A brief hiatus

I recently received three books to review, but I’m going to be a bit slower than usual because I have a lot of other things on my plate right now. I have not abandoned you!

Happy Memorial Day

In a singularly non-patriotic post, here's an old Animal Planet video that I received via a basset breeder friend. It may be a tribute to problem-solving, canine style. Or more likely an example of clever training. Whatever the case, it’s funny.

Playing the ponies, part 3

In this, my final post on Robert Bacon’s Secrets of Professional Turf Betting, I’m first going to share the passage that was highlighted in the Daily Speculations blog and then look at the chapter entitled “You Must Speculate—You Can’t Grind.”

The would-be professional must learn how to translate every price and every bet into a matter of percentages. He has to get a feel for prices. So each day before the races are run, he should mark down his favorite and his second choice in each race for the next day. Then he should compare his selections and prices with the prices actually paid in these races (published in the results charts after the races are run). “Whatever you do, go over the results charts in detail after the races. Study not only the prices of the money horses, but also the prices of the losers.” (p. 61)

After the student is successful at these “paper” predictions, he should try picking the first through fourth choices in each race. And eventually, he should begin making full lines on entire races—before post. “But here is something to remember. DON’T look at anybody else’s selections or prices or handicaps before making your own selection and prices. That is a rule with no exceptions. If you look at some other prices or selections first, the line you will come up with will be a sort of scrambling of his line and your line. Almost invariably, it will combine the weakest features of both. You’ll have the mistakes and the trite opinions of his line and yours. But the possible ‘bright work’ and getting-away-from-the-public part of his figures and yours, will be discarded.” (p. 62)

Bacon reiterates this point in more passionate language a few pages later. Would-be professionals “must take care not to look at any papers or listen to any predictions before making prices. And, above all, they must take care not to get into conversation with any of those gabby blabbermouths who always want to express dull opinions on horses and racing. Those ‘creeps’ are POISON! The professional soon learns to avoid them at all times.” (p. 70)

And, the final takeaway I want to share from Bacon’s book is that you must speculate rather than grind, or “you must gamble rather than attempt to chisel.” (p. 83) Bacon’s point is that you shouldn’t place bets on so-called sure-things in safety positions. The player at the racetrack can’t grind or chisel because “the racetrack has all the grind and chisel privileges! … [I]f there is a Lady Luck, she favors the bold player who has the courage of his convictions.” (p. 84) “Forget all those ideas of ‘grinding out a day’s pay’. If you want to make a day’s pay at the races, get a job watering horses, or pitching manure into trucks. But never try to grind it out of the mutuels. Perhaps the quickest way to get cured of the ‘grind’ notion is to try to grind with progression betting. That cuts short the pain! The flat-bet grinder might last a month or two, or even all summer before his capital is wiped out.” (p. 87)

Playing the ponies, part 2

In the first part of this post I said that the professional bets according to a plan and uses past performance charts to pick horses. But having a plan is not the same as using a fixed system. “[I]f the public play ever did get wise to the facts of life, the principle of ever-changing cycles of results would move the form away from the public immediately. Few players take into consideration the principle of ever-changing cycles of results, although the minor ups and downs of this principle can be seen at every long race meeting.”

Bacon looks at one of the older betting systems, calling in its simplest version for a play on the horse most recently in the money. “When this system was known only to a select few, it made money for them. … But, after a time, one of the men who had made money playing it, is said to have decided to publish it and sell it to the public for a fat price. Hardly had the public commenced scrambling for copies of his system before a hundred or more imitators and system pirates began rewriting the system and using its principles for supposedly ‘new’ systems of their own. It was only a matter of a few years before there were hundreds of cheap imitations of the system. It became common knowledge among even the most ignorant players.” And what happened? “Originally, it was claimed that the method picked horses averaging 3-to-1. But soon the weight of the public’s money knocked the prices to 5-to-2. Then to 9-to-5, as more and more people learned the method and learned to read the new past performance charts which were just getting into wide circulation at the time. Then the prices came down to an 8-to-5 average. Finally, the down-trend in odds made the average price of these horses at some major tracks a scant 3-to-2. …

“Suppose the system originally had two winners out of each seven horses played, on average. That meant two winnings of $3 and five losings of $1 each, on dollar plays—all on average, of course. That gave a flat bet winning of $1 on each seven dollars invested. But when the prices were driven down to 5-to-2, the flat bet winning was wiped out. The system just broke even. And finally, at the later odds of 3-to-2 average price, the system lost $2 on each seven bets of $1, even though the percentage of winners (two out of seven) remained the same. To be accurate, we should say ‘even IF the percentage of winners remained the same.’ Because, in actual racing, the percentage of winners does not remain constant as the public’s play beats down the prices of horses picked by any set scheme.” (pp. 29-30)

Bacon claims that the turf is the “poor man’s opportunity.” He writes: “It seems that people who have failed at everything else have more chances of succeeding at turf betting than people who have been very successful. Perhaps, because the former try to follow the rhythm of results sequences, while the latter try to force the races to run their way, as they have forced everything else in their own lines.” (p. 78)

How can a person get started playing the ponies? He starts with money for ten bets—say, $20—plus $20 in reserve. He waits until he sees what he thinks is a perfect overlay spot to place his first bet. Win or lose, he has to wait patiently for another overlay spot before placing his second bet. With each bet he is using 5% of his total capital. Let’s say that he is successful and runs his capital up to $200. At that point he should reduce the size of his bets relative to the size of his account—let’s say, from 5% to 4%.

