Major Speaking Themes for 2019

The Over-Connected World
The world is becoming more vulnerable as everything gets more connected. The Internet of Things even allows your phone to control your fridge! However, attacks on networks can flash around the world in seconds.
Are we living in a “Brittle New World” that is prone to sudden catastrophic risks? Can businesses survive an Electronic Hurricane?
What lessons can we learn from Complexity Science?

Evolution & Unpredictability
Evolutionary Biology suggests we are a mistake – the product of chance mutations. Can this offer lessons in risk taking & decision making?
What chance do we have of predicting the future?
Can evolution offer better ideas and ways to think and plan for the future?

The Big Data Dilemma
The current excitement regarding “Big Data” is everywhere – Is this misplaced?
The banks started crunching masses of data in the 90s and then applied sophisticated models for risk that proved disastrous. Is the rest of the commercial world about to make the same mistakes?
Do we risk making poor decisions because of “Model Mania” and misunderstanding the limitations of data?

Maybe it’s the political atmosphere or the still felt aftershocks of the credit crunch from ten years ago – but uncertainty still seems to be the watchword of the day.

Lots of clichés tumble out about the U word. We are told markets can’t stand it, in commerce firms sell solutions and boast how they can eradicate it; and for many religions certainty is their stock in trade, indeed they often promote their priests and prophets as Merchants of Certainty. Uncertainty must be banished if not eliminated.

One aspect of uncertainty that bears closer examination is how it relates to our progress through life and on the career ladder. I must say straightaway I dislike the term ladder, and think most people will find the better metaphor is a maze. We make good and bad decisions, lucky and unlucky turns in our careers and life; it’s not really a ladder we are on, more often happenstance and some stumbling along the way – just like a maze.

But as we post rationalise our previous decisions and actions we smooth out the wrong turns and bumps, attribute good luck to personal ability and try to remove bad luck from our memories. So the comforting image of the ladder redolent with a sure steady path is what we cling to. The now seemingly inevitable ascent is carefully plotted in the career history and our achievements gradually accumulate in neat order.

Now this creates a lovely feeling of control and certainty, almost as if our success was pre-ordained! Interestingly in the early stages of this climb, things are genuinely certain, from our early school days there are timetables and structure, exams and well mapped out decision points; this carries on into university though students tell themselves they are “breaking the rules”.

On entering work, again things are often pretty structured, corporate hierarchies, the demands of company values and mission statements all build the certainty cocoon. But somewhere up this ladder or more likely bumping around in the maze, things change. As we get promoted and take on more responsibility and decision making we find we are exposed to far more uncertainty. The rules based command & control structures don’t work so well in the messy slippery world of big decision making. New markets, new products, new regulations can all contribute to more of the U word.

So all that training in obeying rules and sticking to plans (as opposed to constant planning) can become redundant if not positively wrongheaded. As we climb further up we enter a void. Very different, and often totally new and unfamiliar skills and approaches are now needed, as many of the previous rules and structures fall away. This is a world where difficult questions are more important than simple answers, and are not addressed by past certainties and so called solutions.

It always fascinates me when someone has risen through the ranks of an organisation – they have somehow managed to switch from the certainty environment to the difficult slippery world of the unknown. This is a rare quality.

Wellington put it well when he said “All the business of war, and indeed all the business of life, is to endeavour to find out what you don’t know by what you do; that’s what I called ‘guessing what was at the other side of the hill.’”

Perhaps this an element in The Peter Principle – do we get promoted to the level where the uncertainties start to overwhelm us?

Here are three thinkers I enjoy and can recommend

Dave Trott
Sharp thinking and clear writing from one of the all time greats in advertising.
Blog LinkHere

Mark Blyth
Professor of Political Economy at Brown University.
Essential reading for those interested in what’s really going on behind economic data and politics.
His website
His regular podcast

David Miller
Equity fund manager, 30+ years veteran who writes about the big themes in financial markets.
Latest Blog

I must admit my heart sinks whenever I sit through a presentation that makes great use of slides with pictures of playing cards, chess pieces and pensive players, all used to reinforce the speaker’s message on strategy, or the way forward (sigh!) or the particular business mission they are espousing.

Anyone with an ounce of experience knows that business, risk and indeed life, is not a neatly packaged and defined game. In fact, it’s the exact opposite.

