Prediction Market Theory: How a book published in 1921 can help explain the 2008 Wall Street Crash!

By Leighton Vaughan-Williams
June 29th, 2009

The Betfair Prof, Leighton Vaughan Williams, explains it all…

Born and brought up on a farm in McLean County, Illinois, he claimed that the only reason he turned to economics was that plowing was too hard on the feet. Well, farming’s loss was economics’ gain, and Frank Hyneman Knight’s seminal volume, Risk, Uncertainty and Profit, published in 1921, was to show just how great that gain was.

In this major contribution to economic thought, Knight makes an important distinction between insurable and uninsurable risks. According to Knight, profit—earned by the entrepreneur who makes decisions in an uncertain environment—is the entrepreneur’s reward for bearing uninsurable risk. Essentially, he was highlighting the distinction between measurable risk and what he terms ‘uncertainty’. The world of business, he argued, falls into the realm of this uncertainty, since it deals with “… situations which are far too unique for any sort of statistical tabulation to have any value for guidance. The conception of an objectively measurable probability or chance is simply inapplicable.”

What makes Knight’s insight so topical is that these ideas are particularly relevant to financial markets, where surprises occur regularly. For years Knight was ignored by the theorists of mainstream financial economics, who either didn’t know or didn’t care for Knights’ belief in “the sheer brute fact that the results of human activity cannot be anticipated”. Knight was perhaps over-stating his case, but the theorists who followed him, with their mathematical models of risk management, went to the diametrically opposite position, constructing a mathematically tractable universe in which rational agents can measure and value risk and return, and trade them with confidence.

In this alternative universe, risk can be reduced to statistical variance and forecasts of the future can be encapsulated in measurable probabilities. The implication is that economic agents are indeed rational, or failing that, act ‘as if” they are (the famous ‘as if” theorem first proposed by Milton Friedman in his 1953 ‘Essays in Positive Economics’). The other implication is that the financial world is ‘ergodic’, in the sense of possessing a stable, recurrent underlying structure.

In this alternative universe, all risk is insurable and the collapse of the sub-prime mortgage market shouldn’t have been such a big deal. After all, the risk of that happening was insurable, wasn’t it? Of course it was, using so-called ‘credit default swaps’ (CDSs). In this context, these are basically bets (otherwise termed ‘private insurance contracts’) based on whether people will default on their mortgages. Unlike bookmakers and betting exchanges, those laying the bets were, however, unregulated and investment houses that sold them weren’t required to set aside funds sufficient to cover their potential liabilities. At their height, the nominal value of the CDSs was in excess of $63 trillion (63,000 billion dollars!). And when the ‘insurance’ was called in, the layers just didn’t have the money to pay.

Goodbye Bear Stearns, Goodbye Lehman Brothers, Goodbye conventional wisdom.

Could a well-constructed prediction market have predicted all this? I guess it depends who was placing the bets!

Tags: bear stearns, Betfair, Betfair Predicts, Betfair Prof, conventional wisdom, frank hyneman knight, lehman brothers, leighton vaughan williams, prediction exchange, Prediction Market Theory, Prediction Markets, risk uncertainty and profit, wall street crash Posted in Betfair Prof, Blog, Prediction Market Theory, Prediction Markets, Stock Market |

What do prediction markets, an article published in 1952, and the Babylonian Talmud have in common? And where does Don Quixote fit in?

By Leighton Vaughan-Williams
June 17th, 2009

“Believe me, no: I thank my fortune for it, my ventures are not in one bottom trusted,
Nor to one place; nor is my whole estate upon the fortune of this present year: Therefore my merchandise makes me not sad.” So speaks Antonio in Act 1, Scene 1 of William Shakespeare’s ‘The Merchant of Venice’. Compare the injunction more than a thousand years earlier, of Rabbi Isaac bar Aha, contained in the Babylonian Talmud, that “One should always divide his wealth into three parts: a third in land, a third in merchandise, and a third ready to hand”.

Or more than a thousand years even further back, the rejoinder contained in chapter 11 of the Old Testament book of Ecclesiastes to “Divide your merchandise among seven ventures, eight maybe, since you do not know what disasters may occur on earth.” An alternative translation is to “…divide your investments among many places, for you do not know what risks might lie ahead.” I think you get the point that the principle of what we now call ‘portfolio diversification’ is not a new one.

So by the time Miguel Cervantes had Sancho Panza declare in ‘Don Quixote’ that the part of a “wise man [is] to keep himself today for tomorrow and not to venture all his eggs in one basket”, the idea was well established in literature. It took another 250 years or so, however, before the theory was formalized by a 25-year-old graduate student at the University of Chicago. His name was Harry Markowitz, and his paper, published in the June 1952 issue of the ‘Journal of Finance’ was called, simply enough, ‘Portfolio Selection.’

Essentially, Markowitz’s paper was a guidebook in preparing a ‘free lunch’, in the sense of reducing an investor’s risk without reducing expected earnings. The strategy was based around the construction of a portfolio of assets which balance out one’s exposure to risk, rather than reinforcing those risks. Take, for example, a mythical economy in which there are only two investment opportunities, umbrellas and sunscreen. If the weather is sunny and dry, the investment in umbrellas will perform poorly, and the investment in sunscreen well. If the weather is wet and dull, on the other hand, the reverse applies. By diversifying your investment between the two, you are reducing the volatility (one important measure of risk) of the returns from your investment.