And what happens if he loses his entire starting capital? “SO WHAT? He’s been strong. He’s done his best. He just wasn’t ready. His life didn’t go with it! He didn’t hock his car, or his house, or his job. He can tell his wife he drank up the money, lost it playing poker with the boys, gave it to a sick friend, or anything! Of course she’ll put up a heated discussion. So what? She argues anyway, even if he spends a deuce on one of his hobbies. But the whole incident is forgotten in a few days. Nobody gets hurt.” Then the player studies more and “makes paper workouts day after day from the past performance papers or from his file of results charts.” He can try again the following season “with more knowledge and with more determination to have the required patience and guts.” (pp. 81-82)

(to be continued)

Playing the ponies, part 1

I don’t play the ponies because I’ve never had any interest in horse racing. But a recent post on the Daily Speculations blog sent me in search of a copy of Secrets of Professional Turf Betting by Robert L. Bacon. The book was published in 1952; I have no idea whether it is still useful to the “turf speculator.” It is, however, definitely a worthwhile read for the “financial markets speculator,” aka trader. Since there’s a lull in hot-off-the-press books, I decided to devote a brief series of posts (maybe three) to it.

Why do professionals win? They win because “they know the ‘inside’ principle of beating the races, the same principle that must be used to beat any speculative game or business from which a legal ‘take’, house percentage, or brokerage fee is extracted. That principle is: ‘COPPER’ THE PUBLIC’S IDEAS AND PLAY AT ALL TIMES!” To “copper,” by the way, is an expression that comes from the game of faro and means to bet against.

The public must be wrong because the percentage of winning post favorites at the major tracks is somewhere between 20% and 40%. When other considerations are factored in, the author claims that “as nearly as can be estimated, the public is wrong 70% of the time at major tracks.” So the public can win only about one race out of every four. And the average payoff price of the favorites is $5.58 for a $2 bet. So at best the public pays $8 to make $5.58—not exactly the kinds of results to which the professional aspires.

The bloke who uses some “senseless mechanical method, such as following the Number Six post position in every race,” does better than the player who steps into all the switches and traps. If the take is 10% and he bets eight races and a daily double at $2 each, he should come home, on average, with $16.20 of his $18 betting capital.

The professional, of course, aims to win. He sets out to win the difference between the public’s losses and the percentage of the track take. That is, after the track takes its percentage—say, 10%, the balance of what the amateurs lose is cut up among the professionals. They have coppered the public’s ideas and play.

What distinguishes the professional from the amateur? First of all, the professional has a carefully crafted plan and sticks to it (though not slavishly as we will see in the next post). Among other things, he “bets straight to win, only, because there is the least unfavorable take-and-breakage percentage against the straight position. He never bets place or show; that keeps him out of the amateur’s position switches. … Besides sticking to the win slot, the professional always makes bets of even amounts [on any given day]… [The amateur, by contrast] keeps switching [methods], amounts and positions so that he never has a worthwhile bet on a winner at a worthwhile price.” (p. 25)

The professional plan, stripped to its bare bones, is to play all the sound overlay spots. That is, play all the spots where the odds you have calculated are better than the odds at post time; if you believe the horse is 5-to-2 you don’t bet the horse if it is 8-to-5 at post time, but you do bet if the horse is 5-to-1. The professional makes one to three sound plays per day (some days no plays) at the track where he operates.

Of course, the professional has to be able to find sound overlay spots. He does this by studying past performance charts, by paying close attention to the scale of weights, and by being able to put himself in the shoes of the odds maker. He has to understand how those who calculate the odds he is trying to beat operate, which means he has to be familiar with the table of booking percentages and understand how a book (the total of all the betting percentages in a race) is tallied.

(to be continued)

Cohan, Money and Power

Goldman Sachs is not exactly the number one brand in the world. Admittedly, it’s hard to beat Apple these days in popularity contests. But Goldman doesn’t even come close: on the contrary, it’s a firm that people love to hate. William D. Cohan’s Money and Power: How Goldman Sachs Came to Rule the World (Doubleday, 2011) provides fodder for the Goldman haters, exposing among other things a long history of conflicts of interest.

Cohan’s long book is not, however, the stuff that tabloids (or Rolling Stone—think of Matt Taibbi’s piece, later expanded into
Griftopia) are made of. It’s carefully researched, with well-crafted portraits of Goldman’s leading players, definitely worth reading.

