The E in Risk

Over the years I have tended to rail against people who claim to be risk managers but in truth are only risk measurers. This causes great problems, as whilst examining past data (data are always in the past) is very important, it poses a trap if we fail to follow through to the true risk management piece. As humans we love “solutions” so a nicely crafted statistical model with loads of data can give a false sense of control and security. The risk management piece should be to carefully question the assumptions in any model, be open to a wide range of outcomes and scenarios, and to be willing to re-examine past mistakes in the model.

The re-examination part is important, with the exception of very predictable past data sets (for example, tide tables or sunrises) pretty much everything in the future, in varying degrees, will be different to the past. Models tend to point us towards a static snapshot rather than being flexible enough to account for dynamic changes. The risk management role is to take all of this into account and as the old maxim goes “questions are often more important than answers”.

All well and good you may say, but we are still focusing mainly on the past, driving via the rear view mirror rather than peering ahead through the windscreen. This brings us to the third element that is often ignored or given too little time, the importance of risk identification. The very best risk managers are on top of the first two parts just mentioned and devote a significant amount of time and resources to the identification piece. There are a variety of techniques, scenario planning being one of the most common. Additionally, many try “horizon scanning” or searching for “faint signals” all of which makes sense.

We are all however up against a particularly difficult issue – that of Emergence. How do things start to appear or indeed seem to suddenly smash us right in the face from nowhere? Needless to say there is no nice neat answer, let alone the constantly sought “solution”. Emergence is a key component in Complexity Science and in broad terms can be defined as when an entity is observed to have properties its parts do not have on their own, properties or behaviours that emerge only when the parts interact in a wider whole.  This can be from the relatively simple, of say traffic jams or birds flocking, through to trying understand what is a living being or system. This may all seem arcane for the hard pressed risk manager, but we can draw some broad conclusions and guidelines.

In this third stage of risk identification, we must remain aware that financial markets are dynamic and frequently unpredictable. Your model can trap you into generating a series of constrained snapshots that do not allow for sudden or unexpected changes. Be aware of unlikely or unusual relationships emerging in markets – the killer one is often new patterns of liquidity and volatility. that seem well outside the norms.

A key component of Emergence is that it doesn’t obey nice linear patterns, so that using normal tools is often of no use or even downright misleading. Power laws seem to frequently drive such complicated relationships and are often referred to as scale free networks. A feature of such is the likelihood of clustering in these networks and the potential for the cascading of risks, previously uncorrelated risks that start to work closely together. The classic financial example is that when markets crash previously uncorrelated asset classes suddenly become joined at the hip. A good example of this was the initial fall in in the price of gold at the time of the LTCM crisis in 1998.

The whole topic of risk identification and in particular Emergence is now a vital part of risk management. Here are some books that look at the issues and explain Complexity and Emergence in straightforward terms:

Critical Mass – How one thing leads to another
By Philip Ball 2005

The Origin Of Wealth: Evolution, Complexity, and the Radical Remaking of Economics
By Eric Beinhocker 2007

More Than You Know: Finding Financial Wisdom In Unconventional Places
By Michael Mauboussin 2009

Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It
by Erica Thompson 2022

My Investment Philosophy

In my book Financial Speculation I concluded with this final round of my thoughts and approach to investment.

I think these stand, and will continue to stand, the test of time.

Yeah I know….but

In this concluding section I want to restate some of the major themes of this book. Firstly and most importantly finance is simple but not easy. There is a fashion these days to believe that finance is complicated and wrapped up in complex maths and arcane terminology. This need not be the case; the basics of finance are simplicity itself. The whole business can be seen in terms of three basic actions; buying or selling, borrowing or lending, and executing the transaction now or at a future date. The idea that much of financial activity is based on accruals and annuities; and the fact that financial risk can easily be understood in terms of four simple graphs should not be forgotten.

The hard part of course, is in the doing or the execution of financial business. The vagaries of the inner self, the imponderables caused by time, the nature of volatility, all conspire to make financial speculation a difficult endeavour. On top of this the megaphone advice, research and sales patter that engulf us all is extremely difficult to survive. Experts, gurus, and pundits have an answer for everything and an instant view about the future for every likely paying customer. To be able to shut yourself off from these sirens is perhaps the hardest part of the business.

