Tag Archives: risk

Skin in the Game: Hidden Asymmetries in Daily Life – Taleb

2018, Random House, 279 pages

Book Blurb

From the New York Times bestselling author of The Black Swan, a bold new work that challenges many of our long-held beliefs about risk and reward, politics and religion, finance and personal responsibility.

“Skin in the game means that you do not pay attention to what people say, only to what they do, and to how much of their necks they are putting on the line.”

In his most provocative and practical book yet, one of the foremost thinkers of our time redefines what it means to understand the world, succeed in a profession, contribute to a fair and just society, detect nonsense, and influence others. Citing examples ranging from Hammurabi to Seneca, Antaeus the Giant to Donald Trump, Nassim Nicholas Taleb shows how the willingness to accept one’s own risks is an essential attribute of heroes, saints, and flourishing people in all walks of life.

The phrase “skin in the game” is one we have often heard but rarely stopped to truly dissect. It is the backbone of risk management, but it’s also an astonishingly rich worldview that, as Taleb shows in this book, applies to all aspects of our lives. As Taleb says, “The symmetry of skin in the game is a simple rule that’s necessary for fairness and justice, and the ultimate BS-buster,” and “Never trust anyone who doesn’t have skin in the game. Without it, fools and crooks will benefit, and their mistakes will never come back to haunt them.”

Author Blurb

Nassim Nicholas Taleb spent twenty-one years as a risk taker before becoming a researcher in philosophical, mathematical, and (mostly) practical problems with probability. Although he spends most of his time as a flâneur, meditating in cafés across the planet, he is currently Distinguished Professor at New York University’s Tandon School of Engineering. His books, part of a multivolume collection called Incerto, have been published in thirty-six languages. Taleb has authored more than fifty scholarly papers as backup to Incerto, ranging from international affairs and risk management to statistical physics. Having been described as “a rare mix of courage and erudition” he is widely recognized as the foremost thinker on probability and uncertainty. Taleb lives mostly in New York.

Great Writers Give You Great Ideas

Taleb, as assiduous readers will recall, planted the idea in my mind that a theory of tragedy could be based on risk. While wandering around the big Borders bookstore in Providence Place Mall one evening, his book Fooled by Randomness jumped out at me. Around this time, I had been reading a pile of economics books: A Random Walk Down Wall Street by Malkiel (recommended) and various books by Jeremy Siegel (less recommended). It was at this time I discovered concepts like the efficient market hypothesis and that finance is really quite interesting. There was also a personal reason to learn about investing. My seven year fairy-tale run in academia was coming to an end and it was time to become a civilian again. I still had an investment portfolio that, believe it or not, I had still been adding to while in university (to the tune of $25 or so a month–saving is a hard habit to break). I hadn’t really done anything with it since the Bre-X and Dot Com crash of 1999, but I figured it was time to get back into the game.

1999 was a bad year for investing. My Royal Bank advisor had steered me into tech (it’s the new economy) and precious metals (another hot sector) mutual funds. In addition to exorbitant management fees (round 3% those days), both sectors crashed. Panicked and bummed out, I sold and, by selling, locked in my losses. I lost interest in investing for six years. After which time, I decided if I was going to get back into the game, I would learn how the system worked and do everything myself in a self-directed account. So, I picked up Taleb’s Fooled by Randomness to become a better investor. But the unanticipated outcome was that I would also base a theory of tragedy around the impact of low-probability, high-consequence events. But hey, that’s another story. Back to Taleb.

Hidden Asymmetries in Daily Life

The book’s subtitle is “Hidden Asymmetries in Daily Life.” What does that mean? Taleb’s argument is that symmetrical situations in which risk and reward are balanced are preferable to asymmetrical situations in which rewards can be had without risk. Take, as an example, building a house. The best case scenario is if you build the house yourself because you’re taking on the risk (if could go over budget, the design could be faulty, etc.,) and reaping the potential reward (if it goes well you save a bunch of money). When you take on risk for a shot at a reward, you have skin in the game.

But let’s say you don’t know how to build a house. You’d have to hire a general contractor (GC) to frame the house and look after the plumbers, electricians, glazers, and other subtrades. The good thing is that you have a pro to build your house. The bad thing is that the risks and rewards to your pro are less symmetric: he doesn’t realize the upside. If the house: a) comes in under budget, b) is built to higher standards, or c) is built three months ahead of schedule the GC doesn’t realize the benefits. To him, the risks and rewards are asymmetric. In other words, he doesn’t have as much skin in the game. Taleb’s solution: incentivize the GC with a performance bonus. That way the homeowner and the GC align their risks and rewards. They place their goals on a less asymmetrical and a more symmetrical footing.

That’s the gist of the book: have skin in the game. Talk is talk. Talk is cheap. You have to walk the walk. Don’t ask someone what hot stock to invest in or what their investing philosophy is. Simply see what they have in their portfolio. And beware of asymmetry: if you get advice where you, but not the person giving the advice, is exposed to the harm should the advice fail, run away.

Unsurprisingly, Taleb’s praise is directed to people who have skin in the game. He singles out the Roman emperor Julian the Apostate, who fought in the front lines on the eastern front. In a more recent example of noblesse oblige, during the Falklands War, Prince Andrew also fought on the front ranks, where the danger was the greatest. By taking responsibility for their privilege, they had skin in the game. Martyrs (who die for their beliefs) and businesspeople (who stake their own funds) are further examples of those who have skin in the game. Whistleblowers who face smear campaigns while protecting the public also win Taleb’s praise. In fact, one of the dedicatees of the book is Ralph Nader, who was a victim of an intimidation campaign when he called out General Motors for defective products.

Also unsurprisingly, Taleb’s ire is directed to people who, by gaming asymmetrical situations, profit off the system without putting skin in the game. Journalists, politicians, and academics (especially economists) win his ire. He singles out journalists on BNN or Bloomberg who recommend stocks while they themselves don’t hold positions. The situation is asymmetric because viewers are exposed to harm if the recommendation fails while the journalist gets a paycheque either way.

Taleb singles out politicians who bail out failing institutions: the politicians take the credit for saving the world while it is the taxpayers who fund the bailouts, not the politicians. Taleb devotes significant attention to Bob Rubin, a former Secretary of the United States Treasury. As Secretary of the Treasury under Clinton, Robert Rubin had opposed regulating collateralized debt obligations (CDOs), credit default swaps, and other derivative instruments that Warren Buffett would later refer to as “financial weapons of mass destruction.” After his tenure as Treasury Secretary, he received over $120 million from Citibank, which was rolling in the cash by offering these selfsame derivative financial instruments. But when these derivative instruments led to the 2008 financial crisis and banks needed to be bailed out, the bailout money came out of taxpayers’ pockets, not the pockets of folks like Bob Rubin who had made a fortune by promoting them. To Taleb, this “Bob Rubin Trade” showcases asymmetry: heads I win, tails the taxpayers lose.

Taleb also singles out academics, mainly economists. To Taleb, they come out with fancy economic models and give their models the stamp of approval with their academic credentials. But since academics are divorced from reality (one of his quotes runs: “In the academic world there is no difference between academia and the real world; in the real world there is”) their models seldom work. Economists create asymmetry because real world traders are exposed to harm if they use the economists’ models while economists continue to collect their salaries no matter whether they are right or wrong.

The Lindy Effect

An interesting concept that gains prominence in Skin in the Game is the Lindy effect. The Lindy effect (named after the New York delicatessen where the idea began) states that the longer something survives, the longer it is likely to survive. A Broadway play, for example, that has been playing for 400 days is likely to play for another 400 days. A religion that has been around for a thousand years can be expected to be around for another thousand years. A book that has been in publication for fifty years is likely to be in publication for another fifty years. If, after fifty years it is still in print, then it will likely last another hundred years. If after another hundred years it is still in print, then it will likely survive another 200 years. And so on.

What is the relationship between the Lindy effect and the idea of skin in the game? According to Taleb, concepts and ideologies also have skin in the game. The role of a writer, for example, should not be to please book reviewers (who are not experts and do not have skin in the game) but to please future readers. Time, to Taleb, is the ultimate arbiter. You can fool some of the people today, but if it stands the test of time, it’s legit. Take, say, a fashionable diet, something like the Atkins diet. It’s new, so who knows if it’s good or bad for you. But take fasting days. Many religions have had fasting days for a long, long time. Fast days are “Lindy proof.” They stand the test of time. Because they stand the test of time, they are very likely to be good for you. Consider also coffee (which has been around 600 years) versus today’s latest energy drinks (which have been around a decade). Which do you think will stand the test of time?

I’m not sure about this point, but what I think Taleb is saying with the Lindy effect is this: when you take risk, you have skin in the game, which is good. Risk and volatility is sort of the same thing: if the ride gets too volatile, it’s game over for your endeavour. Volatility and time are also sort of the same thing. So, when you’re taking risks to put skin in the game, you’re actually going one-on-one against time. If you have an idea, to put maximal skin in the game, you want to go against all the other ideas that were and will be out there. It’s a tough game, but there is a reward: the Lindy effect. If you make it to the top, chances are you’ll (or your idea) will stay alive. Not sure if that’s it, but that’s my interpretation of the Lindy effect as it relates to this volume.

