Sunday, September 17, 2017

Henriques, A First-Class Catastrophe

Black Monday (October 19, 1987), when the Dow Jones Industrial Average fell over 22%, was not a black swan event. Although it occurred in the context of heightened geopolitical risk, with Iran hitting two American-owned ships with Silkworm missiles and the United States retaliating by shelling an Iranian oil platform in the Persian Gulf, the potential for a huge market sell-off had been telegraphed day after day in 1987.

Diana B. Henriques, an award-winning financial journalist writing for The New York Times, is the author of The Wizard of Lies (the best-selling book about Bernie Madoff, subsequently made into an HBO movie), Fidelity’s World, The Machinery of Greed, and The White Sharks of Wall Street. In A First-Class Catastrophe: The Road to Black Monday, the Worst Day in Wall Street History (Henry Holt, 2017) she once again lives up to her reputation for careful, exhaustive research and engaging prose.

People (I among them) have often claimed that the financial market is a complex adaptive system. Henriques convincingly shows that, in the run-up to Black Monday, it was complex but not reliably adaptive and certainly not a system. Moreover, she claims, “we are still living in the world revealed to us on Black Monday.” In fact, the factors that led to the 1987 crisis “have become even more deeply embedded in Wall Street’s genetic code.”

Henriques explores multiple areas in which the financial market (and here I include equities, bonds, and derivatives) exhibited the potential for cracks in the 1970s and 1980s, starting with the fractured regulatory agencies. Also contributing to the crisis was the introduction of indexing, initially for pension funds, would give rise to herding; these huge funds were “all likely to shift their assets in the same direction at the same time.” Portfolio insurance, often incorrectly cited as the cause of Black Monday, relied on index arbitrageurs (and there had to be enough of them) to zig when it zagged. Computerization sped up trading and the back office processing of orders but brought with it the inevitable glitches.

Populating these potentially problematic areas were people who were protective of their turf, powerful, and creative—regulators and heads of exchanges, agents for financial behemoths, and innovators. As a result of the extensive interviews the author did with the primary players, we get a sense of how they understood their roles in this calamity.

A First-Class Catastrophe is a first-class book. Perhaps through it we will learn some lessons that were ignored in the wake of Black Monday.

Wednesday, September 13, 2017

Page, The Diversity Bonus

Scott E. Page is one of my favorite writers. A professor of complex systems, political science, and economics at the University of Michigan, he is the author of The Difference, Complex Adaptive Systems, and Diversity and Complexity. He also gave a wonderful on-line course on model thinking, still available on Coursera.

The Diversity Bonus: How Great Teams Pay Off in the Knowledge Economy (Princeton University Press, 2017) continues his thinking on the complicated, often contentious subject of diversity. The core logic for how diversity produces bonuses relies on linking cognitive diversity (differences in information, knowledge, representations, mental models, and heuristics) to better outcomes on tasks such as problem solving, predicting, and designing. Cognitive diversity is to be distinguished from identity diversity (differences in race, gender, age, physical capabilities, and sexual orientation), although identity diversity can often contribute significantly to cognitive diversity.

Some people try to view diversity as analogous to a diversified investment portfolio, but they miss the point. “The portfolio performs like the average. The problem-solving team performs like the best. Actually, the team does even better if team members can share ideas.”

Page is careful not to overpromise on the benefits of diversity. Although in some cases cognitive and identity diversity produce bonuses, “in others (see the US Congress) they contribute to conflict.” Wall Street, however, is a place where both cognitive and identity diversity pay off. “Team-run funds outperform individuals and gender-mixed teams outperform all-male teams.”

Page’s book offers a compellingly pragmatic justification for both cognitive and identity diversity. Unlike normative arguments for identity diversity and inclusion, which “seek to redress past wrongs or create a more equitable future,” the diversity-bonus logic “shows that cognitively diverse teams perform better on complex tasks.” The widespread view that diversity harms performance (exemplified by Antonin Scalia’s opinion that schools and employers face a choice: they can choose diversity, or they can choose to be “super duper”) overstates the case. True, “replacing a member of a relay team with a slower runner or hiring a data analyst who makes errors at a higher rate based on identity considerations sacrifices quality on the altar of social justice.” But when it comes to complex tasks, having a diverse team is not a sacrifice but is often instead a benefit.

