re forced to rely more and more on the Net’s capacious and easily searchable artificial memory, even if it makes us shallower thinkers.”

Carr warns: “When we outsource our memory to a machine, we also outsource a very important part of our intellect and even our identity.”

And, yes, while writing this piece I checked my e-mail and looked at some charts. My own brain is constantly being, as T. S. Eliot wrote, “distracted from distraction by distraction.” Perhaps it’s time for some serious effort at rewiring.

Çaliskan, Market Threads

We all know that cotton prices have been soaring. Or do we? Koray Çaliskan’s Market Threads: How Cotton Farmers and Traders Create a Global Commodity (Princeton University Press, 2010) is a fascinating study of the international cotton market. Its theoretical focus is the nature of price and how it is determined in a range of environments, from commodity futures markets to providers of indexed spot prices to the markets for buying and selling the commodity itself. In the process of developing this theme, the author takes us to the cotton fields of Egypt and Turkey as well as to the global markets and individual companies that buy and sell the physical cotton that is used in our cheap T-shirts as well as our 400-thread-count sheets.

Çaliskan challenges the classic model of supply and demand. In its stead he proposes that most prices are “prosthetic devices” that are “made, produced, and challenged by a multiplicity of actors in a market process that happens in a variety of trading places.” (p. 85) These prosthetic prices are trading tools that are used to make actual prices—that is, prices that normally result from bargaining and become contractual prices to buy or sell a certain number of bales of a particular variety of cotton.

If you are at all curious about how cotton is grown and harvested, how it is graded, and how it moves around the world this book is rich in detail. Çaliskan did fieldwork in Turkey and Egypt, sometimes literally working in the fields alongside local farmers. He spent time with cotton traders in these countries as well. He even enrolled in a two-month training program in Memphis, Tennessee, designed for future cotton traders.

A couple of random takeaways. Cotton farmers in Turkey sell their entire crop immediately after harvest to repay the loans they took out (rarely from banks) to grow the cotton; “growing cotton requires farmers to borrow heavily.” (p. 144) As a result, they are forced to sell into a market where prices are depressed. By contrast, as I recently learned, cotton farmers in the United States receive government subsidies to store their cotton until the price becomes more favorable.

Children, sometimes as young as seven, work in the fields performing such tasks as collecting cotton-leaf worm eggs and harvesting the crop. “There is usually no reward for good work, yet mistakes are punished either through defamation, or at times beatings. … An overseer told [the author] that he was warned by the field’s owner not to hit children’s hands, but their backs instead if necessary, for the hands are needed the most. … These small hands are perhaps the cheapest and most abundant labor force behind the making of a commodity for the world market.” (p. 172)

Although the author undertook extensive ethnographic research and shares abundantly, this book is really about the dynamics among the players that determine that illusive thing called price. It demonstrates in vivid detail how essential knowledge and bargaining skills are to finding a price and how far removed from reality the traditional model of supply and demand can be. All in all, an intellectually exciting book which I thoroughly enjoyed reading.

Taleb's aphorisms

Just in time for holiday sales Nassim Taleb is back with what The New York Times dubs a "happily provocative new book of aphorisms," The Bed of Procrustes. If you are among the unwashed who don't understand the reference, "the Procrustes of Greek mythology was the cruel and ill-advised fool who stretched or shortened people to make them fit his inflexible bed." It's easy to understand why Taleb invoked this fool: "we humans, facing limits of knowledge, and things we do not observe, the unseen and the unknown, resolve the tension by squeezing life and the world into crisp commoditized ideas, reductive categories, specific vocabularies, and prepackaged narratives, which, on the occasion, has explosive consequences."

The book is short and inexpensive. I will undoubtedly succumb and buy it even though it evokes mixed memories of exchanged aphoristic barbs with a titan in his (very different) field. Academic cleverness can easily turn ugly. But then why should the battles for intellectual capital be any different from those for other forms of capital?

