Monday, 18 August 2014

Misbehaving supermodels: She ain't so pretty after all

“Beauty is a form of Genius--is higher, indeed, than Genius, as it needs no explanation…It cannot be questioned. It has divine right of sovereignty. It makes princes of those who have it.” - Oscar Wilde. 

One does not usually associate supermodels with those in the risk management profession.  While the term ‘models and bottles’ has long been associated with high-flying investment bankers, their middle-office brethren, the risk managers, have always played the nagging house-wife to the bread-winners of high finance.  Yet those in the middle office, while far removed from the limelight of the catwalk, have taken to supermodels of a different kind; models whose beauty is defined by mathematically elegant expressions of risk.



The financial supermodels of risk managers are numerous, and their creators often achieve a form of celebrity status amongst fellow academics and industry practitioners.  Markowitz’s Modern Portfolio Theory, the ensuing Capital Asset Pricing Model and the Black-Scholes-Merton Options Pricing model are all prime examples where the model’s creators were deemed (perhaps foolishly?) worthy of Nobel Prizes.  A notable exception to this honour-roll, however, is the widely used (and Basel regulated) Value at Risk (VaR) metric.

Perhaps because of its practical development from within industry, as opposed to the white-glove environment of academia, VaR is seen as more of an every-day risk management tool, rather than a feat of ground-breaking intellectual rigor.  Essentially, it summarises risk to a single number; the dollar amount of mark-to-market losses on a portfolio that should not be exceeded within a certain time frame at certain high level of confidence.  But it is this supposedly simple nature of VaR, combined with the exposure of risk managers to it every day, which makes this unassuming supermodel potentially the most dangerous.

Nassim Taleb, author of Fooled by Randomness (2001) and The Black Swan (2007), has been one of the fiercest critics of VaR as a risk management tool.  One of Taleb’s primary criticisms is that models of uncertainty are too precise, given the condensation of complex factors necessary to produce a single-figure risk measure for a large portfolio.  He argues that such undue precision enables investors and managers to be lulled into a false sense of security, breeding contempt for risk and a false sense of control.

Yves Smith is similarly scathing of VaR as an effective risk management tool in her book Econned (2010).  Aside from arguing that the degree of abstraction necessary for the production of a VaR discards important information about the behaviour of the underlying systems, she directly devalues what a VaR estimate is really worth.  By adopting confidence levels of 95-99%, which are relatively good at predicting day-to-day risk, she argues that VaR does not focus on what is really important to risk managers, namely what lies in the remaining 1-5% of the loss tails.

Indeed, VaR is silent with regard to what lies beyond the chosen confidence level, and this silence can prove deadly.  Hull (2012), details how undesirable risk-taking can be inadvertently encouraged when VaR is used to try and limit the risks taken by a trader.  In essence, traders who like taking high risks in the hope of realising high returns (and fat bonuses) are able to structure trades that satisfy VaR limits imposed by a bank while simultaneously exposing the bank to massive losses in the silent tail, utilising a return distribution that is anything but normal.

Defenders of VaR, such as industry practitioners and authors Eric Falkenstein and Suna Reyent, point to more recent methods of estimating the tail risks, such as Extreme Value Theory, Expected Shortfall and Conditional VaR.  Importantly, they note that most firms don’t rely solely on VaR, but supplement this measure with other methods such as stress-testing and Monte Carlo simulation.  Yet detractors such as Smith and Taleb argue that all of these approaches send broadly similar signals, and do nothing much to solve the problem of reliance on historical data.

The very nature of historically-based volatility estimation methods upon which VaR is based, such as GARCH modelling, certainly seem to imply the adoption of pro-cyclical capital policies by financial institutions.  By encouraging banks to hold less capital in good times and dictating they hold more capital in times of market turbulence, they encourage build-ups of leverage followed by a rush to the exits and the freezing of credit markets.

Sadly, given the cut-throat nature of the global capital markets, management’s hands are often effectively tied when deciding which risk metrics to push.  It doesn’t take much imagination to envision competitive pressures forcing the hand of management to adopt capital-light risk metrics during times of low volatility, of which Basel regulated VaR classifies as a prime candidate (the upcoming Basel III is an attempt to rectify this).  While the risk managers may have their stress-tests and methods for estimating tail risks, anecdotal evidence from the GFC overwhelmingly points to the sacrifice of long-term risk management on the altar of next quarter’s results; the nagging wife losing out again to the breadwinner of the household.

This race to the bottom of minimally regulated capital requirements in order to remain competitive and satisfy shareholders has the effect of focusing the attention of risk management on the numbers.  Similarly, where profitable risk-taking by utilising high levels of leverage can be justified by focusing on the numbers and ‘black boxes’, as with Long Term Capital Management and other so called ‘scientific’ hedge funds, the focus inevitably remains on the justifiable metrics, rather the nature of the assets under management.

