Hirsch, Stock Trader’s Almanac 2016

The new year will soon be upon us, and with it comes the continuation of a long tradition. The Stock Trader’s Almanac is now in its 49th edition. Well, not quite the track record of The Old Farmer’s Almanac, which launched in 1792, but presumably a tad more data driven.

The spiral bound, green lexotone-covered almanac opens flat for easy access to its information or for jotting down notes. The format remains essentially the same as that of recent editions, with a calendar section, a directory of trading patterns and databank, and a strategy planning and record keeping section. The calendar section has on facing pages historical data on market performance (verso) and a week’s worth of calendar entries (recto). January’s verso pages, for example, give the month’s vital statistics, January’s first five days as an early warning system, the January barometer (which has had only eight significant errors in 65 years, one of those in 2014), and the January barometer in graphic form since 1950. Each trading day’s entry on the recto pages includes the probability, based on a 21-year lookback period, that the Dow, S&P, and Nasdaq will rise. Particularly favorable days (based on the performance of the S&P) are flagged with a bull icon; particularly unfavorable trading days get a bear icon. A witch icon appears on options expiration days. At the bottom of each entry is an apt quotation. There’s about a five-square-inch space in which to write.

The Stock Trader’s Almanac pays particular attention to the presidential cycle, and its message is mixed for 2016. On the one hand, “election years are the second-best year of the four-year cycle and sixth years of decades have been up double digits four in a row, so 2016 has some solid history behind it.” On the other hand, “eighth year of presidential terms represent the worst of election years since 1920. In eighth years, DJIA and S&P 500 have suffered average declines of -13.9% and -10.9% respectively.” Admittedly, there are only six data points in this eighth year series (new to this edition), but of them only 1988 was positive.

What other seasonals are powerful? The best six months is still “an eye-popping strategy.” Since 1950 the best months are November, December, January, March, and April. Add February, “and an excellent strategy is born!” These six consecutive months gained 17,883 Dow points in 65 years, while the remaining May-through-October months lost 1066 points. In the last two years this pattern has been less “eye popping.” The DJIA gained 4.8% in 2013 and 4.9% in 2014 between May 1 and October 31 and 6.7% and 2.6% between November 1 and April 30.

As always, this year’s almanac is chock full of data that will delight traders who believe that past is prologue.

The turkeys arrived for their Thanksgiving dinner

I took this picture of deer and wild turkeys feasting in my back yard at dawn yesterday. A couple of turkeys flew into the vegetable garden, eating who knows what in the garden paths. When it was time for the turkeys to move on, one of birds in the garden was stymied. He/she had no idea how to get out and instead paced up and down along the fence, inevitably ending up in the corner. The turkey’s family briefly showed some concern but then abandoned the dullard. I finally went out to open gates, hoping that this might prove an avenue of escape. Obviously my presence and the clanging of metal was frightening enough to inspire the turkey to “get wings.”

Benjamin Franklin might have called wild turkeys “birds of courage” and proposed that the wild turkey, not the bald eagle, be the official animal of the United States, but this particular wild turkey exhibited neither courage nor any problem solving skills.

Happy Thanksgiving

Mellon & Chalabi, Fast Forward

I just received my copy of next year’s Stock Trader’s Almanac. The page I normally turn to first is the editor’s choice of best investment book of the year. I don’t think I’ve ever agreed with the choice, but I always note it in my review. This year it turned out that I hadn’t read the top pick, so I felt I needed to remedy that state of affairs. I set some time aside to read Fast Forward: The Technologies and Companies Shaping Our Future by Jim Mellon and Al Chalabi (Fruitful Publications, 2015). And although I admit I read it in a manner befitting its title, it was definitely worth the time I put in, and probably considerably more.

This seems to be the fifth book that Mellon and Chalabi have written. Their earlier efforts are Cracking the Code, Wake Up!, Top 10 Investments for the Next 10 Years, and Top Ten Investments to Beat the Crunch!

Fast Forward analyzes technologies in eight areas: robotics and automation; life extension; the internet of things; transportation; energy; payment processing; 3D printing; and media, publishing, education. Much of what they write is a summary of material that has been covered extensively in the media. But what is new and valuable is that the authors describe companies, both private and publicly listed, that are engaged in these technologies. It is therefore an idea book for technology investors. In the third appendix to the book they list the public companies chapter by chapter, along with the exchange on which they trade as well as their ticker and market cap.

