Knight, Knight, Automated Trading Dreams

“The four most beautiful words in our common language: I told you so.” (Gore Vidal)

Glitch Driven Trading

The software glitch that pushed Knight Capital to the brink of extinction has simply reaffirmed two truths we’ve known for a long time (see: Rise of the Machines).  Firstly, the rise of machine driven trading is exposing markets to risks that aren’t manageable.  Secondly, the people regulating the markets don't understand, or don't want to acknowledge, what those risks actually are.

Behind this lies a fundamental issue: you can regulate to punish people retrospectively for their failures or you can limit innovation to reduce the probability of the issues happening in the first place.  It’s time to focus on the latter rather than the former because, if "this could happen to anyone" it could happen to you.

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Risk := ON

Quantitative Squeezing

As the immediate fears of market immolation have faded the switch in investors’ heads marked “Risk” has moved to the OFF position. All those little signs of uncertainty, the mass synchronisation of share price movements, the endless twittering and wittering about the imminent end of the known world have faded, to replaced by the normal measures of complacency in the face of unimagined dangers.

It’s likely that the relief generated by the Eurozone’s ability to stitch together a patchwork quilt of compromise to keep Greece from defaulting and the general resilience of corporate profits is only temporary. A reckoning must come when quantitative squeezing replaces quantitative easing. Getting this right requires finessing on a grand scale by the lords of finance; not impossible, merely very, very difficult.

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HONTI #3: Don’t Fear Volatility

Rule #3: Don’t worry about short-term price trends, turn off the portfolio tracker.

Risk

"The investor with a portfolio of sound stocks should expect their prices to fluctuate and should neither be concerned by sizable declines nor become excited by sizable advances"; Ben Graham, The Intelligent Investor

Imagine if you could pick up the paper every morning and riffle through the pages until you get to the property section where, half way down the third column, you could find the current price of your own home. Imagine further that this price was set by a bunch of people you’ve never met making apparently random bets based on a combination of intuition, centralised economic statistics, a bunch of robots programmed by people with the social skills of a twig and, a couple of times a year, the real price achieved by one of your neighbours actually selling.

Welcome to the world of asset price volatility.

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Dread Risk: Investing Outside the Goldfish Bowl

Goldfish Don't Have Defensive Moats

To argue that many investors and all markets are like goldfish, continually forgetting the recent past as soon as they swim around the corner of their cute seaweed festooned castle, is to do our piscine friends a disservice: goldfish have a memory span of up to three months. Investors sometimes struggle to be consistent for three hours consecutively.

It often seems like people have a switch in their heads marked “Risk”. While this is in the “OFF” position they’ll happily fill their boots with any old rubbish stock as long as enough other people are buying it. Yet as soon as life’s rich uncertainty rears its ugly head the switch gets set to “ON” and they head for cover behind the seaweed in the hope that their tiny castle can protect them. Memo to markets: risk is always with us, no matter how bad your memory – and castles in goldfish bowls don't have defensive moats.

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Economics & Psychology: Reconciliation?

Continued From Economics & Psychology: The Divorce …

By the early 1970’s, as the long bull market of the post war years collapsed in a welter of unforeseen problems, financial professionals confronted the real meaning of risk on a systemic basis. As markets crumbled in the face of economic uncertainty trading companies turned to economists in academia in the hope of finding a way through the mess, or at least some excuse to get people to buy stocks.

What they discovered was a way of measuring risk that appeared to offer the option of quantitatively managing investments in a rational way, rather than relying on the intuitions of individuals. This approach has come to dominate the securities industry ever since. At the same time, though, a small revolution was brewing in psychology. And it's been fermenting revolution ever since.

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Trading On The Titanic Effect

Scary Tactics

If you’re sailing icy seas you’d generally want to keep a watchful eye open for icebergs. Unless, of course, you’re in an allegedly unsinkable ship, in which case you’d probably prefer to opt for a spot of partying and an early snooze on the poop deck instead. The craft’s designers will likely not have bothered with wasteful luxury items like lifebelts, emergency flares or lifeboats either: what would be the point?

