MacKay, Extraordinary Popular Delusions and the Madness of Crowds

Charles MacKay’s Extraordinary Popular Delusions and the Madness of Crowds, originally published in 1841 and reprinted by Traders Press in 1994 along with Le Bon’s The Crowd, recounts three “moral epidemics”: the Mississippi scheme, the South Sea bubble, and “tulipomania.” I assume everyone’s familiar with stories of tulipmania, although in a 2007 University of Chicago Press book by the same name Anne Goldgar argues that not one of these stories is true. I haven’t read her book, so I can’t pass judgment on her debunking.

The South Sea bubble resonates, among other reasons, because Sir Isaac Newton apparently lost a fortune in the venture. And he’s famously quoted as saying, in respect to the unrelenting rise in South Sea stock, that “I can calculate the movement of the stars, but not the madness of men.” By the way, for those who think that the South Sea Company bubble had anything to do with the South Seas, wrong! Although its original charter granted the company a monopoly on the trade to the South Seas, the company’s sights were set on the gold and silver mines of Peru and Mexico.

The Mississippi scheme, engineered in France by the Scotsman John Law just prior to the South Sea bubble, also revolved around precious metals, ostensibly to be found in great abundance in and around Louisiana. Law, an adventurer and gambler who for a time accumulated considerable sums by “pursuing a plan, based upon some abstruse calculation of chances” (p. 185), grew up in a banking family. After shooting his opponent dead in a duel in England and escaping from the authorities, he traveled from country to country in Europe, studying finance and the principles of trade by day and gambling by night. When he arrived in France, its financial system was in shambles. He convinced the court that he should be allowed to establish a bank that would manage the royal revenues and would issue notes both on those revenues and on landed security. “He made all his notes payable at sight, and in the coin current at the time they were issued. This last was a masterstroke of policy, and immediately rendered his notes more valuable than the precious metals. The latter were constantly liable to depreciation by the unwise tampering of the government.” Law also declared that “a banker deserved death if he made issues without having sufficient security to answer all demands.” (p. 193) Law’s notes appreciated 15% in one year, his bank opened branches across France, and Law became a cause célèbre. Law also proposed the establishment of the Mississippi Company.

Law’s successes only seemed to grow. The French regent kept conferring new privileges on the bank—monopoly of the sale of tobacco, the sole right to refine gold and silver—and finally proclaimed it the Royal Bank of France. Once the bank became a public institution its formerly sound business practices were eroded. And since Law’s name was virtually synonymous with outsized returns, investment in the Mississippi Company was frenzied and its stock kept rising. In 1719 the Mississippi Company was granted the exclusive privilege of trading to the East Indies, China, and the South Seas as well as all of the possessions of the French East India Company. The company changed its name to the Company of the Indies and created 50,000 new shares. And Law “promised a yearly dividend of two hundred livres upon each share of five hundred, which, as the shares were paid for in billets d’état, at their nominal value, but worth only 100 livres, was at the rate of about 120 percent profit.” (p. 196)

The French public went wild trying to buy into this “too good to be true” guaranteed path to wealth, and the price of shares sometimes rose 10 or 20% in a few hours. The problem was that it was a paper system. Law seemingly forgot his earlier declaration that “a banker deserved death if he made issues without having sufficient security to answer all demands.” The investors who started cashing out early had no problem getting specie for their shares, and shrewd operators quietly and methodically converted their notes into specie and, sensing looming troubles, sent wagonloads of coins to foreign countries. Soon enough there was a shortage of gold and silver in France, so not only was there no way to repay investors but the entire French banking system was at risk. In response the government handed down edict after edict that eventually rendered shares in Law’s company worthless. Miraculously, Law escaped with his life, settled for awhile in England, and died in Venice.

I would like to close this post with “the moral of the tale,” but as we know only too well, no one ever seems to learn from the bubbles of the past. This time is always different.

You want to be depressed?

Somewhat belatedly here's a link to Don Fishback's post entitled Robert Shiller's Data Can Be Depressing based on work done at CXO Advisory.

Crask, Options Strategies for Sophisticated Traders

Mitch Crask introduces the reader to the switch spread trade in Options Strategies for Sophisticated Traders (Traders Press, 2005). In essence, it turns “a debit spread or straddle into a credit position by switching some or all of the long options in debit spreads to single stock futures.” (p. 2) Why go through this exercise? Why not just put on a credit spread using only options? Crask points to three essential differences between options and single stock futures that make the switch trade preferable. First, the price of the single stock future is not directly related to the volatility of the underlying stock. Second, the single stock future does not experience time decay. And third, most single stock futures at fair value have a delta at or very close to 1.00.

Early on Crask walks the reader through a simple bull switch credit spread using a July 2003 closing price for eBay. Step 1: Buy the September 105 call for a debit of $7.60; sell the September 110 call for a credit of $4.80, for a net debit of $2.80. Step 2: Buy the September single stock future for $108.28 minus the eBay close of $108.14, for a premium loss of $0.14. Step 3: Sell the September 110 call for $4.80. Now you have a net credit of $4.66. What have you accomplished? You lowered the breakeven point from $107.80 to $103.62. And whereas the maximum gain you could have realized on the debit spread was $2.20, you now have a maximum potential gain of $6.38 on the switch spread (strike of short call minus the cost basis of the single stock future). On the downside, you have increased your risk profile. Whereas the maximum loss was $2.80 on the option spread, the switch spread has for all intents and purposes unlimited risk since the single stock future can fall all the way to zero. Crask suggests that the trader of the switch spread place his stop at the point of maximum loss on the initial option spread. In this case, the reward/risk ratio of the switch spread is 2.28 compared to 0.79 for the option spread.

In this book Crask analyzes switch strategies for the most popular option spread trades, including verticals, calendars, straddles and strangles, butterflies and condors, and box spreads. For those option traders who love to dissect positions and think about the myriad ways to structure trades, Crask offers an interesting alternative.

One disadvantage of the switch spread trade is that it requires the trader to pony up more money. The margin for single stock futures is 20%. The other potential disadvantage, and here I’m not on sure ground, is that there may be liquidity issues with single stock futures. They never really took off as a stand-alone product, and I’m not sure how much volume there is in the EFP (exchange for physicals) market. I checked the OneChicago site for SSF volume, and it seemed anemic. But even if the precise trade Crask recommends isn’t practical, it should get those little grey cells in options traders’ brains working.

Le Bon, The Crowd

Gustave Le Bon wrote La psychologie des foules in 1895; it appeared the next year in English translation as The Crowd: A Study of the Popular Mind. Traders Press republished it along with Charles MacKay’s Extraordinary Popular Delusions in 1994.

Le Bon was no fan of the masses, alternatively dubbed crowds. He saw them as a destructive, barbaric force in human history and feared that in his lifetime they would once again overrun human culture. “Today the claims of the masses are becoming more and more sharply defined, and amount to nothing less than a determination to hark back to that primitive communism which was the normal condition of all human groups before the dawn of civilization.” (p. 15)

In the process of railing against the masses and expressing views that are decidedly racist and sexist, Le Bon offers insights into the herd mentality that is, alas, all too common in the markets and the irrational exuberance that, though infrequent, is even more devastating. So what are these crowds and how do they shape their members?

