Thursday, November 27, 2014
I have mixed feelings about the wild turkeys that visit. They have been known to peck at the ground-level windows of my house with such vehemence that I could easily envisage a flock of turkeys promenading around the living room. But my heart went out to the turkey I watched being murdered by a coyote a couple of weeks back--right outside of my vegetable garden.
I'm thankful I wasn't that turkey. And no, I'm not having turkey for dinner today.
Wednesday, November 26, 2014
So let’s turn to the message, without further value judgments.
Achieving success as an active trader means making “$200 on our trades each day.” All you have to do to make your “day’s pay” is to purchase 1,000 shares of the right stock and sell it for “just $.20 more per share than you paid for it.” (p. 50)
But how can the trader identify the right stock? Pugliese lists nine rules: (1) stay away from stocks that are higher than $30 a share, (2) avoid brand-name stocks, (3) steer clear of stocks with insufficient tier depth, (4) stay away from stocks with low trading volumes, (5) avoid stocks with high trading volumes, (6) pass up stocks with very few active market makers, (7) keep your spread to a minimum, (8) follow the stock trend both in pre-market and during the day to get a sense of direction, and (9) look for market maker traps.
Once the trader has created a list of tradable stocks and found the ax for each, “the only thing left for you to learn is when to buy a stock and when to sell it.” (p. 101) The answer is simple: the trader has to pay attention to support and resistance levels.
That’s it. “Once you hit $200, you have earned your day’s pay and can retire for the day.” (p. 123)
Well, actually that’s not quite it because Pugliese has ten trading rules of the road, including no overnights and no dollar cost averaging.
He concludes by inviting the reader to visit his educational site for “even more information on furthering your trading career.” (p. 187)
Monday, November 24, 2014
There’s an abundance of information available online about option spreads and combinations, and Nations of necessity covers much of the same territory. But he proceeds more analytically, and he deals with issues that most online descriptions ignore, such as ways to mitigate wide bid/ask spreads. Take, for instance, the long call condor. Nations looks at an AAPL call condor that, using midpoint pricing, costs 18.87 and that, buying on the ask and selling on the bid would cost 0.63 more. What if we were to replace the in-the-money call spread “with something that’s out-of-the-money and has bid/ask spreads similar to the bid/ask spreads of these other out-of-the-money options?” That is, what if we sold a put spread with the same strikes instead of buying that call spread—and again sold at the bid and bought at the ask? Instead of paying a 0.63 penalty, we now pay only 0.27. This “new, magical structure” is an iron condor. (pp. 201-202)
In eleven chapters this book deals with vertical spreads, covered calls, covered puts, calendar spreads, straddles, strangles, collars, risk reversal, butterflies, condors and iron condors, and conversion/ reversal. Every strategy is encapsulated in cheat sheets and, more importantly, is illustrated with examples, complete with tables and figures. Here, for instance, is the graph of a vertical spread he analyzes, which includes the probability of profitability—something he explains how to calculate on the previous page.
Unlike Nations’ previous book, Options Math for Traders, this one is math-lite. He confines his discussion of option pricing to a single chapter and refers the reader to his website Option Math to download a free spreadsheet that calculates theoretical option values using the Black-Scholes model and inputs supplied by the user.
But it provides an excellent conceptual framework for understanding spreads and combinations. With the help of this book the reader can progress from being a trader who uses options to an options trader.
Wednesday, November 19, 2014
I’m not sure how many of these articles made their way into books. I know that Kevin Roose’s “One Percent Jokes and Plutocrats in Drag: What I Saw When I Crashed a Wall Street Secret Society” was recycled in his Young Money.
This is not the kind of book that lends itself to a review, but I thought I’d share the gist of Jia Lynn Yang’s article “Maximizing Shareholder Value: The Goal That Changed Corporate America.”