Granger causality and cointegration

I think we can all agree that if there is any causality in the financial markets it is not the same as classic scientific causality. Most tellingly, there are no financial laws that dictate that the occurrence of B (the effect) depends on the occurrence of A (the cause). Moreover, the often cited requirement of spatial contiguity is irrelevant. About the only thing that seems to be left from classic scientific causality is antecedence—that is, that the cause must be prior to the effect. But even that may be called into question. Think of the common situation in which the anticipation of an event gives rise to market movement. The event hasn’t yet occurred, yet it has to be referenced in describing the cause.

Let’s start our journey with the form of causality most popular with those engaged in time series forecasting. It is named after its developer Clive W.J. Granger, winner of the Nobel prize in economics (along with Robert Engle) in 2003. In his own words:

“The basic ‘Granger Causality’ definition is quite simple. Suppose that we have three terms, X_t, Y_t, and W_t, and that we first attempt to forecast X_t+1 using past terms of X_t and W_t. We then try to forecast X_t+1 using past terms of X_t, Y_t, and W_t. If the second forecast is found to be more successful, according to standard cost functions, then the past of Y appears to contain information helping in forecasting X_t+1 that is not in past X_t or W_t. … Thus, Y_t would ‘Granger cause’ X_t+1 if (a) Y_t occurs before X_t+1; and (b) it contains information useful in forecasting X_t+1 that is not found in a group of other appropriate variables.

"Naturally, the larger W_t is, and the more carefully its contents are selected, the more stringent a criterion Y_t is passing. Eventually, Y_t might seem to contain unique information about X_t+1 that is not found in other variables which is why the 'causality' label is perhaps appropriate."

Granger’s concept, as applied to time series, essentially says that although the current value of a time series can often be predicted from its own past values, the introduction of a second time series can improve predictive accuracy. This second time series, however, must be related to the first in a particular way. Otherwise, pairs of non-stationary time series can be highly correlated but not causally related. For instance, bread prices in Britain and sea levels in Venice both rise over time and hence are correlated, but they are clearly not causally connected. Enter the concept of cointegration.

In his Nobel lecture Granger explained: “if a pair of series [is] cointegrated then at least one of them must cause the other.” What does it mean for two series to be cointegrated? Here are three ways of picturing cointegration. First, Granger’s own. He compares a time series to a roughly stretched out string of pearls. Suppose, he says, that there were two similar strings of pearls, both laid out (or thrown) on the same table. “Each would represent smooth series but would follow different shapes and have no relationship. The distances between the two sets of pearls would also give a smooth series if you plotted it. However, if the pearls were set in small but strong magnets, it is possible that there would be an attraction between the two chains, and that they would have similar, but not identical, smooth shapes. In that case, the distance between the two sets of pearls would give a stationary series and this would give an example of cointegration.”

Here’s another example of cointegration offered by Thomas Karier in his book Intellectual Capital: Forty Years of the Nobel Prize in Economics (Cambridge University Press, 2010). (I can only assume he doesn’t own an untrained basset hound.) “Suppose a person and a dog are free to wander in any direction and we track their movements. If the person and the dog are unrelated, then there may not be any apparent relationship between the two paths. However, if the dog belongs to the person, then their paths should coincide more frequently and Granger would say that the two paths are cointegrated.” (pp. 270-71)

And finally, from Kevin D. Hoover comes what many would consider the best image for participants in the markets: the randomly-walking drunk and his faithful, sober friend who follows him to make sure he does not hurt himself. “Because he is following the drunk, the friend, viewed in isolation, also appears to follow a random walk, yet his path is not aimless; it is largely predictable, conditional on knowing where the drunk is.”

Pairs trading is often based on cointegration because theoretically this approach guarantees mean reversion in the long run although, as we know, not profits. (Those interested in pursuing this line of thinking might want to start with the Trading with Matlab blog post "Pairs Trading—Cointegration Testing." But, like the untrained basset hound, I’m wandering.)