When a person joins a crowd, according to Le Bon, he gives up his conscious personality and takes on the collective mind of the crowd. Since it is the conscious elements of character that distinguish people one from the other (for instance, intelligence) and the unconscious elements (instincts, passions, and feelings) that they have in common, the person who joins a crowd abandons rational behavior in favor of instinctual behavior. “The heterogeneous is swamped by the homogeneous,” Le Bon claims. And, he continues, “In crowds it is stupidity and not mother-wit that is accumulated.” (p. 26)

A person is transformed when he becomes a member of a crowd. He acquires “a sentiment of invincible power which allows him to yield to instincts which, had he been alone, he would perforce have kept under restraint.” He doesn’t feel any individual responsibility; he’s protected by the anonymous crowd. Moreover, “under the influence of a suggestion, he will undertake the accomplishment of certain acts with irresistible impetuosity.” (pp. 27-28) He’s further reinforced by the similar behavior of the other members of the crowd.

In a crowd rumor becomes fact, the possible becomes the inevitable, and the faster an idea circulates—the more hype (or, as Le Bon would say, contagion)—the more incontrovertible it becomes. “Like women, [a crowd] goes at once to extremes.” (p. 43) And like (the myth about) lemmings, the investing crowd usually suffers devastating consequences.

* * * *

So, in our first foray into the world of crowds, we have Le Bon’s hypothesis that the crowd is unintelligent and often insidious. The person who joins a crowd relinquishes his individuality, his rationality, and his moral and intellectual restraint. The next post dealing with this theme will look at a specific example of the madness of crowds, the Mississippi scheme. And, as promised, in time I’ll move on to the seemingly conflicting notion of the wisdom of crowds.

A preview and a link

This coming week I’m going to begin a series of posts on crowds. I plan to start with Le Bon’s classic nineteenth century analysis, move on to a case study from MacKay’s book on the madness of crowds, and then look at notions about the wisdom of crowds. I’ve just put in an inter-library loan request for Scott Page’s book The Difference, so it might be a while before I finish the series. But I think it will yield some insights along the way.

For those of you who enjoy chart overlays here’s a link to the Moore Research Center's multi-year correlation studies of the DJIA index and the S&P 500 index. It appears among the subscription links on their site, but it is available at no charge. (I'm not sure why.) While you're at it you might want to check out the two "subscriber" links below the DJIA and S&P link under the heading "Correlations" and just above the "Free Links" box for a look at inter-market futures correlations and inter-market gold/silver correlations.

Journaling software

I am normally very well organized. My downfall was what to do with those ideas that I couldn’t put on a “to do” list and subsequently cross off but that deserved a better fate than being scrawled on a piece of paper, and then what? They belonged in a searchable data base. This sounds pretentious, I know, but bear with me because you might have the same problem. What do you do with insights you glean from others, “sparks of genius” of your own, rambling thoughts, the occasional chart you want to save that doesn’t fit into any neatly defined category? And the list of problem children could go on and on.

I found a solution to my troubles in the form of the freeware program
My Journal. It was written in 2006 and never updated, so I can’t predict its life expectancy. In brief, don’t commit those paradigm shifting ideas to it. But you can have several journals, you can index them, and—most importantly—you can search them by key words. This program may not be your ideal solution, but look around. Journaling software is a useful tool, in large part because you no longer have to remember where you left your keys.

Natenberg, Basic Option Volatility Strategies

Sheldon Natenberg is best known for his 1994 classic Option Volatility and Pricing. In an effort to bring the concept of option volatility to the mathematically challenged, Natenberg wrote Option Volatility Trading Strategies in 2007. This book has now been updated with bonus online content under the title Basic Option Volatility Strategies: Understanding Popular Pricing Models (Marketplace Books, 2009).

Curiously, in some ways I found this book more difficult to grasp than his first book. On the surface, it’s very easy sailing; you can zip through it in no time. But you’re left not quite knowing what you’ve learned. Admittedly, I didn’t listen to the hour and a half video that accompanies this book, nor did I take the tests and check the answers online.

Volatility trading, as Natenberg describes it, is a virtually impossible strategy for the retail trader; it’s straight out of the market maker’s playbook. It is, in a nutshell, “a multi-step option hedging strategy that begins by identifying options that are mispriced in the marketplace, then buying those that are under-priced and/or selling those that are overpriced. As a second step, you then offset your initial option position by taking an opposing market position—a delta-neutral position—in the underlying security. . . . Finally, over the life of your volatility trade, you would periodically buy (or sell) shares of the underlying security as needed to keep the entire position delta-neutral (a process known as ‘dynamic hedging’). The goal of volatility trading is thus to create a risk-free position that will capture the disparity between an option’s inaccurate market price and its true value.” (p. 147)

But just because volatility trading requires a larger inventory than most retail options traders will ever have need to manage and ideally a commission-free trading environment (and the reader gleaning some basic ideas from this book should never even contemplate it) doesn’t detract from the critical importance of the notions of volatility. Natenberg identifies four kinds of volatility. First, there’s future volatility—the volatility of the underlying contract over some period, usually the period between the present and the applicable options expiration. Second, there’s historical volatility—the fluctuation of prices in the underlying in the past. Third, there’s forecast volatility, that is, the projections that volatility forecasting services provide about the volatilities of the underlying contracts. And finally, and the only kind of volatility that applies directly to options, is implied volatility—the marketplace’s own forecast of the future volatility of options.

“All option decisions begin by comparing implied volatility to the future volatility. Why? Because we equate implied volatility with the price of the option and equate the future volatility with the value of the option. That’s an absolute: it doesn’t matter what you’re trading, whether it’s options or anything else. You are always trying to compare price and value. If something has a high price and a low value, I want to be a seller. If something has a high value and a low price, I want to be a buyer.” (pp. 79-80) It’s easy to dismiss this insight as just another way of saying “buy low and sell high or sell high and buy back low” but, especially when looking at options trades, it’s critical to have some method of predicting the future volatility of the underlying contract, whether it be systematic or discretionary. Then and only then can the trader start to figure out what kind of an options trade to put on.

Insect survival and trading

I was reading Audubon magazine the other night and was intrigued by the piece on biomimicry and the accompanying magnificent photography. By the way, the original article “Where It All Begins” along with web exclusives is available online.

The article started me thinking about ways in which traders might mimic nature to their advantage. First and foremost, it’s critical for traders to survive. It’s all very well to be king of the jungle, but the king can be taken out by a single bullet. Lots of impressive kills, but vulnerability to that one fatal encounter.

Let’s jump quickly from the single animal to a class of animals—those pesky insects. Insects have been around for several hundred million years, so they’ve certainly passed the survivability test. Most experts seem to agree that insects have survived mainly because of their rapid adaptation to changing environments. This adaptation is furthered by their particularly fecund reproductive powers.

To translate the survival skills of insects into trader terms, they use high frequency adaptive trading systems. I show here an example of a very high frequency self adaptive trading system (presumably "overly adapted" to attain such a perfect equity curve);
the source is irrelevant because unless you’re Goldman Sachs or the like you can’t possibly trade this way. (But don’t you love the image of Goldman high frequency traders as a horde of insects? Of course, high frequency trading has to be automated, so traders get replaced with algorithms, which alas don’t lend themselves to such a compelling image.)

The trader with fingers poised on shortcut keys and monitors covered with charts, quotes, and spreadsheets can’t begin to emulate the mosquito. But we shouldn’t forget that butterflies are insects as well, and they move at a more leisurely pace. And no, in answer to those who slept through biology, snails and slugs aren’t insects.

