The impact of the Covid-19 pandemic upended markets, at least temporarily, in 2020. While broad indices have bounced back sharply there remain huge divergencies between the winners and losers. It has been a stark reminder that financial markets do not follow neat rules and their characteristics are not stable. Why should they be, when they reflect the interactions of people framed by the ever shifting social and institution context of today? We believe the pandemic is a timely reminder of how a truly long-term investor should be looking at risk and about how recently we may all have been looking in the wrong place.

Back in the 1920s and 30s, John Maynard Keynes at Cambridge and Frank Knight at the University of Chicago were both writing about the difference between statistical risk (think standard deviation around a mean) and uncertainty – that there are things we just cannot predict or model. Knight criticised what he called: “The near pre-emption of economics by people who take a view which seems to me untenable, and in fact shallow, namely the transfer into the human sciences of the concepts and products of the sciences of nature.” By which he meant the use of simplistic static models of objectives and preferences to reflect human behaviour and therefore the characteristics of asset classes.

And Keynes wrote in 1937: “By uncertain knowledge…I do not mean merely to distinguish what is known for certain from what is only probable…The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the rate of interest twenty years hence, or the obsolescence of a new invention…About these matters, there is no scientific basis on which to form any calculable probability whatever.”

But Keynes and Knight’s thinking was superseded in the post-war period by a belief in models and quantification that became the dominant narrative in both economics and finance. In this neoclassical narrative the economy tends inexorably toward an optimal equilibrium point. In the investment world this led to the belief in optimal portfolios where risk is simply what you used in mean-variance optimisation ie annualised standard deviation of returns – or volatility. It’s a framework that sees risk as something akin to the probability of throwing two sixes with fair dice; something very controllable and calculable.

More recently, critics have challenged this framework. In his influential book Black Swan, Nassim Taleb wrote about the importance of extreme events, which the familiar bell-curve of the normal distribution says are exceptionally unlikely, but which seem anything but. It is now almost a cliché to quote the unfortunate David Viniar, CFO of Goldman Sachs who wrote of the global financial crisis: “We were seeing 25-standard-deviation events several times a week.” In his typically forthright style, Taleb writes: “The bell curve satisfies the reductionism of the deluded”, which is a fancy but concise way of saying that typical statistical analysis as practiced in the investment business doesn’t capture real world outcomes very well.

But neither the financial crisis nor the Covid-19 pandemic were really black swan events in Taleb’s sense of being left-field events that could not have been predicted. Indeed, as Jeremy Farrar of the Wellcome Trust wrote in a Newsweek article in March 2020: “A pandemic of this magnitude was not only predictable, it was predicted…We called for immediate, forceful and coordinated action. The response was non-existent.”

Does that sound familiar? We could argue the same for climate change or antimicrobial resistance. And if you ask an investment strategist at the beginning of any given year to list the ten risks that might derail the outcome, global pandemic is almost always on there. But we find it hard to deal with these kinds of risks.

Bringing together many of the critiques of modern risk management in one fascinating book, Radical Uncertainty: Decision-making Beyond the Numbers, John Kay and Mervyn King coin the phrase radical uncertainty to describe situations: “When we know something, but not enough to enable us to act with confidence. And that is a situation we all too frequently encounter.”

Perhaps it is precisely this radical uncertainty that truly long-term investors should put at the heart of their approach to risk management. For those long-term investors whose wealth is only valuable as a source of continuous spending (a perpetual foundation or university endowment for example) the concern must be about what will be the return generating potential of the portfolio not just from today but from 20 years or 30 years hence. Not just the portfolio value at a point in time but how it generates the returns that are needed to support spending.

Here we perceive a convergence between sustainability, broadly defined, and plain old long-term investing. We want to be invested, in x years’ time, in a set of assets that are capable of generating at least as much purchasing power as our assets do today. To do so, they will have to be as relevant to society in year x and will have survived the twists and turns of crises, along with social, political and technological changes.

Of course, this has always been the case, but we believe it will be even more so over the next 20-30 years. In a research report we published last year, we argued that a series of sustainability issues had reached a stage whereby they would have significant impact on investment returns and should not be ignored. This is particularly because they are themselves the source of increasing uncertainty. Sustainability issues such as climate change are not cyclical, they are directional; they take us somewhere new, where historical relationships are less useful or even downright misleading.

