Rowland and Lawson, The Permanent Portfolio

Talk about simple. Investing doesn’t get much simpler than The Permanent Portfolio: Harry Browne’s Long-Term Investment Strategy (Wiley, 2012). Craig Rowland and J. M. Lawson explain how to implement the 25%-25%-25%-25% (stocks, bonds, cash, gold) asset allocation strategy that Harry Browne recommended in his 1987 book Why the Best Laid Investment Plans Usually Go Wrong.

Browne assumed that financial markets are uncertain, which to him meant that no can predict what the market is going to do next and, as a corollary, that no one can time the market. He also admonished investors not to depend on any one investment, institution, or person for their financial safety. He even urged investors to keep some of their assets outside the country in which they live as protection against natural or manmade disasters and “against a government that may try to solve its financial problems by confiscating citizens’ private property.” (p. 11)

The Permanent Portfolio is a steady Eddie performer. Starting in 1972 after the gold standard ended and then looking at annualized real returns by decade (ending in 2009), the Permanent Portfolio returned +5.7%, +4.7%, +4.3%, and +4.2% with less volatility than competing portfolios. A 75/25 portfolio returned -2.3%, +10.5%, +12.4%, and -1.2%; a 50/50 portfolio -2.1%, +9.1%, +9.8%, and +0.6%; and a 25/75 portfolio -2.0%, +7.6%, +7.2%, and +2.2%.

Although there is a Permanent Portfolio mutual fund (with a different allocation: 20% gold, 5% silver, 10% short-term Swiss government debt, 15% real estate and natural resource stocks, 15% aggressive growth stocks, and 35% U.S. Treasury bills and bonds) and a new Permanent ETF, the authors suggest that investors, unless they want convenience, can get better diversification geographically and institutionally on their own.

It is somewhat amazing that the authors can fill over 300 pages writing about Browne’s 25-25-25-25 asset allocation strategy, but they manage—and in a way that investors searching for a way to grow their wealth can learn from. For instance, Rowland and Lawson explain rebalancing bands, tax considerations, and buying and storing gold (yes, they suggest holding at least some physical gold and storing part of it locally for emergencies and the rest abroad if you are able).

Browne’s strategy won’t appeal to those who are convinced they can outsmart the markets. It may not even be the best passive asset allocation plan. But it’s certainly better than investing on a wing and a prayer.

Little, Trend Trading Set-Ups

If you’ve read L. A. Little’s previous book, Trend Qualification and Trading, which I reviewed last year, you can skim through the first part of Trend Trading Set-Ups: Entering and Exiting Trends for Maximum Profit (Wiley, 2012). Essentially, Little introduces what he calls neoclassical technical analysis based solely on price, volume, and time. No squiggly lines, no patterns. Neoclassical technical analysis relies on the distinction between qualified and suspect trends for trade direction, anchor bars and zones for timing, and a trading cube that “offers a visual of the qualified trends across the differing time frames for a stock, its sector, and the general market it is part of as well as the inherent relationships between these three related components.” (p. 56)

In the second part of the book Little moves on to the task of formulating a trading plan and finding the highest probability trade set-ups.

Part and parcel of any trading plan is determining position size. But since in trading nothing is black and white, when trying to figure out trade size it can be misleading (and dangerous to the bottom line) to plug some numbers into a ready-made model and then confidently go full steam ahead. “Knowing when the probabilities for success are significantly greater than failure affords the market participant the luxury of making comparatively outsized trades in such situations. Money is made in the markets in bundles most of the time. It does not just arrive day in and day out. In fact, it usually leaks out rather than leaks in. Being able to make a larger bet when the probability for success is greater while at the same time the reward-to-risk of the trade is quite favorable is the Holy Grail of trading.” (p. 100)

So how does a trader identify high probability set-ups? First of all, there are only two basic trade types—breakouts and retraces. But there are seven possible and related scenarios for these set-ups, which I can’t possibly describe in a brief review. These scenarios are “tightly coupled” around the concept of retest and regenerate. “The term retest and regenerate was first coined to describe the common and repetitive situation where a swing point is broken and a suspect trend created (volume does not expand on the break). In the ebb and flow that accompanies most markets and stocks, it is overwhelmingly probable that when a stock breaks out under such conditions it will, after some period of time, retrace back to the area where it broke out to retest.” (p. 115) It is turns out that this is true not only of suspect trends but of confirmed trends as well.