The question is whether Granger causality is the best we can come up with. What are its flaws? That will be the subject of the next post in this series.

Day, Investing in Resources

Anyone thinking about adding commodities to his portfolio, especially gold, would do well to read Adrian Day’s Investing in Resources: How to Profit from the Outsized Potential and Avoid the Risks (Wiley, 2010). It is sensible, well documented, and written in fluid prose.

Day is a gold bug, arguing that the precious metal is “the asset of choice for the next few years.” For one thing, it will perform well in a variety of scenarios; it is not subject to the “major risk associated with the resource complex, namely slowing demand from a major recession.” (p. 79) In fact, Day identifies fourteen reasons for gold to continue to go up, from monetary instability and reflation policies to supply and demand imbalances.

Let’s assume that we buy into the thesis that we are in the midst of a commodities super cycle yet know that commodities can be extremely volatile. What is the best way to gain exposure to commodities and at the same time control risk?

Addressing the second question first, Day suggests that investors divide their commodity investments into a core portfolio and a trading portfolio. “The core is intended to provide exposure to the broad complex for the duration of the super cycle. Here you will buy with less regard to price, hold for the long term, and accept volatility. In the trading portfolio, however, price is more critical, you will hold for shorter periods trying to maximize gains, and you will attempt to use volatility to your benefit. The goals are different: One is intended to provide certain exposure to the sector for the duration of the cycle, so what you own is critical; the other is intended to maximize gains from the sector, so how and when you own is critical.” (p. 125) Sometimes the same stock is included in each portfolio. Indeed, one of Day’s favorite strategies is “to take a long-term position in a favorite stock and then trade around the edges.” (p. 126)

Day carefully assesses the various ways of gaining exposure to commodities. He looks at the pros and cons of holding physical commodities, primarily precious metals, including numismatic coins (“an area rife with ignorance and worse”). He points out a spate of problems with commodity ETFs—the not-insignificant drag on returns from the need to continually roll over futures contracts, their complicated and often unwelcome tax treatment, and CFTC rules that enforce daily trading limits and overall investment levels for various commodities.

He devotes three chapters to investing in mining companies: the major producers, the junior producers or developmental companies, and the explorers. For investors, he contends, “the selection criteria and investing tactics should be different for each group.” (p. 149)

After his detailed analysis of investing in gold and gold companies, Day then moves on to the other metals--silver, platinum, copper, and the base metals and rare earths. In the final hundred pages of the book he looks at the energy sector and, briefly, at agriculture. He concludes with some suggestions for building a commodities portfolio.

Investing in Resources is a thoughtful, practical book for anyone who thinks that the commodity “Super Cycle” has years left to play out.

Causation, the beginning of a journey

We have a seemingly insatiable urge to find causes for things. From “The market sold off because…” to “smoking causes cancer” to (and I kid you not) "Fear of hell makes us richer, Fed says." If x causes y, we seem to be in the comfortable world of rationality. There are reasons why y occurred; it was not some random or inexplicable event.

We distrust correlations because they often appear to lack rational, defensible foundations. Perhaps worse, they often masquerade as causal relations. James Stock, a Harvard economist, offered an example that is perhaps even more bizarre than the “fear of hell” study. “He noted that U.S. national income has been growing significantly for at least the last 100 years, and at the same time Mars has been slowly but steadily getting closer to the Earth. Because of these two long-term trends, it is virtually guaranteed that a simple statistical correlation would support the hypothesis that U.S. national income is determined by the country’s proximity to Mars.” (Thomas Karier, Intellectual Capital, p. 269)

And yet some correlations intuitively seem more causally linked than others. Let’s assume that we were presented with two equity index trading systems, one based on the relative strength or weakness of the U.S. dollar and the other on the motion of the planets. Let’s assume further that back tested over ten years these systems had identical profiles. Which system would most people be likely to embrace? The former, I assume, since we can more or less explain the sometimes simple, at other times complex relationship between equities and currencies whereas most people would be hard pressed to make any sense of the relationship between equities and the planets.

