Category: Forecasting

“He who foretells the future lies, even if he tells the truth.” (Chinese proverb)

Hi!  And thank you for your interest!  I hope I manage to retain it.

My name is Andrew.  I have spent most of my working life as a consultant in the energy sector.  I want to reflect on this life and see what can be learned from it.  I want to start with the business of forecasting.

I have been employed by developers of large projects such as power stations, HVDC power cables, gas pipeline consortia, storage facilities; by prospective lenders of money including banks, private equity funds, pension providers and public bodies; and by governments and regulators interested in their commercial viability and possible consequences for energy consumers, the enviroment and the economy.  Most of the time, these clients have been interested in my forecasts: forecasts of energy prices, power station output, energy flows between nations and atmospheric pollution; forecasts for the next 15-20 years usually and sometimes up to 50 years into the future.

Based on evidence to date, my forecasts have always been wrong.  Of course, with long range forecasts one can hope they turn out right in the end; but it would be fair to say they have not got off to a very good start.

In this series of blogs, I want to explore why it is that forecasters like me are so much in demand.  I will consider how and why we are cajoled, usually against our better judgement, into making forecasts in the first place; and the distinction between what we can genuinely offer and what we are asked to do.  This will involve making conjectures about business psychology as well as energy economics.  Such conjectures are based on personal experience; I hope they are more illuminating than the forecasts.

The price of oil will, er, always stay the same

In July 2008, the price of oil (Brent crude, to be specific, but it doesn’t really matter) was 145 $/bbl (dollars per barrel).  The market’s view of future oil prices (ICE Brent monthly, again the details don’t matter) was 140 $/bbl extending out over the following 9 years, i.e. to summer 2017.

Roll forward six months to January 2009.  The price of oil had collapsed to 45 $/bbl, less than a third of its level in the previous summer.  The market’s new view was a slow recovery from 45 to 70 $/bbl in 2012.  (Of course, the market was unashamed at having slashed its forecast by more than 50% from the previous July.)  As things turned out, the spot price rose above 125 $/bbl in 2011 and again in 2012, suggesting that it would have been better to stick with the original forecast.

More recently, in early 2015, the spot price was 115 $/bbl and the market foresaw a gradual decline to 100 $/bbl by 2020.  Six months later, the spot price collapsed to 48 $/bbl.  Has the market learned from its mistakes?  Well it is predicting a slow rise to 70 $/bbl by 2018 …

Essentially, the market assumes the current price will be extended into the future, perhaps with a slow rise or slow decline.  It has proven incapable of predicting the sudden rises and falls (what posh people call “volatility”).

Perhaps others have done better?  In the near term, this is meant to be impossible according to most economists: the market takes account of all the information that is available and represents the combined wisdom of all of its participants.  In a ‘liquid’ market such as crude oil, this should be unbeatable, not that that stops others from trying.

The best known and one of the most reputable of these ‘others’ is the International Energy Agency, or IEA.  The IEA annually produces its World Energy Outlook or WEO, a weighty 600 page pdf that is almost unreadable but certainly very learned.  It contains highly researched and methodically produced analyses for the world economy and the future of energy prices over the next 20-30 years.  And how has it performed?  Well, a wide range of academic investigations have been done on this question and the general consensus is the WEO’s performance to date has been slightly better than flipping a coin and guessing the outcome.

In his excellent book “Thinking, Fast and Slow” Daniel Kahneman explains why we should not expect much from pundits who make long range predictions.  Most surveys into the perfomance of long range forecasts by experts show that dart-throwing monkeys would have achieved a similar level of success.

And yet we still do it

So why do we make forecasts?  I guess one answer is a tendency to conflate luck with skill.  The Chinese proverb at the start of this blog is not generally appreciated, at least in my experience.  If someone succeeds – in this context, meaning they make a prediction that turns out to be accurate – they ascribe it to skill rather than good fortune, wilfully overlooking the fact that if blind apes throw darts at a dartboard then eventually one of them will hit the bulls-eye.  (You might be familiar with Alan Sugar of The Apprentice, and his widely disseminated motto: “there is no such thing as luck in business”.)

And yet, we think that forecasting is necessary, that someone has to do it.  That has always been my top excuse.  And we believe in data, increasingly so in this age of ‘big data’: the more facts we have about what happened yesterday, the more confident we are in our ability to predict what will happen tomorrow.  In general we believe in progress – technological and scientific progress – so that past failures are rationalized as being the results of inferior past techniques and knowledge: we are better now, we think, and will not repeat the same mistakes.  With such a positive mindset, no track record of failure, however stark, deters us from trying again.

None of this quite gets to the heart of the psychological motivation for foretelling the future.  In my next blog, I will describe my own reflections on this, accumulated over the last thirty years of unsuccessful predicting.