The author has done extensive work to assign probabilities of failure to each of these scenarios. For example, the probability that a confirmed bullish trend will fail when a retest and regenerate sequence occurs within six bars of the breakout is 19.86%. For a suspect bullish trend, the probability is 11.35%.

Little provides trade entry decision ledgers for a range of scenarios. They are essentially checklists where, if a certain number of items is true, it is then appropriate to check the potential reward versus risk to make a final trading decision.

Trend Trading Set-Ups is a clear testament to the principle that trading is simple (although not too simple) but not easy. I don’t know what a good trader’s track record would be following Little’s method. I can say, however, that it’s a thoughtful, plausible approach to trading. And I don’t say that too often.

Stock Trader’s Almanac 2013

The election season is nearing its end and the candidates are making their last ditch efforts to sway voters. Which means, among other things, that it’s time for another look at how the presidential cycle influences stock prices. The Stock Trader’s Almanac (Wiley, 2013), edited by Jeffrey A. Hirsch and Yale Hirsch and now in its 46th annual edition, is the premiere source of this information.

A spiral-bound hardcover, the almanac includes a calendar section, a directory of trading patterns and databank, and a strategy planning and record 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 62 years), and the January barometer in graphic form. 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.

So what, based on history, do we have to look forward to post-election? For starters, the post-election year is the worst performing year of the four-year presidential cycle. The average annual gain in the DJIA for the four-year cycle beginning in 1833 was: post-election year 2.0%, mid-term year 4.2%, pre-election year 10.4%, and election year 5.8%. The total percentage gains were 86.1%, 187.0%, 469.5%, and 254.5%. Of the 21 post-presidential election years since 1929, the Dow closed up 11 times: 1933, 1945, 1949, 1961, 1965, 1985, 1989, 1993, 1997, 2005, and 2009. Jeffrey Hirsch doubts that 2013 will be number 12. “After the yearend rally and positive 2012, we are concerned that the next major bear market will occur in the 2013-2014 period.”

So far this year Hirsch’s favorite defensive play has been HDGE (AdvisorShares Active Bear ETF), managed by John Del Vecchio and Brad Lamensdorf. Del Vecchio is also the co-author of the almanac’s choice for best investment book of the year: What’s Behind the Numbers? (With any luck I should be getting my review copy of this book soon.)

Traders and active investors who thrive on historical data will once again have a heyday with this almanac. Take, for instance, the notion of the super-8 days. “The market currently exhibits greater bullish bias from the last three trading days of the previous month through the first two days of the current month, and now shows significant bullishness during the middle three trading days, 9 to 11, due to 401(k) cash inflows.” (p. 88) In 2011 the super-8 day returns totaled 13.93%, the rest of the month (13 days) saw a total loss of 5.68%.

The promotional blurb describes the Stock Trader’s Almanac as “the ultimate desktop market data bank.” I never consider anything ultimate, but this almanac comes pretty darned close. And that’s praise from someone who tends not to pay very much attention to seasonals.

Addicted to reading?

For those who follow this blog because they like to read, here's an enjoyable piece from the WSJ: My 6,128 Favorite Books by Joe Queenan.

Travers, Hedge Fund Analysis

Investors who are thinking about handing over a portion of their assets to a hedge fund manager are often at a loss about where to turn. Some of the legendary funds have either closed or are not accepting new outside money. A lot of funds are underperforming duds. A few are frauds. New funds that often outperform are unknown quantities. What is an individual investor (admittedly, one with a fair amount of time on his hands) or a professional responsible for allocating institutional money to do? For starters, he can read Frank J. Travers’s Hedge Fund Analysis: An In-Depth Guide to Evaluating Return Potential and Assessing Risks (Wiley, 2012) and learn how to become his own due diligence analyst.

