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Featured AIQ Podcast: Risk and resilience in an age of uncertainty
What does COVID-19 teach us about the nature of risk and uncertainty? Find out more in this episode.
[Sound effects to evoke an old-fashioned tavern: hubbub of voices, clink of glasses, the roll of dice. These effects continue under the narration]
Picture the scene. The year is 1525, and we are in the town of Pavia, near Milan. This is the home of Gerolamo Cardano, a noted Italian doctor.
We find Cardano in his usual night-time haunt: a gambling den. He needs money to support his two layabout sons, but he’s on a losing streak.
[New sound effect: all is quiet apart from a quill pen scribbling in a notebook]
After yet another loss, Cardano returns home and reflects on the nature of luck. He writes a treatise called Book on Games of Chance, in which he uses mathematical formulae to predict the results of dice throws.
Cardano’s book proved to be hugely influential. It was the first systematic attempt to define the laws of probability. Understanding these laws meant people were able to weigh up alternative courses of action, based on the likelihood of success or failure. And this approach revolutionised everything from warfare to wealth allocation, from farming to family planning. We had begun to master the art of risk-taking.
[Clip from BBC News report]
[Italian police announcement] “All residents stay at home”, orders the police. From Naples in the south to the supermarkets of Rome to the financial capital up in Milan, news of the restrictions spread as fast as the virus…
Fast-forward to today, and Italy is slowly recovering from the effects of the coronavirus pandemic. In recent months, Cardano’s name has cropped up in conversations among Pavia’s residents, as they grapple with the implications of the coronavirus. Is it safe to visit family as lockdown eases? When should schools and workplaces reopen? The answers to such questions depend on weighing the odds.
The same is true around the world. The COVID-19 pandemic has made dodging risk the stuff of everyday life. People have been forced to make tough decisions about how best to protect their health and safeguard their livelihoods. We are all risk managers now.
But the pandemic also shows some events are simply impossible to predict with any certainty, however sophisticated our understanding of risk. In a highly globalised economy, a viral outbreak at a Chinese wet market can rapidly escalate into an international crisis. Predicting the future is devilishly difficult.
That doesn’t mean we must simply accept our fate, however. In this episode of the AIQ podcast, we’ll explore the nature of risk in a complex world. Is it ever possible to foresee the future? And how can we stay resilient at a time when life seems more uncertain than ever before? Listen on to find out.
[Sounds of aeroplanes, old-fashioned jet engines]
In 1954, a Comet passenger jet, manufactured by the de Havilland company in London, crashed in mysterious circumstances, confusing engineers and safety officials. The rest of the fleet was grounded for three months while improvements were made. But just two weeks after flights restarted, another Comet jet blew up over Italy.
To understand what happened to those planes, we need to consider the nature of risk and uncertainty.
For most of history, the future was considered to be beyond human knowledge or control. What changed was the advent of risk management. We realised that by studying the effects of human behaviour, we can start to gain a picture of how future events may play out.
The process started with Cardano’s book on games of chance, and his statistical method was later developed by mathematicians and philosophers. As our understanding of risk and probability became more sophisticated, human beings made massive leaps forward in science, engineering, government and finance.
But early thinkers on risk knew the limitations of their theories. Not every situation can be quantified using statistical methods, which are best suited to scenarios with fixed rules and parameters, like games of cards or dice.
In the early 20th century, two economists, Frank Knight and John Maynard Keynes, drew attention to an important distinction. They argued there was a difference between risk, which can be measured, and uncertainty, which cannot.
In finance, for example, credit investors know there is a risk a company may default on its debt: this can be estimated and priced by looking at factors such as the company’s credit rating and the strength of its balance sheet. This risk is a “known known”.
But there are other hazards that can’t be measured precisely, or even foreseen. This is the domain of uncertainty: the “unknown unknowns”.
[Replay the jet-engine sound effects]
That brings us back to those mysterious plane crashes. After a fresh investigation, the cause of the accidents was eventually found to be metal fatigue originating in the corners of the jets’ square-shaped windows. (Ever wondered why most plane windows are oval in shape? This is the reason.)