We take it for granted today that a company’s primary purpose is to maximize shareholder value, but that wasn’t always the case. “Rather, it was introduced by a handful of free-market academics in the 1970s and then picked up by business leaders and the media until it became an oft-repeated mantra in the corporate world.” (p. 162)
“In the decades after World War II, as the U.S. economy boomed, the interests of companies, shareholders, society, and workers appeared to be in tune. … Even until 1981, the Business Roundtable trade group understood the need to balance these different stakeholders. ‘Corporations have a responsibility, first of all, to make available to the public quality goods and services at fair prices, thereby earning a profit that attracts investment to continue and enhance the enterprise, provide jobs, and build the economy. ... The long-term viability of the corporation depends upon its responsibility to the society of which it is a part. And the well-being of society depends upon profitable and responsible business enterprises." (p. 164)
Today those words sound positively utopian. We have succumbed to Milton Friedman’s infamous 1970 remark that the only “social responsibility of business is to increase its profits.” (p. 165) This shift in objectives, Yang contends, “helped spawn the rise of executive pay tied to share prices—and thus the huge rise in stock-option pay. As a result, average annual executive pay has quadrupled since the early 1970s.” (p. 165)
I found a different set of figures from the Economic Policy Institute, a union-oriented organization: that “from 1978 to 2013, CEO compensation, inflation-adjusted, increased 937 percent, a rise more than double stock market growth and substantially greater than the painfully slow 10.2 percent growth in a typical worker’s compensation over the same period. The CEO-to-worker compensation ratio was 20-to-1 in 1965 and 29.9-to-1 in 1978, grew to 122.6-to-1 in 1995, peaked at 383.4-to-1 in 2000, and was 295.9-to-1 in 2013.”
This isn’t the place to parse economic data. Suffice it to say that CEOs are making much more, workers are treading water, and shareholder value is rising. Goals are no longer balanced.
Monday, November 17, 2014
In this his first book, Doug Kass on the Market: A Life on TheStreet (Wiley, 2014), Kass, with the help of his editor Daniel Robinson, offers a selection of these columns. They document the thinking of a conservative short seller (or, the stuffed animal the cover portrays him holding, a teddy bear) over a range of market conditions.
The book is divided into nine sections: where it began, short-selling, lessons learned, the great decession: subprime and credit/debt crisis, recovery, against the grain, Wall Street personalities, Buffett watch, and surprises. There’s some overlap, and some understandable repetition, but Kass covers a lot of territory in more than 500 pages.
I was most interested in his investing advice. Let me share a few of his pearls of wisdom here.
“Regardless of one’s modus operandi (fundamental, technical, or a combination of both), logic of argument and power of dissection are the two most important ingredients in delivering superior investment returns. Common sense, which is not so common, runs a close third.” (p. 51)
“Under a normally trending (and upwardly sloping) market (and dependent upon my degree of confidence), I would have as much as 67% (when fully invested) of my portfolio in investment holdings (with a majority of longs), and I would have as much as 33% of my portfolio in trading rentals (again, a majority of longs).”
In a range-bound market, “I would be more inclined to trade stocks…. In this case, I might only be as much as 40% committed to investments and perhaps as much as 60% in opportunistic rentals, with a mix of both longs and shorts.”
In a downwardly sloped market, “in theory, my portfolio … would be dominated by shorts, but, in reality, it’s not practical, as the asymmetric risk/reward of short sales would reduce the overall commitment to shorts even in a correcting market phase.” (p. 94)
“Avoid illiquid and heavily shorted stocks. If you don’t, eventually a short squeeze will be the outcome, and there will be heavy losses with it.
“Trade around your short positions, and ladder your shorts with the timing of expected catalysts (in terms of the calendar) to ensure superior performance and participation in market downdrafts.” (p. 17)
Since I devote this blog almost exclusively to books on trading and investing, I’m always interested in what other people read. In 2011 Doug Kass described The Most Important Thing by Howard Marks as “a tour de force, … the single-best investment primer I have read” since Graham and Dodd’s Security Analysis (1934) and Graham’s The Intelligent Investor (1949). I wasn’t so effusive in my review.