This approach is diametrically at odds with the value-based investment strategy of arguably the world’s most successful investor, Warren Buffett (a long time critic of VaR and Modern Portfolio Theory).  Rather than focusing on statistically definitive volatility as a measure of risk, Buffett’s value investment approach relies instead on a hard-headed analysis of an investment’s prospects rather than its price movements.  Unfortunately, these types of business judgements and valuation skills are not easily taught, and are ugly and vague when compared to mathematically beautiful models and claims of scientific justification.

Thus, while VaR and other quantitative risk measures are known to have significant shortfalls, management seeking justification for myopic risk taking and regulators seeking a hard, enforceable rule, are seemingly destined to focus on the simplified, backwards-looking numbers, which are worth almost nothing when it comes to estimating anything other than day-to-day risks; the very risks which least require sophisticated risk-estimation tools.

Although the beauty of risk management’s supermodels may indeed have divine sovereignty, to quote once again Oscar Wilde, “The truth is rarely pure and never simple.”  While Basel lll may prevent history from repeating, continued reliance on supermodels like VaR will make sure it rhymes.

Friday, 15 August 2014

Problems of the Rich & Famous

Being rich and/or famous has its own unique set of problems, as The Spear recently saw first-hand.

As The Spear drove along his street this morning, he looked in his rear view mirror to spy none other than the car of the richest household in the neighbourhood (if the sizes of mansions are any indication).   Easily identifiable by its custom plates, the convertible Mercedes Benz was being driven by the jewel-burden woman of the household with one of her old-money friends for company in the passenger seat, and a brand new Persian rug poking up in a roll from the back. 

There was only one problem with this image of sundry wealth: it was pouring rain.  The size of the Persian rug had prevented the duo from raising the hood on their convertible, leaving the pair as drenched as the Merc’s leather upholstery.

The Spear remained dry in his second-hand Mazda.

While most people seem to like the idea of being rich and famous, this may be because they have never been exposed to the problems which only the rich and famous are subject to.  People may question how someone as famous and successful as Robin Williams could consider taking their own life, but the reality is these most of these people could never know just what problems that level of success can bring.

Sunday, 27 July 2014

The Opportunity Cost of Talent

There is an implicit cost that comes with the possession of talent of one sort or another: the inability to use that talent for more than one thing at a time.

The notion of Opportunity Cost, widely used throughout the world of economics and finance, is defined by Investopedia as:

The cost of an alternative that must be forgone in order to pursue a certain action. Put another way, the benefits you could have received by taking an alternative action.

In the realm of capital budgeting - which is a largely analogous to how a person decides which projects they will undertake - the opportunity cost, otherwise termed the ‘discount rate’, is the term on the denominator of the equation of the present value of the project.  Thus, the higher the discount rate (opportunity cost), the lower the value any particular future benefits from the project become.

A relatively talented individual under normal circumstances is often confronted with a relatively good set of options, or potential projects.  For instance, those who score highest in their tertiary entrance exams will be able to choose from any course in any university.  Likewise, very good looking people are generally inundated with a plethora of potential suitors.

Therein arises the problem of the relatively talented.  Because they are faced with a multitude of options, deciding which option is best becomes a hard task.  When the opportunity cost of any action is so high, the relative value of one seemingly good option over another becomes marginal, and given the number of variables usually in play, it is hard to determine which course of action is actually best.

Imagine a genius like Leonardo da Vinci.  If he were alive today, he probably would have been sent to a special school for the especially gifted, and put on the fast track to the inevitable PhD in mathematics.  Would he have been happy with that?  Seeing as left to his own devices he ended up a painter, sculptor, architect, musician, mathematician, engineer, inventor, anatomist, geologist, cartographerbotanist, and writer, it is plausible that he would have felt some angst over his wide-ranging talents within being so narrowly applied.

He doesn't look too happy

For the relatively untalented, the path of action is normally much more straightforward.  As with increasing the relative returns on a project by reducing the discount rate, those with a low opportunity cost often know when they are presented with a good deal: a well-paid job v minimum wage/unemployment, a trip abroad v no holiday at all, anybody v isolation.  Beggars can’t be choosers.

So, if instead of taking what you can get, you find yourself asking if you’re getting all you can take, welcome, friend of The Spear, to the land of the relatively talented.

Monday, 14 July 2014

Specifying Specificity

Once upon a time The Spear wrote specifications as part of his job.  What he quickly came to realise, without really giving it much thought, was that there were essentially two very different ways of specifying requirements, each with their own strengths and weaknesses.  We use both every day.

The first is an outcome-based, or ‘top-down’ specification.  It focuses on what is trying to be achieved, without giving much detail as to how it is to be achieved.  For instance, ‘the shirt must be cleaned,’ is a form of top down specification. 

Outcome based specifications are often used when the specifier is short on time or technical expertise, where the process used to achieve the outcome is not deemed to be critical.  They are a kind of ‘catch-all’ that cannot fail to capture the want. 