The first step is to troll through hedge fund databases, some available at no cost, screening for potential candidates. Let’s say you want an equity long/short fund in the U.S. with a minimum three-year track record, annualized return in the top quartile of its peers, minimum assets under management of $250 million, and reasonable liquidity terms. You can narrow the field substantially with just these parameters. Making some qualitative judgments here and there, let’s assume that you manage to whittle the funds down to just five for further review. Your real work is about to begin as you evaluate which fund is the best fit with your total portfolio of investments.

Travers chooses one of these funds, which he dubs Fictional Capital Management, as his case study. He analyzes it from start to finish, including mock interviews with key investment personnel and an operational review. The analysis is exhaustive.

In fact, the book is so detailed that I’m sure even the least astute analyst could successfully use it as a complete cheat sheet (or, the less tainted word, template) in performing his own due diligence. Travers has performed a real service for anyone who is trying to find the right hedge fund to add to his portfolio.

Nahin, The Logician and the Engineer

Back when I took high school physics, a course taught by a thoroughly uninspired and uninspiring man whose name I have mercifully forgotten, a group of guys (who I suspect went on to become TV repairmen) and I had a pact. I would do their math homework and they would do my “hands-on” projects, especially those involving electrical circuitry. Left to my own devices I would undoubtedly have sent sparks flying in all directions.

Fast forward. Here I am with Paul J. Nahin’s book The Logician and the Engineer: How George Boole and Claude Shannon Created the Information Age (Princeton University Press, 2012). The author promises that no knowledge of electronics is required, just an understanding of polarity, Ohm’s law for resistors, and the circuit laws of Kirchhoff. “No more than a technically minded college-prep high school junior or senior would have.” Well, that stirred up a lot of bad memories.

So, rather than pretend that I relish looking at wiring diagrams I decided on a different tack. Motivated by a book I recently finished but cannot review for a while (Mastery), I thought it might be worthwhile to look at how Boole and Shannon, men from different centuries and very different backgrounds, came to be such remarkable thinkers.

In today’s post I’m not drawing any conclusions, just presenting short biographies.

George Boole was born in Lincoln, England, in 1815. His father was a cobbler who “seems to have been able to do anything well except his own business of managing the shop.” His real interests lay in mathematics and the construction of optical instruments, interests that he shared with George.

Boole’s formal education was scanty—after primary school a brief stint at a commercial school. He taught himself languages in preparation for becoming a clergyman. But fortunately for the world he soon enough found his true calling. At the age of sixteen he became an assistant teacher of Latin and mathematics at a small boarding school, a job he lost after two years. Among his many sins, he did math problems in chapel. In the evenings, “after a day of being a bad teacher to dull boys,” he plowed through a book on differential calculus which prepared him to read the classics of Lagrange, Laplace, Newton, and Poisson. “As Boole later explained to a friend, he managed it all by sheer force of will, just reading and re-reading, over and over, until he understood.” (p. 20)

Boole continued to teach at various day and boarding schools, all the while writing math papers, inspired perhaps by the establishment of a new math journal, the Cambridge Mathematical Journal. The editor of the journal, Duncan F. Gregory, gave Boole “almost incredibly generous aid,” without which “it is not unreasonable to imagine that Boole’s spirit would have been crushed right at the start.” Gregory published Boole’s early papers and then, when one was too elaborate for the Journal, recommended that Boole submit it to the Transactions of the Royal Society of London. This paper earned Boole a Royal Medal as the best mathematics paper published in the Transactions in the previous three years.

At the age of 34, with no university degree, Boole was appointed professor of mathematics at Queen’s College (today’s University College), Cork, Ireland, where he spent the rest of his short life. He continued to publish and moved “from one honor and achievement to the next.” (p. 27) He died, presumably from pneumonia, shy of his fiftieth birthday.


Claude Shannon was born in Michigan in 1916. His father was a business man and probate judge; his mother, a language teacher and high school principal. Early on Shannon displayed an interest in how things work; when he was in high school he earned pocket money by fixing radios at a local department store. He graduated from the University of Michigan with degrees in mathematics and electrical engineering and then, as a graduate student, got a job as a research assistant in MIT’s Department of Electrical Engineering to work part-time on Vannevar Bush’s differential analyzer, the world’s most advanced analog computer.