Markowitz’s genius was extending this idea to devise a strategy for reducing risk without reducing expected returns, and making it mathematically tractable. It was to earn him a Nobel Prize in Economic Science in 1990. Markowitz was not thinking about prediction markets in 1952, but an interesting perspective on the whole concept of prediction markets is the degree to which they can provide a hedging function for pre-existing risks. For example, film studios might ‘sell’ (or ‘lay’) the success of their box-office receipts as a way of partially insuring their investment.

Similarly, a politician up for election can back his opponent as a way of insuring against a defeat at the polls, as can those likely to be adversely affected by the election of a particular candidate. And what happened to Antonio? For all his diversification, he hadn’t foreseen the apparent effect that the fickle finger of fate had unleashed on his far-off merchant ships, and before he learned the truth it had almost cost him a pound of flesh. If only he could have consulted a prediction market!

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Prediction Market Theory: What the 2009 Epsom Derby can tell us about the market, and about the ballot box!

By Leighton Vaughan-Williams
June 9th, 2009

The Betfair Prof, Leighton Vaughan Williams, takes a look at the ins-and-outs of the Epsom Derby…

The weight of opinion among the spokesmen of the major bookmakers, as reported on the morning of Epsom Derby Day, was that the John Oxx-trained ‘Sea the Stars’ would go off an even more sold favourite than he was in the early trading. And indeed, all the 7 to 2 soon disappeared, to be replaced on the bookmakers’ boards by 11 to 4, and by the time the market opened on course, that price (bar the odd 3 to 1 and 5 to 2 in places) was pretty much set in stone.

Meanwhile, Criterium de Saint Cloud winner ‘Fame and Glory’, available at a general 4 to 1 in the morning, opened on course at 7 to 2, touched 4 to 1 in places, and after frantic late trading, went off as 9 to 4 favourite. What happened? Well, an enormous late plunge, including one confirmed wager of £40,000 to win £110,000 might have had something to do it! All those 7 to 2 and 4 to 1 offers were soon wiped off the boards and market-watchers who like to follow in those bettors who unload the biggest satchels might perhaps have been forgiven for thinking the horse was home and hosed before it even exited the stalls.

In the event, the Montjeu colt performed creditably enough, and might well have benefited from a stiffer pace, but was never going to prevent Mick Kinane from following up his 2001 Derby success on Sea the Stars’ half-brother Galileo.

So what can we learn from this? Well, the consistent money pointed firmly in the direction of Sea the Stars. The money for ‘Fame and Glory’ was late and big, but from what we can ascertain derived from a few very large individual punts. Still, money is money, and prices in a market respond to the weight of it, wherever it comes from. But live, flesh-and- blood price-setters need not respond solely to the sheer relative volume of money about different horses, but also to what information the money is imparting. Would you as a price-setter respond in the same way to ten bets of £4,000, placed gradually throughout the day, as you would to one £40,000 punt three minutes before the off? And should you?

In the event, we know that the late and very large plunge came for the unbeaten colt that was already known to travel and to stay. And we were confirmed in our knowledge that he travels and stays. The only part of the triumvirate of qualities that wasn’t confirmed was his unbeaten status. If the market was like a ballot box in a first-past-the-post election, the winner of the 2009 Investec Derby and the winner in the market would, I judge, have been one and the same. But betting markets don’t work quite like ballot boxes. Most obviously, you can buy more than one vote.

And so the market got it wrong and the ballot box (most probably) got it right. Would that the same were always true in the world of politics!

Tags: Betfair Prof, Epsom Derby, fame and glory, horseracing predictions, montjeu, politics predictions, prediction exchange, Prediction Markets, sea the stars Posted in Betfair Prof, Blog, Horseracing, Prediction Market Theory, Prediction Markets |

Prediction Market Theory: Alice’s adventures in the looking glass world of prediction markets!

By Leighton Vaughan-Williams
June 1st, 2009

What’s Alice In Wonderland got to do with Prediction Markets? It’s a wonderful world, says Leighton Vaughan Williams…

When Alice journeyed through the looking glass, Lewis Carroll tells us, she came across a Queen who claimed to be “one hundred and one, five months and a day.” “I can’t believe that!” said Alice. “Can’t you?” the Queen said in a pitying tone. “Try again: draw a long breath and shut your eyes.” Alice laughed. “There’s no use trying”, she said: “one can’t believe impossible things.” “I daresay you haven’t had much practice,” said the Queen. “When I was your age, I always did it for half-an-hour a day. Why, sometimes I’ve believed as many as six impossible things before breakfast.”

Well, there’s not space enough to consider six impossible things here, but let’s think of one, and it’s a big one. It’s the idea that market prices, be it the stock market or the Betfair market or any other person-to-person betting market, already incorporate and fully reflect all available information. And so you can’t beat the market, unless you get lucky.