There are two main paths we can follow in trying to sort all this out. One is to embrace a kind (and possibly kinds) of causality that is either weaker than or different from “mainstream” causality. The second is to redefine the kinds of effects we are expecting, from invariable or regular to probabilistic (and “probabilistic” covers a wide range of possibilities). Ideally, these exploratory paths will eventually converge.

I’ve decided to begin a series of posts, erratically spaced, to inquire into these issues. Quite frankly, I don’t know where we’ll end up. Perhaps back where we began. Perhaps with such a watered-down version of causality that it’s virtually indistinguishable from correlation. But with any luck the journey will be educational. Maybe it will even inspire some ideas for system development and testing.

Proofiness

I’m going to do some posts on causality and correlation—undoubtedly fewer than I originally planned because I realized soon enough that struggling with a philosophical concept that has stymied the best minds for centuries and writing a trading/investing blog are not really compatible enterprises. Prefatory to this ill-conceived yet even in its truncated form perhaps enlightening venture, let me suggest that you “taste-test” Proofiness: The Dark Arts of Mathematical Deception by Charles Seife (Viking, 2010). Here are some links that provide interviews with the author and/or tidbits from the book.

"Lies, Damned Lies, and ‘Proofiness’"

"Fibbing with Numbers"

"The Dark Art of Statistical Deception"

Thomsett, Trading with Candlesticks

The prolific Michael C. Thomsett, probably best known for his books on options, has a new release: Trading with Candlesticks: Visual Tools for Improved Technical Analysis and Timing (FT Press, 2011). He describes the key single-stick signs, double-stick moves, and complex stick patterns. For those unfamiliar with the intricacies of candlestick charting, this is a clear, well-illustrated account.

It is also a sobering book for anyone who thinks that candlestick charts in and of themselves provide entry and exit signals. As Thomsett writes in what is perhaps an overstatement, “By itself, the chart—candlestick or other type—has limited value. … The candlestick chart is the easel, and the broader indicators are the paint.” (p. 18)

Over and over again Thomsett illustrates false signals, especially in single sticks—the marubozu that is followed by a downtrend, the dragonfly doji where price breaks below the doji’s lower shadow. Even complex candlestick patterns are often unreliable. In brief, it is insufficient to recognize a candlestick pattern; the pattern must be analyzed. In the case of reversal patterns, “the analysis should include judgment about whether the signal is true or false, the degree of strength or weakness in the reversal, and whether or not it confirms another indicator (or is confirmed in turn). Confirmation can include additional candlestick patterns, moving averages, and traditional technical signs.” (p. 91)

Candlestick charts monitor price. But “focusing solely on price trends is a mistake because changes in volume indicate changes in trading activity, and such changes often accompany or even anticipate changes in price trends. The same is true for changes in volatility levels; broadening trading ranges or repeated violations of support and resistance indicate coming price changes.” (p. 119) Combining such indicators as on-balance volume or Chaikin money flow with candlestick price trend analysis can “improve timing and bolster an initial indicator.” (p. 126) Recognizing changes in volatility as evidenced in such chart patterns as triangles and wedges is also an important part of a trader’s analysis.

Added to the mix are trendlines, Bollinger bands, MACD, overbought and oversold indicators (RSI and stochastics), support and resistance levels, and traditional patterns such as the head-and-shoulders formation. The rationale for all this “paint” is that a system with a series of confirming signals is more accurate than a single-indicator system. Thomsett does, however, warn against ending up with a canvas that uses so many colors that it becomes an unintelligible mess.

Thomsett is writing for the novice who wants to learn about candlestick patterns and who aspires to join the legions of chartists and technicians. His book is a reasonable place to start, especially since he dampens enthusiasm, stressing the ever-present possibility of false signals, no matter how many indicators confirm.

