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.

Wednesday, March 22, 2017

Become a financial superforecaster

Superforecasting was one of my favorite books of 2015. Although Philip E. Tetlock and Dan Gardner pretty well steered clear of the financial markets in the book, recognizing that markets are, as I wrote in my review, “rife with aleatory uncertainty (the unknowable),” they nevertheless believed that, even in the financial markets, learning to become a superforecaster would pay off.

Now we all have a chance to become part of the Good Judgment community and try our hands at forecasting. Who knows, maybe we’ll discover that we have what it takes to become a superforecaster.

Here’s the press release announcing the challenge.

Good Judgment Inc (GJI) and the CFA Society Los Angeles are launching an exciting new partnership for the members of CFA Society Los Angeles, the wider global CFA community, and those interested in becoming better forecasters in the world of economics and finance.

CFA charterholders and other interested parties will have the opportunity to compete in the “CFA Society Los Angeles 2017 Finance & Economic Challenge” ( on a battery of forecastable questions debuting on February 16 on Good Judgment Open (GJI’s crowdsourced forecasting platform). Participants will be challenged to forecast pressing questions on a variety of topics, such as:

• Before 1 July 2017, will new federal funding be approved for the California High-Speed Rail Authority's "bullet train" project?
• What will be the end-of-day closing value for the euro against the U.S. dollar on 15 February 2018?
• Before 2018, will Tesla file for bankruptcy or begin restructuring their debt in a corporate workout?

The CFA Society Los Angeles Board of Governors agreed that posting a challenge focused on economics and finance on Good Judgment Open would provide its members a superb platform to interact on important questions of the day, while simultaneously improving their ability to make good judgments.

Why forecast with GJI and CFA Society Los Angeles?

1. Keeping score is essential to get the feedback that improves accuracy. So often in human judgment, there is no objective measurement of success. Good Judgment Open uses a scoring system that allows forecasters to learn how the accuracy of their forecasts differs from the crowd.

2. Small improvements in forecasting add up.

3. Forecasting is a skill that can be best cultivated in dedicated forecasting tournaments (demonstrated by the work of Dr. Phil Tetlock, co-founder of GJI and co-author of “Superforecasting: The Art and Science of Prediction”)

4. The 25 economics and finance questions will offer experts in the broader business community an opportunity to leverage their expertise to forecast questions relevant to their work.

To participate in the “CFA Society Los Angeles 2017 Finance & Economic Challenge,” please go to and register for the Challenge to begin forecasting.

Champ, Going Public

Norm Champ spent almost 20 years in the private sector practicing law and serving as general counsel of a hedge fund before opting to join the SEC. Going Public: My Adventures Inside the SEC and How to Prevent the Next Devastating Crisis (McGraw-Hill, 2017) recounts his five years (“adventures” is a stretch) in government.

My initial reaction to this book was negative since it focused so much on the petty. But then, upon reflection, I decided that it was undoubtedly an accurate, if limited, account of how people function, and don’t function, inside government agencies. And for this reason was worth reading.

When Champ began his first job at the SEC, heading up investment management exams in New York, he assumed that the SEC was “a typically dysfunctional bureaucracy that needed to fix what had been broken.” Instead, he found that “there were parts of it that had never been built.” For instance, there were no internal guidelines on how to do the examinations of financial firms; “employees were more or less left to use their best judgment.” And some of the procedures “were slanted toward what was best for government workers—not enforcement of the federal securities laws. Examiners at Madoff’s firm actually drafted a letter asking the options exchange for records of his trading, but the examiners appear to have decided not to send the letter because it would pull in too many records that would have taken a long time to review. If those examiners had had procedures requiring them to verify at least some trading, they would have sent the letter and Madoff might have been unmasked because he did not trade at all—on the exchange or anywhere else.” And lest you think these investigators were swamped with work, on average they completed only a little more than two exams per person per year.

Civil service protections and union grievance procedures make it nearly impossible to fire SEC employees. The one case Champ cites in which an employee was actually let go involved a supervisor who had not shown up at the office in about five years (and who nonetheless got his standard annual raise). A new manager succeeded in having him terminated.

Another commonplace in the SEC and throughout the federal government is the anonymous complaint. Since employees have such strong job security, they can send the inspector general and others anonymous grievances without fear of consequences. “Those opposed to change use anonymous notes to protect the status quo.” During Champ’s tenure at the SEC, these nameless complaints appeared constantly. It cost him thousands of dollars in legal fees to help navigate the investigations.