Although I wouldn’t put Fast Forward among the best books I’ve read this year, for those who want to explore investing in burgeoning technologies it is a useful starting point.

Grimes, Quantitative Analysis of Market Data: A Primer

Adam Grimes’s brief book, Quantitative Analysis of Market Data (only 35 pages of text), which kindleunlimited subscribers can read for free, is indeed a primer. He starts with the formulas for percent return, both simple and logarithmic, and shows how we can standardize these returns for volatility, using ATRs, historical volatility, or the standard deviation spike tool (measuring each day’s return as a standard deviation of the past 20 days’ returns). He describes normal distribution, running mean, and running median for Cauchy-distributed random numbers.

The bulk of the book consists of an explanation of “three simple tools that should be part of every trader’s tool kit: bin analysis, linear regression, and Monte Carlo modeling.”

Traders who are familiar with the most rudimentary mathematical principles of finance will learn nothing from this book. But it’s a good place for the mathematically uneducated to start and a quick review for those whose grip on statistical modeling is tenuous.

Baker, The Trade Lifecycle, 2d ed.

Retail investors and traders are for the most part blissfully ignorant of how their orders are processed. They buy, sell, and see their account balance either increase or decrease. Or they track open profits and losses. Some days even this seems like far too much information. And, if we are to believe Nicolas Darvas (How I Made $2,000,000 in the Stock Market), it may well be.

For people who work in the capital markets, however, understanding the anatomy of a trade is of vital importance because it sheds light on how banks and trading firms are structured. Where do risk managers fit in? What does the back office do? It is this kind of understanding that Robert Baker aims to impart in The Trade Lifecycle: Behind the Scenes of the Trading Process, 2d ed. (Wiley, 2015).

He pays special attention to the role of technology in the trading progress, which makes perfect sense since it’s an increasingly important part of finance. For instance, as of this past April, of about 33,000 full-time employees at Goldman Sachs, 9,000 of them were engineers and programmers. Goldman had more tech employees than Facebook. As the Business Insider article which reported these figures noted, “The massive on-boarding of tech talent shows just how seriously investment banks regard technology as a means of security and infrastructure.”

Baker’s book may not be a page turner, but it is a useful outline of how firms develop, arrange, test, approve, monitor, report, and audit trades.

Ursone, How to Calculate Options Prices and Their Greeks

Those option traders who care about the Greeks (and not all do) normally rely on trading platforms for their calculated values. Why do the calculations yourself when an algorithm can do it for you? Just as no adult works out a long division problem on paper, almost no option trader bothers to use the Black Scholes model to solve for a value that he can find by plugging a few numbers into an online calculator.

The problem with taking this shortcut is that most option traders don’t understand how their positions can change prior to expiration. They don’t know what’s under the hood. And, unlike driving a car from point A to point B, where the road is relatively straight, the car is reliable, and you can arrive safely at your destination in blissful ignorance of how the parts of the car work, trading options without any knowledge of how the Greeks affect both one another and the price of options can be lethal.

Pierino Ursone’s How to Calculate Options Prices and Their Greeks: Exploring the Black Scholes Model from Delta to Vega (Wiley, 2015) sets out to fill this void. It requires no advanced math skills (though occasionally it invokes Excel to make the reader’s life easier) but instead offers mostly back of the envelope calculations.

For instance, the 20% to 80% delta region is almost linear. “This linearity promotes working with a lot of rules of thumb and easy derivations for the Greeks. It is a strong tool for being able to come up with values for the Greeks without applying the option model.” (p. 79)

The book is not for beginning option traders, but at the same time I don’t think one should wait too long before tackling the material it covers. I personally learned quite a bit from it, much of practical value. And it’s book I’ll keep around for when I need a refresher course.

Support your local sheriff / blogger

With the holiday shopping season nigh upon us, I think it’s an appropriate time to thank those readers from the United States who have used this blog as a launch pad for their Amazon shopping. I would also like to encourage readers (U.S. only; I don’t have bank accounts elsewhere) who haven’t already done so to consider joining my supporters.