You have, of course, just fallen foul of the Titanic Effect, one of a number of self-fulfilling behavioural biases where your expectations bias your behaviour and make it more likely that you’ll fall foul of the very problems you think you’ve overcome. Oddly, though, the problem suggests the solution: scare the living daylights out of the crew before you cast off.

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Losing the Lender of Last Resort

Governments Aren't Risk Free

One of the carefully nurtured ideas that sits at the heart of most modern finance is the idea that there’s a risk-free asset that we can retreat to when we lose our nerve. This is the financial equivalent of the philosopher’s stone, capable of saving us when nothing else is.

Almost by definition the lender of last resort is the government and the risk-free asset usually ends up being government backed debt. The only slight fly in this magic ointment is that not only is government debt not risk-free but neither are governments themselves: it turns out they have a nasty habit of not being there exactly when you need them most.

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Risk, Reality and Richard Feynman

Rocks and Risk

One of the problems that lies behind many of the crises that have afflicted the financial sector over the past thirty years or so is that business managers seem to have difficulty relating the level of risks that they’re taking to something akin to reality. For various reasons, not entirely unrelated to the need to make business cases look reasonable, the potential risks in many transactions are downplayed to the point where they simply vanish.

This isn’t, however, a problem exclusive to the financial sector. Many other organisations face these problems as their managers are squeezed between rocks and hard places. As NASA, and its astronauts, have found to their cost.

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Cardano’s Gambit

Gamblers ‘Nonymous

Investing is, up to a point, gambling. Most of us don’t think of it in that way but if we conceive of the universe of stocks as a gas of randomly moving particles buffeted this way and that by forces largely beyond their – and certainly beyond our – control then there’s no other conclusion that can be drawn.

However, we don’t really believe this. What we generally believe is that although randomness is pervasive in stocks there’s a pattern that lies beneath the surface which we, in spite all evidence to the contrary, can pick out. For the idea that there are repeatable patterns hidden within apparently random games of chance we can thank one of our more unlikely heroes. Meet Girolamo Cardano, medieval physician, professional gambler and mathematician extraordinaire.

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In Value, Risk is Not Reward

Free Lunches

In looking for a free lunch many long-term investors gravitate towards value investing where the evidence is that so-called value stocks offer excess returns over medium term periods. This approach, however, brings with it a range of issues of mental discipline that can cause all sorts of strange behaviours, including an unreasoning attachment to stocks that have no merits whatsoever, apart from their consistent appearance on stock filters of a certain kind.

Over and above this, though, there’s a problem with the way that value investing is conceived. To the extent that it offers improved returns the general belief is that it does so by ensuring that the investor takes on more risk. This is exactly the wrong way for most investors to proceed: we want more returns for less risk. And done properly that's exactly what value investing can achieve for us.

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On Incentives, Agency and Aqueducts

Risk Management, Roman Style

There’s an aqueduct in Segovia, in Spain, that’s stood the test of time. A lot of water has flowed over that bridge … two thousand years worth, more or less, since it was built by the Roman Empire. Back then risk management consisted of getting the chief engineer to stand underneath the structure when they removed the supports: now that’s a proper incentive.

Incentives stand at the heart of a lot of human behaviour in corporations but financial theorists have had a great deal of difficulty in understanding that an incentive is not necessarily the same as a financial reward. Although the ideas of psychologists and sociologists are slowly seeping through there’s still a long way to go before there’s a proper appreciation of what motivates people. In the meantime we’re stuck with Agency Theory, the sheer power of grim self-interest: it’s like real life but not as we know it.

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Fall of the Machines

IT Illiterates Beware

A while ago in a piece named “Rise of the Machines” I suggested that automated algorithmic trading systems were a problem waiting to happen. Sadly this was wrong because the problems had already happened. As this article from the Financial Times shows, these systems had been misbehaving even before Wall Street freaked on May 6th 2010.