We also live an age that worships information technology, the computer and the ability to communicate globally on a very cheap basis. All very worthy achievements, but secondary to the business of speculation and finance. The market is not primarily about technology, it is not just about software packages and the latest developments in global bandwidth; it is still a business about judgement and skill.

History is another overlooked area within financial markets; in the manic atmosphere of always wanting to know what’s next, we are in danger of forgetting the bigger picture. In finance there truly is nothing new under the sun; of course markets have got more sophisticated, the pricing of risk has probably become more accurate, and trading volumes and activity have exploded in the last twenty five years. But the basic themes and underlying cycles are still in place; their amplitude and frequency may change but the core characteristics still hold true. Much money can be made by studying long term relationships and understanding the linkages between various asset classes. The prevailing orthodoxy that markets should be analysed and traded in narrow vertical sectors is myopic and stupid.

Magic solutions don’t exist, econometric models, technical analysis, high frequency data analysis, genetic algorithms, kernel regression systems et al; none of them will give you the perfect answer. They may be right some of the time, but we must remember that markets are dynamic not static. By this we don’t just mean the prices move constantly, but that the characteristics and emotions of a market are in constant flux; it’s virtually impossible that a static system can capture all of this activity on a consistent on going basis. Flexibility is a key attribute in investment, and systems by definition are usually too rigid.

Performance claims by others must be viewed with a particularly critical eye; ignore the marketing drivel about fund manager’s league tables, industry award and surveys, and out performing pointless benchmarks. The only test is how much money, you or your investment manager made. Is it consistent? Is it sustainable? Does the manager understand the market or have they just been lucky in a bull market? Much is made of transparency in today’s markets but the case for clearer and more accurate investment information still remains unanswered.

Perhaps one of the best ways forward is in the realm of behavioural finance. This has grown in popularity in recent years as more research has been done into the decision making processes of market participants, and on trying to understand their motives and rationale for their actions. It may be a cliché but understanding ourselves may in fact be more important than understanding the markets. How we act under pressure is perhaps more vital than trying to predict any sudden move or surprise. Learning to control ourselves is much more attainable than trying to learn how to control markets.

Because we are all different in our approach and our capacity for risk we will find that different ideas and angles suit us best in trading; that is why it is pointless to get hung up on one idea that seems to work for someone else.

Costs are, as we have seen, another overlooked but dangerously toxic area. The costs of constantly trading can be vast; in trading, less is often more. Rushing around like a madman constantly trading is stupid, your broker will love you, but your bank manager maybe very concerned. So called ‘small’ costs such as brokerage, spread and the hidden factor of slippage are potentially fatal, only the greenest of newcomers fail to understand this. Also losses are natural, it is hard to say that we should welcome them, but we have to get used to them; they are constant visitors in this world.

Finally remember that speculation and investment is about understanding the difference between price and value. Fashions come and go; pet theories, big market names and high finance ideas ebb and flow; but correctly understanding the relationships between price and value remains the key. Every investor or speculator has to find that out for themselves; and for many of us it remains a hard battle. Don’t believe anyone who says it is easy – they are misleading you. As I said earlier it’s simple to understand but not easy to do.

I will leave the very last comment to that titan amongst American bankers J.P. Morgan who when buttonholed by an anxious journalist outside the New York Stock Exchange during a period of anxiety was asked what the market would do next. Morgan fixed the journalist with a calm stare and coolly replied “Fluctuate!”

Money, Martingales and Pyramids

This is an extract from my book Financial Speculation and looks at the tortuous topic of money management in an investment portfolio.

No definitive right answers of course!

“There are three main elements to a successful investment; direction, timing and money management. Each of these is progressively more difficult to master. Many market players (though not usually the most successful) seem to think that correctly anticipating market direction is the key to success; in fact it’s a relatively small part of the trading experience. Undoubtedly timing is important, but again not as vital as one may at first believe. But by far and away the most important element in trading is money management. One can be excellent at direction and timing, but if you fail to follow prudent money management rules you will come unstuck. Equally, and this may seem somewhat perverse, one can be relatively poor at direction and timing but disciplined money management rules will at least reduce your problems and may even keep you profitable.