Now, this is the fifth volume of Taleb’s Incerto series and it seems with the Lindy effect he’s come full circle. So, the Lindy effect says that something which has survived a long time will likely keep surviving. Unless, of course, this something runs into a black swan. Assiduous readers of Taleb will remember that the second volume of Incerto was called The Black Swan: The Impact of the Highly Improbable. The black swan phenomenon is when highly improbable events happen that change everything. Take the very idea of the black swan. The idea came from the Roman poet Juvenal, who said that “a good person is as rare as a black swan.” The punchline is, of course, that black swans don’t exist. So, for hundreds of years, the phrase “black swan” came to denote something that doesn’t exist. And, what is more, the Lindy effect made the “black swan” analogy more and more prevalent as time went on. Until of course, an actual black swan was sighted in Australia by a Dutch sailer in 1636. So, it was a black swan event (sighting a creature that was not supposed to exist) that brought an end to the Lindy effect on the original use of the term “black swan” as understood by Juvenal. It will be very interesting if, in a future work, Taleb pits these two contrasting phenomena against one another.

Does Risk Theatre Have Skin in the Game?

It’s always interesting to tie the books I’m reading back into what I’m doing. This keeps things real. It gives reading a purpose. Here’s a quote from Skin in the Game that confirmed I was on the right track:

The deprostitutionalization of research will eventually be done as follows. Force people who want to do “research” to do it on their own time, that is, to derive their income from other sources. Sacrifice is necessary. It may seem absurd to brainwashed contemporaries, but Antifragile [the previous title in the Incerto series] documents the outsized historical contributions of the nonprofessional, or, rather, the non-meretricious. For their research to be genuine, they should first have a real-world day job, or at least spend ten years as: lens maker, patent clerk, Mafia operator, professional gambler, postman, prison guard, medical doctor, limo driver, militia member, social security agent, trial lawyer, farmer, restaurant chef, high-volume waiter, fire-fighter (my favorite), lighthouse keeper, etc., while they are building their original ideas.

It is a filtering, nonsense-expurgating mechanism. I have no sympathy for moaning professional researchers. I for my part spent twenty-three years in a full-time, highly demanding, extremely stressful profession [he founded a hedge fund called Empirica Capital, which, coincidentally, bet on black swan declines in the stock markets] while studying, researching, and writing my first three books at night; it lowered (in fact, eliminated) my tolerance for career-building research.

For the last eleven years, I’ve been writing a book: The Risk Theatre Model of Tragedy: Gambling, Drama, and the Unexpected. But, the book was not enough. As Taleb would say, writing the book is like “talking the talk.” Like the Efficient Market Hypothesis, the Black-Scholes equation (for pricing options), and other economic models that Taleb disdains, the risk theatre model of tragedy, while not an economic model, is an academic model nonetheless. As an academic model, it could use some more skin in the game.

To give the risk theatre model of tragedy some more skin, I started up, with Langham Court Theatre, the 2019 Risk Theatre Modern Tragedy Competition. We would award cash prizes to dramatists worldwide to write risk theatre tragedies. We would help these dramatists develop risk theatre to the highest levels by workshopping their plays. And, to help offset travel and accommodation expenses, we’d offer a stipend for dramatists to come attend the workshop in Victoria, Canada.

To fund the book and the competition, I work a real-world job as a project manager for PML Professional Mechanical. I oversee $25 million of construction projects: a mixed use commercial building with Save-on-Foods as the anchor and two residential towers above for Bosa/Axiom, a distinctive condo called the B&W (it’s clad in sections of black and white bricks) for Abstract Developments, and two 20-storey towers for Chard Developments. In other words, I’ve got skin in the game. If Taleb’s thesis is correct, the book and the theatre competition stand a greater chance of success because I’m putting my money where my mouth is.  Here’s hoping. Time will tell.

Until next time, I’m Edwin Wong, and I’m doing Melpomene’s work. By the way, this is a great book. Read it. If you haven’t read any volumes in the Incerto series, and are looking for a place to start, you couldn’t go wrong with the second volume, The Black Swan.

The (mis)Behavior of Markets: A Fractal View of Financial Turbulence – Mandelbrot and Hudson

2004, Basic Books, 328 pages

Back Blurb

The (mis)Behavior of Markets offers a revolutionary reevaluation of the tools and models of modern financial theory. From the gyrations of the Dow to the dollar-euro exchange rate, mathematical superstar and inventor of fractal geometry shows us how to understand the volatility of markets in far more accurate terms than the failed theories that have brought the financial system to the brink of disaster. Updated with a new preface on the financial crisis of 2008, Mandelbrot’s insights are more valuable than ever.

Author Blurbs

Benoit Mandelbrot is Sterling Professor Emeritus of Mathematical Sciences at Yale University and a Fellow Emeritus at IBM’s Thomas J. Watson Laboratory. The inventor of fractal geometry, he has received the Wolf Prize in Physics, the Japan Prize in science and technology, and awards from the U.S. National Academy of Sciences, the IEEE, and numerous universities in the United States and abroad. His many books include Fractals: Form, Chance and Dimension, which later expanded into the classic The Fractal Geometry of Nature. He lives in Cambridge, Massachusetts.

Richard L. Hudson was managing editor of the Wall Street Journal’s European edition for six years, and a Journal reporter and editor for more than two decades. He is a graduate of Harvard University and a former Knight Fellow of MIT. Now the CEO and editor of Science Publishing Ltd., he lives in Brussels, Belgium.

A Fractal View of Financial Turbulence?

Fractal (from Latin frango “to break” e.g. fracture, fraction, fragment, etc.,) geometry was invented by Mandelbrot. It is a real-world, anti-Euclidean geometry in that it is the geometry of rough surfaces as opposed to the straight lines and perfect planes of Euclid. You can use fractal geometry to model structures where similar patterns recur in smaller and larger scales: for example cauliflower heads (a small head is a smaller version of a larger head) or coastlines (little nooks and crannies are scaled down versions of fjords). The immediate question than is: what do fractals have to do with financial turbulence? Well, the answer is that, rises and declines in stock prices also recur in similar and recurring patterns in smaller and larger time scales. For intuitive proof, compare one day, one month, one year, and one decade stock charts. Would you be able to tell, were the dates removed, which was which? Wall Street pros can’t. It’s just a bunch of wiggly lines. Wiggly lines that go back and forth like the coastline. And, like the coastline that exhibits self-similarity under 1x, 10x, and 1000x magnification, the stock chart exhibits self-similarity in one day, one month, or one year intervals.

This was Mandelbrot’s key insight, and a momentous one. It’s momentous because the implication is that, even if stock and commodity prices don’t go up and down randomly (they react to news, world events, and investor sentiment), their fluctuations can be modelled by the rules of probability as though they were random.

Late Work

One of the appealing things about The mis(Behavior) of Markets is that it is a late work. He turned 80 in 2004, the year the book came out. Long time readers of this blog will know that I’ve been a fan of late works for a long time: Beethoven’s Opus 111, Bach’s The Art of the Fugue, Mozart’s Requiem (unfinished at the time of death and played at his funeral), Nietzsche’s Ecce Homo, Sophocles’ Oedipus at Colonus (he successfully defended himself in court against charges of senility by citing his play), and Goethe’s second part of Faust. Directness of theme, abandonment of artifice, a brutal sense of honesty, a heartfelt and personal expression, a sense of possibility, and a glimpse of the bigger picture characterize the best late works. There’s an excellent book that talks about late style by scholar Edward W. Said entitled On Late Style: Music and Literature against the Grain. It’s fitting that that work is itself a late work.

Mandelbrot himself was keenly aware that he was himself producing a late work in writing The (mis)Behavior of Markets. Here’s a telling quote from the book (in the prelude written by coauthor Hudson):

In 2004, in his eightieth year, Mandelbrot continues making trouble. He works the same full schedule–including weekends–as he always has. He continues publishing new research papers and books, lecturing at Yale, and traveling the world of scientific conferences to advance his views. Why not? After all, as he points out, Racine’s most enduring play, Athalie; Verdi’s greatest opera, Falstaff; Wagner’s Ring Cycle–all were written in the twilight of life, when the artist, after years of experience and experimentation, was at the height of his powers.

Prejudice against the Speculative Markets

Mandelbrot devotes a chapter of the book to mathematician Louis Bachelier. Bachelier had dared to write base his dissertation on the volatility of bonds at The Bourse at the Paris exchange. His idea was that, although you could never know where future bond prices would end up, you could mathematically evaluate the odds of the fluctuations because bond prices would follow a ‘random walk’. The random walk is based on the random path of pollen grains suspended in water. And just as the path of pollen grains could be plotted on the bell curve, so could bond prices.