Consider some of the main features of chess; It has defined rules, is played in a totally linear fashion, has only one opponent and has a defined objective. Risk is almost the exact opposite of these conditions; rules are slippery and sometimes incomplete or non-existent, you are frequently up against multiple competitors, and whilst avoiding losses and trying to make worthwhile profits, objectives can change or be driven off course with little or no notice. And perhaps most devastating of all – risk is not linear, it doesn’t move around on nicely defined tramlines, indeed our attempts to build such structures to somehow contain risk is often the cause of huge problems and losses.

So why the game analogy and the players with furrowed brows? Well it’s a comfortable image, somehow we can become the clever player in a difficult game. You need skill and brains – and the presenter sells his ideas that will give you these if you follow his mantra. So yet again we are being sold what we most crave – certainty!

Certainty always sells – it is a desire very close to the human heart and mind. We feel uncomfortable with uncertainty, and to address that we try to build rules and structures we can monitor and measure, and tell ourselves we have a robust risk management regime.

Well up to a point Lord Copper – some areas of risk do lend themselves to such measures, but only if there are deep past data that behave in a predictable fashion in the future. A good example would be tide tables; from massive past data we can predict with a high level of confidence when tomorrows high tide will occur. In this very narrow example the game metaphor works, but in the slippery non-linear world of business risk such models can and do come unstuck.

In The Black Swan Nassim Taleb coined the term Ludic Fallacy to illustrate how misleading it can be to overuse games as a framework with which to consider risk. It is important that use much more agile thinking when tackling risk and uncertainty. It is frequently a world with few neat rules, lacking in past data and no amount of torturing that data will give rock solid certain guidance for the future.

One little rule of thumb I like to use, is to remember “The Map is Not the Territory”. However good your risk model it is always an approximation, an estimate built on assumptions and possibly insufficient data and can be riven with spurious accuracy and curve fitting.

Risk cannot always be solved like a puzzle, it can be more akin to riding a tiger.

Time to drop the Chessmen slides please!

This is an extract from “Two Speed World” which I wrote with Terry Lloyd and looks at the science of storytelling.

The late Professor David Ingvar a Swedish neurobiologist examined the scientific basis for storytelling. He found that a specific area of the brain, the frontal/prefrontal cortex, handled behaviour and knowledge along a timeline and it also handled action plans for future behaviour. Ingvar’s research demonstrated that damage in that area of the brain is found to result in an inability to foresee the consequences of one’s future behaviour. He concluded that the brain is ‘hardwired’ to do this and that plans are created instinctively every moment of our lives; planning for the immediate future, that day, that week and even years ahead. As these plans can be retained and recalled, Ingvar called them ‘memories of the future ‘.
We can illustrate this with a simple example of personal experience which we have all come across. Imagine you are taking up a new interest or perhaps sport, let’s say skiing. Before the new interest our minds had no particular focus or thoughts on the topic – but now suddenly we find there seems to be lots of magazine articles, perhaps special sales offers on ski equipment, and we notice more and more people seem to be talking about skiing! A coincidence or something weird is going on? In fact it’s neither, for as Ingvar’s research demonstrated we are now tuning our minds to potential future pathways and outcomes – in this case skiing. As a result we are building a memory of the future that centres around future skiing trips and adventures.
This activity is crucial – if we don’t open our minds to such pathways and planning we simply will not retain information on a given topic. Our brains are continually bombarded with a vast number of unordered stimuli such as sights, sounds and smells which cannot all be assimilated. All the input the brain receives is compared with previously constructed future memories and if there is no match it is discarded. In other words an unforeseen event cannot be seen. It goes straight over your head, or perhaps more literally doesn’t stick in the brain.
At the group or corporate level where there is obviously more than one brain involved, it is far harder to create a shared library of memories of the future. However the importance of rehearsing all likely possible futures is clearly a powerful tool, and this was recognised in the 1980s by Royal/Dutch Shell who use it as the technical basis for their planning technique of scenarios , as will be discussed later in this chapter.
In Chapter One we recounted the story of the Rainhill trials for the selection of the locomotive for the Liverpool & Manchester railway – curiously there is a coda to this story that fits in with Ingvar’s research. At the opening ceremony of the railway, which was the first in the world to have double tracks, the local Liverpool MP and former cabinet Minister William Huskisson was killed by one of the locos as he had left his carriage and was unaware of another train coming in the opposite direction. It was if he had no previous thoughts or memories of how railways would operate, and so had no intuitive understanding of the risks posed.

