Wednesday, August 16, 2017

Partridge, Superinvestors

Matthew Partridge’s Superinvestors: Lessons from the Greatest Investors in History: From Jesse Livermore to Warren Buffett & Beyond (Harriman House, 2017) is a superficial book. In about 150 pages Partridge, who writes for MoneyWeek magazine in Great Britain and bases this book on a weekly column he did for the magazine in 2016, profiles and rates 20 so-called superinvestors. The idea was to look at “their strategies, performance, best investments and the lessons that ordinary investors could learn from them.”

Featured are an eclectic lot: Jesse Livermore, David Ricardo, George Soros, Michael Steinhardt, Benjamin Graham, Warren Buffett, Anthony Bolton, Neil Woodford, Philip Fisher, T. Rowe Price, Peter Lynch, Nick Train, Georges Doriot, Eugene Kleiner and Tom Perkins, John Templeton, Robert W. Wilson, Edward O. Thorp, John Maynard Keynes, John ‘Jack’ Bogle, and Paul Samuelson.

For those who like to keep score, Partridge rates these investors on four metrics: “their overall performance, their longevity, their influence on other investors and investing in general, and how easy it is for ordinary investors to emulate them.” For each metric an investor could earn between one and five stars. Leading the pack, with 18 points each, are Bogle and Graham. The runners-up, with 17 points each, are Fisher and Buffett.

Partridge’s takeaways from the investing careers of these men are: (1) the market can be beaten, (2) there are many roads to investment success, (3) be flexible ..., (4) … but not too flexible, (5) successful investing requires an edge, (6) when you do have an edge, bet big, (7) have an exit strategy, (8) ordinary investors have some advantages, (9) big isn’t always beautiful, and (10) it’s good to have some distance from the crowd.

Sunday, August 13, 2017

Nevins, Economics for Independent Thinkers

Daniel Nevins, a veteran of the asset management industry and a self-taught economist, takes on the mainstream, predominantly Keynesian establishment in Economics for Independent Thinkers: A Practical, No-Nonsense Guide to Understanding Economic Risks (Wallace Press, 2017). For a more realistic, fertile paradigm he recommends returning to the likes of John Stuart Mill, Alfred Marshall, Walter Bagehot, and Arthur Cecil Pigou and, for more recent inspiration, to Wicksell, Mises, Minsky, Schumpeter, and behavioral economists.

Providing the structure for Nevins’s view is what he calls the C-H-B triad: credit cycles, human nature, and business environment. This structure is “intentionally nonmathematical. Whereas modern economists require all ideas to be expressed as models …, C-H-B tells us that abstract modeling is ill-suited for big risks like recessions, depressions, and crises.” Nevins, by the way, started his career as a quant.

Nevins lays out ten rules of economic analysis, including “Major changes in the economy are shaped largely by public policies,” “Some sources of financing are riskier than others,” “If you’re searching for clues about the future, production indicators don’t produce,” and “We shouldn’t torture the data until they speak.”

Today, Nevins argues, there are “extraordinary connections between the economy and investment results,” so “investors who ignore the economy may be setting themselves up to fail. … Decision makers who understand the economy’s stress points fare best.” They have “a better understanding of what might happen next in the economy” and, as a corollary, in the financial markets. Economics for Independent Thinkers provides an economic framework for improving investment decisions.

Wednesday, August 9, 2017

Faber, The Best Investment Writing

Meb Faber has assembled a wonderful collection of 32 short pieces in The Best Investment Writing, volume 1 (Harriman House, 2017). The contributors are Jason Zweig, Gary Antonacci, Morgan Housel, Ben Hunt, Todd Tresidder, Patrick O'Shaughnessy, Meb Faber, David Merkel, Norbert Keimling, Adam Butler, Stan Altshuller, Tom McClellan, Jared Dillian, Raoul Pal, Barry Ritholtz, Ken Fisher, Chris Meredith, Aswath Damodaran, Ben Carlson, Dave Nadig, Josh Brown, Wesley Gray, Corey Hoffstein and Justin Sibears, Jason Hsu and John West, John Reese, Larry Swedroe, Cullen Roche, Jonathan Clements, Michael Kitces, Charlie Bilello, and John Mauldin.

There’s such an abundance of research and thought in this volume that it’s hard to pick out a couple of pieces to write about. My choices are decidedly idiosyncratic.

First, Wes Gray’s “Even God Would Get Fired as an Active Investor.” Who can pass up a title like that? Gray’s “God” knows what stocks are going to be long-term winners and losers and initially constructs a long-only portfolio that will be the top decile five-year winner. The problem with “God’s” portfolio, rebalanced monthly and analyzed from 1927 to 2016, is that it has terrible drawdowns. Unfortunately, “God’s” long-short hedge fund has the same problem. As Gray writes, “The relative performance on God’s hedge fund is often abysmal and he’d surely make the cover of Barron’s or the WSJ on multiple occasions throughout his career. The passive index would eat his lunch on multiple occasions—often getting beaten by 50 percentage points—or more—on multiple occasions!” The moral of the story is that active investors must have a long horizon. And, I would add, the faith that they, or their fund managers, are more god-like than their competition.

Second, Jason Zweig’s “A Portrait of the Investing Columnist as a (Very) Young Man.” Zweig’s parents were antique dealers (as were mine), and young Jason was a quick study (I wasn’t). He recalls a sale he made and “a dirty old rag” he discovered—an early Frederic Church painting which ended up in the collection of the White House. He notes “how important it is to be in the right place at the right time. The art and antiques business in the 1970s was a remarkable confluence of inefficiencies and opportunities to exploit them.” That market has now changed dramatically: “undervalued art and antiques have all but disappeared.” The stock market, like the antiques market, has also stopped handing out rewards to the well-informed stock-picker. “If you’re applying the tools that worked so well in the inefficient markets of the past to the efficient markets of today, you are wasting your time and energy. … If investors are to prosper from inefficient markets, they have to evaluate which markets still are inefficient. Areas like microcap stocks or high-yield bonds, where index funds can’t easily maneuver, offer some promise.”