Unfortunately for Bachelier, academia deemed The Bourse to be to degraded of a place for true mathematicians. So, instead of graduating with a ‘trés honorable’ honour, he received a ‘mention honorable’. This consigned him to a life of obscurity. It wasn’t until the 1950s, a decade after his death, that his star picked up. Some are born posthumously.

Now it seems that the prejudice against true mathematicians working in finance remains to us today. Since my childhood, I’ve loved reading science books. Inevitably, each one will mention Mandelbrot and how fractal geometry is the best thing since sliced bread. But, you know, I don’t think any of them talked about Mandelbrot’s pioneering work in the 1960s examining price volatility in cotton markets (in the 60s, historic data on cotton pricing was complete, readily available, and accurate). Since then, Mandelbrot has devoted a lot of time and published quite a bit on how markets work. Heck, Eugene Fama was one of his students (he supervised his dissertation). But it wasn’t until I stumbled on this book (probably through a Marketwatch or Bloomberg article) that I had any idea that Mandelbrot had anything to say about the markets. In fact, I was so surprised when I found out, I googled to see if this was the Mandelbrot or another fellow with the same name.

So, You Think You Know What Risk Is…

Risk can be many things. Risk can be loss. Risk can be when something happens that you didn’t expect would happen. These sorts of risk are hard to quantify. But, if risk is volatility, it can be quantified. Take the 52 week high and low of Apple stock. The range between the high and low is the volatility. This sort of volatility can be expressed mathematically, using the laws of probability–that’s why the economists like it. They put in into formulas and win Nobel Prizes.

Beginning with Bachelier, it was thought that, if one graphed the daily movements of a stock, the price data would arrange itself into the standard distribution of a bell curve. The mean price would fill out the familiar bulge in the centre of the curve, and the larger price swings would be captured in the ‘tails’ of the curve. The larger the price swing, the less probable it is to happen. The bell curve is popular because it fits many natural phenomena. Human height, for example, fits a bell curve: 68% of American men are between 68-72 inches tall; 95% are between 66-74 inches tall; 98% are between 64-76 inches tall. The bell curve doesn’t rule out a 10′ giant. But the tail at this extreme is so flat that you would never expect to see one. IQ scores and the returns on betting on a series of coin tosses also fit a bell curve.

The idea of using the standard distribution of the bell curve to represent market risk was so prevalent that when Bachelier was rediscovered in the 1960s, the standard tools of finance all took it up. As a result, the standard tools MBA students learn to model the market are all based on the mild and predictable sort of risk the bell curve predicts. These tools are: modern portfolio theory or MPT by Harry Makowitz, the capital asset pricing model or CAPM by William Sharpe, and the Black-Scholes formula by Fischer Black, Myron Scholes, and Robert Merton. Markowitz, Sharpe, Scholes, and Merton all received Nobel Prizes for their work. Black would have as well, if he had lived another two years (the Nobel is not awarded posthumously).

The question Mandelbrot poses is: what if the bell curve is wrong? What if the odds of catastrophic ‘tail’ events in the market such as the 29.2% decline on Black Monday (October 19, 1987) are a thousand or a million times more likely than what the standard model posits? And, what is more, what if the stock market has a memory?–the standard model is based on a random walk. Like how each flip of the coin, the daily movements of the stock market are independent of one another. But, what if, in the real world, volatility cascades? Cascades in that a 3% drop one day increases the odds that it will continue to fall in the following days? Mandelbrot’s answer? If the bell curve is wrong, then we are like shipbuilders who think gales are rare and hurricanes are myths. We sail into doom. And we encourage others to sail into the storm with the comfort of dead wrong economic models. It’s like if we planned a mission to go to Mars based on old Ptolemaic models of the solar system.

To show how the bell curve is a poor measure of risk, Mandelbrot provides examples from the cotton, commodity, and stock markets: the data doesn’t fit the curve. ‘Impossible’ tail events happen in reality far more frequently than the bell curve allows.

The Solution

This was the most confusing part for me. Mandelbrot himself says that the math isn’t complete. Just as Bachelier had to wait a good 60 years for the math to catch up to his ideas, Mandelbrot’s ideas of fractal turbulence may have to wait another generation or two. He himself says the math is very hard. This book is more a call to arms that something has to be done. He does offer some suggestions, though.

In addition to the standard, bell curve distribution, there appear to be other probability distributions. There’s the Cauchy distribution. And there’s also a whole family of L-stable or ‘Levy’ distributions. These other distributions, from what I gather, have fatter tails. But they too, don’t capture the how real world risk works. It may be that they overstate the odds of catastrophic tail events. And it does not appear possible to insert other types of probability distributions into the standard models of finance (e.g., Black-Scholes, MPT, and CAPM). All the standard model, for some reason that a mathematician would understand, use the bell curve because it fits into the equation. Here I could be wrong, but that’s what I’m gathering.

In the future, the multifractal model of financial turbulence might be able to create a ‘fingerprint’ of a stock’s volatility. Right now, one of our best models of risk is the VaR or ‘Value at Risk’ model (also based on the bell curve). You start off by deciding how safe you want to be. Let’s say the maximum loss you are willing to take in a year is 10%. You then find a stock using the VaR model where, 95% of the time, the losses will be 10% or less. How is this safe, asks Mandelbrot?–the point is that 5% of the time, the losses can be more than 10% and up to 100%. It is only the illusion of safety. But let’s say someone uses the multifractal model to create a fingerprint of a stock’s volatility. This, to me, would still be based on historic price data. If the company hasn’t gone out of business, would the fingerprint capture the possibility of the stock going bankrupt, or, in other words, going down 100%?

Mandelbrot says many times that it’s not possible to make money (yet) from this multifractal view of stock market volatility. That may be true, but I wonder…if all the standard models underestimate volatility (because they use the bell curve), then wouldn’t that mean that the market is underpricing volatility? There should be some way of betting on irrational gains and losses and making money. Let’s say the market is saying that the odds of a 10% daily collapse is 1:1,000,000. But the odds are actually higher, 1:100,000 or something like that. There must be some financial instrument you could use to short the market so that when the 10% daily collapse happens, you could clean up since you know the ‘true’ odds and the market, which uses the incorrect model, has mispriced that eventuality.

Another idea to make money: if volatility is greater than commonly thought, would that be an argument for buying an equal weight index rather than a market weight index? With an equal weight index, you would have the same constituent stocks as an index investor (in a market weight index such as the S&P 500). But since stocks bounce up and down from their ‘average’ or ‘mean’ price, each time you invest fresh money, you would buy whichever stock had fallen the most. If you used a buy and hold strategy, because volatility is greater, you should be able to pick up a couple of points over the market weight buy and hold investor. Or?

Of course, these ideas aren’t based on the multifractal model, but rather, on volatility itself. Perhaps the way to make money on the multifractal model would be to market it to a data company such as Thomson Reuters. Thomson Reuters would use the mathematical model to project future growth, volatility, and other parameters of a stock. It might even use the model to draw future stock charts and run them through Monte Carlo simulators. Investors would, in turn, use this information in putting together resilient and efficient portfolios which maximize return and minimize risk.

Betting on Volatility and Turbulence

I should mention that I’ve put money on a sort of equal weight index. In March 2015, I picked 20 small companies in my play portfolio. They were picked somewhat randomly, but not completely at random. Since, for the most part, I’m an index investor, and the Canadian TSX Composite is dominated by financials (banks and insurance), oil & gas, and materials (mining), one rule was that none of these 20 companies could be from these sectors. The idea was that I wanted the small-cap portfolio to zig when the TSX Composite was zagging. So I ended up picking some industrials, consumer staples, healthcare, and technology stocks. Why small-cap? Well, I wanted to capture volatility and small-caps tend to move up and down violently than their more stable large cap brethren. In this small-cap portfolio, the idea is never to sell. But whenever I added money to the portfolio, I would top up the stock that had been most hammered (to keep the portfolio equal weight). This way, when things turn around (which they will do unless your pick goes bankrupt), you’ll pick up a little extra because you’ve said yes to volatility. Why 20 stocks? Well, you have to have enough stocks to have some winners and losers. And you can’t have too many stocks that you’re just replicating the index. Between 20-30 seems like a good number where the losers will hit you, but not too hard and the winners will help you, but also not too much. If you have too few stocks, and just happen to pick the losers, you’re going to get really hurt. But if you have too many stocks, the winners aren’t really going to impact the portfolio that much. It’s a question of concentration.