Two Speed World – Ashley & Lloyd

From my book Financial Speculation

One aspect of financial losses that is often overlooked is what we may term prospecting risk. Drilling for oil, mining for metals or for that matter producing theatre shows and films all have the same risk profile, and also have some lessons for financial investment.

Typically,prospecting risk has two main characteristics: first, the risk should be spread over a number of ventures, for example a number of theatre shows. This is just normal common sense and simple portfolio diversification, and helps guard against the fact that a high proportion of them are likely to be failures. Indeed in the film industry in any ten
projects it is likely that there will be five or six total failures, three or four that barely cover costs and hopefully one or two big successes (though not necessarily blockbusters) that cover all the costs of all the films plus a healthy profit margin. Second, the timing of where the successful 10% or 20% comes in the run of projects can be vital. This may seem irrelevant, after all if say you have divided your capital up into ten equal portions and allocated it accordingly to say ten drilling projects; it shouldn’t matter whether the pay dirt strike is first or last. True but there is a very large caveat. It is vital that you stick to only using the allocated capital for each project, if you overrun your resources you may run out at, say, drilling attempt number eight, and there is a chance that the big winner would have been number nine or ten. With these types of risks containing your costs is vital, and cost overruns are the nightmare of any mining prospector, movie producer or theatre impresario. The parallel in trading is our trading losses. If we fail to exercise sufficient discipline whilst experiencing losses there will be no chance to stay in the game to catch the big winner.

Unfortunately the world is full of romanticised stories of how down on their luck business heroes conquered all by betting their last cent on the one project. (The early oil prospecting experiences of J. Paul Getty make an interesting read in this respect.) But we only hear of the great successes while the silent majority of failures disappear into the land of losers anonymous. This survivorship bias plagues the investment world.
So the lesson of losses is learn to accept them as a normal part of the investment business, but be ruthless in containing them because if you don’t the market will be ruthless with you

With Christmas and the New Year hoving into view here are four books I have enjoyed and would recommend to read and to give as gifts

Reckoning with Risk: Learning to Live with Uncertainty by Gerd Gigerenzer

What is the Name of This Book? The Riddle of Dracula and Other Logical Puzzles by Raymond M. Smullyan

The Music Instinct: How Music Works and Why We Can’t Do Without It by Philip Ball

Misbehaving: The Making of Behavioural Economics by Richard H Thaler

From my book Financial Speculation

Francis Galton was the epitome of the wealthy upper class Englishman during the Victorian era, a polymath with a high degree of curiosity and a private income, he spent his entire life investigating and researching new ideas. His range of interests was diverse enough to encompass criminology, where he helped pioneer finger-printing techniques, weather patterns, where he devised the classification of cyclonic and anti-cyclonic weather systems; and he even conducted experiments to test the efficacy of prayer – though his results were not very encouraging on that front. And of more direct relevance to our interest in finance he spent a great deal of time looking at statistics and probability.

Whilst looking for ways to enliven his lectures on statistics Galton developed in the mid 1870’s a simple mechanical device he named a quincunx. The apparatus which he first demonstrated at the Royal Institution in London comprised a wooden box with a glass front and a funnel at the top. Metals balls of equal size and weight are dropped via the funnel to fall through a number of rows of pins spaced equally in the box. Each row was offset from the previous row so that the pins sat between the gaps of the row above. These pins then deflect each falling metal ball to the left or right with equal probability and at the bottom of the box each metal ball finished by falling into one of a number of compartments. After a number of metal balls are dropped through this device a pattern in the compartments below starts to emerge. The balls start to describe a binomial distribution which with a large number of rows approximates to our previous curve – the normal distribution.

With this device Galton sought to demonstrate that seemingly random events or facts do in fact tend to arrange themselves into a distribution. So it would appear that the distribution curve we examined earlier is a natural occurrence that appears even when seemingly random events take place. Galton went on to do a large number of experiments that looked to see if in fact distributions did appear in natural life. His researches conclusively proved that they do, and furthermore the outcomes were often quite close to the normal pattern described by the quincunx.

