The communications theorist Paul Watzlawick wrote that a phenomenon remains unexplainable as long as the range of observation is not wide enough to include the context in which the phenomenon occurs. Failure to realise the intricacies of the relationships between the matrix in which it takes place, induces one to attribute to his object or study certain properties the object may not possess.
One hour after polls closed in the Brexit Referendum, the implied probability, on Betfair, the world's largest betting exchange, that the UK would vote to remain in Europe was 94%! Perhaps, not surprisingly, many people went to bed, believing that the vote was a done deal. The most surprised come the next morning, were perhaps the FX traders, who awoke at 4am to take their taxis into work, only to find that the UK had voted for Brexit. Many financial traders had put their faith in the betting markets, and accordingly bet that the pound would rise significantly on the back of a result in favour of Bremain. The following two tables reveal
the extent to which sterling volatility eased off as a remain vote looked more certain (the second table is a snapshot of the Betfair
EU Referendum betting market with sixty five million pounds traded and hardly a penny looking to get on the Brexit outcome.)
The stance adopted by a majority of FX traders, represented a serious case of overconfidence - they had fallen into the age old trap of believing that they knew more than they actually could have known: or, putting it another way, they had been duped into believing that betting markets were omnipotent and contained some additional information about the outcome of the referendum that the polls had missed, and they chose to slavishly follow them. (Kahneman; When they come together, the emotional, cognitive and social factors
that support exagerated optimism are a heady brew.)
It was not the first time in the recent past that betting markets had called events wrong. A previous, and recent humiliation had occured in relation to the Greek Referendum vote. Betfair, in particular, got it badly wrong, with its betting market on the event showing a 75% implied probability of a YES vote, as polling opened. In contrast to this bullish optimism, the Guardian's poll of polls correctly called a No vote, but was largely ignored by the betting public.
The result of the Greek Referendum also represented a significant blow for the prediction market fanboy Justin Wolfers, who in an article in the NYT on the Greek Referendum (quoting Betfair prices) had written; as they adjust betting odds in response to the flow of money, their odds come to represent a quantifiable assessment of the conventional wisdom. The problem, for Wolfers, being that the conventional wisdom was wrong.
Greek Referendum 2015 Polls*
Source: Guardian (Average of Six Polls).
Greek Referendum 2015 Betting Exchange*
Closer to home, on the eve of the 2015 UK General Election, the implied probability of a Conservative Majority (the actual outcome) on Betfair was 7%. A seperate betting market also implied a 91 per cent probability of there being no overall majority in the House of Commons. Six days later the Tories had won 330 of the 650 seats — an overall majority.
Source: Betfair Betting Exchange.
Whilst speaking about his pre-election forecast on the 2015 UK General Election, Nate Silver said:
The forecast assigned too little of a chance to an outcome like this one, especially given that there have been significant polling errors in the UK before. It is a good lesson as we begin to plan our coverage for the 2016 U.S. election.
In July 2015 Silver wrote as regards Donald Trump's Presidential propsects; In the long run — as our experience with past trolls shows — Trump’s support will probably fade. Or at least, given his high unfavorable ratings, it will plateau, and other candidates will surpass him as the rest of the field consolidates.
On 7 October 2016, Donald Trump saw fit to mock Silver: He's always been on the right side of what happened and he didn't predict me.
The notion that markets are omnipotent and capable of pricing in all of the available information pertains. Speaking on the subject of prediction/betting markets, Justin Wolfers recently wrote in the New York Times; their odds come to represent a quantifiable assessment of the conventional wisdom. Professor Leighton Vaughan Williams, of the Political Forecasting Unit at Nottingham Business School; The power of the betting markets to assimilate the collective knowledge and wisdom of those willing to back their judgement with money has only increased in recent years as the volume of money wagered has risen dramatically.
There is only one problem with this notion of conventional wisdom enshrined in a super smart betting market - it gets things wrong. Trump was right - nobody saw him coming. On the 7th of July 2015 the implied probability on Betfair of Donald Trump becoming President was 4%. When betting opened on the next Labour Party Leader after the departure of Ed Miliband, Jeremy Corbyn was not even quoted in the betting. When he did enter the betting he was quoted at 100/1.
2016 U.S. Election Implied Probabilities.
Source: Bettingmarket.Com analysis. 07/07/2015.
