Financial market movements, business cycles, oil cycles and even the rise and fall of companies, corporate leaders and politicians – none of them can be properly explained and predicted by the traditional narrative model. Anadarko photo.
Oil market forecasting not compatible with traditional storytelling methods
By John Kemp
LONDON, Feb 8 – “Once upon a time …” Storytelling is one of the most fundamental human impulses.
Humans have been telling stories for thousands of years as a means of entertainment but more importantly to help them make sense of the world around them and to transmit that understanding to others.
Narratives are a way of organizing a series of actions or events to understand the process of cause and effect, helping make sense of the past and anticipate the future.
“Anthropologists, who conduct research on the behaviour of diverse tribes around the world, have observed a universal that people use narrative to explain how things came to be and to tell stories.
“Visitors to any human society will observe people facing each other, sitting around the television, or the campfire, together and vocalizing, and more recently tweeting, stories,” according to economist Robert Shiller.
“It seems the human mind strives to reach enduring understanding of events by forming them into a narrative that is imbedded in social interactions” (“Narrative economics”, Shiller, 2017).
Or according to the Pixar rules of storytelling, compiled by Emma Coates, the ideal narrative runs: “Once upon a time there was … , Every day …. , One day … , Because of that … , Because of that … , Until finally …” (“Pixar tips”, Washington Post, June 25, 2012).
The narrative impulse is hard-wired into our brains and is present in every creation myth, fairy-tale, history book, academic research paper, newspaper, political rally and corporate earnings call.
Satisfying stories obey a few simple rules:
- Good stories start at the beginning (“once upon a time”) and move linearly through a sequence of events to a conclusion (“the end”).
- Cause and effect are closely and intuitively linked and should be roughly proportionate to one another (big consequences should stem from big causes).
- Each effect should have a single cause, or at most a small and easily comprehended number, rather than result from the complex and incomprehensible interaction among many causes.
- Heroes and villains should be clearly identified and eventually be rewarded or punished by the chain of events according to some definition of morality.
- Luck, chance and randomness can play a part, but hard work, intelligence, worthiness and free will are more important in determining outcomes.
The problem with the campfire model (mono-causal, linear, proportionate, moral and determinant) is that it fails to explain many important real-world processes (which are non-linear/circular, exponential, amoral and random).
Financial market movements, business cycles, oil cycles and even the rise and fall of companies, corporate leaders and politicians – none of them can be properly explained and predicted by the traditional narrative model.
In these real examples, processes are multi-causal, complex, do not always produce virtuous winners, and often do not lead to clear outcomes and predictions.
Descriptions of real-world processes often fail as satisfying stories – while emotionally pleasing stories often fail to explain and predict the real world properly.
Politicians, business leaders, campaigners and opinion formers often prefer simpler narratives that provide a more satisfying explanation, stir an emotional response and serve as a call to action.
The narratives used to frame and explain an issue can have a powerful impact on how businesses, employees, customers and voters respond and the choices they make (sometimes unconsciously).
Storytelling can influence the real world as much as the other way around, so narratives can be instruments of power, whether they are right or wrong.
But forecasters and analysts should prefer accurate descriptions of real processes, for all their limits of complexity and indeterminacy.
The limits of predicting outcomes from circular and complex processes with a significant random element mean forecasts should normally be expressed as scenarios with an associated probability distribution.
Even then, many forecasts are hyper-sensitive to small changes in the starting point or assumptions about the causation process, so the probability distribution itself is often highly unstable or uncertain.
Forecasters should always be humble about their ability to make accurate predictions, especially far into the future or when many variables are changing simultaneously.
Often the most useful part of forecasting is the discipline of having to think in a rigorous way, identifying and analyzing all the potential variables in play, getting a better sense of the range of uncertainty.
Once the key variables have been identified, some risks can be eliminated, transformed, insured or managed, while others simply have to be borne.
Campfire storytellers are judged by the emotional satisfaction their narratives provide; forecasters and analysts should expect to be judged by a different standard.
Acknowledging and embracing uncertainty is not a sign of failure or lack of courage but an honest admission of the limits of forecasting and of the complex way in which processes evolve.
John Kemp is a Reuters market analyst. The views expressed are his own.
(Editing by Dale Hudson)
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