Monday, August 7, 2017

Coll, The Taking of Getty Oil

There are takeover battles and takeover battles. The Getty Oil-Pennzoil-Texaco battle in the 1980s was one of the ugliest and most litigious, finally resulting (thanks to Carl Icahn’s shuttle diplomacy) in Texaco, on the day that it emerged from bankruptcy protection, owning Getty Oil and settling the Pennzoil lawsuit against it for $3 billion. In 1987 Steve Coll wrote a masterful account of the maneuvering for Getty Oil by a large, some still well known, cast of characters. It has recently been republished—and is still a compelling read.

Coll, currently a staff writer for The New Yorker and dean of the Graduate School of Journalism at Columbia University, is the author of seven books, several of them winners of major prizes. A seasoned journalist who spent two decades at The Washington Post, Coll knows how to keep the reader engaged in a story, even one that’s long (in this case nearly 500 pages) and complicated. For one thing, he uses a lot of dialogue. And he keeps the players in the drama, such as the “flaky” Gordon Getty, front and center.

I’m very glad that The Taking of Getty Oil was republished and that a new generation of business people and investors can make its story part of their knowledge base.

Sunday, July 23, 2017

Updegrove, The Turing Test

Elon Musk has long been warning about the risks of artificial intelligence, in 2014 likening AI developers to people summoning demons they naively think they can control. Frank Adversego, the brilliant hero of Andrew Updegrove’s thrillers (this is the fourth in the series), could tell developers a thing or two about AI run amok. His challenge in The Turing Test: A Tale of Artificial Intelligence and Malevolence is to use his human cunning to outwit and destroy “Turing,” a program that is at least 7,455 times more intelligent than the average human being. And no, Turing isn’t “evil.” It has basic ethical controls built into it, beginning with Asimov’s Three Laws of Robotics and including his so-called Zeroth Law: “A Robot may not harm humanity, or by inaction, allow humanity to come to harm.” But ethics does get complicated.

The Turing Test is more cerebral than Updegrove’s first three books, all of which I've reviewed here, but it’s still a page turner. And right now it's selling on Amazon for $0.99.

Tuesday, July 18, 2017

Wilmott & Orrell, The Money Formula

Money has been pouring into quant funds even though, on average, in the first half of this year they dramatically underperformed the S&P 500. And even though they were implicated in the recent financial crisis and in other spectacular blow-ups (think LTCM). ‘Quant’ still has a magic ring to it.

For years Paul Wilmott has been a leading, if often critical, voice of quantitative finance. In The Money Formula: Dodgy Finance, Pseudo Science, and How Mathematicians Took Over the Markets (Wiley, 2017) he teams up with David Orrell, an applied mathematician and writer, to produce an overview of the history and key principles of quantitative finance as well as an analysis of its current state and how it is evolving.

The Money Formula is written in language that non-quants who are reasonably knowledgeable about the financial markets, especially derivatives, will not only understand but chuckle over. Although the book doesn’t cover new ground, it often offers fresh perspectives and insights, especially on volatility and hedging.

The central thesis of the book is that in finance there are no laws, deterministic or probabilistic, only toy models. For those who try to build models, the aim is “to find models that are useful for a particular purpose, and know when they break down.” The alternative approach is to “abandon the idea of mechanistic modeling and just let the computer look for patterns in data.” Perhaps best, “use a mix of techniques, while being aware of the advantages and disadvantages of each.”

The Money Formula may not be a “must read,” but it is definitely a worthwhile read, especially for anyone who wants to trade systematically or who aspires to be a quant.

Wednesday, June 14, 2017

Bauer, Unsolved!

Sometimes I think I’m preparing for my reincarnation as a massively successful hedge fund manager, along the lines of Jim Simons. Thus my interest in code breaking.

In tackling Craig P. Bauer’s Unsolved! (Princeton University Press, 2017) I’m starting at the top, with ciphers that have resisted all attempts to crack them. Bauer does mix in a few ciphers that have solutions (which he helpfully provides) to shed light on those that remain unsolved.

Some of the unsolved ciphers come from the ancient world, but one of the more intriguing is the handiwork of Edward Elgar, the British composer. One of his Enigma Variations was a musical representation of a daughter of a close friend of his wife, whom he called Dorabella. It was in a letter to Dora that Elgar wrote the following squiggly cipher:

These squiggles were, it seems, a variation of the way he signed his own initials:

But the encoded message to Dora remains a mystery.

Then there were the so-called killer ciphers. For instance, the Zodiac killer, who went on a killing spree in 1968 and 1969, sent ciphers to newspapers. Some of these ciphers were solved, but one remains unsolved. The Zodiac killer’s identity was never discovered, and he was never apprehended.

Bauer’s lengthy book offers a panoply of ciphers ripe for the solving. Alas, I made no progress at solving any of them. I have the feeling I’m going to “come back” as a lowly ant.

Wednesday, May 31, 2017

Desai, The Wisdom of Finance

Mihir A. Desai’s The Wisdom of Finance: Discovering Humanity in the World of Risk and Return (Houghton Mifflin Harcourt, 2017) takes “the unorthodox position that viewing finance through the prism of the humanities will help us restore humanity to finance.” This sentiment is actually becoming more mainstream. For instance, there’s the just published Cents and Sensibility: What Economics Can Learn from the Humanities by Gary Saul Morson and Morton Schapiro. But Desai, a professor at the Harvard Business School and Harvard Law School, outshines his competition in at least two respects: he distills finance down to a few key components, and not the usual suspects, and he brings to bear on them insights from a wide range of often unexpected sources. For instance, “the first chapter lays down the foundations of risk and insurance, with the help of Francis Galton’s quincunx, the author Dashiell Hammett, the philosopher Charles Sanders Peirce, and the poet Wallace Stevens.”