In Bush Shannon found “an early mentor” (and champion) “every bit as important to him as Gregory had been to Boole.” (p. 29) Shannon’s job involved understanding and maintaining the analyzer’s controller, a complex circuit of over 100 relays. It wasn’t long before Shannon had his epiphany of marrying Boolean algebra with electrical switching circuits. He described his work in his MIT master’s thesis, labeled by many “the most important master’s thesis ever written.”

After a foray into genetics (and eugenics) for his Ph.D., Shannon eventually ended up at Bell Labs for “an astonishingly creative fifteen years,” doing some work early on in cryptography, and in 1948 publishing “the Magna Carta of the information age,” his “Mathematical Theory of Communication.”

Shannon was strange man. Not only did he ride a unicycle through the corridors of Bell Labs while juggling balls, but he created all manner of toylike gadgetry. Some of the gadgets were scientifically intriguing, others pointless. Perhaps the weirdest was Shannon’s “Ultimate Machine.” Arthur C. Clarke described it thus: “It sits on Claude Shannon’s desk driving people mad. Nothing could look simpler. It is merely a small wooden casket the size and shape of a cigar box, with a single switch on one face. When you throw the switch, there is an angry, purposeful buzzing. The lid slowly rises, and from beneath it emerges a hand. The hand reaches down, turns the switch off, and retreats into the box. With the finality of a closing coffin, the lid snaps shut, the buzzing ceases, and peace reigns once more. The psychological effect, if you do not know what to expect, is devastating. There is something unspeakably sinister about a machine that does nothing—absolutely nothing—except switch itself off.” (pp. 35-36)

In 1958 Shannon left Bell Labs to go back to MIT. There he became interested in portfolio theory and, as William Poundstone described in Fortune’s Formula, became wealthy by applying his ideas to his personal finances.

Unfortunately Shannon was eventually afflicted with Alzheimer’s disease and spent the last seven years of his life in a nursing home.

Wachtel, The Sensible Guide to Forex

HSBC recently released a report announcing a new era for FX where, as a result of central bank intervention and low interest rates, currency trading has become much more volatile and harder for investors to interpret. “The demise of carry has brought ‘onion skin’ layers of uncertainty into the FX market, tears and all.”

Enter Cliff Wachtel’s The Sensible Guide to Forex: Safer, Smarter Ways to Survive and Prosper from the Start (Wiley, 2012). It is a beginner’s book, written for those who never participated in the glory days of carry when “the FX market had the luxury of a clear framework for understanding and trading currencies, “ a time when, if you got your interest rate calls right, you were basically home free.

Wachtel offers a different kind of framework, one centered on trader psychology and what the author calls RAMM (risk and money management). He complements these key elements with technical analysis and a smattering of fundamental analysis. Although this framework is certainly not unique to forex, Wachtel explains at length how it can help an investor identify, execute, and manage simple, low-risk, high-yield, longer-term FX trades.

The first half of the book deals with the basics; the second half with trade examples, momentum and timing indicators, intermarket analysis, and “newer, smarter” methods. If you’re one of those impatient souls who peeks at the last pages of a mystery before you’re even familiar with the characters, I’m sure you’ll want to know up front what the newer, smarter methods are. I’ll accommodate, but only with a single sentence. “For those seeking simpler ways to tap the potentially faster profits from short- to medium-term (ranging from minutes to weeks) trading of forex, with more controlled risk, we introduce two new and very useful instruments: forex social trading [and] forex binary options.” (p. 295)

Wachtel breaks little new ground in this book, but he offers a solid, far-reaching course in trading. Beginners will learn a great deal (even though, if they have little experience in the markets, they will have to stretch to grasp everything). For those who have yet to trade profitably the book may serve as a useful refresher course. Even investors who think that “trading” is a four-letter word will discover how to use currencies to diversify their portfolios and to ride long-term forex trends for lower risk, higher income.