Fans of Warren Buffett will undoubtedly turn immediately to the section that describes Kass’s trip to Omaha to ask questions as a “credentialed bear,” one who wrote a column in 2008 explaining his rationale for being short Berkshire stock. They won’t be disappointed.
The final section of the book is devoted to his annual list of possible surprises for the coming year, a practice he started in 2002. I don’t know why anyone would ever want to go through this exercise since, as Woody Allen said (and as Kass quotes him), “I’m astounded by people who want to ‘know’ the universe when it’s hard enough to find your way around Chinatown.” (p. 428) Predicting the future is harder yet. To Kass’s credit, he lays everything out—the prescient as well as the dead wrong.
Wednesday, November 12, 2014
Mary Pilon’s The Monopolists: Obsession, Fury, and the Scandal Behind the World’s Favorite Board Game (Bloomsbury) is a well-crafted tale of how Monopoly came to be and how the wrong person was given (actually, falsely claimed) credit for creating it.
Under the best of circumstances attribution is a tricky business. For instance, every school child is taught that Thomas Edison invented the light bulb, and yet he was only the most famous in a string of inventors who contributed to electric lighting. Volta developed the first practical method of generating electricity in 1800, Humphrey Davy invented the electric arc lamp in 1802, Warren de la Rue developed a platinum filament light bulb in 1840, Joseph Swan came up with a light bulb that used carbonized paper filaments in 1850, and Henry Woodward and Matthew Evans filed a patent in 1874 for an electric lamp with carbon rods. They sold their patent to Edison in 1879, the same year in which he filed a patent for an electric lamp with a carbon filament. And, of course, Edison did not work alone; he had a large team of researchers. It is more accurate, therefore, to say that Thomas Edison and his team invented the first commercially practical incandescent light.
In the case of Monopoly, the journey from first iteration to wildly popular board game was more incremental. But one thing we can now say with certainty. Charles Darrow, the unemployed salesman whose alleged invention—or so the official story went—rescued both Parker Brothers and Darrow from financial collapse, did not create the game. He simply reaped its benefits.
In the beginning was a woman, Elizabeth Magie, a follower of the anti-monopolist Henry George. During the day she worked in the Dead Letter Office, in the evening she pursued literary and theatrical ambitions and dabbled in invention. At the age of 26, for instance, she patented a gadget that improved on typewriter technology. She also taught classes about George’s single tax theory. Wanting to expand her audience for George’s theory, she came up with a board game, which she called the Landlord’s Game. “It is a practical demonstration of the present system of land-grabbing with all its usual outcomes and consequences,” she wrote in 1902. “[S]omewhat surprisingly, Lizzie created two sets of rules: an anti-monopolist set in which all were rewarded when wealth was created, and a monopolist set in which the goal was to create monopolies and crush opponents.” (p.33) We know, of course, which set of rules the public came to embrace.
The Landlord’s Game became popular, mainly among east coast, left-wing intellectuals. It was played at the Wharton School and Columbia and by the late 1920s was a sensation in the fraternity scene at Williams College. One of the students who played the game at Williams produced his own version of it, calling it Finance. He couldn’t find buyers for his game, but before he abandoned the project altogether he taught the game to some Quaker friends, “who would modify it and change its course in the most unlikely way.” (p. 79)
A group of Quakers moved to Atlantic City to “establish a healthy, fresh-air community, complete with modest accommodations and prayer lodges.” (p. 80) Well, you can pretty well guess the next stage in the game’s development, though I’d wager to say that you don’t know why Baltic Avenue is less valuable than Marvin Gardens or that ‘Marvin Gardens’ turned out to be a tell-tale copying error (the correct spelling was ‘Marven’).
Unfortunately it’s a short step from the innocent Quaker innovators to the dark side of the game’s history.