Since Cohan's book has been extensively reviewed, for this post I decided to extract some lessons for individual traders from Goldman’s successes and failures. And Goldman, lest we forget, had a lot of failures.

One lesson is to exploit the weaknesses (or laziness) of others. For instance, a Goldman trader recalled that his boss always called Friday “Goldman Sachs Day,” the rationale being that traders at other firms were goofing off on Friday. If the Goldman traders came in on Friday intent on actually doing something while others had their guard down and were less competitive, their focused energy could make a big difference.

A second lesson is to set high goals. For instance, John Whitehead said that “when a department head accepted a higher goal, he worked harder and smarter to achieve success.” Or there’s the story of the near-disastrous acquisition of J. Aron, the commodities firm. In 1982 its profits were half of what they were the year before; by 1983, there were no profits at all. Robert Rubin was given the job of turning Aron around. He in turn handed the day-to-day management over to Mark Winkelman. Winkelman presented Rubin with a business plan that called for Aron to make $10 million, “a meaningful rebound toward profitability after years of slippage.” Rubin was not impressed. He said: “Mark, ten million dollars is not why we bought J. Aron. Tell us what we need to do to make a profit of one hundred million dollars this year.” The much higher goal meant, among other things, a major restructuring, an expansion of trading vehicles, and a significant upward shift in J. Aron’s risk profile. (Previously, they ran an essentially risk-free business.)

A third lesson is to push your bet when there is an obvious moneymaking opportunity but cut back when the opportunity disappears. Of course, easier said than done. Goldman pushed hard with its currency trades in 1992 and 1993. At one point in 1993 there were 500-plus prop traders at Goldman in London, all with basically the same position and all making wads of money. But in December 1993 the dynamic began to change. For instance, a single trader had made a massive bet (over a billion pounds) that the British pound would rise against the yen. In February 1994 disaster struck; in fifteen trading days the pound lost ten percent of its value against the yen and by the time the trade was closed this lone trader had lost somewhere between $100 million and $200 million. The losses overall in the London office had spiraled out of control. One problem was that “the culture at the time—and this was throughout the trading culture—was that you don’t tell a trader what to do.” Goldman soon enough started to put sophisticated controls in place with the creation of a proprietary system that gave the firm an enormous advantage in the assessment and monitoring of risk.

Goldman’s risk management is renowned. And, of course, its complexity goes far beyond what an individual trader would ever need. But one partner explained it, at least in part, in layman’s terms: “You need to look at everything in terms of the size. You know Bob Rubin always talked about small but deep holes. You can’t afford to lose a lot of money even if the odds are very low. You just have to protect yourself.”

Au, A Modern Approach to Graham and Dodd Investing

I have to give Thomas P. Au credit. In a world in which newsletters flaunt triple-digit returns and so-called educators tantalize prospective students with riches easily won and it seems virtually everyone cherry picks the dates that demonstrate outsized returns, Au the value investor showcases his trades in 1999. It shouldn’t come as a shock given the runaway market that year that he underperformed the S&P 500. And A Modern Approach to Graham and Dodd Investing (Wiley) was published only five years later, in 2004. So score one for integrity, zero for marketing skills.

Au’s “real-time experiment,” which occupies a single chapter, humanizes an otherwise fairly dry, earnest book. The tone may reflect the decade the author spent at Value Line, I don’t know, but even though Au writes clearly and is willing to tackle some big-picture issues, his book is easy to put down and hard to pick up again. And that’s a shame because he has some ideas that might prove useful to the twenty-first century value investor.

Here I’ll share two.

Although there is no single formula to determine when a stock is attractive, Au thinks that the investor’s best bet is the investment value formula: investment value (price) = book value + (10 * dividends). As corollaries to the concept of investment value, Au suggests that “A purchase cannot be considered a bargain unless it is undertaken at roughly one half of investment value” and “An acquirer is often willing to pay roughly twice investment value for control of a company.” (p. 123) As caveats, there must be a satisfactory leverage ratio (normally debt less than 30% of capital) and satisfactory earnings (ROE of at least 10-12%).

A case in point from history—and, on a personal note, an investment that paid my salary for a year and a summer many years later. “In the late nineteenth century, Andrew Carnegie turned a ‘small’ fortune for his day, of about $1.5 million, into a very large fortune of his time. He bought an interest in a steel company at a bargain price, watched it double to investment value, compounded it at roughly 15 percent per year for a period of roughly 30 years, and sold his holdings to J.P. Morgan at about twice the going market price, the premium that Morgan was willing to pay for control in order to fold Carnegie’s steel company into what became U.S. Steel.” (p. 124) You can do the math, but basically Carnegie realized a more than 256-fold return ($1.5 million invested, $412 million return). Not too shabby. Alas, the investor who bought U.S. Steel in 1900 and miraculously lived another hundred years would have had no return on his investment.