It seems that some Paris firms are doing something similar and calling this a multifractal strategy. Mandelbrot dismisses such attempts in his book as being far from multifractal: to him, it is just betting on stocks ‘reverting to the mean’. He’s absolutely right. But I can’t help but think that if volatility is so great, and if volatility is the measure of how much a stock deviates from its mean price, then shouldn’t it be easy to pick up a few extra points by a continual buying and holding equal weight strategy? Here were my picks from three and a half years ago and the performance:

AG Growth International (AFN) +17.8%

AGT Food and Ingredients (AGT) -28.0%

Alcanna (CLIQ) -21.4%

Boston Pizza Royalty Income Fund (BPF.UN) -21.5%

Boyd Group (BP.UN) +133.5%

Capstone Infrastructure (CSE) taken private at a gain of +37.6%, used proceeds to buy Cipher Pharmaceuticals

Chemtrade Logistics (CHE.UN) -27.6%

Cipher Pharmaceuticals (CPH) -49.6%

Clearwater Seafoods (CLR) -39.0%

Descartes Systems (DSG)  +126.2%

Great Canadian Gaming (GC) +74.7%

Highliner Seafoods (HLF) -59.3%

Innergex Renewable Energy (INE) +17.4%

Intertape Polymer (ITP) -7.3%

K-Bro Linen (KBL) -20.2%

Morneau Shepell (MSI) +56.2%

NFI Group (NFI) +257.3%

Northwest Company (NWC) +13.7%

Park Lawn (PLC) +4.4%

Premium Brands (PBH) +246.5%

Student Transportation (STB) taken private at a gain of 38.9%, used proceeds to buy Park Lawn

Western One (WEQ) -44.2%

If you look at the returns, I think you’ll agree there’s no shortage of volatility: the best performer was NFI (a maker of buses and motorhomes) at +257% and the laggard was Highliner Seafoods (a maker of fishsticks) at -59%. In the portfolio, two stock more than tripled (NFI and PBH), two other stocks more than doubled (BYD and DSG), and three stocks lost more than 40% (CPH, HLF, and WEQ). The volatility is there.

But the question is, how did the portfolio do? In three and a half years, with dividends, it’s up 26.3%. That equates to a rate of return of 6.9% each year. Compare this to the S&P TSX Small Cap Index (market weight). Total return in the last three and a half years is 20.1% for an annualized return of 5.7%. The little equal weight portfolio has done well compared to the market weight index. But of course the results are statistically meaningless as the two portfolios hold different stocks. You’d have to compare a market cap to a equal weight portfolio tracking the same index to draw meaningful conclusions. Perhaps a topic for a future blog?

One insight, does, however, emerge from this small cap portfolio: the business model really gives you little idea of how a stock will perform. Who knew that a bus and motorhome manufacturer (New Flyer) would triple? Who knew that Premium Brand Holdings, a company that makes Starbucks breakfast sandwiches and the sliced meats you find at grocery stores would be a top performer?–geez, they just make black forest ham! Who knew that a worldwide lentil distributor would be down a third? Aren’t people supposed to be eating more lentils? Who knew that Highliner Seafoods would be down over half? Isn’t seafood consumption up and growing? And why is K-Bro Linen down a fifth?–don’t they have the lock on hospital linen cleaning contracts in all the major cities?

If you had asked ten experts three and a half years ago to predict where these 20 stocks were going, I don’t think any of them would even be remotely close. You would have to have known that India would have frozen out Canadian lentils (AGT). You would have to have known that the government would have stripped CLR of part of their arctic clam license. You would have had to have predicted that oil would go down to twenty dollars a barrel (WEQ). You would have had to have predicted Valeant’s business model would explode, dragging down the whole pharmaceutical industry (CPH). How could anyone have known? And you know, it’s going to be like this going forwards. The things that will affect this small cap portfolio are the things we don’t know yet. Until then, I’ll keep picking up a few points on volatility. That I do know will be there. Funny, the only certain thing is that things are uncertain.

A Mystery

Mandelbrot spends a bit of time talking about power laws. Instead of a bell curve distribution where the tails are imperceptible, cotton prices, wheat prices, interest rates, and some stocks follow a power law distribution which allows for large price swings. Gravity and earthquakes also follow a power law distribution: double the distance or power, and the force of attraction or the frequency is four times less. In a section of the book, Mandelbrot tells the story of Harold Edwin Hurst, a hydrologist who cracked the code of how high to build a dam to tame the Nile.

The problem with calculating how high to build the dam was that the Nile would not only experience really dry and really wet years, but also that the wet and dry years would cluster together in an unpredictable pattern. In his attempt to understand flooding, Hurst looked through any reliable, long-running records on climate he could find, from tree ring growth, sunspot patterns, discharges from Lake Huron, and annual water levels at Lake Dalalven in Sweden. People thought he was a crack, since how could such varied phenomena be related? He looked through 51 different phenomena, and found that everywhere he looked, the range obeyed a three-fourths (0.73) power law. It was as though this three-fourths power law is a constant of nature. Now this is interesting. It makes me want to learn math so that I can figure out why this is. This is one of these questions that you could spend your life looking into.

I have to agree with Taleb that this is “the deepest and most realistic finance book ever published.” I read it three times. And, if I didn’t have a stack of other deserving titles, I would have read it a fourth time.

Until next time, I’m Edwin Wong, and I’m doing Melpomene’s work.

Low-Probability, High-Consequence Events in Greek Tragedy: Aeschylus’ Seven Against Thebes

Thanks to Professor LB and the Department of Greek and Roman Studies for setting up this seminar. And thanks to all the students and faculty who came out on a cold and snowy Friday afternoon. Great turnout (we packed the conference room) and very receptive audience for this homecoming lecture. Judging from the discussion period that followed the presentation, there’s a sharp band of students at UVic! My old roommate TS from the happy days of UVic undergrad (who’s know Professor TS of English Literature) received a research grant to fly out to hear the talk, so that was extra fun! The core of this presentation was delivered at the APA earlier this year. This version has been revised to take into account the feedback from APA which was: hammer home the point that the gate assignations are random. The preconceived (and likely mistaken) notion that Eteocles decides the assignations remains very strong with readers of the play. If the assignations are random (as I argue), the play is actually quite fun, dramatic, and full of suspense. If the assignations are decided and preordained (as others argue), the play is quite static. Which would you rather have? BTW the image on the poster is from the Exekias Vase and it depicts Achilles and Ajax playing dice. Probably a high-stakes game as they have their spears handy just in case!

Exekias Vase

DEPARTMENT OF GREEK AND ROMAN STUDIES SEMINAR

FRIDAY, FEBRUARY 23 2:30 PM CLEARIHUE B415

 

Low-Probability, High-Consequence Events in Greek Tragedy: Aeschylus’ Seven Against Thebes

 

I present to you a question: does it seem that tragedy in general—not just Greek tragedy—goes out of its way to dramatize low-probability, high-consequence outcomes? Low-probability refers to events are that are unlikely, events that are 1000:1 against, events such as Birnam Wood coming to Dunsinane Hill. In Shakespeare’s play, the witches tell Macbeth that nothing can harm him until Birnam Wood removes to Dunsinane Hill. It’s highly unlikely that the trees will take up their roots and hike up the hill. But when the troops camouflage themselves under Birnam Wood, the high-consequence event unfolds. Macbeth is caught flat-footed. All is lost.

 

We see something similar in Sophocles’ Oedipus rex. The messenger comes out of left field to tell Oedipus that he’s inherited the Corinthian throne, and, oh, by the way, your parents aren’t who you think they are. How do I know that?—well, I saved you when you were a babe and your real parents had exposed you. Who are my real parents?—well, you have to ask the shepherd. What are the odds of a messenger, and not any messenger, but this messenger coming to Thebes at this exact moment? It’s as likely as Birnam Wood coming to Dunsinane Hill. But it happens, and the outcome has high consequences, as Oedipus goes from being a king to an outcast.

 

This presentation is on how tragedy dramatizes low-probability, high-consequence events. But there’s one problem: how do we know that an event in tragedy is unlikely? Something has to happen, and anything that happens is, in a way, unique. How do we quantify the odds of what takes place against what did not take place?

 

Aeschylus’ Seven Against Thebes is the one unique play where it’s possible to quantify the odds of what didn’t happen. In Seven, seven attacking captains lay siege to seven-gated Thebes. One brother, Polyneices, marshals the attack. Inside Thebes, the other brother, Eteocles, coordinates the defence. The worst-case scenario occurs if the brothers meet at the seventh gate. They would shed kindred blood and miasma would result. If they go to different gates, the worst-case scenario is averted. Or, if they find themselves at a gate prior to the seventh gate, Eteocles could substitute another captain in his place. But the worst-case scenario occurs if they’re both at the final gate, as substitutions are no longer possible.

 

With seven gates, seven attackers, and seven defenders, what are the odds of the worst-case scenario? Let’s look at this this way. What are the odds of rolling a six on a six-sided die? There’re six equally probable outcomes, so the answer is 1:6. Now what are the odds of rolling two sixes? The outcome of two independent rolls is the product of their individual probabilities. 1:6*1:6=1:36. Now, if there are seven gates, and the assignations are random, there’s a 1:7 chance that Eteocles goes to the seventh gate. The odds of Polyneices going there are the same, 1:7. So we multiply the odds together and find that, the odds of the worst-case scenario is 1:49. Now, what are the odds of the worst-case scenario not happening? The answer is 48 out of 49 times. See how Aeschylus doesn’t dramatize the likely scenario, but rather the worst-case scenario which is 48:1 against. Thanks to Seven, we can quantify how tragedy goes out of its way to deliberately dramatize low-probability, high-consequence events.