Aerospace engineers described the square-window problem as an unknown unknown, or “unk unk” for short. A design flaw so tiny it would have been impossible to spot before it cascaded into a crisis.
In modern finance, unknown unknowns are better known by another name: “black swans”.
Nassim Nicholas Taleb
Before the discovery of Australia, we had no reason to believe that swans could be any other colour but white. There was an expression in Medieval England, “you’d sooner see a black swan than…” It was a saying like “when pigs fly” or “when George Bush does something intelligent…”. Until we saw Australia, the sighting of a single bird destroyed millennia of confirmation.
That’s the voice of former derivatives trader -turned author Nassim Nicholas Taleb, who popularised the black swan metaphor. By his definition, black swans are outliers, because nothing in the past can convincingly point to their possibility – until they are staring you in the face.
True black swans are rare, however. More often, risks belong to a related category: “known unknowns”; hazards we can anticipate in a general sense without being sure exactly when or where they will occur.
In her new book, Uncharted, the author and entrepreneur Margaret Heffernan says the coronavirus pandemic fits the description of a known unknown. As she puts it, such outbreaks are “generally certain but specifically ambiguous”.
They are generally certain, in the sense that epidemics have always happened, and there’s no reason to believe they will stop happening; they are specifically ambiguous, because there is no profile of an epidemic, which means they are inherently unpredictable. We don’t know when they will break out, where they will break out, or what the disease will be.
You can’t say, “If we see these five things happening that means an epidemic is coming.” They are unpredictable; you just don’t know what to be looking for. […] You simply know that you don’t know.
Experts warned repeatedly of the threat of a pandemic in recent years. In a TED Talk in 2015, Microsoft founder Bill Gates said global health systems “are not ready” for the outbreak of a novel flu pathogen.
But no-one predicted COVID-19 would emerge in late 2019 in the Chinese city of Wuhan, jumping the species barrier from a wild animal to a human host. Nor did anyone foresee that the spread of the new virus would coincide with the sudden decision by the Saudi government to slash the price of oil in February 2020, making the panic in financial markets even worse.
[Digital effects: beeps and clicks from the workings of a machine]
Some commentators have suggested new technologies, such as artificial intelligence, could have anticipated the pandemic.
Didier Sornette, a professor at the Swiss Federal Institute of Technology Zurich, is one of the world’s leading experts on risk. By carefully monitoring disturbances in complex systems, he has been able to detect early signs of crisis in various environments, from heavy industry to finance.
But Sornette acknowledges that many events are impossible to capture within numerical models. He argues that not even the most advanced data-driven methods could have predicted the onset of COVID-19 precisely, though they might have been helpful in mapping its subsequent transmission across borders.
In this case it was predictable and unpredictable at the same time. Predictable in the sense that, as has been much commented upon, pandemics were at the top or close to the top of the list of concerns among risk managers and experts across the world over recent decades. […] It was predictable in the same way an earthquake is predictable: you can predict another one will happen, but you don’t know when. So yes it was knowable but not in the sense of precise timing.
Sornette’s approach acknowledges the difference between risks that can be modelled probabilistically and uncertainties that cannot. Though the distinction is simple enough, it is often overlooked by experts who believe they can perfectly chart the course of the future.
“Expert” forecasters are taken by surprise more often than they may like to think. A famous study by the US psychologist Philip Tetlock found the average expert in geopolitics and economics – defined as those with more than 12 years’ experience – is about as accurate in predicting the future as a chimpanzee throwing darts at a target.
Tetlock found amateurs are often better than experts at predicting the future. He called these people “superforecasters”. Their predictions consistently beat the average, at least when it comes to answering short-term questions with highly constrained parameters.
Superforecasters come from a range of backgrounds, but they share a particular character trait: open-mindedness. They are rarely wedded to a single ideology or perspective; they are open to challenge and debate in the interests of learning more; and when the evidence shifts, they are willing to change their minds.