I’m not claiming that the only winning strategy is adaptive and relatively high frequency. But sometimes nature offers us insights that shouldn’t be ignored. The trader who uses the same strategy day in and day out, blithely ignoring the prevailing environment, will have a short life expectancy. And the trader who waits for that one perfect trade doesn’t have probability on her side. As the high-reproducing insect would say, you just have to do it over and over again!

Bucket shops

We know about bucket shops from Jesse Livermore. They were storefront businesses that let people place directional side bets on stocks. The bets stayed within the walls of the bucket shops; the owner of a bucket shop took the opposite side of the trade of its clients and charged a commission. Naturally, some owners were more honest than others, but for the most part the small-time speculator lost money because he was a bad trader, not because the game was rigged. Richard D. Wyckoff, in Wall Street Ventures & Adventures through Forty Years, originally published in 1930 and reprinted by Traders Press in 1986, describes the transformation of bucket shops from gambling parlors that were the launching pads for future star traders to scams that entrapped the naïve retail investor. And, sadly, there were the futile attempts of the New York Stock Exchange to shut them down. In the end it was the media that sounded their death knell.

Wyckoff started his career on Wall Street in 1888 as a runner. He performed back office tasks, delivering negotiable bonds and stock certificates and collecting money. This literally meant running from building to building, “rushing wild-eyed from one house to another to complete their deliveries before the last fifteen seconds of the delivery hours were ticked off on the old Gold and Stock tickers.” (p. 15)

That was the norm. By 1890, however, he had another task. The New York Stock Exchange, desperate to shut down the bucket shops and always coming up short, resorted to an extreme measure. It simply stopped the ticker service, not only to the bucket shops but to its own members as well. The ticker tape went silent. So the runners had the hapless task of running between the exchange and their offices to provide quotes that were clearly delayed. “No one in any of the offices knew prices until his boy arrived. This could not last. Nobody wanted to trade when the ticker wasn’t ticking.” (p. 19) The bucket shops could simply have waited out this nitwit strategy of the NYSE; it lasted only several days. But they used private wire services to transmit quotes to their offices across the country. Their customers weren’t worse off than those of the NYSE.

Fast forward to 1920. In a much more insidious form the bucket shops continued to thrive. “There was a difference between the old-style bucket shop, with its two-point-margin method, and the bucket shop 1920 style. The modern shop got hold of people with substantial amounts of money and swindled them by means of alleged information, discretionary accounts and actual transactions (frequently executed on the New York Stock Exchange through dummies).” The bucketeer “got hold of a client, preferably in another city, ascertained how much money he had, induced him to put up more and more by reporting purchase for him of this or that stock at 3 or 4 points below the market and announcing that he ‘already had a profit’ of $2,000 or $3,000, etc. When the amount of margin that could be extracted from the victim had about reached the limit, he was ‘sent to the cleaner’; in other words, he was put into a fictitious transaction that cleaned him out. Often, in fact, he was left in debt to the bucket shop.” (pp. 261-62)

The authorities were powerless to stop these swindles. The bucket shop lobby saw to it that New York state laws were ineffectual, and the New York Stock Exchange just kept wringing its hands. Finally the press entered the picture. Starting with Wyckoff’s Magazine of Wall Street and continuing with such large-circulation publications as the New York Herald and the Saturday Evening Post, reporters exposed the new bucket shops for the swindling operations they were. Emboldened, New York beefed up its state laws, the NYSE figured out ways to deprive the bucket shops of their services, and-- most importantly--the public stopped handing over its hard-earned money to the bucketeers. Soon enough, one shop after the other folded; the era of the bucket shops was over.

Of course, such profitable schemes never really die. We can look at credit default swaps, for instance, as a variation on the old bucket shop idea—unregulated side bets.

Averaging Up, a weak-kneed approach

Trade management is a particularly thorny subject. There are compelling arguments, for instance, for putting the whole position on at the beginning of the trade and subsequently scaling out. An all in/all out approach is also eminently defensible. In a scalping environment, in fact, the all in/all out approach is the only one that makes sense to me. But today I’m going to write about my own personal preference in markets that have decent ranges. It doesn’t matter whether the market is trending or simply making large swings.

The most vulnerable point of a trade is the entry, so this is where I want my size to be smallest. My model, like so many others, is based on multiples of three. So assume that I want my maximum size to be three contracts. I enter with one contract. If the trade goes in my direction I hold it through the first swing and subsequent retracement (preferably contained by the 20EMA; I don’t want to see my winning trade turn into a losing one if I can help it). I then add two contracts. The rationale is that the second push up or down is often larger than the first. And yes, I’m basing this on a dumbed down version of Elliott wave theory. As the second leg starts to roll over I exit one contract and take some profits. After yet another retracement I add one final contract, bringing the total back to three. When the third leg begins to roll over I exit all three contracts.

This description is, of course, no more than an outline, and there are lots of variations to it. There are times, for instance, that it’s wise to exit the whole position after the second leg. But on balance, executed wisely, it improves the bottom line.

Michael Gutmann wrote an excellent article in the February 2009 issue of Futures Magazine, available online, entitled “Calibrating Profit and Loss Strategies” in which he showed that aggressively adding contracts to a winning position when a longer-term trend can be identified offers the most impressive profitability results. His so-called war zone model never scales out, which is why I describe my approach as weak-kneed.

Wyckoff, Wall Street Ventures

Richard D. Wyckoff’s Wall Street Ventures & Adventures through Forty Years (originally published in 1930 and republished by Traders Press in 1986) should be on every trader’s reading list. Not only does it capture the spirit of Wall Street and deal making in the years between 1888 and 1928, it also provides insights into Wyckoff’s own trading strategy. And for Livermore fans, there’s a description of his methods—and of those who ganged up to bring him to his knees.

I’m going to write separate posts on Wyckoff’s tape reading and on bucket shops, especially as they evolved into predatory scams. Today’s is a smorgasbord of “tasty takeaways” from the book.

Does history repeat itself or at least, as Mark Twain claimed, rhyme? We can only hope so, at least in the case of GM. “In this year, 1913, General Motors was selling on the New York Stock Exchange around $30 a share. There were only 164,000 shares of common stock outstanding on which no dividends were being paid. The company had found itself in financial difficulties a few years before, had been forced to borrow $15,000,000 on pawnbrokers’ terms, and the bankers lending the money had secured control by means of a voting trust.” Wyckoff had some inside information about company operations and believed it had a great future. So he tried to get a piece of the action. Visiting the bankers one after the other, he tried to get an option on 10,000 shares at $30 a share. Of course, he would take only a part himself and parcel out the rest. No dice. The bankers decided to stand pat. “Thirty dollars a share made the entire outstanding stock worth about $5,000,000. Fifteen years later it had a $4,000,000,000 valuation. The low point for General Motors in the year of my negotiation was 25. Within three years that same stock sold at 850.” (pp. 195-96) So have hope, American taxpayers.