At this point we can depart from Francis Galton but use his ideas and clever box like device to look at financial derivatives. Derivatives have been around since finance began, some claim there is a reference in Aristotle to an option like instrument, and certainly by the Middle Ages very crude option like transactions were being executed. As we saw earlier with the story of Russell Sage, by the second half of the nineteenth century stock options were starting to emerge as a recognised, although specialist and niche, financial market. Of course options really took off with the publication of the Black-Scholes formula in 1973, which for the first time sought to accurately value options. The financial de-regulation of the late 1970’ and early 1980’s really boosted derivative trading and nowadays the global market has expanded massively. It is estimated by the latest (June 2008) Bank for International Settlements report to have an outstanding nominal value in excess of US$680 trillion. This is a truly eye watering number. To give you an idea of just how large – A trillion (being one million millions in modern usage) can be expressed in a number of ways – there are a trillion seconds in 31,710 years!

The Black-Scholes formula was just the start of a series of equations that sought to value and price options, and still remains one of the best known in the business, to calculate it, we need the following inputs:
1. The time to expiry of the instrument
2. The asset price; i.e. the stock, commodity or currency price
3. The strike price
4. The implied volatility of the instrument
5. The so called risk free interest rate – typically the yield on low risk short maturity government securities. E.g. 90 Day Treasury Notes

From these basic inputs we can get an option valuation, but it comes with a number of conditions and caveats, namely:

1. The asset price follows a log normal random walk
2. The risk free interest rate and volatility are known functions of time
3. No transaction costs in hedging portfolio
4. No dividends paid during the life of the option
5. No arbitrage possibilities
6. Continuous trading of underlying asset
7. Underlying asset can be sold short

A number of important problems strike one about these conditions; first and foremost an enormous assumption is being made that the underlying instrument is continuously traded, this of course ignores that most dangerous of foes – lack of liquidity. Secondly in the real world, brokerage, bid offer spreads, slippage (effectively the monetary cost of less than perfect liquidity) and taxes all loom large. In fact as we will see these charges can be quite punishing. So whilst Black-Scholes gives us the first serious approximation for pricing options risk it is hemmed in by a number of limitations. In fact it is probably true to say that it is more important to understand these limitations than to necessarily worry about the underlying maths. Risk assessment is not just about cold equations, the judgements we make about the softer more fuzzy elements of the decision process are often much more important. It is unlikely the maths alone will protect us – we have to know the context in which the result was calculated.

But let us go back to Mr. Galton’s box with its pins and metal balls, as it can produce a useful mental picture with which to consider and understand option pricing. Consider Chart Nine. The position of the funnel represents the current price of the underlying instrument; move it to the left to decrease the price; move it to the right to increase the price. Every row of pins is an increment in time, one day say, and the number of rows represents the time to maturity. The horizontal distance between neighbouring pins represents the volatility; moving the pins further apart increases volatility; moving them together decreases volatility. The figure shows the passage of one ball as it bumps down onto a pin and has to go either right or left, before falling to the next row. This represents the daily price movement of the underlying instrument and the movement of the option by one day towards maturity. At the bottom, the ball will drop into a box. The boxes are divided into two groups by the strike price. The boxes to the left hold winners for owners of put options; the boxes to the right hold winners for owners of call options. In each case, the boxes furthest from the strike price are the most valuable. Increase the strike price and there are more put winner boxes; decrease the strike price and there are more call winner boxes. When we drop a large number of balls, they finish up (expire) in the boxes distributed in the bell shaped curve that we met earlier. For the mathematically inclined, this requires us to deal in logarithms of prices, rather than the prices themselves, but ignoring this does not affect overall picture.

Many aspects of option behaviour can be understood from this model. In the example in the figure, the put option is ‘in the money’, while the call option is ‘out of the money’. You can see that adding more rows of pins (increasing the time to maturity) increases the number of winners that are far from the strike price, so generally increasing the value of the option. Increasing the distance between the pins (raising the volatility) has the same qualitative effect. The model also highlights the arbitrary nature of the underlying assumptions of the Black-Scholes formula. For example, why should all the pins be equi-distant?

Now in a way this is all just a parlour game it’s not meant to be a serious substitute for Black-Scholes or any of the myriad successor mathematical formulae for options and alike; but it does provide us once again with a quite vivid picture of option risk and a broad idea of how prices react in the three dimensional landscape of derivatives risk.