In subsequent chapters Desai deals with such topics as options and diversification, risk and return, asset pricing, the principal-agent problem, mergers, and debt and bankruptcy. Again, with exceedingly well chosen examples from the humanities.

Everyone hates finance, including novelists. From Leo Tolstoy’s “How Much Land Does a Man Need?” and Theodore Dreiser’s The Financier to the increasingly less sympathetic main characters of Wall Street, American Psycho, and Cosmopolis, the theme is “the untrammeled desire for more.” And real life provides more than its fair share of these financial archetypes—for instance, Martin Shkreli. So is insatiable desire fundamental to finance? Desai argues that it’s not, that finance is primarily the story of risk, though he admits that “the asshole theory of finance” is powerful: that is, “it’s not the people who finance attracts who are bad. It’s just that finance fuels ego and ambition in an unusually powerful way.” To counter all the antiheroes in finance, real and fictional, he introduces the reader to Willa Cather’s O Pioneers!, a “story that truly belongs in every finance textbook.”

Desai’s book is an eye-opening, wonderful read. I highly recommend it.

Sunday, May 21, 2017

Barker, Barking Up the Wrong Tree

I am one of over 290,000 people who subscribe to Eric Barker’s weekly blog newsletter, “Barking Up the Wrong Tree.” Now, in a book of the same name (HarperCollins, 2017), he tackles the question of life success—what is it and what produces it? Through multiple anecdotes, all illustrative of the fruits of solid scientific research (he has nearly 50 pages of endnotes), Barker takes us on an often strange, counterintuitive journey.

Along the way we learn curious facts about prison gangs, pirates, even Moldovans. We discover that, despite the many significant advantages of optimism—a longer life, for instance—depressed people (and “depression is pessimism writ large”) are better at making predictions. We learn how to turn something that’s boring or overwhelming into a game that’s winnable, has novel challenges and goals, and provides feedback. We are told to “use trying and quitting as a deliberate strategy to find out what is worth not quitting” and then to set aside a small percentage of time for “little experiments” to keep learning and growing. And, oh yes, eminent scientists have traditionally had a lot of hobbies. “Getting lots of different ideas crashing together turns out to be one of the keys to creativity.”

We all need role models. Barker offers us one: a Toronto raccoon. “Their ability to get into trash cans shows a level of grit and resourcefulness that is almost beyond compare.” In 2002 Toronto financed the development of “raccoon-proof” trash cans. “How well did they work? Well, let’s just say that in 2015 the city spent an additional $31 million dollars to create a new, redesigned ‘raccoon-proof’ trash can. Not a good sign, folks.”

Barker’s book is a first-rate read—illuminating, humorous, and compassionate. (“Self-compassion beats self-esteem.”) It’s by turns empowering and humbling. Sounds like life, doesn’t it?

Sunday, May 14, 2017

Clifford, The CEO Pay Machine

Everybody, except perhaps the CEOs themselves and their compensation committees, know that CEO pay in the U.S. is out of control. At large firms the CEO-to-worker compensation ratio, 20 to 1 in 1965 and 26 to 1 in 1978, is now more than 300 to 1, perhaps as high as 700 to 1. (In Japan the ratio is 16 to 1, in Denmark 48 to 1, and in the UK 84 to 1.) How did CEO pay in the U.S. become so untethered to the wages of average workers and what can be done to bring it back in line, if indeed doing so would be in the best interests of the companies themselves and the economy as a whole?

Steven Clifford, formerly CEO of King Broadcasting Company and National Mobile Television and a director of 13 companies, tackles these questions with wit and compelling logic in The CEO Pay Machine: How It Trashes America and How to Stop It (Blue Rider Press/Penguin Random House, 2017). He sets out to show “how the sausage is made—how the Pay Machine actually works, how its parts interact, and how every step in the process pushes CEO pay to higher and higher levels.”

He starts with a fairy tale about a loan officer at the Midwest Bank who asks his fairy godmother to help him get a promotion because his $75,000 salary isn’t enough. Ah, she replies, she can do better than that. She can get him more money for the same job. Applying CEO compensation practices to the loan officer’s pay package, the fairy godmother steers him, wide-eyed step by wide-eyed step, from his modest $75,000 salary to a whopping $5,845,000. In the process, the author sketches out the inner workings of the CEO Pay Machine.

Excessive CEO pay, the author argues, harms companies, shareholders, and the economy and undermines democracy. Not just because it is excessive but also because of the way in which it is typically structured. For instance, it usually misaligns CEO incentives with effective corporate practices and goals.

Clifford lays the blame for the emergence of the Pay Machine at the feet of “three totally unrelated actors: Michael Jensen, Milton Rock, and Bill Clinton. … They were not attempting to overpay CEOs and might be stunned and insulted to be grouped together as causal agents.” Jensen’s basically sound recommendations (that CEOs own a significant amount of company stock and be paid in part for performance) were largely misapplied.

Rock and his fellow compensation consultants introduced the idea of using peer groups to calibrate executive pay and benchmarking (usually above-average) to the salaries of the peer group CEOs. It’s easy to see that “the above-average benchmarking of pay within peer groups creates a relentless upward spiral in pay—a game of CEO leapfrog. Every time a CEO leaps, he establishes a higher compensation base for the next CEO in the group to leap over.” By the way, at this year's annual Berkshire Hathaway meeting, Charlie Munger said:"I have avoided all my life compensation consultants. I hardly can find the words to express my contempt." He did, however, find the words at the 2012 meeting when he said: for "compensation consultants, prostitution would be a step up." Warren Buffett added at this year's meeting, "If the board hires a compensation consultant after I go, I will come back mad."