Sunday, September 10, 2017

Kinlaw et al., A Practitioner’s Guide to Asset Allocation

William Kinlaw, Mark P. Kritzman, and David Turkington have written a carefully researched book that reaches sometimes counterintuitive (or at least counter to common wisdom) conclusions. A Practitioner’s Guide to Asset Allocation (Wiley, 2017) is directed at professional investors and advisors, but some of the material might be useful to systematic traders as well. Although the authors rely on quantitative analysis, they do not overwhelm the reader with math and statistics. For those who need a brief refresher course to understand the gist of the text, there is a chapter late in the book explaining basic statistical and theoretical concepts.

Among the misconceptions the book sets out to rectify are:

1. Asset allocation explains more than 90% of investment performance.

2. Investing over long horizons is less risky than investing over short horizons.

3. Factors offer greater potential for diversification than asset classes.

4. Equally weighted portfolios perform better out of sample than optimized portfolios.

The authors explore such questions as whether, to increase expected return, it’s preferable to apply leverage to a less risky portfolio than to concentrate a portfolio in riskier assets, as theory holds. Answer: “what is inarguable theoretically does not always hold empirically when we introduce more plausible assumptions.”

They also address the thorny problem of regime shifts. They investigate three approaches to managing risk (using volatility as a proxy for risk): stability-adjusted optimization, regime-sensitive asset allocation, and tactical asset allocation based on regime indicators. They suggest that the first two approaches “yield static portfolios that most likely will still experience wide swings in their volatility.” Tactical asset allocation is more flexible, and “although this additional flexibility may not always improve performance, we have provided encouraging evidence to suggest that some investors might profit from tactical trading, given the right insights and methods.”

There’s a lot of meat in this book. Investors and advisors who devote time to it, especially those with some quant skills, will come away enriched.

Friday, September 8, 2017

Zomorodi, Bored and Brilliant

Boredom has become a fashionable subject. Henry Alford, in his New York Times (August 10) review of seven books about boredom, suggests that “the ‘boredom boom’ would seem to be a reaction to the short attention spans bred by our computers and smartphones.” Boredom is something we have lost to technology--something, we are told, we should strive to regain. Most authors these days aren’t seeing boredom as “the graveyard of your spirit” but as “a lull before the gorgeous storm.”

Put down your smartphone. The boredom that follows will foster creativity. Or at least that’s the thrust of Manoush Zomorodi’s Bored and Brilliant (St. Martin’s Press, 2017). The author, host of her own weekly radio show and podcast on WNYC, Note to Self, created the Bored and Brilliant Project. It was “a weeklong series of challenges designed to help people detach from their devices and jump-start their creativity.”

If you’re addicted to your gadgets, Zomorodi’s book might help you step back a bit. If, however, you want to understand how having free time can trigger your imagination, you’ll have to turn elsewhere. Similarly, if you want to understand what boredom is in all of its varied manifestations, you’ll need another guide.

Thursday, September 7, 2017

Gardner, The Motley Fool Investment Guide, 3d ed.

The Motley Fool will probably always be most closely associated with the 1990s and the roaring stock market. But their business is still going strong. And so now, for the third edition, David and Tom Gardner have completely updated their classic The Motley Fool Investment Guide: How the Fools Beat Wall Street’s Wise Men and How You Can Too (Simon & Schuster) for a new generation of investors.

For those with the motivation and the proper temperament, the Gardners advocate stock picking over index investing. They are partial to small caps and recommend “’business-focused investing’—that is, seeking out great and amazing growth-opportunity businesses.”

Tom Gardner, in constructing his Everlasting Portfolio, considers five features of companies: culture, strategy, financials, safety, and valuation. David Gardner is more aggressive. He advocates Rule Breaker investing, which is about “seeking growth in dynamic companies that are disrupting and shaping industries, businesses, economies, and even our daily lives.” These companies are the first movers in important and emerging industries, they have visionary leadership and smart backing, they have identifiable competitive advantages, they’re good brands, their stocks have already done pretty well, and stodgy backward-looking observers will declare their shares overvalued.

After the authors take the would-be investor through some basic accounting principles, they introduce advanced topics, such as shorting stocks and options.