Experienced investors know that that markets are often difficult to read and can be very fickle, also they can be extremely unforgiving if our judgement is not spot on. We also know that humans have a very strong desire for certainty; the research by Abraham Maslow on The Hierarchy of Hygiene factors demonstrates how certainty plays an enormous part in our lives and is an important component of our well-being.

So the investor is faced with two incompatible forces, the inherent uncertainty and instability of the marketplace and a deeply held personal desire for certainty, comfort and predictability. This tension is absolutely central to how we address markets, their volatility and perceived risk. The most common “coping strategy” in such circumstances is to adopt a mode of thinking called The Illusion of Control. By this I mean we seek ways to convince ourselves we are on top of things, and that we can, through superior skill, knowledge and self-assessed ability stay on top of any sudden shocks or volatility. In fact we often fool ourselves into believing that we can start to influence events or at the very least we “knew that was going to happen”.

One tell-tale sign of trouble is that we tend to underestimate the role of chance in human affairs and to wrongly believe games of chance to be games of skill. Many readers will know of the Gambler’s Fallacy and the false hope of the winning streak or hot hand in a game of chance. Here we try to super impose our own internal certainties on to outside events – in this case (gambling) where the game is specifically designed for us to lose money! Surely we know you cannot predict the next in the series of heads or tails – but a long run of say heads can create an overwhelming belief the next time it “must” be tails!

Also we should note that both novices and those who believe themselves expert in a field are all prone to overestimate their own abilities – research shows novices’ ignorance often blinds them to their lack of expertise, and equally galling, the expert in a field is often very unwilling to change their views, even in the face of solid facts!

So what can we do to try and straighten out our investment decision making?

The key lies in two characteristics we need to develop – firstly to acknowledge that we have no special insight when looking at a financial market – we may of course analyse a forgotten corner and therefore have more information than our competitors, but that doesn’t mean that we have an unassailable advantage – maybe just a small edge. That edge can be important but only if we keep strong controls in place on allocation size, develop a sensible stop loss strategy and realistic expectations of profit targets.

Secondly we are all experts at only hearing what we want to hear – the market place is full of information, news, rumours and gossip and we can fall into the trap of cherry picking this to find the facts that suit our position. One way to overcome this maybe to just reduce the overall amount of information we try to read and process – this is really a case of where less is more.

Three Thoughts for Investors
1. Guard against over confidence – this usually shows itself in taking greater and greater risks. Investors should always use strict portfolio management rules. The temptation to think this is “The Big One” can be fatal – fortunes are not make (and kept) by single dead certain investments. Your aim should be to invest in consistent risk adjusted size and to aim to win on a ratio of 2 to 1. In time this would be an extremely successful strategy.

2. Don’t confuse accuracy of information with greater performance. A lot of behavioural research points out that investors get plenty of additional confidence and comfort from more and more information but there is little evidence that it improves the accuracy of their predictions.

3. Most bad investment decisions and behaviour can be really helped by keeping an accurate decision journal – this is a difficult discipline, but writing down one’s reasons for an investment and keeping accurate records of what went right and crucially what went wrong can be a powerful tool in focussing the mind, and reminding ourselves we are not Masters of the Universe!

Even a cursory glance at how financial markets digest information quickly shows that they are erratic, and prone to either over or under reaction. The information process is not smooth and continuous; new facts, opinions, rumour, and news usually enters the market in a haphazard manner, after which the market reacts. This usually happens in a rather jerky and ill-defined way, this is where the information inefficiencies lie; and from these inefficiencies the bright, well informed and, yes once in a while the lucky, can profit.

One way to consider how information hits the market is to imagine a set of balance scales, with the pans holding piles of information; one pan holds any positive information about the market, the other anything negative. News, rumours and plain facts drop constantly into one or other of these pans, leading to an overall balancing position that represents the net emotion and thinking of the market. But there is a twist, our imaginary scales are sticky, so don’t always react straightaway when a new piece of data or information is dropped into one of the pans. Then quite suddenly the scales may shift as the ‘stickiness’ gives way. This is pretty much what happens when markets try to digest news, there is no smooth information flow; at the risk of stating the obvious the trick is to try and anticipate when the scales (i.e. the market realisation) suddenly tip and change.

The news and information is not important in itself, it is market the reaction, or lack of, that is the key. In markets it is often the tiniest movement or change, the lightest of last straws on the camels back if you like, that sets forth the cascading market move.