In case you don’t know how the system works, I get a small referral fee for anything you buy during your shopping session after you’ve clicked on one of my book links or used the Amazon search box on the right-hand side bar—it could be electronics, clothing, pet supplies, you name it. It costs you absolutely nothing, and it gives me another incentive, however financially modest, to keep on blogging.

Thanks very much. I really appreciate your support.

Brown et al., Make It Stick

I trust that if you read this blog you are engaged in a course of lifelong learning. But how much do you remember of what you allegedly learned? Peter C. Brown, Henry L. Roediger III, and Mark A. McDaniel offer suggestions for improving retention in Make It Stick: The Science of Successful Learning (Harvard University Press, 2014).

Among their claims,

“Learning is deeper and more durable when its effortful. Learning that’s easy is like writing in sand, here today and gone tomorrow.”

Rereading text and massed practice [the single-minded, rapid-fire repetition of something you’re trying to burn into memory] are among the least productive study strategies.

“Retrieval practice—recalling facts or concepts or events from memory—is a more effective learning strategy than review by rereading.”

“When you space out practice at a task and get a little rusty between sessions, or you interleave the practice of two or more subjects, retrieval is harder and feels less productive, but the effort produces longer lasting learning and enables more versatile application of it in later settings.”

“When you’re adept at extracting the underlying principles or ‘rules’ that differentiate types of problems, you’re more successful at picking the right solutions in unfamiliar situations.”

“People who learn to extract the key ideas from new material and organize them into a mental model and connect that model to prior knowledge show an advantage in learning complex mastery.”

These are just a few bullet points from an altogether excellent book. It’s well worth reading, and remembering.

Zweig, The Devil’s Financial Dictionary

Jason Zweig’s The Devil’s Financial Dictionary (PublicAffairs, 2015) is a book that probably every reader wishes he had been clever enough to write. Following in the satiric tradition of Ambrose Bierce (The Devil’s Dictionary, 1906), Zweig has compiled a marvelously witty set of definitions and explanations of financial jargon. Part exposé, part elucidation, it is almost always savagely amusing.

Three examples:

“QUANT, n. A trader or investor who relies primarily or exclusively on computer software and mathematical formulas without the noisy distractions of human judgment. The results, of course, can only be as good or bad as the judgment of the human who designed the computer software and the mathematical formulas.” (p. 142)

“VOLATILITY, n. The extent to which an investment’s short-term returns differ from its long-term average returns, technically known as standard deviation and colloquially known as Oh my God!” (p. 179)

HEAD AND SHOULDERS, n. A purported pattern in TECHNICAL ANALYSIS in which the price of a stock or other asset bounces up a little, down a little, up a lot, down a lot, up a little, then down a little—which is supposed to mean a lot about how the price will move in the future. If that reminds you of the lyrics to the children’s song,

  Eyes and ears and mouth and nose,
  Head, shoulders, knees and toes, knees and toes,

you might well be right, but you have no future as a technical analyst.” (p. 91)

Freeman-Shor, The Art of Execution

The Art of Execution: How the World’s Best Investors Get It Wrong and Still Make Millions by Lee Freeman-Shor (Harriman House, 2015) is a slim book. Its goal is to sear into the reader’s brain one key message: that investments need to be managed. In the words of the old saw, investors need to cut [or double down on] their losses and let their winners run.

The author manages over $1 billion in high-alpha and multi-asset strategies for Old Mutual Global Investors. From this position he was able to analyze 1,866 investments, representing a total of 30,874 trades, made by 45 leading investors from June 2006 to October 2013. He had given each of these investors between $20 and $150 million to invest for his Best Ideas fund, “with strict instructions that they could only invest in ten stocks that represented their very best ideas to make money.” (p. 6) Only 49% of these investments were profitable, and yet most of the investors still made a lot of money for the fund. The key to their success was knowing what to do when they were losing and what to do when they were winning. In brief, the bulk of their success came from wisely managing their positions.

When these investors had losing positions, they adopted one of three personae: Rabbits, Assassins, or Hunters. The Rabbits, whom the author wishes he had never hired, exhibited a buy and hope mentality. They did not adapt to changing circumstances; they did nothing to mitigate a losing situation. Of the 946 investments that lost money, 19 lost more than 80% and 131 lost more than 40%. Of those that fell by 40%, not one eventually produced the required returns to get back to breakeven.