To the new investor, the authors say “there’s no rush. Consider starting with an index fund or some blue-chip stocks exclusively in your first year. … When you’re convinced you can outdo index-fund investing, and you’re confident you have the timeline and temperament to stick with it even when things don’t go your way, explore the worlds of Rule Breakers, small-cap stocks, and other corners of the market that might appeal to you. Find your edge, and then over time, push your edge to the edge.”

Wednesday, September 6, 2017

Tillinghast, Big Money Thinks Small

Joel Tillinghast, the sole manager of the Fidelity Low-Priced Stock Fund from its inception in 1989 until 2011, when six co-managers were added, has been an outperformer. A $10,000 investment in his fund when it launched would have been worth almost $300,000 in 2015, versus roughly $74,000 for the Russell 2000 and $104,000 for the S&P 500. So it’s definitely worth listening to what he has to say in Big Money Thinks Small: Biases, Blind Spots, and Smarter Investing (Columbia Business School Publishing, 2017).

Tillinghast’s book is a cornucopia of investing wisdom, some acquired as a result of the inevitable mistakes, which he readily shares.

One bit of wisdom, which is not commonplace, is that Tillinghast focuses on a business’s distinctive character rather than its business strategy or positioning. “Most companies lack a strong character. This does not mean that they will be poor investments—only that they are less apt to be exceptional.” As examples of character, Tillinghast writes that, to him, “Apple seems smart, elegant, and occasionally quirky but otherwise easy to get along with. GEICO is honest, thrifty, and good-natured.”

He lists six things that make him nervous: companies that must lie to stay in business, tiny audit firms, inside boards, glamorous rollups, financial firms, and sunny havens.

Ascertaining the value of a stock requires assessing the four elements of value: profitability or income, life span, growth, and certainty. This is no easy task since these elements “reflect regular patterns of social behavior,” not the laws of physics. “Elevated profitability reflects a product that buyers want that, for whatever reason, they cannot get elsewhere. Longevity is shortened by periods when the immediate demand for a company’s product falls. … Growth reflects either substitution away from a competing product or a product that allows users to do something that they could not do before. Certainty reflects contracts and the general inertia of institutions and human behavior.”

Tillinghast provides case studies to illustrate his points, of which the above are but a tiny sample.

I suspect that most retail investors will be overwhelmed by the amount of work that Tillinghast puts into his investment decisions. They can still learn from his book, even if it’s not to turn their money over to shysters. But for those investors, retail and professional alike, who enjoy research and careful thinking Big Money Thinks Small is an engaging guide.

Sunday, August 27, 2017

Tegmark, Life 3.0

We don’t know whether artificial intelligence will ever attain the level of artificial general intelligence, with the ability to accomplish virtually any goal, including learning. That is, as the title of Max Tegmark’s illuminating book (Knopf, 2017) puts it, we don’t know whether we will ever reach Life 3.0. Even so, as we enter the age of AI, it is important to think about what sort of future we want so “we can find shared goals to plan and work for.” “If a technologically superior AI-fueled civilization arrives because we built it, … we humans have great influence over the outcome—influence that we exerted when we created the AI.”

Tegmark posits three stages of life: biological evolution (Life 1.0), cultural evolution (Life 2.0), and technological evolution (Life 3.0). In Life 1.0, with bacteria being a good example, both the hardware and software are evolved rather than designed. With Life 2.0, our current status as human beings, the hardware (DNA) is evolved but the software is largely designed, through learning. Life 3.0 will design both its hardware and software. “In other words, Life 3.0 is the master of its own destiny, finally fully free from evolutionary shackles.”

Tegmark is a professor of physics at MIT and president of the Future of Life Institute, which advocates for beneficial AI and AI-safety research. Both projects involve a heavy dose of ethical debate and decision making. For instance, should we have autonomous weapons, which select and engage targets without human intervention? The author and a colleague wrote an open letter in 2015 arguing against autonomous weapons, a letter signed by over 3,000 AI and robotics researchers and 17,000 others.

Life 3.0 engages the reader in a wide range of future scenarios, from those where superintelligence peacefully coexists with humans (even if, in one scenario, as a zookeeper) to those where humanity goes extinct and is replaced by AIs (or by nothing, if we self-destruct). Tegmark admits that “there’s absolutely no consensus on which, if any, of these scenarios are desirable, and all involve objectionable elements. This makes it all the more important to continue and deepen the conversation around our future goals, so that we don’t inadvertently drift or steer in an unfortunate direction.”

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.