Why do I write this blog? Wyckoff, the editor, principal contributor, managing editor and make-up man, procurer of articles from others, advertising solicitor, business manager, and statistician of The Ticker, the monthly magazine he founded, answers. “As number after number of The Ticker was prepared, I began to see that I was getting more out of it than anyone else. The articles selected for publication were only a small part of the material examined and considered. Much that was of value, in one way or other, left a residue of new knowledge. Writing articles clarified many things in my mind. Much came out of my head that I did not know was there.” (p. 163)

Wyckoff’s magazine was intended to teach its readers general methods by which to acquire money-making ability in the stock market. It was a money-losing proposition. “I had, for the first time in my life,” Wyckoff writes, “run into debt, in attempting to put over a publication which taught the public how to play the market. I had succeeded in training myself—and in finding out that the public did not want to be trained, but wanted me to do the ‘doping out’ for them.” (p. 189). So he started a weekly forecasting service, The Trend Letter. Naturally, it was a huge success. Wyckoff was a good tape reader and he made money for his subscribers. And at $50 a year, as opposed to the measly $3 a year for The Ticker, The Trend Letter was a cash cow for Wyckoff. Indeed, to mash metaphors, why learn to fish when for $50 a year you can have as much as you can eat?

Paul Tudor Jones

I normally spend at least part of my weekends reading so that I'll have something to write about during the week. So I rely on the works of others to fill the gap. Today I'll link to two not particularly timely but nonetheless fascinating pieces on Paul Tudor Jones, the monumentally successful hedge fund manager. Both are interviews; the first is from 2008; the second dates back to the heady times of January 2000.

Enjoy, and I'll ply you with my own words tomorrow.

Ideas for the hares

I feel as if I’m being bombarded with provocative ideas that may someday become part of a theory of the epistemology of trading. Don’t hold your breath; I’m an intellectual tortoise not a hare. But en route I’ll share my sources so those hares among you can race ahead.

First, from the blog Vix and More comes this piece about Kafka, Surrealism and Trading. And second, I call your attention to the recent discussion on the Yahoo group e-Mini Traders Anonymous; see especially posts of Dominique, Mark, and scalperscott.

Peirce and abduction

It sometimes seems as if the only philosophers traders have ever heard of are Karl Popper and Ayn Rand. I assume that more than anything else it’s because of the power of association. George Soros lauded Karl Popper and he’s rich; Alan Greenspan was part of Ayn Rand’s inner circle and he’s influential. Logic like that can leave you both undereducated and broke.

Popper’s doctrine of falsification (that a theory is scientific only insofar as it is falsifiable and that scientists can’t prove hypotheses to be true but can only identify which hypotheses are false) is incomplete but nonetheless important. Ayn Rand I leave to her fans.

I’ve always been intrigued by how people formulate hypotheses and how they fix broken ideas. Both are central to investing and trading. Today I want to deal with the first and introduce Charles Sanders Peirce’s notion of abduction, outlined in papers written just after the turn of the twentieth century. [His name, by the way, for those unfamiliar with his work is pronounced “purse.”]

Peirce recognized three elementary kinds of reasoning: deduction, induction, and abduction. Deduction and induction are familiar logical concepts. Abduction is not; we normally understand abduction to mean kidnapping. But for Peirce abduction describes “all the operations by which theories and conceptions are engendered.” It “consists in studying facts and devising a theory to explain them.” It offers suggestions; it “suggests that something may be.” It’s something like a conjecture or a guess.

The form of inference is this:
“The surprising fact, C, is observed;
But if A were true, C would be a matter of course,
Hence, there is reason to suspect that A is true.”

Or, as further elaborated, “A mass of facts is before us. We go through them. We examine them. We find them a confused snarl, an impenetrable jungle. We are unable to hold them in our minds. We endeavor to set them down upon paper, but they seem so multiplex intricate that we can neither satisfy ourselves that what we have set down represents the facts, nor can we get any clear idea of what it is that we have set down. But suddenly, while we are poring over our digest of the facts and are endeavoring to set them into order, it occurs to us that if we were to assume something to be true that we do not know to be true, these facts would arrange themselves luminously. That is abduction.” We cannot say that the hypothesis is true or even probable (that is, not probable in a way that underwriters could safely make it the basis of business). But it’s likely, “in the sense of being some sort of approach to the truth, in an indefinite sense. The conclusion is drawn in the interrogative mood.”

The value of these tentative hypotheses is economic—“economy of money, time, thought, and energy.” They allow us to regulate our future conduct rationally; induction from past experience gives us reason to believe that an abductive inference will be successful in the future.

So what value does Peirce’s hypothesis about abduction hold for the trader or investor? First, it does not restrict hypotheses to those that can be falsified. These are not scientific hypotheses in Popper’s sense. They make sense out of data but make no claim to truth themselves. They offer a way of moving forward, of trying to make things work. They may eventually give way to other hypotheses that are a better fit with the facts. But in the meantime they have pragmatic value.

Trading and investing do not lend themselves to true scientific hypotheses. No matter how sophisticated the mathematics, for instance, financial hypotheses are in the end mere conjectures with only a vague claim to truth. Does that make them worthless? Of course not. If they rise to the level of abduction (that is, if they are the result of inference, not merely a shot in the dark), they provide a way of looking at surprising or snarled data and making sense of it. Abductive inferences, it should be stressed, don’t have to be mathematical. That may be the flavor of the day, but there are many ways to hypothesize about financial data. It’s all up to the abductive powers of the trader!

SFO

If you don’t subscribe to SFO (Stocks, Futures and Options Magazine), you should. You can subscribe here. First of all, it’s free—in a print and online edition for U.S. residents, online only for the rest of the world. But it’s a far cry from those free magazines that go straight to recycling. Some of the best known names in the trading world contribute to its pages. There are interviews, “spotlights” on issues of national economic importance, and a range of materials for the active trader. In the last two issues, for instance, there were articles on system design, multiple timeframe trading, point and figure charts, chandelier stops, trading models vs. mechanical systems, and a new indicator to assess downside risk.

I’m in no way affiliated with SFO, just a very satisfied reader. The combination of free and good is all too uncommon. SFO does this combination one better. It is free and excellent!

Buttering bread

My father was the quintessential perfectionist. His words of praise, signifying a job well done, were “not bad.” Fortunately my mother made a joke out of all the “not bads,” so I quickly learned to translate “not bad” into “very good.” Not quite the “outstanding” my brother-in-law used to describe the accomplishments of his children but on balance good enough—or, perhaps, not bad.

My father’s perfectionism permeated even seemingly insignificant tasks—buttering bread, for instance. “Take care of the edges,” he said, “and the middle will take care of itself.” He said it not once but every time I put a pat of butter in the middle of a slice of bread and spread outward. These words of wisdom were not original (though at the time I thought they were), but they resonated nonetheless.

Many years later I’ve come to appreciate the wisdom of the bread buttering algorithm. When confronted with a problem our instinct is dig right in and try to get to the heart of the problem. But sometimes the smartest solution is to start poking around at the edges.

Poking around is a slow exploration, looking to discover things that a person on a mission tends to miss. As Kathleen Dean Moore wrote in “Poking Around: The How & The Why”: “[T]he art of poking around means prying at things with the toe of your boot, turning over rocks at the edges of streams, lifting logs to search for snakes or a nest of silky deer mice, and kneeling to examine the tiny bones mixed with fur encased in a predator’s scat. Poking around is more focused than watching, yet less systematic. . . . Unlike hiking, poking around has no set destination. It is more intense than strolling, but more capricious than studying. . . . Poking around is a guaranteed way to learn.”

I stress the notion of poking around because I don’t want the bread buttering algorithm to be translated as “get the entry and the exit right, and the middle will take care of itself.” Not only is this not what I want to say, but, depending on how you interpret it, it’s either false or meaningless.