Champ initiated reforms where he could, first in examinations and then as the top federal policymaker for investment management, also known as the wax museum when he arrived because it was frozen in time and place. IM has three major responsibilities: “it writes the rules regulating the investment management industry, provides guidance to industry and government on how those rules are applied in practice, and reviews documents that mutual funds use to sell their shares to investors.”

Champ’s account of the state of affairs in the wax museum is chilling. He introduced changes, including upgrading antiquated technology and hiring a math geek squad. But, even though he praises the efforts of many of his colleagues who “work so hard for investors,” one has the feeling that the SEC remains a work in (very slow) progress. Of course, as financial regulations get rolled back, it may have more time to improve its own infrastructure.

Sunday, March 19, 2017

Yamarone, The Economic Indicator Handbook

Richard Yamarone, a Bloomberg senior economist, has written a book that, as he himself admits, “is overwhelmingly related to economics as seen from the Bloomberg terminal.” For those of us who don’t have access to such a luxury, The Economic Indicator Handbook: How to Evaluate Economic Trends to Maximize Profits and Minimize Losses (Wiley, 2017) can here and there be a frustrating read. The first chapter, for instance, describes the kinds of data available on the Bloomberg terminal, complete with screen captures: the economic calendar, economist estimates and expectations, the Bloomberg economic surprise index, the events calendar, the economic statistics table, the economic workbench, the Bloomberg orange book of CEO comments, treasury and money market rates, and the Bloomberg financial conditions monitor and its financial market conditions index. Some of this information is available elsewhere but not so conveniently packaged.

Having done his duty to his employer, Yamarone proceeds to discuss in eleven chapters the business cycle, GDP, labor market and employment, retail sales, NFIB small business economic trends, personal income and outlays, housing and construction, manufacturing, prices and inflation, confidence and sentiment, and the Federal Reserve. Most of the data come from publicly available sources.

Yamarone’s descriptions of the various economic indicators are perhaps the clearest I’ve seen anywhere. He explains what the indicators measure, how they are constructed, how they can be used, their strengths and weaknesses, sometimes how they can be tweaked to improve their ability to forecast changes in the economy.

For example, some economists chart the spread between two subsets of the Conference Board’s Consumer Confidence Index: the Present Situation Index and the Expectations Index. “The reasoning behind this strategy is simple: If the expectations index is less than the present situation index, generating a negative spread, the implication is that people are happier with where they are now than with where they see themselves in the near future. Conversely, a positive spread implies a belief that greater prosperity lies just around the corner, a good sign for spending and the economy. The wider the spread in either direction, the drearier or dreamier future conditions are expected to be relative to the present.” This spread has often been a good leading indicator. It “generally bottoms out just before a recession begins and peaks just after it ends.”

Yamarone slices and dices economic indicators, looking for their most predictive elements. He claims, for instance, that perhaps the single most important sentiment indicator is the trending behavior of the Conference Board’s 35-54 age group.

The Economic Indicator Handbook is useful both as a book to read cover to cover and as a reference book. That it comes with a lot of Bloomberg Terminal eye candy—beautiful charts and graphs—only adds to its value.

Wednesday, March 15, 2017

Lidsky, Eyes Wide Open

At the age of 13 Isaac Lidsky learned that he was beginning to go blind; by the age of 25 he had lost his sight entirely. His initial reaction was, naturally, to be fearful since his future seemed dark, both literally and figuratively. In Eyes Wide Open: Overcoming Obstacles and Recognizing Opportunities in a World That Can’t See Clearly (TarcherPerigree/Penguin Random House, 2017), expanding on his popular TED talk, he recounts how he embraced his blindness and “gained a life richer in understanding, connection, and success.”

Lidsky, now 37 years old, has had a life that many would envy—if, that is, they could skip the “being blind” part. He was a child actor, starring as “Weasel” on NBC’s sitcom Saved by the Bell: The New Class. He graduated from Harvard at the age of 19 with a degree in mathematics and computer science and proceeded to found an internet advertising technology company. When it was finally thriving, he left to attend Harvard Law School. After three years as a U.S. Justice Department attorney, he became a Supreme Court law clerk, working for Justices Sandra Day O’Connor and Ruth Bader Ginsburg. He then put aside his legal career to acquire a struggling construction company, growing it tenfold in five years.