Pilon, a staff reporter at The New York Times, does a brilliant job of exposing questionable corporate mores and individual dishonesty and greed. The heroes of the book, such as Ralph Anspach—who uncovered the provenance of Monopoly while engaged in costly litigation over his Anti-Monopoly board game decades later, struggled; the villains thrived. The game, of course, continues. It no longer, however, comes with a printed copy of Darrow’s rags to riches story.
Monday, November 10, 2014
Here I’ll highlight three concepts that are basic to Brandes’ framework: investing versus speculation, value philosophy, and risk.
Brandes expands on Graham’s distinction between investing and speculation. In The Intelligent Investor Graham wrote: “An investment operation is one which, upon thorough analysis, promises safety of principal and an adequate return. Operations not meeting these requirements are speculative.” Brandes adds two more criteria that define speculation: “any contemplated holding period shorter than a normal business cycle (typically three to five years)” and “any purchase based solely on anticipated market movements.” (p. 26)
Value investors agonize over—and disagree about—what characteristics a company must have to be considered a value play. Brandes simplifies the selection process, condensing “the most significant precepts of the value philosophy into a four-step test that you can quickly apply to any company that catches your eye”: “1. No losses were sustained within the past five years. 2. Total debt is less than 100 percent of total tangible equity. 3. Share price is less than book value per share. 4. Earnings yield is at least twice the yield on long-term (20-year) AAA bonds.” (p. 71)
There’s some wiggle room in using these guidelines. As Brandes writes, “Utilities, which are usually buffered from economic influences, may allow a little more leniency on the debt-to-equity or annual earnings growth tests, while for a potentially more volatile technology-based business, these would be two must-pass criteria before we would even consider it.” (p. 73) Moreover, lest one think that value investing can be reduced to a straightforward four-step process, the professional value investor will typically subject any company in which he is interested to much more detailed analysis.
Finally, let’s look at Brandes’ understanding of risk. He rails against conflating volatility with risk. Risk is just what the average investor thinks it is—the possibility of losing money. He argues that “working with equities is not about reading the beta or standard deviation and diversifying away the alpha potential. It means doing some homework, stepping up, and taking on some additional volatility risk that could turn out to be an excellent value opportunity.” (p. 217)
Risk in its true sense cannot be measured in the way that volatility and similar mathematical notions can. But it follows a general pattern. Investors lose money when they overpay, when they sell at a loss (that is, when they didn’t wait patiently for the stock to turn around), when the company itself deteriorated, and when they strayed from fundamental investing discipline and lost focus. Note that only one of these reasons for a loss of capital is outside the control of the investor. In the investing world, where uncertainty is said to reign supreme, that definitely shifts the balance of power.
Wednesday, November 5, 2014
The spiral bound, navy-covered almanac opens flat for easy access to its data or for jotting down notes. The format remains essentially the same, 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 seven significant errors in 64 years), 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. New this year is a three-page section in which “some of the best minds on Wall Street” offer their outlooks for 2015.
The Stock Trader’s Almanac pays particular attention to the presidential cycle, and it bodes well for 2015. Pre-presidential election years are the best performers in the cycle. “There hasn’t been a down year in the third year of a presidential term since war-torn 1939, Dow off 2.9%. The only severe loss in a pre-presidential election year going back 100 years occurred in 1931 during the Depression.” (p. 20)
The presidential cycle isn’t the only thing 2015 has going for it. “The fifth year of the decade is also the best year of the decennial pattern by a long shot with only one loss in the past 13 decades.” (p. 6)
Enjoy it while it lasts, since Jeffrey Hirsch expects a bear market after 2015, “taking the market 30-40% lower into 2017-2018 into the range of Dow 11,500-13,500.”
What other seasonals are powerful? The best six months strategy still works. “Investing in the Dow Jones Industrial Average between November 1st and April 30th each year and then switching into fixed income for the other six months has produced reliable returns with reduced risk since 1950.” In 64 years the Dow gained 17432 points during these months and lost 1066 points during May through October. The S&P gained 1790 points in the same best six months versus 75.5 points in the worst six. And applying a simple MACD timing indicator nearly triples these results.