 

But—how do we know that the process of assigning gates to the attackers is random? Easy. The scout tells us:

 

As I was leaving

they were casting lots (klhroumevnou~), each to divine by fortune

against which of our gates he would lead his battalions (77-9, trans. Hecht & Bacon)

 

Since the attackers draw lots, it stands that Polyneices’ chance of going to the seventh gate is 1:7. How do we know that the process of assigning gates to the defenders is random? That’s harder. It’s not explicit. Eteocles tells us at the conclusion of the first episode that:

 

I will go and assign six men, myself the seventh,

all fully armed oarsmen,

against the champions at the seven exit-points of the city. (357-60)

 

Now, when he says that he “will assign six men, myself the seventh” he doesn’t necessarily mean he’s stationing himself at the seventh gate. So why say this odd phrase?—“assign six men, myself the seventh.” I like Roisman’s explanation: “it is an image of bad luck, since the number 6 + 1 [in dice games] was considered an unlucky throw.”[1] I want to seize and expand this point. There’s something ludic about this play; it exudes a sort of gambling hall or lottery atmosphere. We’ve already talked about how the attackers draw lots and the unlucky 6 + 1 gambling reference. Let’s add to this. For instance, Eteocles remarks as he dispatches Melanippus to face Tydeus that: “The chances of battle are as dice (kuvboi~) in the hands of Ares (511).” What other gaming references are there? Well, when Eteocles interprets the matchup between Hippomedon and Hyperbius, he says: “Hermes, by divine reason, has matched this pair (624).” Hermes, as Hecht and Bacon note, is invoked in his capacity as the god of luck and fortunate coincidence. Finally, the scout tells us after the brothers die that “they have shared out by lot (dievlacon) their full inheritance (1039).” The lottery image, along with the ship of state image, are the two dominant metaphors of this play. Because of the lottery imagery, I’m convinced that a random process must be involved in how Eteocles assigns the defenders. After all, why would he say that “Hermes, by divine reason, has matched this pair” unless they were brought together under Hermes’ tutelage as the god of lots? And why would the scout say that the brothers “have shared out by lot their full inheritance” unless a lottery process was involved in the assignations?

 

I want to share with you that Seven was the first Greek tragedy I read. When I first read it, I thought for sure that Eteocles decides the assignations on the spot, during the shield scene itself. The scout would report and he would say: “Oh, I just have the right guy to neutralize him.” In hindsight, that’s a very modern reading as that’s how a general would decide today. But how would this fit in with the lottery images? It doesn’t. Later I read Zeitlin’s Under the Sign of the Shield where she points out that Eteocles clearly says he’s going to decide the assignations before he meets the scout.[2] But then I thought: “Eteocles decides?—then what’s the point of all the lottery and gambling images?” Then I heard Weckler and Wilamowitz’ argument that some assignations are done before, and some during. While this solves the problem of the tenses, as during the shield scene sometimes Eteocles says “I shall station,” and at other times “He has been chosen,” it seems unnecessarily complicated. Because of the lottery references, I was ready to say that Eteocles decides by lot before he meets the scout. But when I recently read Herrmann’s conjecture, I was immediately convinced: he conjectures that Eteocles decides by lot during the shield scene itself.[3] Herrmann’s conjecture is brilliant. When Eteocles says that he’s going to assign the men before the scout comes, he’s putting their names in the helmet. As for the tenses, as he picks up the lot he can be saying “I will appoint” or “He has been already appointed.” Furthermore, Herrmann’s conjecture gives Eteocles something dramatic to do during the shield scene and, what is more, it means that, the defender assignations, like the attacker assignations, are random. Because all the assignations are random, all the possible matchups at each of the gates exist only as a probability until the moment when the lots are drawn. Because all the outcomes exist as probabilities, we can quantify the exact odds of what takes place against what did take place to verify how tragedy engages audiences with low-probability, high-consequence scenarios.

 

Could Aeschylus and his audience have worked out that the worst-case scenario is averted 48 out of 49 times? No. Sambursky, a historian of science, finds that the lack of both algebraic notation and systematic experimentation held the Greeks back from discovering the laws of probability.[4] The laws of probability would not develop until Cardano starts counting up the number of throws possible with dice two millennia later. But we know that the Greeks were able to understand the concept, if not the math of combinatorial analyses. Xenocrates, for example, mistakenly calculates that, by mixing together the letters of the alphabet, 1,002,000 unique syllables are possible.[5] Despite not being able to compute the exact odds, Aeschylus and his audience would have recognized that the odds of the brothers meeting at the highest gate was an exceedingly low-probability affair.

 

Besides the objective remoteness of the worst-case scenario, what subjective cues give Eteocles hope things will go his way? First, there’s the enemy’s disarray. Their morale is so low that they’re already dedicating memorial tokens to send back home. One of their captains says outright that he’s going to die. They also attack before their seer gives the signal. And there’s infighting between their captains. Contrast this with the improving morale of the chorus of Theban women, who function as a barometer of morale within the city: they start off in panic, but by the first stasimon, Eteocles wins them over. Many indications give Eteocles subjective hope.

 

The surest indication that things will go his way comes in the shield scene. In the shield scene, the scout describes, gate by gate, the attacking captain’s appearance, demeanor, and shield device. Eteocles, in turn, draws the lot to determine the defender and interprets the tale of the tape. Since chance is a reflection of god’s will, you can tell from the random matchups which side heaven favours. In the game of knucklebones, for example, rolling the Aphrodite throw (1, 3, 4, and 6) was considered a propitious sign from the goddess. So, to make up an example, if the bad guy carries a brutal monster on his shield, and your guy happens to be carrying a shield depicting a peasant farmer, that’s heaven telling you: “Your guy’s going to die.” So, how do the matchups work out? Well, in aggregate, the matchups overwhelmingly favour Eteocles. For example, the attacker at the fourth gate sports a Typhon device and he happens to be matched up against the defender bearing the Zeus shield: in myth Zeus had tamed Typhon. Or, as it happens, the attacker at the first gate who shouts out impieties is matched up with a defender who just happens to be “a noble man who honours the throne of Reverence (503).” So, gate by gate, as Eteocles sees the matchups unfolding, he grows more confident.

 

Objectively, the worst-case case scenario is buried deep in the odds. Subjectively, everything’s going his way. He’s unified the city. The matchups look better and better. But what’s happening? The odds of the worst-case scenario go up gate by gate each time the brothers’ lots don’t come up. At the first gate, the worst-case odds are 1:49. At the second gate, they go up to 1:36. By the sixth gate, they’ve escalated to 1:4. See what’s happening? Paradoxically, as he becomes more confident, he’s actually in greater danger, till the point when he’s most confident, at that point he’s in the greatest danger. Even as the situation becomes subjectively better, objectively things are becoming much worse. At the sixth gate, with his cheeks flush with the glow of wine and his hair all but adorned in ivy, as he dispatches Lasthenes to confront Amphiaraus, he seals his own doom in a stunning twist of fate. When the scout announces Polyneices stands at the seventh gate, the low-probability, high-consequence event comes to pass. The event was objectively low-probability because the odds that it happens is 48:1 against. The event was subjectively low-probability because everything was going his way. Tragedy is an engine that makes even foredoomed outcomes exciting by discounting the odds of the inevitable taking place.

 

I think these low-probability, high-consequence events are commonplace throughout tragedy. Take Sophocles’ Oedipus rex. Like Eteocles, Oedipus has played his hand well. Everything’s going his way. “Don’t worry,” says the Corinthian messenger, “you’re really not from Corinth. You’re going to be king of two cities.” At the point of maximum confidence, the low-probability, high-consequence event happens and Oedipus loses all. Or take Shakespeare’s Macbeth. Like Eteocles, Macbeth has played his hand well. “Nothing can harm you,” say the witches. At the point of maximum confidence, the low-probability, high-consequence event unfolds: Birnam Wood. Can you see a general trend?—at the point of maximum confidence, an unexpected, low-probability event unfolds with high consequences.