For those who want to stay fully invested in stocks but change strategies depending on market conditions, Au describes nine market scenarios—high and rising, high and stable, high and falling, moderately priced and rising, moderately priced and stable, moderately priced and falling, low and rising, low and stable, and low and falling. “Of these nine scenarios, Graham and Dodd-type investing has a clear advantage in the three stable scenarios by emphasizing dividend income, and the three falling scenarios by focusing on capital preservation. It is also robust in two of the three rising scenarios, when stocks are low and moderately priced. Its clear disadvantage is in the high and rising scenario, which was the case in the late 1990s.” (p. 215)

Still better off is the investor who can time the market, knowing when to add to his stock portfolio and when to go to cash or bonds. Au offers some timing suggestions, including the notion of generational cycles. “A stock market cycle of 30-odd years … encompasses one strong and one weak generation.” “Strong generations, such as the Baby Boomers, run the American economy in overdrive. Weak generations, like the preceding Silent generation and succeeding Generation X, rein in the excesses of the strong generations.” (p. 307) As is often the case with long cycles, the timing of the next peak and trough is tricky. A complete 80-year generational cycle “would predict a crisis and possibly a war around the year 2021. This is close to the right time frame, but at the rate events are progressing, the climax could come just a bit earlier, in the mid- to late teens.” (p. 308) There will undoubtedly be more crises to come, but I would consider the recent financial crisis one that came far too early by generational cycle standards.

Kroszner and Shiller, Reforming U.S. Financial Markets

A slight but nonetheless thoughtful book, Reforming U.S. Financial Markets: Reflections Before and Beyond Dodd-Frank (MIT Press, 2011) grew out of the fifth Alvin Hansen Symposium on Public Policy held at Harvard in 2009. At this symposium Robert J. Shiller and Randall S. Kroszner presented papers, which were then commented on by Benjamin M. Friedman (the editor of this volume), George G. Kaufman, Robert C. Pozen, and Hal S. Scott.

I assume those readers who watch CNBC are acquainted with Shiller and Kroszner, since both are frequent guests. Shiller, a professor of economics at Yale University, is probably best known for his book Irrational Exuberance. He also developed, with Karl E. Case, the Case-Shiller home price indices that depress us month after month. Kroszner, a professor of economics at the University of Chicago’s Booth School of Business, is a former fed governor.

In this post I want to concentrate on a couple of points in Shiller’s more controversial paper, “Democratizing and Humanizing Finance,” described by Pozen as “almost philosophical.” (p. 102)

Shiller is a firm believer in regulation: “[m]arkets and government,” he writes, “are … inseparable.” (p. 14) Not surprisingly, he considers deregulation, a product of the conservative movement in both government and the halls of academe, one of the causes of the financial crisis. Deregulation not only wanted to get rid of all the referees in the financial “games,” a move that Shiller deems counterproductive: “Referees, and a good set of rules, prevent the rough play and cheap moves that would actually compromise the abilities of the best players.” (p. 24) It also rested on shaky theoretical foundations in the form of the efficient markets hypothesis.

Shiller quotes from the second (1984) edition of the popular finance textbook Corporate Finance by Brealey and Myers, written near the height of the popularity of the efficient markets hypothesis: “We recommend that financial managers assume that capital markets are efficient unless they have a strong, specific reason to believe otherwise. This means trusting market prices and trusting investors to recognize true economic value.” (p. 22) Bubbles, in brief, don’t exist.

A couple of devastating bubbles later, we might be inclined to agree with Shiller that “the efficient markets hypothesis is one of the most remarkable errors [or half-truths] in the history of thought, given its impact on our economic institutions and on the economy.” (p. 30) In its stead Shiller recommends relying on that faculty of the brain (theory of mind--ToM) “which formulates an assessment of the thoughts, incentives, and pretenses of others; that is, a faculty that looks into, and forms a judgment of, others’ minds.” (p. 6) ToM research is intriguing and echoes some early market wisdom (think Wyckoff), but it remains largely a work in progress.

Democratizing finance is a daunting task, and Shiller’s suggestions don’t seem particularly practical. He thinks that hedging markets, addressed to broad swaths of the population, should be encouraged. One such effort, the CME’s housing index futures launched in 2006, has been a flop. “The hope when this market was launched was that it would be the basis for creation of new retail products that would democratize finance by addressing the real risks that homeowners face.” (p. 32) So far this hasn’t panned out. Shiller also advocates subsidizing financial advisors for everybody and eliminating the wealth and income requirements for accredited investor status.

In posing the questions of how finance can be humanized and how it can be democratized Shiller assumes, of course, that finance should be both humanized and democratized. And I’m certain that many theoreticians and practitioners would line up on the other side of the divide. But I think the burden of proof lies with them. (This is a really cheap way of getting out of writing a treatise on the subject.)

Occasionally we should all step back from our daily routine and think about this slice of the world in which we try to earn our keep. Perhaps we could even help someone else understand what it is all about and how they might more fruitfully participate. Think about the possibilities of a volunteer domestic financial corps. That could be a form of grassroots democratization.