Due to the often qualitative nature of the fulfillment of top down specifications (all projects must be accepted at some stage by a human being who gives the ‘OK’), it is typical that such a specification comes with a qualitative acceptance clause such as ‘to the satisfaction of X’.  Contractors and those seeking to satisfy specs hate this ambiguity as it is hard to quantify (i.e. cost).

Their lack of detail gives the person receiving the specification leeway to satisfy the want as they see best.  While this can be a way of efficiently performing the task, it may however introduce unwanted, unspecified side effects.  A shirt may be cleaned, but it may be wrinkled in the process.  It has positively fulfilled a specification which failed to detail undesirable negatives.  As there are infinitely more things that the specifier does not want to happen to the shirt, it is impossible to capture them all in a general top-down specification.

This hunt for exactness leads to process-based, or ‘bottom-up’ specifications.  After stating that only the specification as it is detailed it to be followed, a bottom-up spec aims to detail, item by item, step by step, the process of creating the final output in as much detail as possible.  For example, ‘a shirt consisting of type A white, intertwined cotton fibres of 1.2 microns in diameter, sanitised for 35 minutes in 18L of grade 315 bleach at 66 degrees celcius in an air-tight chamber’ is a bottom-up spec.

These detailed specs are used when the writer has technical expertise in the area of specification and where the process requires a high degree of control, such as in an experiment or high-end manufacturing.  So, whereas a top-down spec may be made by an end-user, a bottom-up spec is more likely to be written by a third-party specialist. 

While infinite detail is impossible to achieve, small ‘catch-alls’ are embedded in the main specification to try and tie up any loose ends, such as ‘to manufacturer’s specifications’ or ‘to the principles of X’, in the effort to at least provide direction to those seeking more information as to how to fulfill the finest details of the spec.

While bottom-up specs are great for the person trying to fulfill the spec because their satisfaction of the spec is mostly free from ambiguity, their very rigidity may prevent the satisfaction of the desired outcome in the most efficient way, or even at all.

If a bottom-up specifier does not know what they are doing, or is not up with the latest developments in the field, a detailed specification may be nothing but a very length recipe for disaster, or the loss of a lot of money.

This is why The Spear, when making his own professional specifications, tended to cover his arse with top-down specifications in any instances where he doubts his own ability to adequately bottom-up specify on a subject.  While generally specifying detail, he would use outcome-based catch-alls wherever he thought the risk of mis-specification was too great.

He wants his shirt to be machine washed with warm water with standard detergent, to his satisfaction.

Tuesday, 1 July 2014

10 Signs You’re Watching Too Much Soccer


1.          You have taken to interviewing candidates via round robbin.
2.          When wronged by a mate, you demand a free kick.
3.          You run around like an aeroplane every time you successfully throw rubbish into a trash can.
4.          You have taken to biting your adversaries.
5.          You have tried to make it through an entire day using nothing but your head and your feet.
6.          You demand your innocence/guilt be settled via penalty shootout.
7.          You dare not pass a queue, lest you are called ‘offside’.
8.          You microwave your meals for an extra three minutes of ‘injury time’.
9.          You operate on ‘Brazil time’.
10.      You by instinct fall to the ground, writhing in agony whenever someone bumps into you.

Saturday, 7 June 2014

Feeling Like a Fraud

Do you ever get that feeling that you are necessarily unqualified for whatever it is that you do?

You may be new to the task or a veritable veteran, yet no matter how many tests you pass or how many years of experience you have, you can’t shake the feeling that you don’t really know what you are doing and that you are continually on the cusp of career-ending failure and exposure as a fraud?

If so, The Spear shares your pain.



Self doubt in this form of ‘impostor syndrome’ is reportedly most often felt by high-achievers; those very people who should have the least reason to feel inadequate.

The Spear has read that graduate students and those at the crossroads in their professional development can be especially susceptible to the feeling, which may explain why The Spear - on the precipice of a possible career change - has been feeling especially fraudulent in recent times, despite all evidence to the contrary.

Thinking back, there is the chance that this feeling has been dwelling in The Spear for some time.

For years he has wondered why his eyes seemed to water slightly when he is given a new task at work.  Perhaps it’s that he’s given tasks at the start of the day when his eyes are still tired, or perhaps it is the act of concentrating on what someone is saying, or as a result of the air conditioning in his office, or maybe, just maybe, it is his inner child welling up at the possibility of impending failure and ensuant exposure and ridicule?  He honestly doesn’t know.

Bertrand Russell said, “The trouble with the world is that the stupid are cocksure and the intelligent are full of doubt."  In a reversal of blissful ignorance, it appears to be the case that the more intelligent you are, the more aware you become of all the things you don’t know, i.e. where some people are too stupid to even know that they are stupid, people suffering from impostor syndrome are usually too intelligent to believe that, while they may not be perfect, they are still relatively talented.

We should be able to take some comfort in this state of affairs, friends of The Spear, for while self-doubt may not be an indicator of intelligence, an aversion for cocksurity removes all possibility of ignorant idiocy.