By contrast, experts in technical fields often cling to a damaging sense of certainty about the future. This can leave their organisations vulnerable to events that lie outside the scope of their models.
Here’s Tetlock, in conversation with Rachel Kipp of Wharton University.
I think a lot of people spend quite a bit of money on advice about the future that probably isn't worth the amount of money they're spending on it and they don't really know, they have no way of knowing, the track record of the people whose advice they're seeking.
The best example of that is probably in the domain of finance, where a lot of money changes hands; it's directed to people who claim to have some ability to predict the course of financial markets; that is an extraordinarily difficult thing to do. I'm not saying it's impossible, or that nobody can do it any better than the dart-throwing chimp, but it's a very difficult thing to do.
I think people should be more sceptical about the people to whom they turn for advice about possible futures – finance would be a case in point – but I think more generally they should be very sceptical of the pundits they read and the claims that politicians and other people make about the future as well.
Experts’ overconfidence about their ability to predict the future was abundantly clear during the financial crisis of 2007-2009. And once the market turmoil hit, an overreliance on numerical models hindered organisations’ ability to adapt. Here’s Margaret Heffernan to explain more.
People in government, people in decision-making positions in corporations want levels of certainty which models purport to provide, and the problem with that is that all of the real risk, the systemic risk, appears to go away and the possibility of picture-perfect decisions starts to feel available. And the truth is since every single forecast can only have probabilities attached to it, and those probabilities will always be under 100 per cent, the opportunity to make the perfect decision is always elusive. We have to make trade-offs and we have to try to make the best decisions we can in light of the information we have, but that information will keep changing and very few models keep up with that pace of change.
The pace of change is only increasing. According to Taleb, global crises are becoming more common, and more damaging, because of the physical and technological connections that characterise the modern world. There are now more situations in which a single variable can have outsized effects, whether that’s an asset bubble, cybersecurity failure, natural disaster, geopolitical spat or a pandemic. Uncertainty is the new normal.
Managing risk in this environment may be daunting, but it is not impossible. Organisations that can grasp the unpredictable nature of the modern world – and recognise the limits of their own knowledge – could find opportunities to thrive amid radical change.
One key lesson to draw from the events of recent months is that attempts to predict the future with certainty are doomed to failure. This is especially the case in finance, where timing the market depends on being right in the specifics, not the generalities.
Investors are trying to build portfolios that stay resilient in a range of scenarios. In this, the finance industry can learn a lot from one of the pioneers of scenario planning.
Let me start with a strong statement. It is impossible to predict the future and it is foolish to try to do so. […] Forecasts fail you just when you would need them most. Forecasts fail to anticipate major changes, major shifts.
That’s the voice of Pierre Wack, who became known for his unconventional risk-management methods at oil company Shell. Wack threw out the centralised planning model the company had previously used and encouraged his teams to think outside the box in planning for a range of potential futures.
Long before the creation of OPEC, he speculated about the possibility that major Middle Eastern energy producers would form a cartel to exert monopoly power. As a result, Shell was able to weather the oil crises of the 1970s much better than its competitors.
Scenario planning has since been applied in a range of other contexts, from business to policymaking. And the approach has a close analogy in modern asset management, where resilience depends on building diversified investment portfolios that can withstand a range of possible developments.
A well-diversified portfolio is not just a random collection of assets, but a set of informed ideas about corporate and economic trends. The art of portfolio management is about ensuring these fit together such that the associated risks are not concentrated in a single geography, sector or factor.
At the stock selection level, too, investors need to be increasingly focused on resilience in an unpredictable world. That means monitoring dynamics such as companies’ debt levels, which is an important index of their ability to withstand adverse events.
Giles Parkinson, global equities portfolio manager at Aviva Investors, says the coronavirus pandemic has shown the importance of reading a balance sheet.
If you’ve got a) a lot of debt or particularly b) debt that has covenants attached to it, then your equity has performed extremely weakly.