Blogger outage

Google's Blogger, the host of Reading the Markets, shut down after a scheduled maintenance on Wednesday night obviously went awry. Although readers were able to access pre-disaster posts, Google "temporarily" removed all posts and comments that had been uploaded post-disaster. And, of course, no new posts could appear.

My Thursday post is now back (though dated Wednesday), but some comments are still in Google limbo. If they don't reappear I'll try to recreate them to the best of my recollection.

Matras, Finding #1 Stocks

The credo of Zacks Investment Research, that “earnings estimate revisions are the most powerful force impacting stock prices,” dates to a 1979 paper by Leonard Zacks, co-founder of the firm. From that insight came the Zacks Rank, available by subscription. The Zacks Research Wizard, another subscription product, further parses the search for winning stocks.

Finding #1 Stocks: Screening, Backtesting, and Time-Proven Strategies (Wiley, 2011) by Kevin Matras, a Zacks vice president, presents screening ideas and trading strategies, all created and tested with the Research Wizard. For the dyed-in-the-wool DIYer, this book can point the way. For most folks who want to follow the Zacks path, it’s a lot easier to let the company’s computers/researchers do the heavy lifting. So consider this book a not-so-subtle variation on the infomercial theme. (I really have to come up with a good word for a book with a sales pitch. Perhaps I’m just behind in marketing lingo and the word is firmly in place, but I welcome all suggestions, especially those that make me laugh.)

What kinds of parameters go into screens for winning stocks? Let’s look at a single screen: all-cap aggressive growth. Here are the inputs: no market-cap restriction, Zacks rank #1, price >= $5, average dollar trading volume >= $1,000,000, estimated one-year EPS growth >= 1.20 * the industry median, but estimated one-year EPS growth <= 50%, P/E using F(1) estimates <= industry median, PEG ratio <= industry median, price to sales ratio <= industry median, and price to sales ratio = bottom #7. Note the number of “value” components in this set of parameters for an aggressive growth screen.

Using a one-week holding period (and not including commissions), over the last ten years “this strategy showed an average annual return of 51.6% for a total compounded return of 6,401.3%. … With a two-week holding period, the average compounded annual growth rate came in at 38.9% for an average total compounded return of 2,734.1%.” (pp. 62-63)

Matras takes the reader through a series of stock screens representing a range of styles that have produced outsized returns. He then introduces technical analysis, explains chart patterns, and shows how to use the Zacks Research Wizard for screening and backtesting. He rounds out the book with chapters on short selling, managing risk, options, and ETFs. And, of course, at the end are links for free trials of Zacks products.

The book is nicely put together and is full of excellent screening ideas. As books touting a product go, this one is first-rate. I have never tried the Zacks Research Wizard, so I can’t pass judgment on it. But I’d give a qualified buy rating to Finding #1 Stocks.

Levy, Your Options Handbook

Useful intermediate-level options books are notoriously difficult to write. Theoretically at least, it’s easy enough to write an introductory book that explains how a call differs from a put or how delta can be understood in terms of the number of shares of stock. But that doesn’t get the would-be options trader very far. Jared A. Levy, in Your Options Handbook: The Practical Reference and Strategy Guide to Trading Options (Wiley, 2011), goes a couple of steps beyond the introductory. He not only covers the basics but also guides the reader into the real world of options trading.

One of the strengths of this book is its breadth. It places options trading within the contexts of fundamental and technical analysis, macroeconomics, risk management, and trader psychology. I should note here that, in addition to a brief foreword by Mark Douglas, Levy turns over two chapters to “outside experts.” We hear from Denise Shull on understanding why you need emotions to trade well and from Dean Somes on turning your trading into a business.

Levy limits his discussion to single-expiration trades. Calls (naked and covered), puts, collars, vertical spreads, straddles, butterflies, and condors--no calendars. So there is no need to worry about such thorny subjects as horizontal volatility skew. In fact, it is only in the last chapter that implied volatility is discussed at any length, a discussion that academics would find seriously wanting.

But Levy, it seems, intentionally tries to keep things simple. For instance, in place of the trickier measures of volatility, he relies on ATR. It gives him a down-and-dirty way to set an initial stop on a long call. Let’s say you want to buy GOOG stock, where the average 14-period ATR over the previous month was $45. To stay outside of GOOG’s normal fluctuations you multiply $45 by 1.2. So your acceptable stop-loss in the stock would be $54. (A hypothesis: subtract this ATR stop loss from the stock price and that’s the strike you buy.) But of course you don’t want to buy the stock, you want to buy a call. How do you set a stop loss on a call? Levy’s method is to “take the ATR of the time frame that I want to be in the trade (monthly max); then … multiply it by 1.2 and then multiply by the delta.” (p. 169) Simple. Does it work? I have no idea. I leave it to those with more time than I have right now to test it out.

Levy walks the reader through hypothetical and real directional and volatility trades. Starting with a fundamental or macroeconomic premise, he chooses a trading candidate and an option strategy. Then, of course, in the case of spread trades he has to pick the right strike prices, expiration, and width of spread—some with the help of technicals. And once in the trade he has to monitor it, perhaps using a trailing stop, and decide when to exit. Levy mentions adjusting a position only in passing; basically, he lets violated stops or a decent percentage return get the trader out of his position.