Pressfield, The War of Art

Steven Pressfield’s The War of Art: Break Through the Blocks and Win Your Inner Creative Battles was published in 2002, but I just came across it. I consider it a find. Pressfield is a novelist, which means that the book is several cuts above the standard self-help manual stylistically. Perhaps even more important, it is infused with humor, so it’s fun to read. Herewith a few excerpts.

The key theme of the book is what prevents us from achieving our dreams, especially our creative dreams, and how to overcome it. Pressfield labels this destructive force Resistance. It manifests itself most notably in procrastination and rationalization. What does it feel like? “First, unhappiness. We feel like hell. A low-grade misery pervades everything. We’re bored, we’re restless. We can’t get no satisfaction. There’s guilt but we can’t put our finger on the source. We want to go back to bed; we want to get up and party. We feel unloved and unlovable. We’re disgusted. We hate our lives. We hate ourselves. Unalleviated, Resistance mounts to a pitch that becomes unendurable. At this point vices kick in. Dope, adultery, web surfing.” (p. 31)

Is the problem fear? No, Pressfield writes. “Fear is good. Like self-doubt, fear is an indicator. Fear tells us what we have to do. … [T]he more fear we feel about a specific enterprise, the more certain we can be that that enterprise is important to us.” (p. 40)

So what then is the problem? Those who are defeated by Resistance “share one trait. They all think like amateurs. They have not yet turned pro.” (p. 62) Pros are not weekend warriors. They show up every day, no matter what, and they stay on the job all day. They master the necessary techniques, receive praise or blame in the real world, and have a sense of humor. They love what they do, but they play for money. “The more you love your art/calling/enterprise, the more important its accomplishment is to the evolution of your soul, the more you will fear it and the more Resistance you will experience facing it. The payoff of playing-the-game-for-money is not the money (which you may never see anyway, even after you turn pro). The payoff is that playing the game for money produces the proper professional attitude. It inculcates the lunch-pail mentality, the hard-core, hard-head, hard-hat state of mind that shows up for work despite rain or snow or dark of night and slugs it out day after day.” (pp. 73-74)

The professional “is prepared, each day, to confront his own self-sabotage. … He is prepared to be prudent and prepared to be reckless, to take a beating when he has to, and to go for the throat when he can. He understands that the field alters every day. His goal is not victory (success will come by itself when it wants to) but to handle himself, his insides, as sturdily and steadily as he can.” (p. 82)

The professional also “dedicates himself to mastering technique not because he believes technique is a substitute for inspiration but because he wants to be in possession of the full arsenal of skills when inspiration does come.” (p. 84)

Some food for thought.

Defining risk, an allegedly impossible task

Glyn A. Holton, a contributor to Haslett’s Risk Management, tackles a fundamental conceptual problem, “Defining Risk” (pp. 113-123). His thesis is that risk lies at the intersection of subjective probability and operationalism.

He starts with Hume, who laid the philosophical foundation for both streams when he wrote: “Though there be no such thing as Chance in the world; our ignorance of the real cause of any event has the same influence on the understanding, and begets a like species of belief or opinion.”

Holton then criticizes objectivists such as Frank Knight and Keynes who believed that risk is real. Knight distinguished between objective or measurable probabilities and subjective or unmeasurable probabilities, designating the former as risk and the latter as uncertainty. For Keynes probabilities apply not to individual propositions but to pairs of propositions where one proposition is not known to be true or false and the second is the evidence for the first.

It’s not important to go into Holton’s arguments against objectivism; we can skip straight to his own efforts to define risk. As a first stab, he suggests that risk has two essential components: exposure (a person has a personal interest or stake in what transpires) and uncertainty. He admits, however, that to define risk as “exposure to a proposition of which one is uncertain” is flawed.