The last culprit, Bill Clinton, executing on his campaign promise to clamp down on excessive executive compensation, set out to eliminate tax deductions for executive pay--at first above a certain level and then, in a compromise move, above a certain level that wasn’t performance based. Business was still unhappy, so he agreed to exempt stock options from this cap. “Boards could now pay unlimited amounts as long as they could pass it off as ‘performance based’ and could grant unlimited stock options with no performance requirements.”

Clifford examines the pay packages and performance of the highest-paid executives of 2011 thru 2014—the CEOs of UnitedHealth Group, McKesson, Cheniere Energy, and Discovery Communications. The disconnect should come as no surprise.

By way of a solution, Clifford proposes a simple, blunt instrument: “For every dollar above $6 million that the companies pay their CEO or any other executive [and this includes all forms of compensation], they would pay a dollar in luxury tax. It would not be tax deductible.” Punkt. No loopholes. And, he realizes, no way it would ever get through this Congress. But maybe someday….

Wednesday, May 10, 2017

Pirie, Derivatives

Wendy L. Pirie’s Derivatives and its companion Workbook (Wiley, 2017) are part of the CFA [Chartered Financial Analyst] Institute Investment Series, books “geared toward industry practitioners along with graduate-level finance students.” The main text is a hefty 600 pages; the workbook is about 100 pages. The text’s nine chapters cover derivative markets and instruments, basics of derivative pricing and valuation, pricing and valuation of forward commitments, valuation of contingent claims, derivatives strategies, risk management, risk management applications of forward and futures strategies, risk management applications of option strategies, and risk management applications of swap strategies. Contributing chapters to this text are Don M. Chance (who does most of the heavy lifting), Robert E. Brooks, Barbara Valbuzzi, Robert E. Brooks, David M. Gentle, Robert A. Strong, Russell A. Rhoads, Kenneth Grant, and John R. Marsland.

This set is not for the casual reader who has only a passing interest in derivatives. It’s a textbook for those who want a solid foundation in derivatives, a foundation from which to engage in financial engineering, managing a trading book, or managing client portfolios. Or for those who simply have a keen interest in financial markets and want more in-depth insight into how derivatives can be used to hedge as well as to speculate.

Here’s but a single example of how derivatives, in this case equity swaps, can be useful: reducing insider exposure. Let’s say the personal wealth of the founder of a publicly traded company is almost entirely exposed to the fortunes of that company. The founder controls about 10% of the company and wants to retain this degree of control, so he doesn’t want to sell any of his shares. A swap dealer might offer him the following deal: the founder would pay the dealer the return on some of his shares in exchange for a diversified portfolio return. In this way the founder would keep his level of control but reduce his risk.

Sunday, May 7, 2017

Covel, Trend Following, 5th ed.

Michael W. Covel’s Trend Following first appeared in the spring of 2004 and went on to sell over 100,000 copies, with translations into German, Korean, Japanese, Chinese, Arabic, French, Portuguese, Russian, Thai, and Turkish. The fifth edition, subtitled How to Make a Fortune in Bull, Bear, and Black Swan Markets, is dramatically expanded. Whereas the first four editions ended on what in this edition is page 322, the text of the new edition continues on to page 561. It adds transcripts from seven interviews Covel conducted on his podcast (with Ed Seykota, Martin Lueck, Jean-Philippe Bouchaud, Ewan Kirk, Alex Greyserman, Campbell Harvey, and Lasse Heje Pedersen) and ten trend following research articles by guest authors.

Covel may be criticized for relying too much on the words of others. He is inclined to string quotations together with minimal commentary. He also uses the margins for more quotations—rightly so, I suppose, since some of them are only marginally related to trend following. This criticism is, however, primarily a stylistic one. The people Covel quotes were in the trenches and knew what they were talking about, so better to hear from them than from an outsider.

Trend trading is no longer as fashionable a concept as it once was—for instance, in the heyday of the “turtles.” It has been replaced, at least in part, by its cousin, momentum trading. What’s the difference between the two? Aside from the fact that relative (cross-sectional) momentum is a more popular factor than time-series momentum, one can say, in very rough outline, that time-series momentum is more forward-looking. In assessing momentum, analysts use a range of inputs, frequently including fundamentals and economic news. Trend following is, as its name indicates, backward-looking; it focuses on where price has been as an indication of where it will be in the future.

Trend trading, traditionally defined as a longer-term strategy, has always been most prevalent among commodity traders, the rationale being that commodity markets trend more than equity markets do. Still, many traders in all kinds of markets, short-term as well as longer-term, employ trend following strategies. Despite some premature obituaries, trend following outside of the managed futures world is far from dead.

And so a fifth edition of Covel’s classic was definitely in order. Covel was wise to add interviews and research articles to his book. They make it all the more valuable.

Wednesday, May 3, 2017

Tian, Invest Like a Guru

If you’re new to value investing and want a fast-reading primer, Charlie Tian’s Invest Like a Guru: How to Generate Higher Returns at Reduced Risk with Value Investing (Wiley, 2017) is just the ticket. If you’ve already read a couple of books on the subject, this one won’t add much to your store of knowledge.

Tian, who runs the website, draws on the insights of Peter Lynch, Warren Buffett, Donald Yacktman, and Howard Marks to advocate for a style of investing that avoids the sometimes bottomless pits of deep-value investing. Buy only good companies, he recommends, following Warren Buffett’s famous advice: “It’s far better to buy a wonderful company at a fair price than a fair company at a wonderful price.” He offers a 20-point checklist for buying a good company at a reasonable price, covering the nature of the business, its performance, financial strength, management, and valuation. The final question is more personal: “How much confidence do I have in my research?” That question, he says, “determines your action once the stock suddenly drops 50 percent after you buy.”

In 2009 GuruFocus began tracking a portfolio of 25 companies that had been consistently profitable over the previous ten years and were undervalued as measured by the discounted cash flow model. Between January 2009 and September 2016 the portfolio returned an annualized 15.7%, whereas the S&P 500 returned 12.0%. In 2010 the website started two other portfolios of consistently profitable companies that sold at close to the 10-year price/sales low and price/book low. Both of them outperformed the S&P 500 by about 2.5% a year.