Your Options Handbook is not a must-have book, but it’s a good book. I would recommend it to the relative novice—skip the really basic books and turn to this one. You won’t have a sophisticated understanding of options, but you won’t be swamped with information that you can’t profitably use at this stage of your trading career.

Zubulake and Lee, The High Frequency Game Changer

The High Frequency Game Changer: How Automated Trading Strategies Have Revolutionized the Markets by Paul Zubulake and Sang Lee (Wiley, 2011) is not an engaging book. It was definitely not written for the retail investor. Instead, it reads like a series of mini-reports from a consulting firm. It should therefore come as no surprise that the co-authors are a senior analyst and the managing partner at Aite Group, “an independent research and advisory firm focused on business, technology, and regulatory issues and their impact on the financial services industry.”

Rather than write a standard review, I’ll pick out two data points from the book that I think might be of general interest.

The number of electronic trade messages quadrupled between December 2006 and 2010. “If U.S. equities continue their pace, Aite Group expects message volumes to average 1.2 billion messages per day by 2011. The market already saw peak days approaching this number in late 2008. … Options pricing is exponentially worse than equities market data volumes. Current … OPRA data peaks exceed 1 million messages per second. Aite Group expects OPRA will generate peaks exceeding 2.2 million messages per second by the end of 2010.” (p. 47) I don’t know whether this projection came to pass, but the infrastructure demands are evident. No wonder some brokers charge for cancelled options orders.

I wrote about the importance of high performance databases in an earlier review. Zubulake and Lee confirm this: “Speed is essential for firms running strategies that feature both real-time and historical data. Aite Group estimates that 90% of quantitative trading firms currently maintain or are developing at least one trading strategy that requires playing back historical data in conjunction with real-time data.” (p. 113) Sure beats trying to keep all that history in your head!

Perez, The Speed Traders

High-frequency trading has mesmerized people in search of easy money, has challenged regulators, and has been an easy target for the press. In The Speed Traders: An Insider’s Look at the New High-Frequency Phenomenon That Is Transforming the Investing World (McGraw-Hill, 2011) Edgar Perez tries to set the record straight. Alternating between an annotated timeline of the development of high-frequency trading and interviews with top high-frequency traders, Perez illuminates the world of speed.

We normally think of high-frequency trading as super-fast order processing, measured in microseconds. And, yes, it is. But a trader’s data feed (whether market quotes or news feed) also has to be lightning fast, as does his database management system. Adam Afshar, one of the interviewees, explained this in the starkest of terms: “High-speed database management, in my opinion, is the linchpin of any computational or robotic trading system. … To put this into perspective, a test done in Microsoft Excel that takes about five months takes five days in SQL … and less than one second in a database management system that is specifically designed for stock market and numerical analysis. … Of course, having low-latency data is important; having an analytics system, be it a genetic algorithm, neural network, or basic network, these are all things you cannot do without, but none of these things makes any sense or has any value, monetizable value at least, if you do not have a very sophisticated high-speed database.” (p. 133) Reading this, I felt—at least for one wrenching moment—that I had been consigned to the dustbin of history. Somehow neither Zeno (Achilles and the tortoise) nor Aesop (the tortoise and the hare) provided consolation.

But speed does not automatically translate into profit. Manoj Narang, the founder of Tradeworx, speaks to this point. “Profitability,” he explains, “can have two distinct meanings in the realm of high frequency, and these meanings are almost mutually exclusive. When applied to high-frequency trading, profitability usually refers to the consistency of profits, because consistency is what makes high-frequency trading so appealing. … However, to most people profitability means something entirely different, which is the overall amount of profit generated. In this regard, the highest-turnover strategies are at a decided disadvantage.” A typical trade will return only about 0.1 cent per share. “And that only includes trading costs, not the costs of running such an expensive and technology-intensive business to begin with!” (p. 197)

Moreover, he continues, assume that high-frequency traders account for the entire market volume, which has averaged 8 billion shares per day, and that they make 0.1 cent per share of profit. The yearly profit would come to $2 billion. “This might sound like a lot of money, but let’s keep in mind that this is the total amount for an entire industry. There are many other corners of the financial industry, such as derivatives trading or hedge funds, that generate hundreds of times this amount of profit in one year.” (p. 197)

Admittedly, not all shops run incredibly high turnover strategies. At the slower end of the scale, high-frequency trading more closely approximates automated day trading where positions can be held for minutes or even hours. Consistency suffers, but overall profitability can increase (or, of course, decrease).

Perez explores the charges that have been brought against high-frequency trading and for the most part, with the help of his interviewees, tries to dispel them. Did high-frequency trading cause the Flash Crash? No. As David Cummings, chairman of Tradebot Systems, wrote: “Who puts in a $4.1 billion order without a limit price? The trader at Waddell & Reed showed historic incompetence.” (p. 155) Some traders also point the finger at the practice of busting trades, which can punish liquidity providers.