It is indeed flawed if one accepts Percy Bridgman’s philosophy of operationalism, developed in his 1927 book The Logic of Modern Physics, which contends that “we mean by any concept nothing more than a set of operations.” From Bridgman’s viewpoint, Holton’s preliminary definition of risk would be inadequate because it is intuitive; it “depends on the notions of exposure and uncertainty, neither of which can be defined operationally.”

The paper’s conclusion is that there is no true risk. “At best, we can operationally define our perception of risk.” Therefore, when assessing risk metrics such as delta, value-at-risk, or beta in financial applications, we can never ask whether they capture true risk or whether they misrepresent risk. The most we can ask is whether a particular risk metric is useful, whether it will “promote behavior that management considers desirable.”

Holton’s conclusion may seem intellectually unsatisfactory, but at least it’s a position worth arguing against.

Quant equation archive

I just found this site, sitmo.com, and thought I would pass along my discovery even though it might be old hat for some of my readers. It has a collection of option calculators as well as a quant equation archive. Lots of fascinating stuff here.

Baker & Nofsinger, eds., Behavioral Finance

Behavioral Finance: Investors, Corporations, and Markets, edited by H. Kent Baker and John R. Nofsinger (Wiley, 2010) is a must-have book for anyone who wants a comprehensive review of the literature on behavioral finance. In thirty-six chapters academics from around the world write about the key concepts of behavioral finance, behavioral biases, behavioral aspects of asset pricing, behavioral corporate finance, investor behavior, and social influences. The book is hefty (757 pages of typographically dense text), and each contribution includes an extensive bibliography. But this is not simply a reference book; it reads surprisingly well.

Why should we study behavioral finance? “Anyone with a spouse, child, boss, or modicum of self-insight knows that the assumption of Homo economicus is false.” (p. 23) In our investing and trading—indeed, in all the financial decisions we make, we are prone to behavioral biases; we are often inconsistent in our choices. Only if we understand the kinds of emotional pulls that negatively affect our financial decisions can we begin to address them as problems. Some of the authors offer suggestions for overcoming these problems.

Here are a few takeaways from the book that give a sense of its tone and breadth.

First, I am happy to report that the literature shows that “high-IQ investors have better stock-picking abilities” than low-IQ investors and they “also appear more skillful because they incur lower transaction costs.” (p. 571) I figure that everyone reading this review falls into the Lake Wobegon category.

Second, individual investors can form powerful herds. “[T]rading by individuals is highly correlated and surprisingly persistent. …[I]ndividual investors tend to commit the same kind of behavioral biases at or around the same time [and hence] have the potential of aggregating. If this is the case, individual investors cannot be treated merely as noise traders but more like a giant institution in terms of their potential impact on the markets.” (p. 531)

Third, what are some of the behavioral factors affecting perceived risk? Although the author lists eleven factors, I’ll share just two. “Benefit: The more individuals perceive a benefit from a potential risky activity, the more accepting and less anxiety (fear) they feel…. Controllability: People undertake more risk when they perceive they are personally in control because they are more likely to trust their own abilities and skills….” (p. 139)

And finally, investors’ attitude toward risk is not fixed. They care about fluctuations in their wealth, not simply the total level. “[T]hey are much more sensitive to reductions in their wealth than to increases,” and “people are less risk averse after prior gains and more risk averse after prior losses.” (p. 355) Interestingly, CBOT traders tend to exhibit a different pattern, reducing risk in the afternoon if they’ve had a profitable morning.

As should be expected in this kind of volume, there is a fair amount of repetition. The same studies are quoted by several authors. We read about such topics as overconfidence and the disposition effect multiple times. The context is different, the principles are the same. But through repetition we come to appreciate the scope of behavioral finance (and often its limitations as well).

Although this book is certainly no primer, the reader needs only a passing familiarity with behavioral finance to profit from it. And for those who are better acquainted with the field, it is a useful compendium and an excellent research tool. It has earned a place in my library.