Because the stock market is saying, ‘ok fine, this might be quite a short, sharp recession, but given what’s happened to your revenues, and therefore your profits, you’re going to see a V-shaped decline in your profits, which is going to trigger covenants which probably means you’re going to need to raise equity.’
This is an environment where, as an investor, it’s really showing some people can only read income statements. But you must also be able to read a balance sheet as well. A lot of investors out there have come unstuck because it’s been shown they can’t read balance sheets.
Another crucial lesson to be learned from the events of 2020 is that organisations need to play close attention to the wider market and social context.
Companies with strong environmental, social and governance credentials are proving to be more resilient to the COVID-19 disruption, perhaps because these firms tend to take a more careful and holistic view of their operations and those of their commercial partners. The best companies appreciate that they are only as strong as the society in which they operate. Here’s Margaret Heffernan again.
No organisation in the world can function without society. We need educated people; we need roads and energy and light. The rule of law. Health. Clean air. These sorts of things are not optional extras.
Every corporation exists within an ecosystem, and the corporation can only be as resilient as the society it inhabits. The health of the organisation depends on the health of the ecosystem, and the health of the ecosystem depends on the health of each individual company.
Perhaps the most important criterion for resilience in an age of uncertainty is the capacity to adapt when circumstances shift. Organisations that can trim their sails and adjust course when the weather turns are more likely to prosper than those that simply batten down the hatches.
A recent McKinsey study tracked how 1,000 publicly traded companies fared during successive crises: it found an ability to adapt to new conditions was a hallmark of the best-performing firms.
Mikhail Zverev, head of global equities at Aviva Investors, says that change can be both a positive and a negative within a portfolio – the skill comes in understanding how it will affect each investment.
Change works both ways; change can be an opportunity and a threat. Primarily, for us, change is a source of inefficiency; when something is changing in a business, when the future isn’t equal to the past in a very meaningful way, the market is more likely to misprice, misunderstand that. Because when you can’t extrapolate from the past any more, you have to quote-unquote do more work, do more digging, that’s more likely than not to uncover new opportunities for us.
So what kind of changes will the coronavirus pandemic bring about? Technology giants, already among the world’s dominant companies, could grow even stronger amid rising demand for networking software. The pressures on global supply chains may prompt a shift from lean, “just-in-time” efficiency to “just-in-case” disaster planning.
These kinds of theses about the future can help guide investment decisions. But in unpredictable times, these ideas need to be open to challenge and revision when the picture changes. Flexibility and humility – not unshakeable certainty in the wisdom of one’s own decisions – are the hallmarks of longer-term success in asset management and beyond.
No-one knew this better than John Maynard Keynes. In the years after he outlined the distinction between risk and uncertainty, Keynes managed an investment portfolio on behalf of King’s College, Cambridge. He grew the value of the fund with a series of accurate market bets based on his forecasts about the business cycle – but he did not anticipate the Wall Street Crash of 1929, which damaged the fund’s value – and cost him 80 per cent of his personal net worth.
In 1929 overnight the bottom fell out of Wall Street and millions of people saw their savings melt away like ice in the summer sun. It was a time of despair and suicide and panic…
Other market forecasters of the era were also caught out: Irving Fisher, then the world’s most famous economist, claimed stocks had reached “a permanently high plateau” only days before the crash.
But unlike Fisher, who doubled down on bad market bets, Keynes was willing to change his mind. This enabled him to adapt to the shifting post-Crash environment and cope with the adverse consequences of his mistakes. As Keynes famously put it in 1940, after he had adjusted his investment strategy and recouped most of his losses: “When my information changes, I alter my conclusions.”
[Outro music fades in]
At a time of radical uncertainty, investors everywhere would do well to heed Keynes’s advice. The coronavirus pandemic has proved how unpredictable the modern world can be. But by staying flexible and planning for a range of different future scenarios, investment companies can manage the risks.
Thank you for listening to the AIQ podcast. Read the latest issue of AIQ magazine, a risk special, at our website at www.avivainvestors.com. Please look out for future episodes and feel free to subscribe through any of the major podcast channels.
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