The Speed Traders offers a sympathetic portrait of an industry that is often demonized. By tracing its roots (going back to Instinet which began operating under an unwieldy name in 1970), Perez demonstrates it to be a logical development of technological change in the financial markets. By separating out some controversial practices, such as flash orders, from high-frequency trading Perez makes it more defensible. All in all, an enlightening book.

Norris & Gaskill, Mastering Trade Selection and Management

Mastering Trade Selection and Management: Advanced Strategies for Long-Term Profitability by Jay Norris with Al Gaskill (McGraw-Hill, 2011) is a how-to book written by the guys from Trading-U.com. I assume that it is intended not only as a stand-alone book but also as a subtle advertisement for their training courses and mentoring. It follows on the heels of their 2009 book, Mastering the Currency Market: Forex Strategies for High and Low Volatility Markets.

I admit to being a bit jaded. I have read far too many trading books, most formulaic and few worth their purchase price, at least as measured against my new idiosyncratic benchmark: would I rather have this book or a gourmet dinner that cost roughly the same? If I benchmarked this book against a Wednesday evening tasting menu (sans wine) at Next Restaurant in Chicago, I would definitely opt for a night on the town. (By the by, a former derivatives trader is the moneyed partner in this allegedly extraordinary restaurant.) Actually, even if I benchmarked it against a few hamburgers at Louis’ Lunch or a couple of specialty pizzas from Pepe’s, both in New Haven, CT, I would still choose the food over the book.

It’s not that this is a bad book. A reader who is relatively inexperienced in trading technically could definitely learn from it. A trader who relies on multiple time frames for entry and exit decisions will find much to like. I personally finished the book still feeling hungry.

So what are the main themes?

Use multiple time frames, ideally trading in the same direction as higher-time-frame trends. Use higher-time-frame charts “to confirm a price signal on a lower-time-frame chart” (p. 53), though the experienced trader can sometimes short circuit this requirement and rely on Fibonacci retracement levels.

As an aid to visualizing multiple time frames on a single chart the authors use color-coded horizontal lines, which they call directional lines. “[T]he directional line marks the low of the current highest closing candle in an uptrend or the high of the current lowest closing candle in a downtrend, and it extends out to the right side of the chart on whichever time frame we need to measure or see. … In most simplistic terms, we can say that if price is below the line, the trend is lower; if price is above the line, the trend is higher.” (p. 40)

Buy the strongest markets, sell the weakest markets.

Potential trade setups occur at the confluence of trendlines and directional lines. The authors also sometimes rely on the old standby pivot point, R1, R2, S1, S2 lines. Trades should be taken only “when structure and momentum are complementing the price pattern.” (p. 128)

The authors’ methods can be followed by trend traders who look at longer-term charts, swing traders, as well as day traders.

I have, of course, drastically simplified the book in reducing it to a few main themes. The authors also write about preparing to trade, the risk involved in economic reports, stop placement, and managing a trade with higher time frames. The book is dotted with helpful hints. For instance, they caution beginners not to take a trade in one market based on the behavior of another, what they refer to as “trading corn in the wheat pit.”

Mastering Trade Selection and Management is not destined to be a trading classic, but in the right hands it can be a useful guide.

Papers of the NAAIM Wagner Award winners

Mebane Faber (World Beta) provided this link to a host of potentially interesting papers. Indulge yourselves.

The CPM Gold Yearbook 2011

In 245 pages The CPM Gold Yearbook 2011 provides more statistics about gold than I even knew existed. (By comparison, the 2010 CRB Commodity Yearbook devoted five pages to gold.) If you are a gold bug and like numbers, charts, and in-depth analysis, this is a real find.

The book is a product of the CPM Group, a commodities market research, consulting, asset management, and investment-banking firm. The firm’s roots go back to a research group launched in 1971 at J. Aron and then, after J. Aron’s acquisition, continued at Goldman Sachs. In 1986 Jeffrey M. Christian formed an independent company “through a management buy-out of the commodities research group of Goldman, Sachs & Co.”

The yearbook is divided into eight chapters: review and outlook, investment demand, supply, official transactions, fabrication demand, China’s gold market, markets, and prices. What kinds of data are provided? In as close to a random selection as I can offer, here are a few samples: U.S. eagle gold coin sales (1986-Jan. 2011), near-term mine development projects, mine production by country (1984-2010) and global production since 1800, reported central bank gold reserves by country and region (1950-2010), Japanese gold fabrication demand by category—jewelry, electronics, dental/medical, other (1976-Feb. 12, 2011), and monthly Comex gold futures trading volume (1975-2010).

Even though the book is a data geek’s dream, it does far more than present raw data. Let me share two bits of analyzed data.