Next Labour Leader Implied Probabilities
Gloria De Piero
Source: Bettingmarket.Com analysis. 08/05/2015.
When betting markets do get it wrong, the so-called experts will always find an explanantion as to why something other than what they have predicted has occured; although strangely, the explanation never comes to light until after the event! Self proclaimed Bremain supporter Leighton Vaughan Williams, famously dismissed the collective intelligence of the 17.4m people that voted for Brexit with an artcle declaring that it was the Sun and Mail wot won it. Oh, if only he had shared this wisdom with his devoted Twitter followers before the vote had taken place. This of course ties in neatly with Tetlock's assertion that experts rarely
if ever admit that they are wrong, and that when they are forced to admit that they were, they are always at hand with a large collection of excuses; timing, an unforseen event had occured, or, they had been wrong but for the right reasons. (the I knew it all along or hindsight bias, sometimes translated as I was simply too clever by half for my own good.)
The betting market arbitrageur is the one punter that is never left holding the baby; he has left the room before the first squeal breaks out. He has won regardless of the outcome. He has surfed the wave of delusion, and parked up his surfboard, long before the tsunami has hit the shore. He and he alone, knows that an enhanced illusion led people to become unrealistically bullish.
When we look back at the Brexit vote, the key question that we must ask ourselves, is just why it was that betting and
financial markets diverged so significantly from the polls (as per the folowing chart from Bloomberg).
The polling average missed the final outcome by around only 4%, and as the following table demonstrates, five of the eleven polls
at the close of voting actually had leave winning. They were simply ignored by a majority of those trading in the betting market.
A significant aspect of the narrative fallacy put forward by those that opposed Brexit, was, that given that a majority of the polls that came out in favour of Brexit were online polls, they had to be wrong - people, it was contended, were seemingly more likely to reveal their true voting intention when contacted by telephone (paradoxical logic par excellence).
Throughout the Brexit Referendum campaign a narrative fallacy took hold amongst a majority of betting market participants; betting market discipline had allegedly harnessed the wisdom of the crowd, who for some reason (perhaps only best known to them, or to the people that like to speak of prediction markets) were allegedly in receipt of some special causal insight that was not available to the pollsters, or indeed to anybody else for that matter; betting market participants believed that they were receiving information that was somehow privileged, or at least extremely insightful and from this they were able to construct a coherent story in which the implied probability suggested by the betting market actually made sense (In another context such behaviour might be labelled schizophrenic).
The tendency to construct and believe coherent narratives of the past also came into play; the result of the Scottish Referendum fed the delusion and crystalised the view that when it came to the actual vote people would vote in relation to their best interests (Bremain). Such a belief highlights the risk of mistaking what’s happened in the recent past for some sort of iron law, and ties in neatly with Kahneman's assertion
that Any recent salient event is a candidate to become the kernel of a causative narrative....The core of the illusion is that we believe we understand the past, which implies that the future should also be knowable,
but in fact we understand the past less than we belive we do.
There was also of course significant anchoring at work. If the betting market says that an event has an implied probability of 90%, then people are going to be influenced by this number (the somebody must know something bias).
When reviewing just why it was that the betting market did get things so badly wrong, we would do well to remember that Tetlock has found that people who spend their time and earn their living, studying a particular topic, produce poorer predictions than dart throwing monkeys. In Expert Political Opinion Tetlock found that the average expert's predictions were no better than a random guess; moreover, he also found that there is something about being a high ranking expert that interferes with forecasting. Human affairs are mostly random and intractable (and often the product of luck): even Tetlock's superforecasters got Brexit wrong.
Kanheman notes that errors of prediction are inevitable because the world is unpredictable. Secondly,
he states that high subjective confidence is not to be trusted. Thirdly, it is unlikely that lessons will be learnt, because facts that threaten livelihood and self-esteem are very very quickly forgotten. Kanheman notes
People can maintain an unshakable faith in any proposition, when they are sustained by a community of like-minded believers.
In what was surely one of the greater ironies of the entire EU Referendum betting market campaign, Mike Smithson, who is regularly quoted in the media as being a betting guru, tweeted that things looked good for Bremain as far as market on Betfair was concerned, but that he had no idea what this actually meant!! Whilst Smithson may well have saved face with this comment, it was hardly a ringing endorsement for his beloved political betting markets.
In the run up to the 2016 U.S. Presidential Election Professor Leighton Vaughan Williams took to Twitter to tweet to Nate Silver about the supremacy of the betting markets.