In investing and trading there are lots of edges to poke around at. There are the small mistakes that reduce profits, there are the tiny advantages that in and of themselves may not make much of a difference but that when combined with some other variable might increase returns. Poke around at those edges, take care of them, and the middle might just take care of itself.

Gregoriou, ed., Stock Market Volatility

Volatility has long been a favorite stomping ground for quants. The heady days of options pricing models in the 1970s which earned Nobel prizes for Merton and Scholes in 1997 (Black had died in 1995 and was thus ineligible) may have passed, but research on both realized (historical) and implied volatility continues. Stock Market Volatility, edited by Greg N. Gregoriou (Chapman & Hall/CRC, 2009), is a collection of 31 studies that deal with such themes as modeling stock market volatility, portfolio management and hedge fund volatility, developed country volatility, and emerging market volatility.

Here are a couple of cheap takeaways from this book. First, switching from a static portfolio strategy to a dynamic volatility timing strategy improves performance. This thesis is not new, and financial engineers have been working hard to develop relationships between volatility and predictability. But it might be fertile ground for enterprising traders who know some statistics and ideally can develop multivariate and rolling GARCH estimators.

Two tables from Hsu and Li’s chapter “Cyclicality in Stock Market Volatility and Optimal Portfolio Allocation” may also be of interest, and one needs no quant skills to understand them. Both tables show asset class volatility and asset class return. The first table focuses on an average bull market cycle and an average bear market cycle, using the standard 20% demarcation line. The second looks at average expansion and recession cycles. These tables, it seems, cover the 30 years between January 1977 and December 2006



Of course, one cannot simply take an average and extrapolate to optimal portfolio allocation. But these tables at least provide a first point of reference.

The Witch of Wall Street and the Peirces

Today’s post is a vignette from Wall Street history, bringing together Hetty Green (born Henrietta Howland Robinson and not yet married at the time of the trial) and a renowned father and son team of expert witnesses.

Sylvia Ann Howland died in 1865, leaving half her fortune of approximately two million dollars to her niece, Hetty H. Robinson. Hetty had already inherited some $7.5 million the year before upon the death of her father. But Hetty wasn’t satisfied with half of her aunt’s estate; she wanted it all. Hetty, later famed as the Witch of Wall Street, produced an earlier will, leaving her the entire estate, with a codicil putatively seeking to invalidate any subsequent wills. The executor of the estate rejected her claim, insisting that the codicil (the original and a copy) was a forgery. Hetty sued the executor. The case, Robinson v. Mandell, was fought for five years.

Two questions were at issue. First, were Sylvia Ann Howland’s signatures to a codicil of an earlier will genuine or were they traced? Second, even if they were genuine, did the codicil invalidate a later will whose terms were much less favorable to her niece?

Benjamin Peirce (a mathematics professor at Harvard) and his son Charles (eventually a preeminent philosopher and about whom more later this week) undertook the task of answering the first question. “Under his father’s direction, Charles examined photographic enlargements of forty-two genuine signatures for coincidences of position in their thirty downstrokes. In 25,830 different comparisons of downstrokes, he found 5,325 coincidences, so that the relative frequency of coincidence was about a fifth. Applying the theory of probabilities, his father calculated that a coincidence of genuine signatures as complete as that between the signatures to the codicil, or between either of them and that to the will in question, would occur only once in five-to-the-thirtieth-power times.” (Writings of Charles S. Peirce: A Chronological Edition, vol. 2, pp. xxiii-xxiv [Indiana University Press, 1987]) “So vast an improbability is practically an impossibility. Such evanescent shadows of probability cannot belong to actual life. . . . The coincidence which has occurred here must have had its origin in an intention to produce it. It is utterly repugnant to sound reason to attribute this coincidence to any cause but design.” In brief, Peirce maintained, the signatures were forgeries.

The court ruled against Hetty, but without deciding on the authenticity of the signatures. The work of the Peirces was all for nought.

When Hetty died in 1916 she left an estate worth between $100 and $200 million. She had arguably been the richest woman in the world (and one of the stingiest).

In case you’re unfamiliar with the exploits of Hetty Green, there’s quite a bit of information online. I suggest in particular the Investopedia article by Andrew Beattie. The book I read some time ago, Hetty Green: Witch of Wall Street, seems to be out of print but is available in a Kindle edition. There’s another book I haven’t read—Hetty: The Genius and Madness of America’s First Female Tycoon by Charles Slack.

Wall Street's math wizards--NYT

I'm calling your attention to a piece published yesterday in The New York Times entitled "Wall Street's Math Wizards Forgot a Few Variables". The journalist Steve Lohr sketches out the new frontier in modeling--trying to extrapolate the methods used to explore online behavior to financial markets. By the way, two authors whose books I've reviewed on this blog are quoted--Andrew Lo and Emanuel Derman. The article is serious and deals mainly with risk management, but I couldn't help imagining brokers becoming little Amazons: "You've bought AAPL in the past, may I suggest RIMM?"

Link

David Varadi started his blog CSS Analytics about the same time I started mine. Although he describes it as quantitative research, most of it will be familiar ground to technical analysts. Most recently, for instance, he gave the calculations for his smoothed double stochastic oscillator. It's definitely worth a look.

Lo, Hedge Funds

Andrew W. Lo, in Hedge Funds: An Analytic Perspective (Princeton University Press, 2008) makes a convincing case that we need new quantitative models for assessing the risks and rewards of hedge funds. Take the case of the imaginary hedge fund Capital Decimation Partners. By traditional metrics its performance over an eight-year period was stellar, and if you didn’t know how it achieved its success you might rush to invest in it. If, however, you found out that its strategy was simply to short out-of-the-money S&P 500 put options you might have second thoughts; do you really want to assume such tail risk (and do you want to pay someone a premium to execute such a mindless strategy)?

Whereas long-only portfolio managers are judged by such widely accepted performance metrics as alpha, beta, volatility, tracking error, the Sharpe ratio, and the information ratio, hedge funds are often held to a single standard—absolute return. In this monograph Lo proposes a set of new measures for hedge funds that are dynamic rather than static in nature. He tries to quantify, for instance, a hedge fund manager’s asset-timing ability with multipoint statistics (the active/passive decomposition and active ratio) that “capture the very essence of active management: time-series predictability.” (p. 197)

Just as there have been no adequate measures of the performance of hedge funds so there is no single summary measure of the risks of these funds. Here Lo is not talking so much about the risk profiles of hedge funds as they affect individual investors (though he does briefly deal with the topic later) as he is addressing the question of systemic risk. In both a theoretical analysis and, later, an assessment of what happened in August 2007 Lo focuses on the themes of illiquidity exposure and time-varying hedge fund correlations.