Tian outlines some of ways analysts evaluate companies. It goes without saying that “none of these valuation methods can justify the stock prices of Amazon and Netflix.” Maybe not, but Bill Miller certainly juiced his Legg Mason Value Trust fund’s returns by investing in Amazon.

Sunday, April 30, 2017

Bookstaber, The End of Theory

“As we embrace complexity we come to the end of theory.” So writes Richard Bookstaber, author of A Demon of Our Own Design, in his new book, subtitled Financial Crises, the Failure of Economics, and the Sweep of Human Interaction (Princeton University Press, 2017). Although he casts his analysis in the context of financial crises, it works perfectly well as an account of financial markets behaving “normally.”

Four phenomena are endemic to financial crises, Bookstaber believes: emergence, non-ergodicity, radical uncertainty, and computational irreducibility. Emergence occurs “when systemwide dynamics arise unexpectedly out of the activities of individuals in a way that is not simply an aggregation of that behavior.” Non-ergodicity is a feature of financial markets throughout. That is, markets vary over time; they do not follow the same probabilities today as they did in the past and will in the future. Uncertainty is radical when it cannot be expressed or anticipated, when we’re dealing with unknown unknowns. Finally, our economic behavior is so complex, our interactions so profound that “there is no mathematical shortcut for determining how they will evolve.”

How are we to survive in a complex, ever changing environment, where the future is not like the past, where projected probabilities are fictions? One short answer is: act like a cockroach. Use coarse, simple rules that ignore most information. “The coarse response, although suboptimal for any one environment, is more than satisfactory for a wide range of unforeseeable ones. … [P]recision and focus in addressing the known comes at the cost of reduced ability to address the unknown.” Alternatively put, don’t rely on optimization based on past data. Instead, use heuristics.

As Bookstaber boldly states, “if you can model it, you’re wrong.” It’s not just that all models are inherently wrong, it’s that models as normally conceived are useless under these circumstances. “If we want to understand a crisis, we have to construct a story, and we must be willing to do so in the ‘road in the headlights’ fashion: ready to change the narrative as the story line develops. A change in narrative means a change in model, and the model changes are not simply a matter of revising the values of various parameters, be it by the statistical tool of Bayesian updating or whatever. It might be a change in heuristics, in the types of agents in the system. … Models need to be like novels, molding to twists and turns and unexpected shifts.”

Bookstaber’s analysis is rooted in the work of the Santa Fe Institute, with a smattering of George Soros’s reflexivity theory added for good measure. It is pragmatic rather than axiomatic, inductive rather than deductive. It’s definitely a worthwhile read.

By the way, the Sante Fe Institute is re-offering its popular (and, I can attest, excellent) online course "Introduction to Complexity." The course started a couple of weeks ago.

Wednesday, April 26, 2017

Morduch & Schneider, The Financial Diaries

Traders and investors know how potentially devastating high volatility can be for all but the most nimble. In The Financial Diaries: How American Families Cope in a World of Uncertainty (Princeton University Press, 2017), Jonathan Morduch and Rachel Schneider show how income volatility wreaks havoc with a large number of American families.

A team of ten researchers followed 235 households for 12 months in communities in southwest Ohio and northern Kentucky, the San Jose (California) region, eastern Mississippi, and Queens and Brooklyn (New York City). None of these sites was thriving, “but all had opportunities.” To qualify for the study, a household had to have at least one working member. Otherwise, the participants were diverse. None was among the richest or the poorest in their communities.

The book alternates between family stories and economic analysis. In the cases that are highlighted, workers do not have a steady pay check. Instead, their income fluctuates week to week, month to month. For instance, a mechanic who worked on commission repairing long-haul trucks at a service center on an interstate highway did reasonably well in the winter and summer. More things went wrong with trucks during those seasons. During the spring and fall, however, his pay was about halved.

Most families whose income was volatile were able to smooth the ups and downs of their finances, “but only to a point. Then, illiquidity is felt sharply.” Thirty-one percent of the best-off, middle-class households were, in the course of the study year, threatened with (or actually experienced) eviction, the disconnection of utilities or cable, or repossession of an asset. Nearly half of the households overall had at least one bank overdraft.

Although most studies talk about income inequality, income volatility is perhaps even more important. In a 25-year study, beginning in 1984, “volatility increased for the poorest 10 percent of households, and it fell for the richest 10 percent. … [O]ver the past generation, the gap in income volatility between the poorest and the richest grew by more than 400 percent, reinforcing divides based on income and wealth.”

The people profiled in this book are hard workers who just can’t get ahead. They move in and out of poverty. (Nearly one-third of all Americans experienced poverty for two months or more between 2009 and 2011.) They save for short-term needs, deplete their savings to fulfill these needs, then start saving again. They never get to the point of benefiting from the miracle of compound interest.

The portraits the authors paint are depressing. They go a long way toward explaining why the U.S. is seeing “deaths of despair” and Donald Trump is in the White House. Moreover, with increasing automation and a freelance workforce, the problem is only going to get worse. The authors offer some suggestions for improving the situation, but most of them require government, employers, and financial institutions working together “in new and different ways.” In the present environment, that is unlikely.

Sunday, April 23, 2017

2017 SBBI Yearbook

The 2017 SBBI Yearbook: Stocks, Bonds, Bills, and Inflation: U.S. Capital Markets Performance by Asset Class 1926-2016 by Roger G. Ibbotson and contributors from Duff & Phelps (Wiley, 2017) is the kind of book one rarely sees these days. Printed in two colors on high quality, heavy stock and measuring 8 1/2” x 11,” it offers 368 pages of beautifully presented returns data along with careful analysis. It is divided into 12 chapters and three appendixes: results of U.S. capital markets in 2016 and in the past decade, the long-run perspective, description of the basic series, description of the derived series, annual returns and indexes, statistical analysis of returns, company size and return, growth and value investing, liquidity investing, using historical data in wealth forecasting and portfolio optimization, stock market returns from 1815-2016, international equity investing, monthly and annual returns of basic series, cumulative wealth indexes of basic series, and rates of return for all yearly holding periods 1926-2016.