The Assassins had stop losses in place, so that all losing trades would be killed when they were down by 20-33%. They were right to take action. Of the 946 losing investments, 41% saw their share price decline further. Of the stocks that subsequently rallied, only 37% returned more than 20%. So, the author concludes, “two-thirds of the time you are likely to be better off cutting a losing position.” (p. 33)

The contrarian Hunters pursued a Martingale approach, doubling down either when they thought that a bottom was in place on a stock in which they still believed or when its stock price had fallen between 20% and 33%. They too posted positive returns even though the odds were against them.

Investors who have winning positions can either be Raiders or Connoisseurs. “Raiders occupy a thin line between success and disaster. These are investors who like nothing better than taking a profit as soon as practical.” (p. 52) They don’t let their winners run. Furthermore, the author notes, “Raiders are often Rabbits when they’re losing—and the combination is fatal.” (p. 58)

Connoisseurs are the most successful investors even though, in the author’s sample, only a third of their ideas made money. What sets them apart? They invest in companies with a predictable growth of earnings and yet look for significant upside potential. They invest big and have focused portfolios. Up to 50% of their assets might be invested in just two stocks. They take small profits along the way but keep the majority of their positions in play, riding their winners. And, of course, when their positions turn into losers, they become either Assassins or Hunters.

Freeman-Shor’s message isn’t new, but it’s one that’s always worth repeating.

Ip, Foolproof

Greg Ip, the chief economics commentator for the Wall Street Journal and author of The Little Book of Economics, has written an intriguing new book: Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe (Little, Brown, 2015). Drawing primarily from finance and secondarily from such diverse fields as forest management, sports, medicine, and transportation, he explores the tradeoff between innovation and crisis. Or, alternatively, though obviously not equivalently, between stability and disaster, between safety and danger, between fear and adventure.

The tension between these opposing forces “bedevils the people whose job it is to steer our economy and manage our surroundings. Philosophically, they fall into two schools of thought. One, which I call the engineers, seeks to use the maximum of our knowledge and ability to solve problems and make the world safer and more stable; the other, which I call the ecologists, regards such efforts with suspicion, because given the complexity and adaptability of people and the environment, they will always have unintended consequences that may be worse than the problem we are trying to solve.” (pp. 18-19)

In the first half of the book Ip demonstrates how “the pursuit of safety leads to behavior that makes disaster more likely.” (p. 125) Football helmets, designed to reduce injuries, became weapons for spearing opponents. Antilock brakes became an excuse to drive faster and brake harder. The global saving glut, a form of insurance, contributed to the financial crisis of 2008 as, of course, did portfolio insurance to the crash of 1987.

The second half of this book offers prescriptions for how to strike the right balance between safety and disaster.

One of Ip’s theses is that it doesn’t make sense to pay any price to avoid a disaster or crisis. “Not only is the price too high, but the nature of complex systems is such that if risk taking is repressed in one arena, it may migrate to another, and even more costs and damage may occur through other means.” (p. 130) For instance, shutting down nuclear power plants because there is a very small chance of a catastrophe (and, even then, the maximum number of deaths is probably in the hundreds) may not be justifiable. Each year deaths attributed mainly to pollution from the burning of wood and fossil fuels total more than 7,000 in the U.S. alone.

Sometimes seemingly excessive risk taking turns out to be good for society. In the course of the dot-com bubble this was manifest not only in the overly indebted Amazon’s ability “to pull another financing rabbit out of its rather magical hat” and stay afloat. It was also manifest in the host of telecom companies that borrowed billions to lay fiber-optic networks between cities and continents –and that subsequently sank. Of the networks we now take for granted, 63% of transatlantic, 35% of trans-Pacific, and 39% of the capacity between the U.S. and Latin America were built by now-bankrupt companies.

We will never eliminate disasters and crises. “Nor,” Ip contends, “should we want to. Periodic crisis is the price we pay for an economic system that encourages, and rewards, risk. Periodic disasters are the price we pay for situating our cities in desirable, productive places.” And so, the book concludes, “Our goal should be to eliminate big disasters, not small ones, to accept a bit more risk and instability today in return for more reward and stability in the long run.” (p. 219)