“The future is dark; the present is burdensome; only the past, dead and finished, bears contemplation.” Geoffrey Elton, historian

“The illusion that we understand the past fosters overconfidence in our ability to predict the future.” Daniel Kahneman, psychologist

Hi! Thanks for your attention, I really hope I do it justice.

Investment analysts try to model/predict the future – and are often very well paid for it – for at least the following reasons:

1. they (and their clients) think they have to
2. they believe in big data, and the forecasting power that arises from analysis of it
3. they believe in progress (technological and scientific), which helpfully creates the delusion (and associated peace of mind) that the latest forecasts will succeed where previous ones failed, and
4. a variety of psychological factors make forecasting big business.

Let’s consider a couple of these psychological factors.  The first one, which has been a part of my working life, is an understandable reluctance to take responsibility, a tendency – endemic in the business world – to “pass the buck”.

The concept of reliance

Consultants like me who have made a livelihood from making forecasts are often required by banks and other lenders to provide “reliance” on them.  This is a weird notion, as most of us are very careful to say things like “investments may go down as well as up”, “the accuracy of projections cannot be guaranteed”, and other such warnings to our clients that they should not place too much faith in the results of our analysis.  It took me a long time to understand what reliance means.

Initially, I thought the concept of reliance was about doing the best job one can – and being able to demonstrate later on that one has done the best job one can – given the state of knowledge and circumstances at the time one does it.  We might not know for sure what will happen in the future, but we can give ourselves the best chance of making an accurate prediction by carefully examining available data and the success or otherwise of past predictions.  This is where ‘big data’ comes in: the more data we can analyse, surely the better we will do?

But that doesn’t really explain the motivation of reliance, or its contractual significance in the world of business.  The bigger issue is devolvement of responsibility – this is the key underlying motive that explains the importance of reliance in business, whereas “making sure these guys do the best job they can” is the ostensible justification.

Few of us really enjoy taking responsibility.  Most who claim they do are pretty confident in the robustness of their positions, so they don’t feel much risk is involved: their shoulders are broad, they might say, without adding they’re not as broad as those they are standing on.  Some people really do enjoy the risk associated with claiming responsibility, but for each of these genuine risk-takers there are several individuals who are just relying on their self-perceived status.

In consequence, the world of business is to a remarkable extent structured in accordance with the desire to pass the buck; corporate structures allow blame to pass up the chain or down the chain, between business units, and between corporate entities.  In my line of work, buck passing goes between developers – who commit to a project on the basis of my forecasts – and insurers – who ultimately pay out when things go badly wrong – in the following sequence.

First, developers are wary of committing too much of their own money, so they limit the liability of their company and bring in debt providers such as banks to finance a large proportion of the project.  Second, the debt providers seek to justify their recommendations to credit committees by engaging “experts” like me and getting us to provide “reliance” on our reports.  Third, the experts carefully limit the terms of this “reliance” and bring in insurance companies to protect us against the limited terms that remain in place.

If projections turn out to be wrong, and a project goes badly and a loan cannot be repaid, the debt providers can blame the experts that forecast otherwise, and if things go very badly they can attempt to sue.  Credit committees blame the bank analysts for bad recommendations, the bank analysts blame the experts they employed on a reliance basis, and the experts point out the thin meaning of reliance in the first place and turn to insurance in extremis.  Financial losses are spread amongst myriad savers and investors and/or diluted through insurance premia.  It is a complex world of devolved responsibility in which everyone and no-one picks up the pieces of misjudgement or incompetence.

Fear of uncertainty

A second psychological factor is perhaps even more fascinating.  It is our fear of uncertainty.

When we tell ourselves that analysis of big data will make our future predictions better, it is because deep down we want to believe in an explicable world, the certainties of which will become apparent with enough number crunching.  When we pretend that we understand past events, we become confident in our ability to tame the darkness of their recurrence.  When we tell ourselves rich stories – scenarios, in the more exalted jargon – we become convinced that we can predict a brighter future.

It is a revealing characteristic that most scenario projections for whatever it is that we are predicting – economic indicators, commodity prices, long-run stock prices – are much smoother than the turbulent fluctuations we have seen historically.  This is sometimes excused on the basis that we cannot predict random events or cyclical behaviour.  But the truth is we want to believe the future will be more serene than the past.

Fear of uncertainty is associated with fear of death.  It takes a brave individual to accept with equanimity the genuine uncertainty and precariousness of life, the fact that ultimately nobody knows and no-one is really in control.  Forecasters in all shapes and forms – long range weather forecasters, energy consultants, investment analysts and stockbrockers, politicians – make a living to a large extent from our strong appetite for the sustenance of certainty.

The great American physicist Richard Feynman said he did not really care about knowledge as such, that it was not ‘knowing’ but ‘the pleasure of finding things out’ that spurred him on.  He frequently thought he himself was wrong, let alone others.  For him, the world is irretrievably uncertain, but the uncertainty didn’t bother him – indeed it excited him.  Alas, very few of us attain that serenity of outlook.