In addition to providing the reader with a trove of tables and graphs based on Morningstar data, the yearbook mines performance data for investing insights. Among them (and this is a very small sample):

  • “The serial correlation of returns on large-cap stocks is near zero. For the smallest deciles of stocks, the serial correlation tends to be higher.”

  • “Unlike the returns on large-cap stocks, the returns on small-cap stocks tend to be seasonal.”

  • “Liquidity appears to be a much better predictor of returns than size.” Between 1972 and 2016 the geometric mean of annualized returns of the least liquid quartile of NYSE/MKT/NASDAQ stocks was about twice that of the most liquid quartile, with a significantly lower standard deviation.

  • Market bubbles, over time and across geographical boundaries, appear to exhibit similar log-periodic power laws before the bubbles pop and markets crash.

The 2017 SBBI Yearbook is expensive, certainly not the kind of book you read in the bathtub or take to the beach. But for those who like to see their data on the page, not on the screen, and who appreciate meticulous analysis, it’s well worth the price.

Wednesday, April 19, 2017

Krishnan, The Second Leg Down

Investors, we know, are inclined to cut their profits short and hold on to their losers. In The Second Leg Down: Strategies for Profiting after a Market Sell-Off (Wiley, 2017) Hari P. Krishnan addresses investors who are seeing their portfolios shrink in value but are loath to sell. Anticipating further market declines, they want to hedge their portfolios. By then, however, traditional hedges such as index puts are expensive. Still, they need something to serve as a “hard backstop against portfolio disaster.”

Krishnan, who received a Ph.D. in applied math, was an options trading strategist at the Chicago Board of Trade and executive director and co-head of alternative asset allocation at Morgan Stanley. He is now a fund manager at Cross-Border Capital in London. Although he is writing primarily for institutional investors, many of his suggestions would work equally well for retail investors.

Options are the most affordable way to hedge a portfolio. When markets are going up, however, they are a waste of money. Month after month they expire worthless. So portfolio managers are disinclined to throw money away by hedging. When the flood waters are rising, however, they want to buy insurance—insurance that’s not prohibitively expensive. And they want to make money off that insurance.

Krishnan takes the reader through possible options hedging strategies, exposing the pitfalls of some of the more popular alternatives such as ratio and calendar spreads. Broken wing butterflies offer more advantages.

What about using VIX futures as a hedge? This doesn’t work; the hedge simply withers away over time. “Maintaining a long volatility position by mechanically rolling VIX futures is simply too expensive.” Simultaneously selling VIX futures and overbuying at-the-money VIX calls, however, is useful in risk-off regimes. “It benefits from large changes in volatility in either direction.”

Since options eventually expire, the question for a hedger is how far out in time to go. Let’s say you’re buying out-of-the-money puts. Short-dated options are cheap and insensitive to volatility. They are a gamma play, offering “tremendous potential when there are large realized moves.” They work well as an emergency hedge. Long-dated out-of-the-money options, those with more than a year to maturity, are best purchased when investors are overconfident. They occasionally offer exceptional value. It is wise to avoid those options that many institutions tend to favor—the 2% OTM 3 month to maturity puts. They are not a Goldilocks solution but rather “the worst of both worlds.”

Another portfolio protection strategy, an alternative to purchasing options, is to devote a portion of the portfolio to trend following. It is not capacity constrained (as weekly options in particular are) and, in a downtrending market, it will stay “piggishly” short.

I have outlined some of the main points of Krishnan’s book, but its real value comes from his sophisticated analysis of such critically important concepts as volatility and skew. This makes the book useful not only to hedgers but even to speculative options traders.

Wednesday, April 12, 2017

Waterhouse, The Land of Enterprise

A couple of years ago I audited a fascinating EdX course offered by Cornell on the history of American capitalism. It’s now archived.

Benjamin C. Waterhouse’s book The Land of Enterprise: A Business History of the United States (Simon & Schuster, 2017) surveys much of the same terrain, albeit in a more abbreviated form. The text of the book is less than 200 pages. And yet, even though the book ranges from the European “exploration, exploitation, and ultimate inhabitation of the New World” to the fallout from the financial crisis, it is not superficial. Waterhouse highlights “the most important historical developments, especially changes in business practices, the evolution of different industries and sectors, and the complex relationship between business and national politics.”

Take, for instance, the rise of general incorporation laws. Before 1800 corporate charters “had to be granted by the sovereign—the king or Parliament in colonial times; the state or federal legislature after independence.” Charters were issued to only 335 businesses during the entire eighteenth century. By the early nineteenth century states started granting corporate charters administratively rather than legislatively, making the process a lot less cumbersome. “In 1811, New York became the first state to enact such a law for manufacturing firms. In 1837, Connecticut became the first state to allow general incorporation for any kind of business. And by 1870, every state had some type of general incorporation law on the books.”

Or consider corporate opposition to environmentalism in the 1960s and 70s. Responding to new standards enacted in 1970 that limited automobile emissions, Chrysler claimed that “citizens have been needlessly frightened” about air pollution. In general, critics of the environmental movement, “conservatives as well as many labor unions,” worried about the social costs—“shuttered factories or higher-priced products”—that would result from stricter environmental regulations. Advocates of environmentalism, according to the president of the Heritage Foundation, were “zero-growth zanies. … Zero growth may help the elites, who can go out and till their organic gardens and watch the sun come up from the serenity of their redwood hot tubs, but it doesn’t do much for those among us who are still trying to make it up the economic ladder.”