 

This way of looking at tragedy I call risk theatre. To me, tragedy’s function is to warn us that at our point of maximum confidence, we are, paradoxically, in the gravest danger. In this way, tragedy speaks to our confident age, an age of both great risk and great reward. While I was writing this, an article appeared in Wired magazine on November 16 on gene editing.[6] In the US, the entomologist Akbari is working on a gene drive, a way to supercharge evolution by forcing a genetic modification to spread through an entire population. With the gene drive, he can take flight away from mosquitoes and vanquish malaria—promising, of course, minimal disruption to ecosystems. And on November 17, USA Today reported that in Italy, Doctor Canavero was getting ready to do the world’s first head transplant on a human being.[7] What could go wrong?—they had already done the procedure on a dog. Akbari and Canavero are confident, and have the best-laid plans. But so did Oedipus, Eteocles, and Macbeth. In today’s technological age of manufactured risk, tragedy ought to and should be seen as a theatre of risk, as we moderns have a moral obligation to come to terms with the low-probability, high-consequence ramifications of our actions. And what better place to explore these than through drama? We emerge from risk theatre with eyes wide open. And I think, if you look at tragedy as a theatre of risk, it will guide you well because you’ll be better apprised that the things that hurt you come where you least expect. I’ll finish by saying that I’ve written a book on risk theatre and that I’m in high-level talks with theatres to produce new tragedies based on this exciting concept. Thank you for listening, and I welcome your feedback on risk theatre, the theatre that guarantees low-probability outcomes, every time.

 

Edwin Wong

edwinclwong@gmail.com

[1] Roisman, Hanna M. “The Messenger and Eteocles in the Seven against Thebes,” in L’antiquité classique, vol. 59, 1990, 22.

[2] Zeitlin, Froma I., Under the Sign of the Shield, 45.

[3] Herrmann, Fritz-Gregor, “Eteocles’ Decision in Aeschylus’ Seven against Thebes, in Tragedy and Archaic Greek Thought, ed. Douglas Cairns, Swansea: Classical Press of Wales, 2013, 58ff.

[4] Sambursky, “On the Possible and the Probable in Ancient Greece,” Osiris 12 (1956) 35-48.

[5] Plutarch, Quaestiones convivales 733a.

[6] Molteni, Megan, “This Gene-Editing Tech Might be too Dangerous to Unleash,” Wired, November 16, 2017.

[7] Hjelmgaard, Kim, “Italian Doctor Says World’s First Human Head Transplant ‘Imminent’,” USA Today, November 17, 2017.

Low-Probability, High-Consequence Events in Greek Tragedy: A Look at Aeschylus’ Seven Against Thebes

2018 Society for Classical Studies Annual Meeting (Boston)

Session 9: Agency in Drama (Presided by Helene Foley)

 

Low-Probability, High-Consequence Events in Greek Tragedy: A Look at Aeschylus’ Seven Against Thebes

 

I present to you a question: does it seem that tragedy in general—not just Greek tragedy—goes out of its way to dramatize low-probability, high-consequence outcomes? Low-probability refers to events are that are unlikely, events that are 1000:1 against, events such as Birnam Wood coming to Dunsinane Hill. In Shakespeare’s play, the witches tell Macbeth that nothing can harm him until Birnam Wood removes to Dunsinane Hill. It’s highly unlikely that the trees will take up their roots and hike up the hill. But when the troops camouflage themselves under Birnam Wood, the high-consequence event unfolds. Macbeth is caught flat-footed. All is lost.

 

We see something similar in Sophocles’ Oedipus rex. The messenger comes out of left field to tell Oedipus that he’s inherited the Corinthian throne, and, oh, by the way, your parents aren’t who you think they are. How do I know that?—well, I saved you when you were a babe and your real parents had exposed you. Who are my real parents?—well, you have to ask the shepherd. What are the odds of a messenger, and not any messenger, but this messenger coming to Thebes at this exact moment? It’s as likely as Birnam Wood coming to Dunsinane Hill. But it happens, and the outcome has high consequences, as Oedipus goes from being a king to an outcast.

 

This presentation is on how tragedy dramatizes the risk of low-probability, high-consequence events. But there’s one problem: how do we know that an event in tragedy is unlikely? I mean, something has to happen, and anything that happens is, in a way, unique. How do we quantify the odds of what takes place against what did not take place? We need a play where we can see this.

 

In Aeschylus’ Seven Against Thebes it’s possible to quantify the odds of what didn’t happen. In Seven, seven attacking captains lay siege to seven-gated Thebes. One brother, Polyneices, marshals the attack. Inside Thebes, the other brother, Eteocles, coordinates the defence. The worst-case scenario occurs if the brothers meet at the seventh gate. They would shed kindred blood and miasma would result. If they go to different gates, the worst-case scenario is averted. Or, if they find themselves at a gate prior to the seventh gate, Eteocles could substitute another captain in his place. But the worst-case scenario occurs if they’re both at the final gate, as substitutions are no longer possible.

 

With seven gates, seven attackers, and seven defenders, what are the odds of the worst-case scenario? Let’s look at this this way. What are the odds of rolling a six on a six-sided die? There’re six equally probable outcomes, so the answer is 1:6. Now what are the odds of rolling two sixes? The outcome of two independent rolls is the product of their individual probabilities. 1:6*1:6=1:36. Now, if there are seven gates, and the assignations are random, there’s a 1:7 chance that Eteocles goes to the seventh gate. The odds of Polyneices going there are the same, 1:7. So we multiply the odds together and find that, the odds of the worst-case scenario is 1:49. Now, what are the odds of the worst-case scenario not happening? The answer is 48 out of 49 times. See how Aeschylus doesn’t dramatize the likely scenario, but rather the worst-case scenario which is 48:1 against. Thanks to Seven, we can quantify how tragedy goes out of its way to deliberately dramatize low-probability, high-consequence events.

 

But—how do we know that the process of assigning gates to the attackers is random? Easy. The scout tells us:

 

As I was leaving

they were casting lots (klhroumevnou~), each to divine by fortune

against which of our gates he would lead his battalions (77-9, trans. Hecht & Bacon)

 

Since the attackers draw lots, it stands that Polyneices’ chance of going to the seventh gate is 1:7. How do we know that the process of assigning gates to the defenders is random? That’s harder. It’s not explicit. Eteocles tells us at the conclusion of the first episode that:

 

I will go and assign six men, myself the seventh,

all fully armed oarsmen,

against the champions at the seven exit-points of the city. (357-60)

 

Now, when he says that he “will assign six men, myself the seventh” he doesn’t necessarily mean he’s stationing himself at the seventh gate. So why say this odd phrase?—“assign six men, myself the seventh.” I like Roisman’s explanation: “it is an image of bad luck, since the number 6 + 1 [in dice games] was considered an unlucky throw.”[1] I want to seize and expand this point. There’s something ludic about this play; it exudes a sort of gambling hall or lottery atmosphere. We’ve already talked about how the attackers draw lots and the unlucky 6 + 1 gambling reference. Let’s add to this. For instance, Eteocles remarks as he dispatches Melanippus to face Tydeus that: “The chances of battle are as dice (kuvboi~) in the hands of Ares (511).” What other gaming references are there? Well, when Eteocles interprets the matchup between Hippomedon and Hyperbius, he says: “Hermes, by divine reason, has matched this pair (624).” Hermes, as Hecht and Bacon note, is invoked in his capacity as the god of luck and fortunate coincidence. Finally, the scout tells us after the brothers die that “they have shared out by lot (dievlacon) their full inheritance (1039).” The lottery image, along with the ship of state image, are the two dominant metaphors of this play. Because of all these lottery images, I’m convinced that a random process must be involved in how Eteocles assigns the defenders. After all, why would he say that “Hermes, by divine reason, has matched this pair” unless they were brought together under Hermes’ tutelage as the god of lots? And why would the scout say that the brothers “have shared out by lot their full inheritance” unless a lottery process was involved in the assignations?

 

I want to share with you that Seven was the first Greek tragedy I read. When I first read it, I thought for sure that Eteocles decides the assignations on the spot, during the shield scene itself. The scout would report and he would say: “Oh, I just have the right guy to neutralize him.” In hindsight, that’s a very modern reading as that’s probably how a general would decide today. But how would this fit in with the lottery images? It doesn’t. Later I read Zeitlin’s Under the Sign of the Shield where she points out that Eteocles clearly says he’s going to decide the assignations before he meets the scout.[2] But then I thought: “Eteocles decides?—then what’s the point of all the lottery and gambling images?” Then I heard Weckler and Wilamowitz’ argument that some assignations are done before, and some during. While this solves the problem of the tenses, as during the shield scene sometimes Eteocles says “I shall station,” and at other times “He has been chosen,” it seems unnecessarily complicated. Because of the lottery references, I was ready to say that Eteocles decides by lot before he meets the scout. But when I recently read Herrmann’s conjecture, I was immediately convinced: he conjectures that Eteocles decides by lot during the shield scene itself.[3] Herrmann’s conjecture is brilliant. When Eteocles says that he’s going to assign the men before the scout comes, he’s putting their names in the helmet. As for the tenses, as he picks up the lot he can be saying “I will appoint” or “He has been already appointed.” Furthermore, Herrmann’s conjecture gives Eteocles something dramatic to do during the shield scene and, what is more, it means that, the defender assignations, like the attacker assignations, are random.