What’s really worrying, though, is that the FT article poses the question: “…has technology reached the point where machines pose systemic risks if they go berserk?” The answer’s pretty obvious to anyone who’s ever crafted a program more complex than the obligatory “Hlelo wrold” initiation, but perhaps the leaders of the financial world are really IT illiterates? Just in case, here’s a primer.

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Utility, The Deus Ex Machina of Economics

The St. Petersburg Paradox

An economic problem posed over 250 years ago still causes angst for economists, investors and actuaries today; largely because it’s never been satisfactorily solved, probably because it can't be. Despite this, the resolution posed all those years ago has travelled down the ages, insinuating itself into every nook, cranny and other archaic crevice of finance you care to mention, like an elasticated thong on an overweight man.

The problem, posed by Nicholas Bernoulli, is known as the St. Petersburg Paradox after the city of residence of his cousin, Daniel Bernoulli, who was the first person to propose an answer to it. Daniel’s great idea – and it was a truly great idea – is known as utility. Without the concept of utility it’s doubtful that any of us would be here to debate this issue, yet the findings of behavioural finance show that it’s almost certainly wrong. The Paradox of St. Petersburg has plenty of life left in it yet.

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Holes in Black-Scholes

Betting on Getting Flattened

It’s a rite of passage these days to diss the Black-Scholes option pricing model. Maybe this is because it’s the best known of the quantitative models that underlie the problems in global finance, although the fact it’s known to fail in unusual market conditions probably doesn’t help. On the flip side, if we know that Black-Scholes doesn’t work at market extremes you’d have thought there’d be ways of making money out of its failures.

Unsurprisingly it turns out that there are people looking at this. It also turns out that only a few have the mental discipline to achieve success because you spend a lot of time losing. You’re throwing pennies under the steamroller and watching others gather them while betting big money on the penny-gathers getting flattened eventually. It’s a discipline requiring courage, intelligence, patience and knowledge of history. So that rules most traders out, then.

Black, Scholes and Merton

Back in the 1970’s Fischer Black and Myron Scholes developed a method of pricing options which, with the typical inventiveness of economists, they called the “Black-Scholes method.” Following adaptations by Robert Merton it’s become the standard method of pricing options and earned all three a Nobel Prize. It’s also become the target of many other economists who either wish they’d thought of it first or reckon it shouldn’t ever have been thought of at all.

Options allow us to take a bet on the future price of some asset like a share without actually going to the trouble of buying it. They give the buyer the right, but not the obligation, to buy or sell the underlying asset at a pre-agreed price by a pre-agreed date. They’re a type of derivative – their value is derived from the underlying asset. Derivatives have been given a bad name over the years, being associated with many of the truly horrible things that the nastier investment gnomes are apt to get up to. However, used correctly, they can be hugely beneficial as they allow the risk associated with any asset to be transferred from where it can’t be dealt with to where it can be.

Essentially an option is a trade in uncertainty. If you can’t, for instance, afford to take the risk that your share portfolio will fall below a certain value then you can use options to protect yourself against this. If the portfolio falls below the trigger point you sell the option and pocket the cash. If it doesn’t then the option will expire and the money you spent on it disappears. Used like this options are a form of insurance. Of course, some financiers have found other more ‘creative’ ways of using them.

Volatility, Liquidity and LTCM

Black-Scholes allows traders to plug in values for asset prices, dividends, interest rates, time and volatility to produce a valuation. Volatility – the amount by which an asset’s price may vary over any given period – is often the critical factor. An asset with high volatility is more attractive to buyers of options because there’s a greater probability that, at some point, it’ll be in the money. Conversely assets with low volatility are more likely to be favoured by option sellers.

Black-Scholes came in for criticism due to its involvement in the collapse of Long Term Capital Management (LTCM) in 1998. LTCM imploded when Russia defaulted on its bonds because the model didn’t cope with the “impossible” liquidity crisis that followed: it didn’t handle the extreme conditions that resulted in no one being willing to accept the other side of LTCM’s deals.

