“He who fears he will suffer already suffers what he fears” Michel de Montaigne

Man does not improve on himself by pretending he is a machine. Accounts of our behaviour that are quantitative and deterministic in nature must always be taken for what they are: useful, but wrong, because incomplete. They deny us a key ingredient which we all know to exist; our minds, and the impact they can have on the physical, manifest world.

Understanding this fact would help re-inject a heathy dose of humility and scepticism into the institutions who profess to be managing our economic affairs, first and foremost the major central banks.

But first it is important to realise the pervasiveness of the intellectual paradigm which sought to equate man with robot, in an attempt to reduce us to a set of causal mechanisms that would help explain our nature and determine our behaviour.

In medicine, for instance, it is only very recently that we’ve started to study with some rigour the impact mental states have on our bodies (see Cure, by Joe Marchant, for a fascinating account of recent research revealing how the brain impacts the body). Prior to that, minds had been relegated to the passenger seat, and effects like placebos were seen as mere tests of treatment ineffectiveness. Today we’re starting to realise they’re in fact key to understanding what the human mind is capable of.

Minds are vexing, because they are hard to understand. In fact, it may well be that the human mind is not sufficiently powerful to understand the human mind. It means humans cannot be studied like inanimate objects, and any economic law that seeks to regiment our behaviour should be taken with a large helping of salt. Alas, t’is not so.

Mindless economics

Nowhere is the confidence in and reliance on mechanistic models more misleading and fraught with danger than in the field of economics.

Simplifications of the way in which the global financial system works are formalised mathematically. They are, like theories in physics, deemed to be universal in character, applying through space (internationally) and through time, and so are extrapolated with confidence and taken to extremes. It is a tendency that Soros calls physics envy, as the economic sciences seek to replicate the same approach, despite dealing with such a different matter.

Just as humans, and their health, cannot be fully understood by denying them minds, so it is that economic systems cannot be fully specified by ignoring that humans are part of the system they seek to explain.

The reason it matters is that policy, impacting each and everyone one of us, is premised on an assumption that there are rules that are reliable and well established.
But does a rate hike always exert downward pressure on economic growth, never mind the starting point? Does an extra quantum of quantitative easing, or purchases of financial assets by the central bank, always boost activity? Central bankers act as though they believe so, but to distort Churchill’s words, however beautiful the model, you should occasionally look at the results.

When challenged to evidence the success of their policies, they show us that the model output without the policy change would have been inferior; the infamous “counterfactual”, which provides no new information as it comes from the very same models used to justify the policy prescription in the first place. It is circular reasoning of the most transparent kind.

A higher premium is put on being precisely wrong than being roughly right, as it helps maintain a veneer of knowledge that is in fact impossible to have, and an authority (they would say credibility) which is mistakenly believed to emanate from the projection of certainty.

Yet the truth is that there may not be – I believe there is not – any such thing as a universal theory when it comes to human behaviour. In fact, a reliable and deterministic model that would tell us our future is not only practically impossible, but logically so. For if such a model could exist, we could at least in theory possess it. And if we did, then the foresight it afforded us would alter our behaviour, rendering the predictions false.

Context matters, as does the belief system of the humans that are engaged with the process. Humans are not mindless automatons, responding to the outside world in predictable way. They are part of the world they react to, and so their psychological states will modify the way they interpret events, thereby leading to different outcomes altogether (see for instance Shiller for an account the importance of narratives in driving economic phenomena).

Under Keynes psychology formed part of economics, and it was only the subsequent mathematisation of the subject which denied us the human mind, and created the need for an outgrowth that refocused on the human element: behavioural economics. A quantitative approach requires measurable inputs, and the mind not meeting this stringent criteria, it was rejected. But as Thaler himself argues, we need the re-unification of economics with mind, not the coexistence of these two approaches running side by side, irreconcilable.

Frailty

For this omission there will be consequences.

Today, we’re in a system that has once again been pumped up with credit because of central bank’s focus on attaining not just price stability, but a level of price growth (inflation) stabilising precisely on an arbitrarily chosen level: generally 2%. Worried about their credibility, and looking at the world only through their mechanistic models, they kept injecting more and more stimulus into economies that needed greater sustainable growth, and not more inflated asset prices or more leverage.

They contributed to a gloomy narrative whereby the future looked bleaker than the past, disincentivising business to invest and incentivising them instead to engage in financial engineering, or the extraction of ‘value’ for shareholders by replacing equity with cheap debt on their balance sheets – a strategy that undermines growth for everyone, themselves included, in the long run.

Though we are seeing a revival of growth and capital investment across economies, we have generated a system that once again presents the frailties that have torn it down time and time again. As Jim Reid from Deutsche Bank shows, ever since the advent of fiat money (or the inconvertible paper money made legal tender by a government decree), booms and busts have become far more frequent. It enables violent cycles of money growth and money contraction, and once again this has been fuelled, instead of dampened, by global central bank activity.

Epilogue

Mind has, to our detriment, been taken out of the equation. Plausible causal mechanisms have been mistaken for reality, and models have been clung to instead of focusing more on the quality of the outcomes.

Worse, this orthodoxy has led to a rejection of the subject by the population at wide. As Joe explains in Cure, “[b]y denying what seems blatantly obvious to many people, that the mind does influence health; that alternative medicines in many cases do work – they contribute to a lack of trust in if not a wilful defiance of, science. If scientists say such remedies are worthless, it just proves how much scientists don’t know”. What, then, of economists?

Mindless methods beget mindless policy. And today we all stand to pay the price, once again.