 

Could Aeschylus and his audience have worked out that the worst-case scenario is averted 48 out of 49 times? No. Sambursky, a historian of science, finds that the lack of both algebraic notation and systematic experimentation held the Greeks back from discovering the laws of probability.[4] The laws of probability would not develop until Cardano starts counting up the number of throws possible with dice two millennia later. But we know that the Greeks were able to understand the concept, if not the math of combinatorial analyses. Xenocrates, for example, mistakenly calculates that, by mixing together the letters of the alphabet, 1,002,000 unique syllables are possible.[5] Despite not being able to compute the exact odds, Aeschylus and his audience would have recognized that the odds of the brothers meeting at the highest gate was an exceedingly low-probability affair.

 

Besides the objective remoteness of the worst-case scenario, what subjective cues give Eteocles hope things will go his way? First, there’s the enemy’s disarray. Their morale is so low that they’re already dedicating memorial tokens to send back home. One of their captains says outright that he’s going to die. They also attack before their seer gives the signal. And there’s infighting between their captains. Contrast this with the improving morale of the chorus of Theban women, who function as a barometer of morale within the city: they start off in panic, but by the first stasimon, Eteocles wins them over. Many indications give Eteocles subjective hope.

 

The surest indication that things will go his way comes in the shield scene. In the shield scene, the scout describes, gate by gate, the attacking captain’s appearance, demeanor, and shield device. Eteocles, in turn, draws the lot to determine the defender and interprets the tale of the tape. Since chance is a reflection of god’s will, you can tell from the random matchups which side heaven favours. In the game of knucklebones, for example, rolling the Aphrodite throw (1, 3, 4, and 6) was considered a propitious sign from the goddess. So, to make up an example, if the bad guy carries a brutal monster on his shield, and your guy happens to be carrying a shield depicting a peasant farmer, that’s heaven telling you: “Your guy’s going to die.” So, how do the matchups work out? Well, in aggregate, the matchups overwhelmingly favour Eteocles. For example, the attacker at the fourth gate sports a Typhon device and he happens to be matched up against the defender bearing the Zeus shield: in myth Zeus had tamed Typhon. Or, as it happens, the attacker at the first gate who shouts out impieties is matched up with a defender who just happens to be “a noble man who honours the throne of Reverence (503).” So, gate by gate, as Eteocles sees the matchups unfolding, he grows more confident.

 

Objectively, the worst-case case scenario is buried deep in the odds. Subjectively, everything’s going his way. He’s unified the city. The matchups look better and better. But what’s happening? The odds of the worst-case scenario go up gate by gate each time the brothers’ lots don’t come up. At the first gate, the worst-case odds are 1:49. At the second gate, they go up to 1:36. By the sixth gate, they’ve escalated to 1:4. See what’s happening? Paradoxically, as he becomes more confident, he’s actually in greater danger, till the point when he’s most confident, at that point he’s in the greatest danger. That’s the genius of Seven: even as the situation becomes subjectively better, objectively things are becoming much worse. At the sixth gate, with his cheeks flush with the glow of wine and his hair all but adorned in ivy, as he dispatches Lasthenes to confront Amphiaraus, he seals his own doom in a stunning twist of fate. When the scout announces Polyneices stands at the seventh gate, the low-probability, high-consequence event comes to pass. The event was objectively low-probability because the odds that it happens is 48:1 against. The event was subjectively low-probability because everything was going his way. By combining subjective and objective probabilities, Aeschylus spring loads the low-probability event so that when it takes place, we feel its impact.

 

I think these low-probability, high-consequence events are commonplace all over tragedy. Take Sophocles’ Oedipus rex. Like Eteocles, Oedipus has played his hand well. Everything’s going his way. “Don’t worry,” says the Corinthian messenger, “you’re really not from Corinth. You’re going to be king of two cities.” At the point of maximum confidence, the low-probability, high-consequence event happens and Oedipus loses all. Or take Shakespeare’s Macbeth. Like Eteocles, Macbeth has played his hand well. “Nothing can harm you,” say the witches. At the point of maximum confidence, the low-probability, high-consequence event unfolds: Birnam Wood. Can you see a general trend?—at the point of maximum confidence, an unexpected, low-probability event unfolds with high consequences.

 

This way of looking at tragedy I call risk theatre. Tragedy warns us, that at our point of maximum confidence, we are, paradoxically, in the gravest danger. I think that tragedy speaks to our confident age, an age of both great risk and great reward. While I was writing this, an article appeared in Wired magazine on November 16 on gene editing.[6] Here in the US the entomologist Akbari is working on a gene drive, a way to supercharge evolution by forcing a genetic modification to spread through an entire population. With the gene drive, he can take flight away from mosquitoes and vanquish malaria—promising, of course, minimal disruption to ecosystems. And on November 17, USA Today reported that in Italy, Doctor Canavero was getting ready to do the world’s first head transplant on a human being.[7] What could go wrong?—they had already done one on a dog. Akbari and Canavero are confident, and have the best-laid plans. But so did Oedipus, Eteocles, and Macbeth. I look at tragedy as a theatre of risk because such an interpretation speaks to our technological age of manufactured risk. In such an age, I believe that we have a moral obligation to come to terms with low-probability, high-consequence events. And what better place to explore these than through drama? We emerge from risk theatre with eyes wide open. And I think, if you look at tragedy as a theatre of risk, it will guide you well because you’ll be better apprised that the things that hurt you come where you least expect. I’ll finish by saying that I’ve written a book on risk theatre and that I’m in high-level talks with theatres in Victoria, Canada to produce new tragedies based on this exciting concept. The goal to start a new art movement in tragedy. Thank you for listening, and I welcome your feedback on risk theatre, the theatre that guarantees low-probability outcomes, every time.

 

Edwin Wong

2018-01-05

[1] Roisman, Hanna M. “The Messenger and Eteocles in the Seven against Thebes,” in L’antiquité classique, vol. 59, 1990, 22.

[2] Zeitlin, Froma I., Under the Sign of the Shield, 45.

[3] Herrmann, Fritz-Gregor, “Eteocles’ Decision in Aeschylus’ Seven against Thebes, in Tragedy and Archaic Greek Thought, ed. Douglas Cairns, Swansea: Classical Press of Wales, 2013, 58ff.

[4] Sambursky, “On the Possible and the Probable in Ancient Greece,” Osiris 12 (1956) 35-48.

[5] Plutarch, Quaestiones convivales 733a.

[6] Molteni, Megan, “This Gene-Editing Tech Might be too Dangerous to Unleash,” Wired, November 16, 2017.

[7] Hjelmgaard, Kim, “Italian Doctor Says World’s First Human Head Transplant ‘Imminent’,” USA Today, November 17, 2017.

Society for Classical Studies 2018 Presentation

Passive Income Part Three – Risk

Passive Income Part Two – Costs ended on a cliffhanger: it addressed why costs are important, but did not get to how costs can be controlled. It.s actually easy: find low cost investment vehicles. To find the right low cost investment vehicles and put them together in a portfolio, an understanding of risk is useful.

What is Risk?

Some say risk is a four letter word. Others say it is the danger of loss. To some risk is that more things can happen than will happen. An economist will say the technical definition which is that risk is the portfolio’s standard deviation. Standard deviation quantifies the variance in annual profits and losses. Economists like it because it can be expressed as a number and being a number, can fit into their equations. It.s hard to quantify ‘shit happens’! The economists’ definition, however, is at odds with how the word is commonly used to express ‘danger of loss’. A portfolio whose returns varies from -1% to -2% each year by their reckoning is less risky than a portfolio whose returns varies between +5 to + 15% each year because the variance in the returns of the first portfolio is smaller. According to the common usage, the first portfolio is clearly ‘riskier’ because it is losing money each year!

For today, however, risk is your tolerance to loss and gain. The more risk tolerant you are, the greater chance you are willing to stomach big losses so that in other years you will have big gains. The less risk tolerant you are, the more you prefer small gains in good years so that losses in bad years are also smaller. This principle works because risk is related to return: the more risk you are willing to take on, the greater your return should be because you are exposed to greater danger. Think of different occupations. A linesman (those guys who connect power lines carrying tens of thousands of volts) makes more money than, say, a deli attendant at a supermarket. That.s because the most dangerous thing in the supermarket is the meat cutter or an irate customer. The linesman takes on more risk and should be compensated for taking risk. It.s the same in the stock market.

So decide whether you.re low risk, medium risk, or high risk investor. There.s actually no way to really figure out until you.re invested (and feel the thrill of making money and the dejection of losing money) so just go ahead and decide. Remember what you decide as we.ll come back to it in a second. Here.s some images to help assiduous readers make their selection.