Peer under the covers of Black-Scholes and you find our old friend, the Gaussian distribution, assuming that extreme events are impossible instead of just rather unlikely. The unlikely happens all the time in markets, usually because of human behavioural biases which kick in at extreme moments and lead to sustained overshoots in valuations and liquidity.

Taleb on Black-Scholes

Nicolas Taleb is a vehement critic of Black-Scholes as can be seen in “Why We Have Never Used the Black-Scholes-Merton Option Pricing Formula“:

“Option traders call the formula they use the “Black-Scholes-Merton” formula without being aware that by some irony, of all the possible options formulas that have been produced in the past century, what is called the Black-Scholes-Merton “formula” … is the one the furthest away from what they are using. In fact of the formulas written down in a long history it is the only formula that is fragile to jumps and tail events.”

Taleb profits from the deficiencies of the model by betting that the markets will go mad, eventually. He may lose small amounts of money most of the time but when things go really wrong he makes a huge killing. However, he’s not the only famed investor to look at the inadequacies of the model.

Buffett on Black-Scholes

Just this year Warren Buffett has shown that Black-Scholes can lead to irrational pricing, even during non-extreme conditions, over very long periods. By looking at the effect including volatility has on option valuations he concludes that this leads to stupid outcomes:

“The ridiculous premium that Black-Scholes dictates in my extreme example is caused by the inclusion of volatility in the formula and by the fact that volatility is determined by how much stocks have moved around in some past period of days, months or years. This metric is simply irrelevant in estimating the probability weighted range of values of American business 100 years from now. (Imagine, if you will, getting a quote every day on a farm from a manic-depressive neighbor and then using the volatility calculated from these changing quotes as an important ingredient in an equation that predicts a probability-weighted range of values for the farm a century from now.)”

Buffett’s suggesting a value investing approach to making money from the indiscriminate application of such models – invest over long enough periods to make short-term human irrationality, aka volatility, an irrelevance. Unfortunately most of us don’t have the lifespans to wait the decades he envisages, but maybe there’s yet another way of profiting from irrational option pricing.

Longshot-Favourite Bias versus Black-Scholes

Back in 1947 Richard Griffith showed that there was an irrational behavioural bias being applied to horseracing odds. The favourite-longshot bias states that favourites are consistently underpriced and longshots consistently overpriced. So a 2-1 favourite is more likely to win than its odds suggest and the 100-1 outsider is less likely to win. This finding has been replicated time and again. In fact you wouldn’t need to add much in the way of skill and judgement to make betting on the favourite consistently a winning strategy. Some other researchers have wondered whether the bias also applies to people investing in options.

Options are either “out of the money” – i.e. trading at a level where they won’t make any money if exercised at the moment – or “in the money” – trading at a level where they are currently worth exercising. Buying an option that’s a long way out of the money is the equivalent of betting on a longshot, buying a deep in the money option, a favourite.

Black-Scholes predicts that calls which are further out of the money will provide greater returns, the opposite of what favourite-longshot bias suggests. The limited evidence so far suggests that it’s the bias which drives the price rather than the model. This would be consistent with irrational investors doing irrational things – exactly the conditions under which Black-Scholes might be expected to fail.

It isn’t yet clear that this research amounts to a way of actually making money but it does, at least, add weight to two conclusions. Firstly, before you put your trust in any automated model make sure you understand it. And secondly, always assume that irrational people will find a way of breaking it, no matter how careful you are.


Related articles: Black Swans, Tsunamis and Cardiac Arrests, Alpha and Beta – Beware Gift Bearing Greeks, Risky Bankers Need Swiss Cheese Not VaR

It’s Not Different This Time

The Smoking Cigar of Behavioural Bias

Not all failures of investment logic are based in human psychological flaws but, to paraphrase Freud, although sometimes a cigar is just a cigar mostly it’s behavioural bias. The smoking gun is almost invariably linked to people doing predictably stupid things. Like building shacks on earthquake fault lines, thinking they can banish risk with a spreadsheet and regarding the lessons of history as too remote to be interesting.