Waterhouse is an academic, but The Land of Enterprise should appeal to a popular audience. It’s a most palatable introduction to American business, and by extension social and political, history. And it serves as an informative backdrop to what we’re seeing today.

Sunday, April 9, 2017

Vaughan & Finch, The Fix

The Libor scandal, which broke in 2012, confirmed people’s worst suspicions about big banks and a system “in which manipulation was not just possible but inevitable.” In The Fix: How Bankers Lied, Cheated and Colluded to Rig the World’s Most Important Number (Bloomberg/Wiley, 2017) journalists Liam Vaughan and Gavin Finch profile the antihero Tom Hayes, “a brilliant, obsessive, reckless, irascible math prodigy who transformed rate-rigging from a blunt instrument into a thing of intricate, terrible beauty.” They also introduce us to his entourage of enablers and co-conspirators.

Hayes, who in 2015, when he was 35, was diagnosed with Asperger’s syndrome, had “a steely stomach for risk.” And a passion to win, whatever it took. In his case, it took getting his brokers to lie to the banks about what was happening in the cash markets.

The Fix is a riveting tale of illegal behavior, usually engaged in for profit, sometimes (or so the justification went) for the stability of the banking sector. It exposes a culture of corruption where even the guilty usually walk. “Of the more than 20 individuals identified by Hayes as taking part in the scheme, he is the only one to be convicted.”

Unlike the jurors in the brokers’ case, who kept falling asleep during the trial, readers of this book will be wide awake from beginning to end. The two authors provide only enough information about Libor to make their story understandable. Financial wonks will undoubtedly be disappointed, but most other readers will compulsively keep turning pages.

Wednesday, April 5, 2017

Chan, Machine Trading

Ernest P. Chan, a physics Ph.D. and a former researcher in machine learning at IBM’s T.J. Watson Research Center, is well known to the quant trading community. He is the author of Quantitative Trading: How to Build Your Own Algorithmic Trading Business and Algorithmic Trading: Winning Strategies and Their Rationale. His most recent effort is Machine Trading: Deploying Computer Algorithms to Conquer the Markets (Wiley, 2017).

In Machine Trading Chan discusses the basics of algorithmic trading, factor models, time-series analysis, artificial intelligence techniques, options strategies, intraday trading and market microstructure, bitcoins, and how algorithmic trading is good for body and soul. Where appropriate, he uses MATLAB code to develop his points.

Chan assumes a working knowledge of linear algebra, statistics, and basic computer science, as well as a familiarity with the financial markets, options in particular. Although he provides exercises at the end of each chapter, his work is not really suitable as a textbook. It is, I believe, best viewed as an overlay to a quant trader’s education.

Chan describes an array of trading strategies, most stemming from the academic literature. Many of these strategies were once profitable but have subsequently deteriorated in performance. (You didn’t really expect Chan, who manages money, to share his “winningest” strategies, did you?) But this isn’t the point. Individual strategies are either examples of the types of strategies that can work in particular markets (for instance, “statistical factors can be more useful for trading in markets where fundamental factors are less important for predictive purposes,” such as the forex market) or illustrative of the process of generating or testing a trading model.

Some of the material Chan presents is relevant only to professional traders with large research budgets. But even individual retail traders can extract nuggets of valuable information from this book—if, that is, they have the necessary background.

Sunday, April 2, 2017

van Vliet & de Koning, High Returns from Low Risk

Pim van Vliet and Jan de Koning, both members of Robeco’s quantitative equities team (with van Vliet responsible primarily for the firm’s conservative equity strategies), have written a book challenging the claim that risk and return are positively correlated. High Returns from Low Risk: A Remarkable Stock Market Paradox (Wiley, 2017) is intended for a broad audience of investors. As a result, even though the authors obviously have quant skills, there’s no razzle-dazzle math on display here.

The book’s results are based on a dataset of monthly closing prices from January 1926 to December 2014 of the U.S. traded stocks of the largest 1,000 companies by market capitalization at any given moment in time. For each of these 1,000 stocks he (I assume van Vliet) measured the rolling three-year historical monthly return volatility and ranked them by risk (throughout risk is equated with volatility). Then he constructed two portfolios, one containing the 100 stocks with the lowest volatility, the other containing the 100 riskiest stocks (the high-volatility portfolio). He rebalanced the portfolios every quarter. Assuming that a person put $100 into each portfolio on New Year’s Day 1929 and reinvested any capital gains for 86 years until New Year’s Day 2015, the low-volatility portfolio was worth $395,000 at the beginning of 2015, the high-volatility, $21,000. Put another way, the low-volatility portfolio returned 10.2% annually on average whereas the high-volatility portfolio returned only 6.4%.

The disparity might be inflated somewhat by virtue of the fact that the calculations start in 1929 and “the low-volatility portfolio wins by losing less during times of stress.” The high-volatility portfolio would have been worth a little over $5 when the market bottomed out in the spring of 1932; the low-volatility portfolio would have been worth $30. Nonetheless, the authors contend, “if we were to start both portfolios in the spring of 1932, the low-volatility portfolio would still ‘win’ by a very significant margin.”

A low-volatility portfolio, it should be noted, doesn’t produce maximum returns. Given ten portfolios, each containing 100 stocks and ranked according to volatility (low to high), and using the same 86-year time frame, the portfolio in the fourth decile performed best (about 12% a year). Even the portfolio in the ninth decile performed better than the low-volatility portfolio. But the portfolio of the 100 stocks with the highest volatility performed far worse than any of the others.

The authors analyze why low-volatility stocks are overlooked in the market, thereby providing an opportunity for solid returns. Basically, “virtually everybody seems to be drawn to the dark and risky side of the stock market.” So, even though the paradox was first discovered over 40 years ago and even though it may become more well known, “there is every reason to believe the paradox will continue to exist and may even become stronger.”