Eyes Wide Open is an intellectually sophisticated, uplifting book that I highly recommend. Yes, it includes advice that you’ve undoubtedly heard before, but the context makes that advice all the more compelling.

For this post I’m going to share two short excerpts that traders might find especially applicable to their endeavors. First, the paralyzing effect of fear.

“Fear narrows your focus and tunnels your vision. … When you confront the unknown, you face the greatest need to look outside yourself, to see beyond your mental database, to broaden your perspective and to think most critically. But fear produces the opposite effect. It beats a retreat deep inside your mind, shrinking and distorting your views. It drowns your capacity for critical thought with a flood of disruptive emotions. … Similarly, fear often emerges when you face a compelling opportunity to take action, to evolve, to make progress, to overcome, to transcend. But fear can be paralyzing. Its inertia is massive. Like its sibling denial and its cousin pride, fear clings to the status quo. Fear thrives in the fictitious minutiae of the mental images it inspires. It immerses you in those images, lulls you into inaction, and invites you to passively watch its prophecies fulfill themselves.”

Second, the devastating message of your inner critic and the response of the strong man.

You will never be good enough, he says. Don’t bother trying. … What remains to be done is vast compared to that which you have achieved. You require far more resources than those already marshaled. … Success is an island fortress, hazy and remote. The critic is obsessed with that fortress, the outcome, the destination, the final product. … You are on a fool’s errand, he says. This is hopeless.”

By contrast, “The strong man values effort, struggle, momentum, growth. He finds none of these things in perfection and thus has no use for it, in concept or in application. … For the strong man, the ‘best’ is a fallacy. He assesses the quality of the effort expended, not the results obtained. … What next? he asks. It is his mantra. Just keep moving.

You’ll be amazed what you can achieve. Lidsky threw out the first pitch at a Marlins-Cubs baseball game to promote Hope for Vision—and it was a strike. All it took for a blind man to learn to throw a regulation pitch was three or four hours of practice.

Sunday, March 12, 2017

Damodaran, Narrative and Numbers

Even as flagging, high-profile hedge funds are looking for salvation in the quant world, academics are raising a red flag. Perhaps we’ve gone overboard in our efforts to reduce all financial activity to a set of numbers. For instance, Robert J. Shiller, in his presidential address delivered at the annual meeting of the American Economic Association at the beginning of this year, extolled the virtues of studying (admittedly quantitatively) popular narratives to understand economic fluctuations.

In Narrative and Numbers: The Value of Stories in Business (Columbia University Press, 2017) Aswath Damodaran, professor of finance at New York University Stern School of Business and a self-avowed numbers man, delves into the role of storytelling in the context of valuing businesses and making investments. Valuation, he claims, is a bridge between numbers and stories. “In effect, valuation allows each side to draw on the other, forcing storytellers to see the parts of their stories that are improbable or implausible, and to fix them, and number crunchers to recognize when their numbers generate a story line that does not make sense or is not credible.”

In the early chapters Damodaran looks at storytelling in general and business storytelling in particular. At issue is whether the stories a business tells (or the investor creates) are possible, plausible, or probable. Damodaran admits that “the lines between the possible, plausible, and probable are not always easy to draw.” He suggests instead thinking about the distinction between the impossible, implausible, and improbable, laying them out on a continuum of skepticism. “Impossible and improbable are quantifiable, the first because you are assigning a zero probability to an event happening and the latter because you are attaching a probability (albeit a low one) that an event will happen. Implausible lies in the muddled middle, since proving that it cannot happen is not feasible and attaching a probability judgment to it is just as difficult.”

Since Damodaran argues that “stories without numbers are just fairy tales and numbers without stories to back them up are exercises in financial modeling,” the core of his book deals with the process of connecting a plausible story to value drivers, using value drivers to estimate value (and, in reverse, extracting stories from existing valuations), and then, in a feedback loop, improving and modifying the narrative.

Damodaran illustrates his points in some detail using the examples of Uber, Ferrari, Amazon, and Alibaba.

The intended audience of Narrative and Numbers includes both entrepreneurs (and managers) and investors. With both groups the goal is to prevent wishful thinking from becoming expectation. Damodaran has carefully and convincingly developed an antidote to that financial poison.