The average grade of gold mined has been steadily declining since the late 1960s. In 1968 it peaked at 12.49 grams per metric ton (g/t). In 2009 it reached its lowest level on record at 1.79 g/t and backed off only slightly in 2010 to 1.83 g/t. At the same time the cost of discovery has skyrocketed, from 51 cents an ounce in 1950 to $75.70 an ounce in 2009. (To be precise, this is a three-year rolling cost of discovery in 2009 dollars.) And production costs have risen for nine consecutive years.

We might say, no wonder gold is trading so high. But we would have reversed cause and effect. With respect to cash costs at gold mining operations, “There are two distinct sets of factors driving average cash costs higher and lower at mines. The first set of factors relates to the actual costs of inputs…. The second set of factors relates to the price of the underlying product of the mine. As the price of gold rises, miners work higher cost properties, on average. As the price of gold falls, they cut back at higher cost mines and the average production cost declines. … The correlation between gold prices and gold mining cash costs between 1980 and 2010 stood at 0.85.” (pp. 71-72)

Moving on to China, since 2007 the world’s largest gold mining country. Despite the rapid rise in gold mine output in China, “growth in gold demand was even stronger, driven by rising investment demand from individual investors who seek to hedge their inflation exposure. This led to anecdotal reports of surges in Chinese gold imports. … In 2010, Chinese investment demand accounted for 29.8% of total Chinese demand. In 2011, Chinese investment demand is forecast to rise 34.7% to 7.5 million ounces, fueled by continued investor interest for gold amid high inflation.” (p. 187, 200) So if you’re long gold, you can add the Chinese investor to your list of thank-yous.

For those interested in buying The CPM Gold Yearbook 2011, it is not currently available through Amazon but can be purchased for full price at the CPM Group Store. It comes in both hard cover and .pdf form; for a small surcharge you can have both. I would recommend opting for both formats because some of the tables in the hard cover edition are set in very small type.

Marks, The Most Important Thing

Pre-publication, publishers scramble to collect favorable comments, preferably from people whose names are recognizable to potential readers. Normally these puffs of critical praise are printed on the back panel of the dust jacket. But occasionally the publisher recognizes that it has hit the mother lode and displays the critical quotation on the dust jacket’s front panel. Columbia Business School Publishing did just that with The Most Important Thing: Uncommon Sense for the Thoughtful Investor by Howard Marks, chairman and cofounder of Oaktree Capital Management. The ultimate praise: “This is that rarity, a useful book”—Warren Buffett. As I start this review, a day before the official publication date, the book is already #197 on the Amazon sales list (and as I’m about to put up the post it’s #160). I’m more accustomed to seeing numbers like 149,328.

Is Buffett’s praise—and I should add Joel Greenblatt, Jeremy Grantham, Seth Klarman, and John Bogle to the list of red-carpet fans—warranted? It all depends on whether you want good old-fashioned investing wisdom or you’re looking for a how-to book or, in Marks’s terms, whether you want to read second-level thinking or first-level thinking. Second-level thinking is “different and better.” (p. 6)

Marks is a value investor who is keenly aware of risk control (not avoidance) and who seeks to exploit market cycles. He prefers judgment to robotic quantification, agnosticism to the self-confident “knowledge” exhibited by forecasters. He makes lists, doesn’t draw charts.

To give a sense of the book, let me quote a few passages.

“There’s only one way to describe most investors: trend followers. Superior investors are the exact opposite.” (p. 91)

“[S]kepticism and pessimism aren’t synonymous. Skepticism calls for pessimism when optimism is excessive. But it also calls for optimism when pessimism is excessive.” (p. 98)

“[T]he real goal of active investment management is to buy things for less than they’re worth. This is what the efficient market hypothesis says we can’t do.” (p. 114)

“In the world of investing, … nothing is as dependable as cycles. … If we can’t know in advance how and when the turns will occur, how can we cope? On this, I am dogmatic. We may never know where we’re going, but we’d better have a good idea where we are. That is, even if we can’t predict the timing and extent of cyclical fluctuations, it’s essential that we strive to ascertain where we stand in cyclical terms and act accordingly.” (p. 125)

“I learned a lot from my favorite fortune cookie: The cautious seldom err or write great poetry. It cuts both ways, which makes it thought provoking. Caution can help us avoid mistakes, but it can also keep us from great accomplishments. Personally, I like caution in money managers. I believe that in many cases, the avoidance of losses and terrible years is more easily achieved than repeated greatness, and thus risk control is more likely to create a solid foundation for a superior long-term track record. Investing scared, requiring good value and a substantial margin for error, and being conscious of what you don’t know and can’t control are hallmarks of the best investors I know.” (p. 151)

The Most Important Thing blends excerpts from client memos—most from the last ten years—with Marks’s current reflections on intelligent active investing. For those who assume that the key to successful investing, the holy grail if you will, is one single most important thing, Marks will disappoint you. The book describes twenty “most important things,” all of which are essential ingredients in achieving (or trying to achieve) above-market risk-adjusted returns.

The book is written in a way that both seasoned investors and novices should appreciate. Reading it probably won’t be “the most important thing” an investor will do, but it might make a top twenty list.