Needless to say money management and risk rules area very personal decision; we all have different ideas of acceptable risk. As we have seen earlier, the dangers of rationalising away losses can be fatal, and so strict adherence to any rules is important. This can be far harder than one may imagine – it is one thing to have rules, and quite another to follow them. Institutions also have money management regimes, with VaR type structures, but these tend to concentrate only on potential losses; ideally a comprehensive money management regime should also address the profits side of the equation.

Most money management is plain commonsense, and is about creating a realistic structure that you can and will strictly follow. The first basic step is usually to divide your trading capital into a number of equal amounts with which to trade – ten is usually thought to be a sensible number. With this you never commit more than 10% of your capital to any single trade. Many speculators play in geared markets (so-called margin trading or via futures contracts) and here any gearing or leverage of more than five times your initial capital is courting disaster (Remember at this level your P&L account is effectively moving at five times as fast as the underlying market). In fact it may be more prudent to limit one’s gearing to no more than three times.

So for an account size of US$100,000 three times gearing gives a total exposure of US$300,000 with no more than US$30,000 committed to any single trade. When you trade, one of two things can happen; you either make money or lose it. Either of these outcomes causes a dilemma; is it right to keep the same trading size, or increase or decrease it?

Starting with losses there is a school of thought that says you should increase your stake after a loss, in an effort to re-coup the previous set-back. This has echoes of a well known gambling strategy called a Martingale; this involves doubling your stake on each successive bet, and is particularly popular amongst roulette players betting on a colour or on the odd or even series. This strategy is superficially attractive, but of course assumes the gambler has an extremely large amount of betting capital. To restrict such strategies, casinos habitually impose table limits that prevent gamblers with very deep pockets from constantly doubling up. Some investors have tried similar tactics to recoup trading losses, but this strategy has the horrific quality that you double your gearing on a reduced capital base. As such it makes no sense at all, and increases your exposures at alarming and probably unsustainable rate.

On a more positive note, what about the more pleasing problem of how should we react after a string of wins? Some would argue that we should increase the investment size (after all each trade is now a smaller proportion of the increased capital pot); though there is a counter-argument that says after a run of successes you should in fact reduce your activity as it is likely that losses will be bound to be coming your way. The problem with the first idea is that of course you have chosen to gear up after your wins, and so any subsequent loss will be correspondingly greater. Equally not increasing you deal size means you are no longer keeping each trade at the same proportion of your capital, and arguably are not maximising your profit potential.

My preference in both the case of losses and profits (I put losses first just to reinforce the dismal fact that losses are a constant part of the investment scene, and so we should accord them due prominence) is to only re-adjust the trade size once a year. Admittedly, if during the year you experience a string of losses, your bets are getting proportionately bigger (because of the reduced capital base) but at a far lower rate than actually increasing their size. Equally in a period of success, you are now effectively ‘under investing’ but that may be prudent after a string of winners. All of this is of course rather subjective and depends on the scale of your winners and losers – an alternative idea instead of the annual review is to re-base your deal sizes every time your capital base increases or decreases by a fixed amount or percentage.

These issues whilst simple hide quite a degree of complexity. Apart from closed out winning and losing trades, some investors choose to adjust the deal size whilst still in the trade. The most common strategy here is called the pyramid or reverse pyramid trade. Here investors refine their trade rules by sub-dividing the individual capital amounts per trade. For example going back to our original figure of US$30,000 per trade, they then divide that into three amounts of say US$15,000, US$10,000 and US$5,000. The idea being that they commit half of the allocated capital at the initiation of the trade and then feed the other two amounts into the market at the appropriate time. Then when closing the position they sell the entire amount in one go. This sounds a good idea, in that you are buying into a rising market and you will achieve an attractive average ‘in-rate’. However, of course, in practice it’s extremely difficult to execute, what for example are the ‘appropriate’ levels to add the second and third portions?

