Four switches and a light bulb, a hint

As with so many things in life, especially things that stump us, “the trick is to realize that there is more to the bulb than light.” (And if this hint isn’t sufficient, read the comments to yesterday’s post.)

Schneeweis, Crowder, and Kazemi, The New Science of Asset Allocation

Asset allocation is a topic that has long fascinated me; I’m infatuated with the idea of moving parts that sometimes correlate and sometimes don’t, that sometimes spike and sometimes dive all being blended into portfolio that can outperform benchmarks, sometimes significantly. Individual investors are usually told to diversify among stocks, bonds, and perhaps real estate and commodities and periodically rebalance. The recommended percentage to allocate to each asset class may vary somewhat from person to person depending on age and risk tolerance, but the general principle is simple and straightforward. Unlike many other recommendations from financial advisors, it’s not even obviously wrong. It’s just boring and intellectually unsatisfying.

Thomas Schneeweis, Garry B. Crowder, and Hossein Kazemi teamed up to write The New Science of Asset Allocation: Risk Management in a Multi-Asset World (Wiley, 2010). As is increasingly the case with financial book titles, this particular title both overpromises and misleads. The book does not blaze new trails, and although it has ample charts, graphs, and the occasional mathematical formula it will not appeal to hard-core quants. That said, the book provides a very readable overview of the tradeoff between risk and return and the role that asset allocation plays in the inevitable balancing act. It provides some intellectual underpinnings to the process of asset allocation, a process that requires both number-crunching and personal judgment. It is also a valuable source of data--for instance, tables that give benchmark returns along with their standard deviations, information ratios, maximum drawdowns, and correlations to other indices.

The book covers a range of topics--risk measurement; alpha and beta; strategic, tactical, and dynamic asset allocation; and core and satellite investment. It also devotes ample space to alternative investments (hedge funds, managed futures, private equity, real estate, and commodities).

Even though I thoroughly enjoyed reviewing material with which I was familiar and occasionally incorporating new insights, I decided for the purposes of this post to look at a simple way to monitor the risk-return profile of a fund or portfolio—adjusting its volatility. The authors argue throughout the book that risk is multidimensional, so this is nothing more than a “quick and dirty” technique. Assume that the five-year historical volatility on a portfolio’s pro-forma returns has been 10% while during the same period the average implied volatility of the U.S. equity market as measured by the VIX has been 18%. That is, the portfolio’s volatility has been about 55% of the VIX. Assume further that the portfolio manager’s job is to keep this ratio roughly constant, increasing portfolio risk if the VIX falls and hedging out some of the portfolio’s volatility with index futures if the VIX spikes. The authors provide the formula for accomplishing this task, a formula that I’ll file away for the time that I am no longer an active trader but have a multimillion dollar portfolio that needs this kind of adjustment, perhaps in my next life.

Okay, so perhaps my readers aren’t all managing funds (though I know that some are) or sitting on multimillion dollar personal portfolios. This book is valuable even for the intraday S&P futures trader, which is why I brought up the portfolio volatility adjustment example. If the VIX gets to elevated levels, portfolio managers who are managing risk start hedging. It’s important to know the depth of the teams on each side of the trade.

Solving fiendish problems

William Byers, in How Mathematicians Think (Princeton University Press, 2007), recalls the interview with Andrew Wiles on Nova. Wiles is the mathematician who proved Fermat’s last theorem after seven years of dedicated work, focus, determination, and, yes, a little help from his friends. (By the way, for Malcolm Gladwell fans, there’s a video from the 2007 New Yorker conference in which he talks about the importance of stubbornness and collaboration in Wiles’s triumph.)

Wiles described the process of solving what I have dubbed fiendish problems: “Perhaps I can best describe my experience of doing mathematics in terms of a journey through a dark unexplored mansion. You enter the first room of the mansion and it’s completely dark. You stumble around bumping into the furniture, but gradually you learn where each piece of furniture is. Finally after six months or so, you find the light switch, you turn it on, and suddenly it’s all illuminated. You can see exactly where you were. Then you move into the next room and spend another six months in the dark. So each of these breakthroughs, while sometimes they’re momentary, sometimes over a period of a day or two, they are the culmination of—and couldn’t exist without—the many months of stumbling around in the dark that precede them.” (p. 1)

Problems in the financial markets aren’t nearly so fiendish as proving Fermat’s theorem. But haven’t we all been in that dark unexplored mansion? Well, that question is incorrect. Aren’t we all still in that mansion? Perhaps we’re in room two or three, perhaps in room six or seven, but I’d wager to say that most of us still spend more time bumping into furniture than seeing the light.

And this reminds me of the puzzle of four switches and a light bulb from Paul Wilmott’s Frequently Asked Questions in Quantitative Finance (Wiley, 2007; a second edition is now available). “Outside a room there are four switches, and in the room there is a light bulb. One of the switches controls the light. Your task is to find out which one. You cannot see the bulb or whether it is on or off from outside the room. You may turn any number of switches on or off, any number of times you want. But you may only enter the room once.” (p. 383) Tomorrow I’ll share the “trick” to the solution, the day after I’ll outline the steps necessary to identifying the correct light switch.