Wednesday, March 29, 2017

Aldridge & Krawciw, Real-Time Risk

Real-Time Risk: What Investors Should Know About FinTech, High-Frequency Trading, and Flash Crashes (Wiley, 2017) by Irene Aldridge and Steve Krawciw is in large measure an advertisement for AbleMarkets, of which the authors are, respectively, president and CEO. That said, and it is a major caveat, the book provides insight into the often overlooked, or inaccessible, world of market microstructure.

Let’s start with front-running’s cousin, pre-hedging. Front-running is illegal, but pre-hedging or anticipatory hedging, though forbidden on the CME, is allowed in the FX market, and equities regulators allow the use of derivatives to pre-hedge. Let’s say you, a sophisticated trader, place an order to sell shares in IBM. Your broker may buy “put options on IBM before executing your order, with the explicit purpose of protecting itself against your information asymmetry. ….The seemingly innocuous options purchase by the broker has wild ramifications in today’s interconnected markets. Aggressive high-frequency traders … continuously scan markets for arbitrage opportunities and will see the temporal discrepancy between the options activity and the still-lethargic IBM stock (your order still has not hit the markets). The HFTs will take off the price you saw when you placed the order just before your order had a chance to execute,” thereby widening the spread and increasing volatility through the larger bid-ask bounce.

The authors tackle the causes of flash crashes, both market-wide and in individual stocks. Market-wide, they pin the blame primarily on broad-based ETFs such as SPY. According to the law of one price, the basket of securities making up the S&P 500 should have the same price as SPY, and normally stat-arb traders quickly eliminate any disparity in price. But consider the following scenario. An S&P 500 stock falls sharply. Stat-arb traders bring SPY into line. But once SPY’s price falls, “a new force comes to influence the markets, potentially causing widespread contagion among other financial instruments in the markets. This new force is macro arbitrage. … Once the price of the ETF drops, most of the securities in the underlying basket are revalued by the macro traders and algorithms, dragging down the prices of most individual securities in the basket. The basket is now once again priced below the corresponding ETF! Next, the vicious cycle repeats itself.” And “once the flash crash begins in a particular market, it can rapidly spread to other instruments, affecting markets across all asset classes and continents. The recovery can be just as swift: All it takes is for one market participant or system to realize the artificial absurdity in the present crash and the low valuations of the securities to begin to repurchase the underpriced instruments.”

To be able to predict intraday risks one has to understand market microstructure. The authors claim that “in addition to the risks associated with HFT, understanding market microstructure can help predict flash crashes days ahead, minimize slippage when placing trades, and, of course, predict short-term price movements in the markets.” And so, they conclude, “incorporating the market microstructure analytics into financial decisions is no longer an option but a requirement for sound portfolio management.” AbleMarkets is, of course, a market microstructure analytics firm.

Sunday, March 26, 2017

Schwager & Etzkorn, A Complete Guide to the Futures Market, 2d ed.

The first edition of Jack Schwager’s A Complete Guide to the Futures Market came out in 1984. No, that’s not a typo. It was 33 years ago. In revising and updating his classic work for publication this year, Schwager teamed up with Mark Etzkorn.

At nearly 700 pages, A Complete Guide to the Futures Market: Technical Analysis and Trading Systems, Fundamental Analysis, Options, Spreads, and Trading Principles covers all the bases, or at least all the bases traders knew about back in the day.

Today the book seems almost quaint. With the exception of six appendixes on statistics in general and regression in particular, there’s almost no math, certainly no machine learning. Quantitative traders would undoubtedly argue that no one can make money with the techniques described in this book. But we’ve heard similar arguments before—technical traders claiming that one couldn’t make money trading fundamentals, fundamental traders countering that they never knew a rich technical trader. The reality is that trading’s incredibly difficult, and the more ways you can think about it the better off you probably are. Unless, of course, you’re willing to accept a completely black-box strategy.

The authors devote about half the book to chart analysis, technical indicators, trading systems, and performance measurement. With the exception of the problem of how to link contract series (nearest futures versus continuous futures), most of the material in this part of the book is not specific to futures trading.

The fundamentals of the various futures markets are trickier. As the authors explain, “Because of the heterogeneous nature of commodity markets, there is no such thing as a standard fundamental model. Among the key substantive characteristics that differentiate markets are degree of storability, availability of substitutes, importance of imports and exports, types of government intervention, and sensitivity to general economic conditions. Consequently, in contrast to technical analysis, in which a specific system or methodology can often be applied to a broad spectrum of markets, the fundamental approach requires a separate analysis for each market.”

Many commodity traders use spreads, simultaneously buying one futures contract and selling another either in the same market or in a related market. As a general rule, spread traders who expect price appreciation in a commodity will initiate an intramarket time spread, long the near month and short the distant month. Gold and silver, however, move inversely to this rule. And the rule has no applicability to nonstorable commodities (cattle and live hogs).

Commodity traders can also use options to express their opinions. The authors devote a chapter to option trading strategies, complete with risk graphs and profit/loss calculation tables for a range of strategies.

The final part of the book is devoted to practical trading guidelines, including 75 trading rules and market observations and 50 market wizard lessons. There’s a lot of wisdom here.

A Complete Guide to the Futures Market lives up to its title and then some. Even those who have no intention of ever trading futures can profit from this book. Yes, it’s old school, but ‘old school’ in this case doesn’t mean ‘passé’.

Friday, March 24, 2017

Weiss, Key to IP

I know this book is off topic, but I thought it worth bringing to your attention anyway.

If you know as much about intellectual property as I did before I read Chris Weiss’s Key to IP: Identifying Your Patents, Trademarks, Copyrights, and Trade Secrets, you’ll come away enlightened.

Weiss is a patent attorney who, in about 70 pages, explains the basics in a non-lawyerly way. That is, his prose is clear, occasionally even amusing. And always informative. I now understand why so many products have “patent pending” printed on their labels. Spoiler: getting a patent can be a very long process.