The first months of quarters are the most bullish, and the first trading day of the month outshines all others combined. You read me right: “Over the last 17 years the Dow Jones Industrial Average has gained more points on the first trading days of all months than all other days combined. While the Dow has gained 8868.89 points between September 2, 1997 (7622.42) and May 16, 2014 (1649.31), it is incredible that 5468.22 points were gained on the first trading days of these 201 months. The remaining 4003 trading days combined gained 3400.67 points during the period. This averages out to gains of 27.21 points on first days, in contrast to just 0.85 points on all others.” (p. 86) By the way, 2014 did not continue this tradition; during the first trading days of the first five months it lost 562.06 points (-135.31, -326.05, -153.68, 74.95, and -21.97).
This almanac is chock full of data that will delight those traders who believe that past is prologue. Even those who are skeptical have to pay attention to data that seasonal traders rely on and that therefore tend to move markets.
Monday, November 3, 2014
In Managing Equity Portfolios: A Behavioral Approach to Improving Skills and Investment Processes (MIT Press, 2014) Michael A. Ervolini, CEO of Cabot Research, offers the beleaguered portfolio manager some suggestions on how to go about improving. That such a book is deemed necessary is somewhat worrisome. Retail investors and traders, whose portfolios are dwarfed by their institutional brethren’s and who don’t collect hefty salaries for managing their own money, have been deluged with works offering much of the same advice—beware of behavioral traps, focus on process rather than outcome, keep a trading journal. Fortunately, since Cabot Research provides “innovative analytics to help money managers improve portfolio performance,” the book also highlights some of the metrics that all traders and investors can use to assess and improve their own performance.
Instead of rehashing the findings of behavioral finance, which I’ve written about on numerous occasions, I’ll focus on the book’s main organizing principle and some of its attendant metrics.
Investing, stripped to its bare essentials, involves three skills: buying, selling, and position sizing. “Familiar as these terms are,” the author writes, “few professionals know with any degree of confidence how much of their portfolio alpha comes from just the buying.” Or the selling, or the position sizing. “Not knowing how effective each skill is means that any attempt to improve is, at best, based on a hunch.” The author advocates adopting an analytical framework that regards performance as “a portfolio of decisions, rather than holdings. … The goal is to rigorously measure skills, process, and behaviors so that managers can do more of what they do well and have the necessary information to make small refinements that have a high likelihood of helping them improve.” (p. 158)
How should a money manager proceed? First, he has to collect data—the more granular the better. “For example, when making adds to existing positions, you might jot down answers to the following questions: Is the position currently a winner or loser? Prior to the add, is it small, mid-sized, or large relative to your typical full weight? How is it performing relative to the two or three basic attributes you use to gauge a stock’s alpha potential … ? How are you feeling—optimistic, pessimistic, confident, fearful, etc.?”
The manager must then analyze the data. “For example, to look deeper into your adds to winning positions, you might create a graph with an x-axis indicating time and two distinct y-axes, the one on the left indicating cumulative return, and the one on the right indicating the size of the adds.” (p. 236) And finally, he must draw up an improvement plan.
Ervolini walks the reader through a few ways to analyze buy, sell, and position sizing decisions. Sell decisions can be critiqued through the lens of holding time—whether positions harvested early are helping or hurting performance. As for buying or adding to positions, you can analyze whether your “high conviction” purchases are outperforming those in which you have less confidence.
The upshot is that you can only know your strengths and weaknesses if you find a way to measure your investing behavior—a way that is, the author recommends, simple (otherwise you won’t do it) and granular (otherwise the results will be too general to be useful). Separate out your trading activities, and here, I would suggest, you can include such things as order type and fill, response to market volatility, source of investment idea, etc. You never know what kinds of analytics might be helpful until you start collecting data and mining the results for performance gold.