I’ve lost my keys!

No, but I have lost the url for the site (compliments of Andrew Lo?) that asks folks to distinguish between a random chart and a real chart. I’ve also lost the reference (and I suspect it’s in one of my books) that said something along the following lines: the distinction is subtle but therein lies $$$$. I don’t need the second reference because the concept is emblazoned in my obviously shrinking brain. But I would really appreciate some help on the first front. Just post it as a comment, and many thanks!

Kotok and Sciarretta, Invest in Europe Now!

There are books that stretch my brain and those that don’t. It is often not a function of the books themselves but rather of the breadth of my knowledge. I received three books from Wiley to review and they span the spectrum. I decided to start with the fastest read, Invest in Europe Now! Why Europe’s Markets Will Outperform the U.S. in the Coming Years by David R. Kotok and Vincenzo Sciarretta (Wiley, 2010). The book’s 215 pages of text are divided into three parts: macro issues, stock-specific strategies, and guru chapters. The third part, which comprises almost half the text, is a series of interviews that Sciarretta did with ten experts on the European markets.

I am not a macro investor nor do I consider myself a seer. Moreover, to me the word “now” means a period much shorter than the time it takes to write and publish a book. So instead of writing a real review, I’m going to use this opportunity to explore two topics—what investment strategies have worked in European equities and what I would have written had I been considered a guru on investing in Hungary (and given only a paragraph’s worth of space).

There has been extensive research in recent years on building multifactor portfolios. I wrote about a fairly new research paper, "Diversification Across Characteristics," a couple of weeks ago. Kotok and Sciarretta’s book provides data from the European markets.

The Eurozone, the authors admit, does not offer the American investor much diversification when it comes to trading strategies; generally speaking, what works in U.S. equities works in European equities. Using the EURO STOXX index as their database, an Italian firm designed and analyzed several 10-stock portfolios (both single factor and multifactor) over a ten-year period—December 31, 1998 through December 31, 2008. The portfolios were rebalanced every three years, leaving the fateful 2008 period to stand alone.

Over the course of the first nine years the best single-factor strategy was low enterprise-value-to-sales stocks with relative strength coming in second. EV/sales returned 16.2%, relative strength 14.4%, and the DJ EURO STOXX 3.7%. Once 2008 was added to the previous nine years performance sagged, but EV/sales was still the best overall at 8.1% and relative strength second best at 6.8%. The index lost 2.9%.

The three multifactor portfolios combined value and previous-year momentum. The winner used as its value component a price-to-cash-flow ratio below 10 and a dividend yield greater than 2%. This multifactor portfolio outperformed all single factor portfolios over both the nine-year and ten-year time horizons—19.4% and 11.1% respectively.

To move beyond the contents of this book, if the authors urge us to invest in Europe now, what about Eastern Europe, more specifically Hungary? (I know more about Hungarian politics than anyone without an ounce of Hungarian blood in her should, so now might be an appropriate time to share a couple of observations.) Hungary has been digging itself out of its financial hole with the help of IMF and EU loans and a stringent austerity program. So far so good. The problem is that national elections are coming up very soon (April 11 is the first round) and the prediction is that the opposition party will win, some say by a landslide. To a Western investor this might sound like good news: a right-of-center party will replace the socialists. The problem is that in Hungary things are topsy-turvy: the socialists have been the advocates of democracy, capitalism, and foreign investment while their opponents have a checkered record in areas normally considered investor friendly. For instance, they have illegally broken contracts with foreign companies. In general they are less democratic, less capitalistic, and more nationalistic. I am, of course, making neither a political nor an investment recommendation, just urging due diligence before investing in a country that has already outperformed most world markets. As of April 1 the BUX ETF, registered in Hungary and a tracker of the BUX Index, has a one-year return of 108.82% and has gained 14.55% year to date.

ETFreplay

I may be a little late to the party, but I just found this site and decided to pass along my discovery. ETFreplay.com is glorious eye candy for the ETF investor.

The fruit of knowledge

This tiny piece from Raymond Smullyan’s This Book Needs No Title (p. 119) is completely off topic but I found it philosophically amusing. So here it is, in toto:

“The reason Adam ate of the fruit of knowledge was that he didn’t know any better. Had he had just a little more knowledge, he would have known enough not to do such a damn fool thing!

“Can we return to the Garden of Eden? Well, if we returned completely, if we entered again into the complete state of innocence, we would no longer have the knowledge to prevent us from eating the apple again. And so again we would fall out of grace. It seems, therefore, that to regard the Garden of Eden, the state of innocence, as the perfect state is simply a mistake. It has the obvious imperfection of being internally unstable and self-annihilating.

“Too bad there weren’t two trees of knowledge in the Garden of Eden, a big tree and a little tree. The only knowledge to be imparted by the little tree should be, ‘It is a mistake to eat of the big tree.’”