Lo also returns to the adaptive markets hypothesis he first proposed in 2004 as an alternative to the efficient markets hypothesis and applies it to the hedge fund world. He draws four Darwinian implications:

1. Arbitrage opportunities exist from time to time. “From an evolutionary perspective, the existence of active liquid financial markets implies that profit opportunities must be present. As they are exploited, they disappear. But new opportunities are also continually being created. . . . Rather than the inexorable trend toward high efficiency predicted by the EMH, the AMH implies considerably more complex market dynamics, with cycles as well as trends, panics, bubbles, crashes, and other phenomena routinely witnessed in natural market ecologies.” (p. 247)

2. “[I]nvestment strategies also wax and wane, performing well in certain environments and performing poorly in other environments.” (p. 248)

3. “[I]nnovation is the key to survival.” (p. 249)

4. “Survival is the only objective that matters. While profit maximization, utility maximization, and general equilibrium are certainly relevant aspects of market ecology, the organizing principle in determining the evolution of markets and financial technology is simply survival.” (p. 249)

Lo’s monograph is first and foremost a scholarly work, replete with formulas and tables. He continues to expand the horizons of quantitative analysis of the financial markets. But his practical experience (he’s the founder of AlphaSimplex) also informs this book, and the combination is powerful.

Cass et al., Bullish Thinking

Bullish Thinking: The Advisor’s Guide to Surviving and Thriving on Wall Street by Alden Cass, Brian F. Shaw, and Sydney LeBlanc (Wiley, 2008) sets out to teach cognitive-behavioral therapy skills to financial services professionals (and, by extension, traders) so they don’t become among the walking wounded of Wall Street. In keeping with the Wall Street theme, they define bullish thoughts as rational, mostly positive, and based on personal and historical evidence. By contrast, bearish thoughts are irrational predictions, expectations, and beliefs. The authors claim that “just one realistic positive thought has the power to wipe out an entire army of negative ones.” (p. 27)

Let’s look at the case of Fearful Frank, a 35-year-old trader in a major slump. He was a high flyer in the late 1990s but after the market bloodbath felt dysfunctional, unable to accept loss or take risks anymore. He had been badly burned on some recent trades and was under great pressure to turn his account around. Dr. Cass, his therapist, offers him three golden rules to transform him into Fearless Frank. First, “Don’t Aim! Just Throw the Ball!” This advice doesn’t mean pitch wildly. “If your research tells you which stance to take on a trade, follow it, be disciplined, and just throw the ball!” (p. 44) Second, “Go for the Batting Title, Not the Home Run Crown.” That is, in a less volatile market “Maybe it’s time to look at yourself as a singles and doubles hitter who only swings for the fences when you are more certain of succeeding.” (p. 44) And finally, “Think Bullish, Not Bearish.” I personally doubt that simply following these three rules will transform Frank into a fearless, disciplined, successful trader.

The authors also claim that it’s important to pinpoint your unique mindset in order to understand why you react the way you do under stress and to find solutions. Here are the major categories. (I only hope you can’t be pigeonholed as easily as I can.)





The problem is that the authors admit that it is impossible to change your mindset to any significant degree, though you can work on how you come across to others. That’s not particularly useful for the self-directed trader or investor, though as we know from Brett Steenbarger’s work this advice can be modulated somewhat.

All in all, Bullish Thinking is a lightweight book. It’s compelling neither anecdotally nor theoretically.

What do you have an ear for?

I’m easily distracted, especially when slogging through a book that could be the final challenge in a copy editor’s reality show. I recalled my college days when my best friends took creative writing. One of their early assignments was to write a piece in the style of The New Yorker's “Talk of the Town.” They assumed this task with ease. Some got closer to the target than others, but no one froze. If I had been foolish enough to take this course, I would have frozen. I’m absolutely tone deaf when it comes to literary style. (And I don’t want to hear the obvious—we’ve read your blog, well, duh!) I’m a voracious reader, and I certainly know when I’m reading Austen and when I’m reading Faulkner. But I can’t even begin to replicate their styles.

On the other hand, I recall trying to explain the difference between 3/4 and 4/4 time in music to a fine literary stylist. One you waltz to, the other you march to, an explanation replete with live demonstrations. And I’m a pretty good teacher. No go; she couldn’t even hear the difference, let alone write a waltz or a march.

In the markets it’s critical to know what you have an ear for and when you’re tone deaf. There are so many ways to make money in the markets that you are almost assured of finding some strategy that you have an ear for. The question is how to discover that strategy.

Alas, I don’t have an answer to that question, yet it’s critically important to find an answer. Here’s one very, very preliminary mind exercise. Assume that if you have an ear for something you can create an original piece that echoes the work of a master and that performing this task isn’t torture. Your final product doesn’t have to be good but, judged by an expert, it can’t be pure trash. For instance, I who have an ear for music could compose a fugue in the style of Bach. It wouldn’t be good but would nevertheless fulfill the assignment. I could not, however, paint a picture in the style of Renoir. (Yes, I know I’m using the “ear for” phrase very loosely here, but humor me.)

Now let’s consider some possible market-oriented assignments. The style is more or less built into the assignment, so it’s not necessary to name a particular person or fund as a model. (1) Analyze a company as a possible short candidate. Look at its reports, its management, and its competition. (2) Write a trend-following system for a commodity of your choice relying on weekly data and then program it for entry and exit signals. (3) Using ETFs, devise a portfolio that, based on a five-year lookback period, has the most promise for high returns and low volatility in the future. (4) Find an intermarket signal that gives the intraday trader of, say, ES an edge.

Unless you have an inflated ego, you probably found some of these assignments undoable. Some you didn’t have the training for, some you don’t have the talent for, some you’re simply bored by. Okay, keep searching. Finding the right assignment is akin to finding the perfect partner. Otherwise, you might find yourself trying to paint that Renoir day after day, week in and week out, meeting with nothing but unmitigated failure. And all the time you were a brilliant engineer, a respectable mathematician, or—yes—a great trader.

Saliba, Option Spread Strategies

Option Spread Strategies: Trading Up, Down, and Sideways Markets (Bloomberg Press, 2009) is a brilliantly structured book. Written by Anthony J. Saliba with Joseph C. Corona and Karen E. Johnson, it describes eight spread strategies in terms a bright novice can understand and someone with a modicum of options experience will relish.

I listened to a Think or Swim webinar the other day and was astounded to learn that only twenty percent of their retail customers use spreads. Since the gurus at TOS focus almost exclusively on spreads in their educational programs, I can only assume that the percentage of spread traders at other firms is even lower. This is really a pity because option spreads offer so much more flexibility than simple calls and puts.

This book covers eight strategies: covered-writes, verticals, collars and reverse-collars, straddles and strangles, butterflies and condors, calendar spreads, ratio spreads, and backspreads. Each chapter follows the same structure. Starting with a brief concept review, the discussion moves on to an overview of the strategy, strategy composition, the Greeks of the strategy, investment objectives, strategy component selection, and trade management. There’s a quiz at the end of the chapter and a final exam at the end of the volume. Each chapter is about thirty pages in length. Since this is an 8-1/2 X 11 book, the layout isn’t crowded; there’s ample room for both text (broken up into bite-size pieces by heads and subheads) and figures. The design is conducive to learning.

Here I’m going to look at a single section from the chapter on vertical spreads to give some sense of the level of the book. The trade management section begins with a piece of sound advice: “One mistake that is consistently made by options traders (probably because they tend to fancy themselves as chess masters) is staying too long in a position or making too many modifications when their market view changes from the initial forecast. The simplest and most effective rule in risk management is this: If the trader is wrong, he should get out!” (p. 56) So, right or wrong, how does the trader exit? Should he exit using the reverse of the original position or its synthetic equivalent? This decision depends on price and liquidity. Price is straightforward, applying the rules set forth earlier in the chapter. Just use the most advantageously priced spread to exit. Liquidity can be a little trickier. “As options move in-the-money, they acquire a larger delta, and this makes hedging them riskier for market makers. Accordingly, market makers will widen the bid-ask spread. . . .” (p. 57) But these in-the-money spreads have synthetic out-of-the-money equivalents, so it is sometimes wise not simply to reverse the position but to exit via a synthetic equivalent.