Bryan Cranston, an online lecturer in politics, and PhD candidate at Swinburne University, Australia, rose to fame after penning an article in the UK's Independent online newspaper under the heading Can Donald Trump win the election? Here’s the mathematical reason why it’s impossible for him to become President. It seemed that the traders on Betfair believed Cranston, for at one point during the evening of election day, the implied probability that Clinton would become the next U.S. President was 88%.
In betting on individual States, the traders on Betfair had Clinton nailed on in Florida, Michigan, Pennsylvania and Wisconsin.
She lost them all to Trump.
To give the polls their due, two of them, IBD/TIPP and USC Dornsife/LA Times, showed victories for Trump, but failed to predict that Clinton would win the popular vote. All of the other major polling outlets, and the great Nate Silver, showed at least a 3-4 point national lead for Hillary Clinton.
When we first visited the French Presidential Election Betting Market in July 2016, Alain Juppe was the warm favourite
in the betting market, with an implied probability of 36%.
Source: Bettingmarket.Com analysis. 25/07/2016.
On the 7 November 2016, the implied probability that Juppe would be French
president had climbed to 68%.
Source: Bettingmarket.Com analysis. 07/11/2016.
Spring forward to 30 November 2016 and Juppe has gone, replaced at the top of the market by Francois Fillon,
who back in July was a 100/1 shot in places (an implied probability of 1%).
FRENCH ELECTION - NEXT PRESIDENT
Marine Le Pen
Source: Bettingmarket.Com analysis. 30/11/2016.
Early December 2017 saw the beginning of what was to become known as the Macron Surge.
Source: Betfair. 08/12/2016.
Spring forward to 29 January 2017 and Fillon has been replaced at the top of the market by Macron.
French presidential election, 2017 - Probabilities
Current Implied Probability
Source: Betfair. 29/01/2017.
Spring forward to 17 February 2017 and Fillon is now significantly trailing Macron and Le Pen.
It is noted that in the space of two weeks the implied probability of a Le Pen presidency has risen to
27% from 20%. This represented a then all time high for Le Pen, even though she had not improved her position in the polls.
French presidential election, 2017 - Probabilities
Current Implied Probability
Source: Betfair. 13/02/2017.
The Richmond Park by-election was a UK parliamentary by-election in the constituency of Richmond Park, held on 1 December 2016.
The Polls had Zac Goldsmith, an independent candidate and anti-Heathrow campaigner, as the clear front runner (see below). As the polls
closed, the implied probability in the betting market that Goldsmith would win the seat was 68% - he duly lost.
Presidential elections were held in Austria on 4 December 2016. Almost without exception the Polls had Norbert Hofer of the Freedom Party of Austria in the lead. On the morning of the contest the implied probability that Hofer would be the next president of Austria
was 73% - he duly lost.
Opinion polling for the Austrian presidential election, 2016
Van Der Bellen
The pollsters and those that build their models around the polls, are, by their very nature, incapable of believing anything other than that the future will be like the recent past. They incorrectly ascribe probabilities to political events, in much the way that
a bookmaker prices up a horse race. The mistake being, as John Gray notes, that Politics is not like horse racing – a finite series of well-defined contests whose outcomes can be used as the basis for calculations of probability.
In a world in which we have come to confuse information with understanding, political betting/prediction markets have become a shortcut to misunderstanding. As matters stand, they are are highly dysfunctional, incapable of fulfilling Bayes’ core insight of gradually getting closer to the truth by constantly updating in proportion to the weight of the evidence (Or as one FX trader put it in the wake of the Brexit vote; None of us knew anybody that voted to leave.).
The final word is best left to Kathryn Schulz who in her book Being Wrong, writes: Our indiscriminate enjoyment of being right is matched by an almost equally indiscriminate feeling that we are right. Occasionally, this feeling spills into the foreground, as when we argue or evangelize, make predictions or place bets. Most often, though, it is just psychological backdrop. A whole lot of us go through life assuming that we are basically right, basically all the time, about basically everything: about our political and intellectual convictions, our religious and moral beliefs, our assessment of other people, our memories, our grasp of facts. As absurd as it sounds when we stop to think about it, our steady state seems to be one of unconsciously assuming that we are very close to omniscient. In a nutshell, we do not like to admit that we were wrong, because we do not like to look like fools.