Sadly the fact that these things are predictable doesn’t make them any less easy to deal with. Our current set of financial woes is a wonderful test bed for those inclined to point to the short-termist biases inherent in the human conditions. We’d do well to enshrine these lessons in our systems now, because it won’t be long before we’ll start to forget.

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Mandelbrot’s Mad Markets

Haunted By Statistics

As we've wandered down the echoing corridors of behavioural finance we seem to be haunted by a troublesome spectre, which refuses to go away no matter how much we prove to it that it’s a figment of economists’ imaginations. Discovered by Francis Galton, appropriated by Harry Markowitz and embedded in risk management models ever since, our ghoulish apparition is a mathematical construct, the Gaussian distribution, aka the bell curve.

The Gaussian distribution keeps on reappearing throughout economic theories as a rule-of-thumb description of how markets behave. With which there is just the smallest problem – markets don’t behave as it would predict. We’ve known this for over forty years, ever since Benoît Mandelbrot showed that cotton prices bound around in a decidedly peculiar way. Markets behave madly far more often than the standard models predict so why anyone should be surprised that they fail catastrophically every so often is a bit of a mystery, really.

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Pascal’s Wager – For Richer, For Poorer

My Grandmother's Lottery

My grandmother, on being told by a friend that if they won the lottery they wouldn’t know what to do with the money, was affronted: “Don't be stupid”, she said, “I’d spend half going down one side of Main Street and the other half going up the other side”. Unfortunately, in the real world, we need to keep an eye on the both sides of the equation – is it worth taking the chance of becoming rich if the downside means being poor?

Blaise Pascal, in another context, tried to answer this question five hundred years ago. Admittedly, in a sign of our changing times, he was less concerned about his terrestrial wealth than his immortal soul. Nonetheless, his argument – forever encapsulated as “Pascal’s Wager” – can just as effectively be applied to the arguments for and against a balanced investment approach.

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Markowitz’s Portfolio Theory and the Efficient Frontier

Managing Risk

You’d have thought that the management of risk in respect of stockmarket investment would have a long and reputable history. After all, the very idea of a share is all about allowing individuals to spread their capital and risks across multiple, partial investments.

This is not so, stockmarket risk management only really started with Harry Markowitz’s seminal paper Portfolio Selection in 1952. Typically the industry then ignored his ideas for twenty years before belatedly getting around to using them for, well, everything. And then some, leading eventually to the invention of the index tracker.

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Risky Bankers Need Swiss Cheese Not VaR

Financial Risk Management is Too Risky

The failures by banking institutions across the world over the last couple of years would have been remarkable in almost any industry. However, when they’re taking place in institutions that are fundamentally all about risk management, closely overseen by phalanxes of regulators, they’re quite extraordinary. Sadly the banking industry was too focused on profits to remember the basic rule of investment.

If pharmaceutical companies or airlines suffered from the same type of risk management failures as the banks we’d all be dying of aspirin overdoses and ducking for cover as airliners crashed in our back gardens. These other industries have more nuanced models of managing risk, relying on combinations of methods. It’s about time the banks learned about the Swiss Cheese Model of Risk.

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Alpha and Beta – Beware Gift Bearing Greeks

A Land of Giants and Dwarves

Anyone involved in the stockmarket for any length of time will eventually come up against the concepts of Alpha and Beta. The terms are freely bandied about as though they can explain the mysteries of the investing universe without, unfortunately, any corresponding explanation of actually what they are.

The best way to think of Alpha and Beta is to imagine a world populated by an inordinate number of very tall and very short people. Everywhere you go you’re either tripping over them or being stood on and squished. As usual the securities industry has latched onto a useful tool and started to use it in an automated, mindless and value destroying way. Of course, the value being destroyed isn’t theirs, it’s ours.

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