Now let’s say the trader wants to modify the spread because the price target has been reached prematurely or the size of the directional movement has been underestimated. Here the trader can continue to participate in the move by rolling the spread using a butterfly. Two pages of “T” diagrams show exactly how to roll the spread up or down.

Option Spread Strategies is to my mind a real keeper. It’s not only instructional but belongs on the shelf as a reference work, especially for those “what now?” moments.

Schabacker on stops

If you haven’t read Richard W. Schabacker’s Technical Analysis and Stock Market Profits: A Course in Forecasting, originally published in 1932 and subsequently republished, most recently by Harriman House in 2005, you have missed an important seminal work. Schabacker expanded on the work of Dow theorists and, by focusing on individual stocks rather than the averages, he discovered new tradable patterns. His brother-in-law was Robert D. Edwards of Edwards and Magee fame (Technical Analysis of Stock Trends); they further analyzed, systematized, and expanded his work.

In today’s post I’m going to focus on one short section of Schabacker’s book: stop-loss orders. I won’t repeat the obvious advice about the wisdom of stops (obvious, that is, except to those who don’t believe in using stops—and, yes, I’m quite aware of systems that are profitable only because they don’t incorporate stops). The question is where to place stops. “While,” Schabacker writes, “we may grant readily that any formula—even a rigid arithmetic rule—is better than none,” ideally there should be some defensible rationale for the placement of stops. “Stops are used to relieve us quickly and automatically of ‘bad trades’ if the forecasts upon which we based those commitments turn out to be mistaken, or if there is an unexpected change in trend. They should be placed, therefore, so that they will be caught by any price movement which reverses our original forecast or indicates that a trend which has been working in our favor now has turned against us. At the same time they should be so placed that they will not be ‘touched off’ by any minor movement which does not upset or reverse our basic forecast.” (pp. 365-66)


Schabacker studies the case of a long position in US Rubber, initiated on a breakout on increased volume over a symmetrical triangle. There were two potentially negative scenarios: first, that price would drop back into the pattern but would then trend up and, second, that there might be a sharp shakeout. It’s the second case that Schabacker wants to protect against. Here he advocates an allowance of x% of the price of the stock at its previous minor reversal low, where x is dependent on the volatility of the stock. With US Rubber he opted for a 5% initial stop. He bought the stock at market on September 24 (presumably somewhere around 33) with a stop at 28.5, 5% below the previous minor pullback to 30. The next day the price dropped back into the pattern slightly to 31.5 but then decisively turned up again, with the 28.5 stop unexecuted.

After prices move away from a good forecasting pattern there will be minor pullbacks, gaps, continuation patterns, and congestion, all of which establish new minor support points that provide a basis for new stop orders. Now assuming that the trade starts to move in the predicted direction and then suffers a minor pullback, how soon is it safe to move the initial stop? “Our rule is to wait until the price ranges of two days are entirely beyond the price range of the day that establishes the new stop-loss level. If we are working in an up-trend . . . we wait until the low prices on two days are higher than the highest price during the bottom day of the dip.” (p. 368)

On October 3 there was a continuation gap from 35.5 to 36. “Continuation Gaps, as we know, set up minor support and resistance levels which are not as a rule broken decisively except by a change in trend.” (p. 369) So, applying the “two days away” rule, the trader should wait until two days range entirely above the high of the gap; in this case it occurred on October 8.

Of course, one never moves a trailing stop except in the direction of profit. So when price moved down to 34, only 0.25 point away from the stop, the stop was kept, not shifted down. And on and on the trade went until it was finally stopped out.

Schabacker cautions against using stops when trading within patterns. “Trading within these areas . . . is precarious at best and, unfortunately, the use of stop orders does not make it any safer since they can seldom be placed close enough to turn the odds in favor of the profit side without undue risk of loss.” (p. 374)

And finally, Schabacker does not advocate simply waiting to be stopped out. “In the great majority of trades the student will, if he follows his charts closely, see some sign of reversal or exhaustion which will enable him to take his profit and get out at a much better level than his current stop orders.” (p. 375)

Richard Wilbur, "Flying"

Richard Wilbur, I am absolutely certain, never contemplated traders when writing his poem “Flying,” published in a recent issue of The New Yorker. But in four four-line ABBA stanzas (yes, a poem with a rhyme pattern), he captures the essence of thousands and thousands of pages of trading books, some very sophisticated. The poem may not resonate with you as it did with me, but I’ve accepted it as my poetic mantra. And I want to share it with you.

Missing the Market's Best Days

Oh, those misleading statistics. Patrick Crook a while back did a one-page summary of literature (all available online) challenging the buy-and-hold mantra: you must stay fully invested so as not to miss those outlier "up" days that account for most of the market's return over time. Entitled Market Timing: Fact or Fiction, it's a quick but nonetheless important read for a holiday weekend.

Falkenstein, Finding Alpha

I have only flipped through Eric Falkenstein’s Finding Alpha: The Search for Alpha When Risk and Return Break Down (Wiley, 2009), so this will not be a review but rather one of those “takeaway” pieces. The central thesis of the book is that risk in general is not related to return. If true (and my instinct says it’s probably an oversimplification), it turns a lot of conventional wisdom on its head. On the other hand, and a more intuitive hypothesis, assets with either extremely low betas or extremely high betas have below average returns. The quintessential low beta example is money under the mattress. As an example of high beta assets he cites far out-of-the-money call options. The beta of calls, of course, increases the farther out of the money you go—that is, as call options essentially become lottery tickets. And beta moves inversely to the delta of the call. He reproduces a graphic from a 2001 study that shows the monthly returns for call options grouped into quintiles based on their deltas.


Another study, looking at data from 1996 through 2005, found that the highest out-of-the-money calls with one month to expiration lose on average 37%. “If there’s a risk premium in equities,” he concludes, “it certainly is not amplified in options in any way, because you lose money, on average, buying leverage market positions by way of call options.” (p. 76) Falkenstein’s argument is flawed because the investor buying a call option is not simply leveraging a position the way he would with a margin account at the applicable margin loan rate; he’s paying a premium to buy a leveraged position. This cuts into potential profits and, indeed on average, tilts toward losses. But this isn’t evidence against a risk premium in equities. Rather, it’s a cautionary tale for those wanting to buy call options.

As people search for alpha they try to find anomalies in the markets. Falkenstein claims that most so-called anomalies don’t really exist, that they are the product of flawed research. For instance, a 1985 study showed that for each year since 1933 going long a portfolio of the worst performing stocks over the previous three years and short the best performing stocks over the same three years would generate an annualized return of 8% over the next three years. This study, like so many that purport to uncover anomalies, produced positive results only because of the tendency of low-priced stocks to move from their bid to ask price. The purported calendar anomalies (the weekend effect and the January effect) apparently suffer from the same fault—the bid-ask bounce in low-priced stocks.

In looking for an alpha strategy Falkenstein says that you should start with the basic metrics of the assets in question—their average returns, their average annualized volatilities, and their cyclicality. The Sharpe ratio of any acceptable alpha strategy should not be radically different from the average Sharpe ratio. For instance, in their glory years convertible bond arbitrage generated Sharpes between 1 and 2. Thus, he argues, an investment strategy with a prospective Sharpe above 2 is undoubtedly the result of overoptimized backtesting and will fail.