If you require helmet, reflective gear, and lights to feel safe riding a bike, consider yourself low risk:

Bike Safety Nerd - Low Risk

Bike Safety Nerd – Low Risk

If you will go for the piece of cheese provided you have safety apparatus, consider yourself medium risk:

Safety Mouse - Medium Risk

Safety Mouse – Medium Risk

If you do vehicle repairs A-Team style, consider yourself high risk:

Road Repair - High Risk

Road Repair – High Risk

Classes of Investments

There.s two major classes of investments: stocks and bonds. With stocks, you are a shareholder in the company. You are a part owner, in other words. With bonds, you lend your money to a company. They will pay you back what you lent them plus a little something extra for your trouble. The nice thing with stocks and bonds is that they.re uncorrelated. That is to say, they do not move in tandem. If one.s going up, the other.s going down. Or if one.s going up, the other.s treading water or not going up quite as much.

Now guess which is riskier? If you guessed stocks, then you.d be right. They also return more than bonds (most of the time). But they are also more volatile. That.s why you also need bonds in your portfolio. Think of them as a ballast. When the storm.s brewing and you.re battening down the hatches, bonds are your best friend, not that diamond mine in Botswana.

Now, since there are two classes of investments and when one zigs the other zags, it seems a good idea to have bits of both in the investment portfolio. Stocks are the engines that drive the portfolio.s growth during good years and bonds are the ballast that help you through the storm. How do we figure out how much of each?

Do you remember what type of investor you are from the previous section? If you.re the safety cyclist, a good starting point is a portfolio of 60% stocks and 40% bonds. If you.re the hungry mouse who will go for the cheese after putting on the necessary safety gear, a good starting point is 70% stocks and 30% bonds. If you.ll trust a 2×4 to hold up your truck while doing repairs underneath it, then a good starting point is 80% stocks and 20% bonds.

Wasn.t that easy?

Investment Vehicles

Which bonds and which stocks to I buy? That.s easy: buy them all! There are these investment products out there called exchange-traded funds or ETFs. They.re exchange-traded because they trade on the TSX (the stock market). They.re funds because they.re baskets of many individual holdings which together represent the total market. For bonds, I.d recommend Vanguard Canadian Aggregate Bond Index ETF. It has a MER (management expense ratio) of 0.19%. For something that holds around 600 different issues of bonds, it.s dirt cheap. Of it.s 600 or so issues, about three-quarters of its holdings are backed by the Canadian government (federal, provincial, and municipal) or government related entities. The remaining one-quarter are issued by companies, mainly investment grade banks and insurance companies.

For stocks, I.d recommend BMO Capped Composite Index ETF. It has a MER (management expense ratio) of roughly 0.1%. I say roughly because they just lowered it and their site frustratingly publishes the ‘Maximum Annual Management Fee’ (which is slightly less than the MER which includes trading costs and other things). I wish everyone would just publish the MER to make comparisons easier. This ETF holds around 230 of the largest companies in Canada: Royal Bank, Manulife, CNR, Valeant Pharmaceuticals, Blackberry, you name it, it.s in there.

In the following blogs I.ll discuss how to buy the bond ETF and the stock ETF. Once you.re set up, it.s a few keystrokes and clicks of the mouse. It.s that easy.

In today.s segment, I discussed risk and how knowing your risk tolerance helps you to put together a portfolio. I also recommended two investment vehicles: one for bonds and one for stocks. Notice how low their costs are: fractions of a percent. In Passive Income Part Two, the average cost of a mutual fund was flagged at 2.42%. The cost of a DIY portfolio with my two recommendation is in the neighbourhood of 0.15%. That is to say, by reading this blog, you save 94% off the posted retail price!

Stay tuned for Part Four of the Passive Income saga! Next time, the discussion will be on the burning question I.m sure all of you are asking: how do I open up an investing account? Well, that.s easy too!

Until next time, I.m Edwin Wong and investing has been how I was able to get out of the rat race to be Doing Melpomene’s Work. I hope others will be able to as well.

Tales of the Unexpected (the Happy Side of Risk)

Do you find most often people—or yourself—try to avoid the unexpected? People say: ‘become better educated’, ‘contain the risk’, ‘watch out for the downside’, ‘better to go with the devil you know’, and so on. There is in the unknown something of a bogeyman. Well that.s true. Especially from my perspective, since I write on tragedy and, well, in that art form, whenever the hero runs across the unknown or the unexpected, the distribution of outcomes is asymmetrically skewed to the downside: i.e. death and destruction! Well, sometimes the unexpected can be very good as well!

Assiduous readers will be sitting on the edge of their seats wondering how the Call for Art is progressing. Today I biked out to Sidney to distribute the flyers at the Island Blue Print and the galleries out there. By the say, Sidney is the best place in the world. People in Sidney just love to be in Sidney. They love to chat with other relaxed and smiley folks. So dropped off the flyer at the two galleries along the main strip. Got an art lesson on some of the new watercolours and oils that they were coming in. Some of these watercolour artists work on their pieces for months! They do three or four pieces a year that they.re absolutely happy with. Interesting work being a gallery buyer as well. Lots of artists coming in: so many works, so little room! Also found an art school by the water. The instructor had a lesson going on but had a prize pupil who she thought would be a perfect fit. There were samples on display and lots of these students are very talented! The only dangerous place in Sidney is the Safeway or I guess Save-on-Foods parking lot. That place has its own laws of driving which I haven.t figured out yet. I don.t think the drivers there have figured out either. But I was wondering if I.d bump into my old colleague Erik at the Starbucks there. He gets his afternoon coffee fix there and it was just about the right time. Lo and behold, he is there! We chat and I stop by the old office to see the boys. One thing I notice: nothing ever changes. The office is exactly the same. Collected 20 bucks on a bet I won from my old boss (we had placed a bet on what the stock price of Lucara diamonds would be New Years Day; he said above $3 and I said under). Also placed a new bet: New Years Day 2016 price of a barrel of oil, which is sitting at $58 today. I say $50 and he says $70. We.ll see! I guess as a patriotic Canadian hopefully he wins! Canada.s frighteningly resource dependent. But hey, maybe it will take a prolonged slump in oil prices to kickstart nascent industries.

But that was a big digression. Are you still with me? I was telling the story of how sometimes the unexpected is skewed towards the positive side. So, biking home (Sidney to downtown Victoria), I take the Galloping Goose. Wonderful. Avoid the highway with all the noise and hubcaps and body parts from all the cyclists who have been struck down on the highway.s shoulder (well, okay, that last part was an exaggeration. But this is what my imagination tells me if i take the highway route). The Galloping Goose takes me by Matticks Farm. Usually I proceed straight through. Actually, every other time I.ve done the ride I.ve gone straight through. But today I was thirsty. And feeling not in a rush. So I stop by and pick up a chocolate milk. Mmmmmm. Finding a place to sit down, I notice there.s a gallery right there! Well, looking at their display, it.s mostly abstract works and landscapes. But i thought, ‘Why not?’. Going in, i.m greeted by Sharon. I tell her about the project and she looks at the flyer. She thinks for a moment…the artists she knows don.t usually do this type of work. But she has a great suggestion: try Moss Street market on the weekend. It.s a little society of artists that would do this sort of thing. And then another great idea. This one I was hitting myself for not having thought of it myself. On the causeway by the Inner Harbour in downtown Victoria, there.s all sorts of activity once tourist season starts going (which is right around now). The patios fill up. There.s clowns, magic shows, musicians, and food stands. And also artists. They do quick portrait sketches. So they.re skilled at meeting someone and capturing the person.s psychology with a few quick strokes. And they work fast. So it wouldn.t cost a fortune. While she was saying this, I was thinking, ‘Good point!’. Okay, so I don.t have a budget (art.s one of those things it.s hard to set a price to and I.d prefer the artist to set a price for the commission they.re happy with), but at one of the galleries I was at, the artist they were suggesting is accustomed to charging in the vicinity of 10k for commissions! I like quality and this project means a lot to me, but 10k can buy a lot of things! So let.s see what happens! I know where to go this weekend on the trail of the Call for Art!–Moss street and the causeway. It.ll be fun to be part of the hubbub too. Writers tend to be in their own company for long periods. Good to go out.

So how does this tie into the unexpected and the upside? Well, i wasn.t planning on stopping at Matticks Farm. It just so happened that I was thirsty while riding by. You know, on the bell curve, they call the left and right ends the ‘tails’ of the curve. Those are the places where very unlikely things happen. And when people talk about them, they usually talk about catastrophes: the hundred year storm, the ‘big one’ (earthquake), and so on. Well, the tail on the right end gets less attention. That.s like the day you meet your future wife or the day the lottery goes with your numbers. These things happen too. To me, what happened today was a bit of good fortune. Not on the extreme right of the bell curve, but good enough to make me happy. Her recommendation was very good. So to me, it.s a reminder to expose yourself to all the things out there. Live life to the fullest or some other wooly expression like that. Deal with the bad when it happens. Because only by exposing yourself to risk can you get the ‘good’ side of risk.

Have a few leads now on the Call for Art. Meeting some more artists, hopefully soon someone can start working on ‘The Dead Man.s Hand’!