“To my mind, the three most important principles when it comes to investing are Albert Camus’ principles of ethics: God is dead, life is absurd and there are no rules.” Hugh Hendry

Risk must be taken for rewards, or returns, to be reaped. This is as true in investments as it is in any other of our pursuits. Too much risk, meanwhile, may lead to points of no return, and this is to be avoided. Fine.

Risk limits are relatively well understood and deployed, especially when they are grounded in common sense rules of thumb and avoid the pitfalls of reliance on mathematical models that offer spurious precision and emotional comfort.

But it is within the outer bounds of no risk and too much risk that lies the subtle and nuanced art of risk taking. It is customary in the industry for this art to be commoditised, by classifying assets into risk levels (in proportion with their historical volatility) and deploying them in combinations that seek to match a specific risk profile. But an investor prepared to think for herself can generate a dynamic (as opposed to static) risk stance that will both better match her individual profile and increase her chances of generating greater returns over time.

How is this to be achieved?

I propose that, for every investor at a given point in time, there is a point of indifference along the risk spectrum. Managing risk implies identifying, and balancing on, this indifference point.

Let me illustrate.

If you have 100% of your assets invested in small cap equities, you are hoping for a continued rally in risk assets.

Conversely, if you have 0% of you funds invested, and have all your money in cash, you have everything to benefit from a market crash and nothing from an asset appreciation. You are hoping for a sell off.

(Hope, it should be noted, should have nothing to do with risk management. It reveals a vulnerability, or an imbalance in the starting position).

Somewhere along the risk scale, between the hope for asset appreciation and the hope of a sell off, must lie a point where you are indifferent between both. You have sufficient skin in the game to benefit from the upside, and enough dry powder to deploy in a downturn, by buying cheaper assets opportunistically if they lose value. By balancing on this point of indifference, investors are best positioned to manage their risk calmly and avoid typical behavioural pitfalls.

This approach is malleable, allowing for the point of indifference to vary between different individuals in accordance with their circumstances, objectives and tolerance for adversity. It is also flexible through time, enabling investors to dynamically adjust the risk they take in relation to their understanding of the market ecology (the point in the cycle, or level of valuations) as opposed to being trapped within a pre-determined and static risk profile.

We are often told that diversification is the key to risk management, and it certainly is a major part of it. Managed well, it reduces the volatility of returns without hampering the long term prospects. But in an environment where most assets are expensive relative to their own history, it is important for investors to think about their overall risk stance alongside the quality of the portfolio diversification.

“An accumulation of facts is no more science than a pile of bricks is a house.” Henri Poincaré

I never cease to find amusement in this comment by Russell Napier:

“Every morning across the world, at meetings in investment institutions, talk invariably turns to explaining the market movements of the day before. If we can understand what forces moved markets yesterday, there is a greater chance that we can understand what will move them today. Of course, on many occasions nobody really knows what moved markets on any given day.
Indeed we can say that what moves markets in the long run is invariably nothing to do with what investors think moves them on a daily basis.”

A similar idea is picked up by Philip Tetlock & Dan Gardner in Superforcasters:

“This compulsion to explain arises with clocklike regularity every time a stock market closes and a journalist says something like “The Dow rose ninety-five points today on news that…” A quick check will often reveal that the news that supposedly drove the market came out well after the market had risen”.

They propose it would be more rational for them to state that: “The market rose today for any one of a hundred different reasons, or a mix of them, so no one knows.”

Our subconscious mind is constantly trying to create order out of chaos and it can sometimes lead us astray.

But do we really have no idea what moves the markets? The answer is nuanced.

In most cases, it is quite possible for market participants to understand why, since yesterday, prices have gone up or down. Key headlines will correctly be pointed at as the major market movers, and to deny this seems preposterous.

So if we do know why markets went up or down overnight, why can we not add up the days to create a plausible account of what is moving markets longer term?

The answer is that market moves are not binary! We may know why stocks rose, but not why they rose by 0.5% and not 1%. We may know why the dollar depreciated, but not why is was by 0.3% and not 0.9%. And yet while this information may seem less important on any one particular day, over time it is the amplitude of the moves, and not just their direction, which dictates where markets tend to longer term.

And here is the thing. The amplitude of the market’s daily moves cannot be explained by the news that came out over the past 24 hours. The market’s susceptibility to that news is key, and depends on forces that are far deeper and less apparent. Longer term trends act like giant magnets with invisible forces on market prices, providing a direction that is obfuscated by daily volatility.

This sits uncomfortably with those who see markets as efficient machines that immediately price in all public information. Because the reality is that in many cases, the market is moving in a direction for reasons that no one has yet identified, let alone rationalised (incidentally, once rationalised, it is priced, and too late to position for).

Demystifying the true longer term market movers requires as much imagination as it does analysis and cannot be induced by only looking at the facts (induction is, in fact, a myth, but that will have to wait for a later post). Plausible causal narratives need be imagined and tested; they can’t be extrapolated from the data. This is why there is skill in investment and why humans will remain necessary in the process.

Russell is right that what moves markets in the longer term has nothing to do with what some investors think move them on a daily basis, in so far as they keep appealing to the most recent headline news. The illusion is created by the fact that they understand the direction and fail to recognise that they cannot explain the magnitude, which is what matters in the longer run.

But for those whose gaze shifts from the rear view mirror to the road ahead and who seek to uncover the hidden causal narratives that explain the market’s susceptibilities and vulnerabilities, a better understanding of market drivers is possible.