Does history repeat itself?

I’ve referenced a couple of overlay charts recently that have predictive value only if you believe that history repeats itself. And that’s a hard sell. Yes, there are boom and bust economic cycles, but they are notoriously difficult to time and rarely have repeating causes or contours. Yet it is so seductive to see squiggles move in sync even though they may have no explicable relationship.

Technical analysis, of course, has to assume some version of a repeating history. Its claim is not so much that history repeats itself but that human beings repeat themselves. That is, human psychology in some generalized form is relatively constant; investors and traders are inclined to respond to certain sets of circumstances in ways that are more or less predictable. The old fear and greed stuff sliced and diced in innumerable ways. Of course, this model presupposes that large groups of individuals—retail investors, institutional investors, hedge funds, etc.—are interacting in an honest casino. If the dice are loaded, all bets are off.

Anyway, back to the question of whether history repeats itself and whether overlay charts make any sense. One reason I decided to venture into this intellectual morass was that I watched (and yes, I admit, saved) the 1987 PBS documentary on Paul Tudor Jones before it was removed from YouTube for copyright infringement. We see the Sancho Panza of the firm running historical correlations and plotting them out ever so slowly and painfully with primitive technology. In the documentary he compares the Dow of the 1980s to the Dow of the 1920s and predicts a rally into 1988 followed by a sharp decline (perhaps a 50% retracement), most likely in March of 1988. Well, that didn’t quite work out. The crash of October 1987 is emblazoned in every trader’s brain. On the other hand, the monumental success of Paul Tudor Jones makes the critics of historical recurrence (assuming that he ever really traded this way) seem like pathetic pedants. By the way, Paul Tudor Jones is out with another call—that the market’s climb has been a bear-market rally and that “record government spending may be forestalling another slowdown and market selloff.” (Bloomberg, Sept. 1)

Dow Theory Unplugged

There were few review copies I looked forward to receiving more than Dow Theory Unplugged: Charles Dow’s Original Editorials & Their Relevance Today, edited by Laura Sether (W&A Publishing, 2009). High expectations are often dashed, but not in this case. This is one of those rare times I can put a book on my conviction buy list. At $39.95 for 391 pages of seminal thoughts about markets this book is a real value play. And, an added bonanza for anyone who cares about book design in an era of cookie-cutter templates, a lot of thought went into the production of this book. So put away your Cliff Notes understanding of Dow theory as promulgated, systematized, and expanded by followers such as Hamilton and Rhea and relish Dow’s own Wall Street Journal columns written between 1899 and 1902. Sometimes it’s in the interstices of generally accepted theory that real gems can be mined.

This is not a book you breeze through in one sitting. Dow’s columns usually start with market reports—“The market drags along” [March 10, 1900], “The market has taken bad news and disappointments in the last few days comparatively well” [May 2, 1900]. Sometimes they comment on rumors (Will the Morgan interests take over the Carnegie Company?, Is the Vanderbilt interest trying to secure control of the Reading Railroad and merge Reading, Erie, and Lehigh Valley into one corporation?). They deal with commodities, bank reserves, and international trade. All in all, a wide range of timely topics.

Dow was far more than a commentator on daily events, however. He also wrote about the art and science of speculation and is, of course, best known for his work on the general movement of markets. Here are just a few snippets. When the “experts” on CNBC pontificate, let us not forget that some of what they say appeared in the Wall Street Journal more than a century ago. For instance, “When the market will not go down on bad news or unfavorable conditions, it usually has some advance shortly afterwards.” (p. 230) Or, commenting on sentiment, “It is hard to find anybody who is willing to express a bearish view of the stock market. This of itself has at times been a bearish argument. Ordinary trading rules, however, have been upset so often in the last two years that even professional traders are becoming more and more inclined to buy stock than to sell them.” (p. 234)

There are some wonderful images invoked in Dow’s book. Let me quote only two here, both dealing with market shifts from equilibrium to disequilibrium. “In the game called the tug-of-war a score of men, an equal number being at each end of a rope, pull against each other to see which party is stronger. In the game called stock exchange speculation, the speculators are at liberty to take sides and the side which they join invariably wins because, in stock exchange parlance, ‘everybody is stronger than anybody.’” (p. 304) Or, citing what the editor claims was a common reference at the time and what would no longer pass muster, “The market may be compared to Mahom[e]t’s coffin, which the faithful allege-to-be suspended between earth and heaven. Assume further that some portions of the community are trying to get this coffin down to the ground, while others are trying to get it higher in the air; also that the workers frequently change places, as they think one side or the other has the easier job, and the analogy is complete. When the pressure is unequal the market responds to the preponderating force; when the market stands still, it may be assumed that the forces are about equal.” (p. 250)

This book should appeal to investors, speculators, historians of the markets, and market theorists. I for one am extraordinarily grateful that the collection was published.

Lo & Hasanhodzic, The Heretics of Finance

Through interviews with thirteen of the best known technical analysts Andrew W. Lo and Jasmina Hasanhodzic introduce newcomers to the field and reintroduce those familiar with technical analysis to old friends. The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis (Bloomberg Press, 2009) is divided into two parts. In the first, analysts are interviewed individually; in the second, they all respond to a single set of questions. The analysts featured in this book are Ralph J. Acampora, Laszlo Birinyi Jr., Walter Deemer, Paul F. Desmond, Gail M. Dudack, Robert J. Farrell, Ian McAvity, John J. Murphy, Robert R. Prechter Jr., Linda Bradford Raschke, Alan R. Shaw, Anthony W. Tabell, and Stan Weinstein.

No common portrait emerges. You are just about as likely to find consensus in a group of technical analysts as you are in a group of economists. Some do statistical analysis, others base their decisions on patterns, still others turn to indicators; some rely to a significant extent on intuition, others decry it. Some don’t even want to be called technical analysts.

Lo and Hasanhodzic come from the quant world. Lo is an MIT professor, Hasanhodzic got her Ph.D. in electrical engineering and computer science from MIT. Lo founded AlphaSimplex, a quant fund, where his co-author is a research scientist. The book’s weaknesses, I believe, stem from the authors’ scientific bent, leading to an urge to standardize. Even in the interview section of the book most people were asked the same questions and the authors refrained from any follow-up. It’s as if they were conducting a survey that would be tainted if they injected themselves into the process in any way. Fortunately many of the interviewees were sufficiently engaging that they triumphed over the format.

A single example of conflicting opinions rendered in graphic prose: When asked whether technical analysis is more effective when applied on its own or when combined with fundamental analysis, Robert Prechter answered: “To me, that’s like asking, ‘Is food more effective when used on its own or when combined with arsenic?’” (p. 79) By contrast, asked the same question, Laszlo Birinyi responded: “We’ve had a lot of success over time combining disciplines. To me a discipline is like one hand clapping; it doesn’t really do much. It’s when you add another hand that you end up making noise.” (p. 21)

Technical analysis is unlikely to go away anytime soon. Even as it’s squeezed from the right by fundamental analysis and from the left by quantitative analysis, there’s plenty of room for skillful players to take a big chunk out of the middle, perhaps by incorporating a little bit from both the right and the left. These thirteen players can help the next generation develop the sharp elbows necessary to defend their turf.