The reverse pyramid idea merely reverses this idea, suggesting that you should commit only a small proportion (say US$5,000) in the initial part of the trade, so that if it goes wrong early on, you have only committed a small part of your capital. If the market does continue to go your way you can of course add the other two larger lumps. The obvious problem here of course is that the average in-rate of the trade is pretty poor, and you may have effectively put the trade on too late or at an unfavourable overall rate.

On balance I think pyramiding and its various derivations should be avoided, it adds a number of subtle complexities to what is already a complicated decision process. It may also sow all sorts of seeds of indiscipline regarding actually cutting loss making positions.

As I said earlier money management is an extremely personal and subjective topic – I find that the best rules are clear and simple; and that you must discipline yourselves to follow them. There are a large number of books on the topic that often have a strong statistical bias and attempt to discuss optimum solutions; that is all fine and well but at the end of the day its your discipline that counts not just the most elegant mathematical solution. It’s likely you will find simple rules the easiest to execute, so stick with them

To summarise then, I find dividing my capital in to ten portions, keeping my gearing low and reviewing my rules annually a happy medium. One final tip – keep a trade diary recording all the details of the trade, the simple act of writing down your investment strategies seems to help keep focus.”

What I talk about these days

As the world of live gatherings is at last recovering and gathering pace (Not least because I sense people are bored rigid with Zoom calls etc) I thought I would outline the current speaking topics that I’m doing.

I continue to do a variety of talks on the differences between Risk and Uncertainty, and allied to this the dangers of relying only on past “Big” data. I look at why models fail, and always will. The dangers of seeing Risk as a bounded game with fixed rules that can be “won”. I particularly dislike the Life is Chess/Poker fallacy – nothing could be further from the truth.

I also talk about what I called the E’s of decision making and risk taking; namely punctuated Equilibrium, Emergence and Entanglement. All of these are rooted in Complexity science and Evolutionary theory. Business is not a machine but an organism, and I try to give real life examples of all these elements.

One other area I’m very interested in is innovation and creativity. The standard business models of Command and Control and a fanatical desire to “control costs” are the enemies of new ideas, products and services. I try to explain how outward looking and enquiring business models are the only proven way to grow businesses and generate wealth.

As well as speaking a great deal on these topics, I should really try and write this blog more frequently – but don’t hold your breath (Speaking is now once again swallowing a lot of my time)

Two Speed World – Physics and Business

In 2010 Terry Lloyd and I wrote a book called Two Speed World in which we set out to examine the two modes of change….incremental and disruptive, in the world of business and finance

A recent article here looks at the issues from a physics standpoint.

In particular I was struck by this opening paragraph in the article (which is well worth reading)

“In The Structure of Scientific Revolutions, the philosopher of science Thomas Kuhn observed that scientists spend long periods taking small steps. They pose and solve puzzles while collectively interpreting all data within a fixed worldview or theoretical framework, which Kuhn called a paradigm. Sooner or later, though, facts crop up that clash with the reigning paradigm. Crisis ensues. The scientists wring their hands, reexamine their assumptions and eventually make a revolutionary shift to a new paradigm, a radically different and truer understanding of nature. Then incremental progress resumes.”

Book Recommendations From the Podcast

At the end of each episode of the Ross & Ashley podcast we offer book recommendations

Here is a summary after our first three episodes

The Silk Roads by Peter Frankopan

Algorithms to Live By by Brian Christian & Tom Griffiths

Why Most Things Fail by Paul Omrerod

Raven Rock The Story of the U.S. Government’s Secret Plan to Save Itself – While the Rest of Us Die by Garrett Graff

Driving the Silk Road: Halfway Across the World in a Bentley S1 by Doug McWilliams

Checkmate in Berlin: The Cold War Showdown That Shaped the Modern World by Giles Milton

Prisoners of Geography: Ten Maps That Tell You Everything You Need To Know About Global Politics by Tim Marshall

Nathaniel’s Nutmeg: Or, the True and Incredible Adventures of the Spice Trader Who Changed the Course of History by Giles Milton

For more information about our Podcasts go to Brigadoon Radio listings at