Thinking with a sustainability mindset is also helpful in encouraging us to think about economies and financial markets as dynamic systems that evolve and change through time, with few, if any fixed constants. Too much of today’s investment risk management takes simplifying theorems and then defines them as laws and applies fixed constants for means, standard deviations and correlations etc. Thinking in systems, by contrast, acknowledges not just that the parameters are constantly changing but also that there can be positive and negative feedback loops, which create big oscillations and tipping points. The big and sudden events that drive markets are often not so much black swans as the results of slowly accumulating pressure and converging trends. Like the moment thousands of tonnes of ice breaks from a glacier and falls into the sea.

While climate change is the elephant in the room of sustainability issues, it is only one potential source of future instability. The world economic system has become increasingly fragile – witness the continuous expansion of debt as well as central bank support for/ manipulation of asset prices – and carbon emissions are not the only trend which cannot be extrapolated without crisis. An economic model that requires ever increasing inequality and a smaller and smaller group of companies making larger and larger profits (in absolute terms and compared to GDP) is similarly not something that can be rationally extrapolated; it is almost mathematically unsustainable. So a prudent investor might anticipate a period of turbulence in coming years, where historical data-driven risk models prove increasingly vulnerable to radical uncertainty.

So what to do about this? Firstly, avoid thinking about risk in too short a term, statistical, sense. If an investment manager comes to you promising to maximise your risk adjusted return ask them what risk? What they are really promising is to maximise returns under one specific set of circumstances. Instead, think of risk as being what threatens your overarching goals – staying in business, having cash to spend, avoiding permanent losses.

You can only maximise returns if you are confident in your model of the future. We have sought to argue that such confidence is unwise. Evolution favours those who survive, so a portfolio that is robust and resilient is preferred over one that tries to maximise or is suited to only one environment. That is course is the perennial argument for diversification – ordinary enough – but it is worth reconsidering in what way your portfolio is truly diversified. A portfolio over-exposed to the UK market, itself heavily exposed to oil, minerals and banks, would have suffered disproportionately during the present Covid-19 crisis for reasons not obvious in advance.

Complex investment strategies are often (though not always) dependent on models and assumptions that may prove casualties of uncertainty. Applying leverage to them only amplifies this risk, in fact significant leverage applied to almost anything reduces its resilience to the unexpected and the ability to hold on. A curious exception seems to be trend following quantitative strategies, which often seem to deliver outsized returns in periods of turbulence (as they did during this year’s sell off) – perhaps because they are constantly adapting rather than anchored to a prior set of beliefs.

At a more granular level, we believe sustainability factors mentioned earlier can be an important tool to reduce lurking risks that have no obvious timing or quantification. Analysing businesses through a sustainability lens brings important fundamental information. Costs imposed on society by anti-social businesses – such as pollution, congestion, exploitation of the vulnerable – are often termed externalities or side-effects in that they do not form part of the economic model of the industry. But as John Sterman, director of the MIT systems dynamics group, tells us: “There are no side-effects, only effects”, and they can come home to roost with unpredictable timing and severity.

Finally, remember that uncertainty has upsides; how can investors be best positioned to benefit as the uncertain future unfolds? Venture capital, properly handled, can offer a diversified investment in the future. Most new ideas fail but those that don’t can offer spectacular gains, sometimes at the expense of established businesses that may already be in your portfolio.

Seeing the economy as a dynamic system rather than a fixed mechanism is fundamental to this view of managing uncertainty so it is appropriate to finish with a quotation from Donella Meadows, environmental scientist and early systems thinker: “Let’s face it, the universe is messy. It is non-linear, turbulent and chaotic. It is dynamic. It spends its time in transient behaviour on its way to somewhere else, not in mathematically neat equilibria. It self-organises and evolves. It creates diversity not uniformity. That’s what makes the world interesting, that’s what makes it beautiful and that’s what makes it work.”

Simon Hallett is head of European endowments & foundations at Cambridge Associates

Charity Finance wishes to thank Cambridge Associates for its support with this article