Economists call this idea the ‘efficient market hypothesis’ and such a world as ‘informationally efficient.’ Now there’s a problem with this ‘looking glass’ world because in it nobody has an incentive to gather information. Why? Because information acquisition is costly and would add nothing to what can be obtained by simply looking at market prices. But if nobody acquires costly information, no trading will take place. And if nobody trades, what drives the market prices to incorporate and reflect all available information, i.e. what keeps the markets efficient?

It’s called the ‘information paradox’, first formalized in a paper published by Sanford Grossman and Joseph Stiglitz in 1980, called ‘On the Impossibility of Informationally Efficient Markets.’ The same applies if information is costless to obtain but there are trading costs. In the real world, of course, there are both information and trading costs, and we have a paradox in spades. But still we are told that the market is informationally efficient. Welcome to the looking glass world of modern financial economics!

So is there a solution to the paradox? Consider the case of a betting market about the age of the looking glass queen. Let’s say nobody knows but lots of people are making guesses, some better informed than others, and betting looking glass money on the basis of these guesses. The queen just hasn’t been telling. Now she has told Alice, and the market will be settled later in the day when she tells the same to the whole world, one in which impossible things really are believed.

Well, Alice has a little bit of time to place her bets before the rest of the world get to know the truth and if she’s clever she’ll bet enough to drive the market to the conclusion that the queen really is one hundred and one, five months and a day. And when the queen announces this is so, everyone will believe her. Alice will be rich, in a looking glass kind of way, and the queen will be not a day older. And the market will be efficient once again! And I think to myself, What a Wonderful World!

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

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Prediction Market Theory: Would John McCain have raised taxes? There’s no need to guess. Just ask the prediction markets!

By Leighton Vaughan-Williams
May 20th, 2009

On September 4th, 2008, Senator John McCain of Arizona delivered his acceptance speech at the Minnesota-St Paul Republican convention as the party’s nominee for President of the United States. For a fleeting few days thereafter it looked as if he and his Alaskan running-mate might actually win the keys to the White House. Indeed, for a short while around this time, the respected political and election forecasting web-site, www.fivethirtyeight.com, had Mr. McCain as slight favourite to succeed George Bush, and the prediction markets were never to see it closer. For the record, Betfair traders were never quite as convinced as most others in the world of election forecasting, but it was getting closer.

It was quite reasonable, therefore, that on September 9th, Greg Mankiw, Professor of economics at Harvard University, should ask the prediction markets to reveal what kind of tax policy the US would get if John McCain should be elected President. We knew the Republican candidate’s stated policy, which was that of making the Bush tax cuts for the wealthy permanent. But what would he actually do if given the opportunity?

For this Professor Mankiw looked to an esoteric Intrade market about the likelihood of the top US income tax rate in 2011 exceeding 38%. He calls this the “Probability of a Tax Hike”, i.e. P (tax hike). It was already part of Barack Obama’s policy platform to introduce this scale of taxation, and politicians do not tend to under-state how much they are likely to increase taxes, and so given the very likely shape of the Congress, Mankiw attributed the probability of such a tax hike in an Obama administration as a sure thing, i.e. P (tax hike) = 1. Using a complementary estimate of the probability of Mr. Obama being elected President of 53% (0.53), he is able to create two new probability scores, i.e. P (Obama) = 0.53 and P (McCain) = 0.47. Now comes the interesting part of the exercise, which is the use of conditional probabilities to estimate the likelihood of the tax rise under a McCain Presidency.

The formula is straightforward. Probability of a tax hike , i.e. P (tax hike) = Probability of a tax hike GIVEN THAT Obama wins times the Probability of an Obama win, plus the Probability of a tax hike GIVEN THAT McCain wins times the Probability of a McCain win. Using conventional symbols, this can be written as: P (tax hike) = P (tax hike I Obama) P (Obama) + P (tax hike I McCain) P (McCain). We have numbers for all of these variables except for the probability of a tax hike by a President McCain. It’s a matter of simple arithmetic, therefore, to deduce what the prediction market says about the likelihood of this. It can be calculated as 0.87 minus 0.53 all divided by 0.47, or 72%. If we reduce the probability of an Obama tax hike from 1 to, say, 0.9, this simply increases the implied probability of a tax increase by McCain (in this particular case, from 72% to 84%).

So would John McCain have raised the top rate of income tax if he’d been elected? Well, the conditional probabilities have been consulted and they’ve given their answer. Yes he could have, and in all likelihood, yes he would have!

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Prediction Market Theory: Why does the poker market differ from the prediction market?

By Leighton Vaughan-Williams
May 14th, 2009

Or does it?  The Betfair Prof, Leighton Vaughan Williams, tells all…

Poker professional ‘Action’ Dan Harrington relates a tale of the day a tournament-playing friend of his made a first foray into a no-limit hold’ em cash game. The friend bought in for 100 big blinds and soon picked up the Ace-King in early position. He raised and got three callers, including the two blinds. The flop came King – 10 - 9, and the first-timer was feeling confident staring down at his top pair, top kicker. Then the small blind bet and the big blind raised. He pushed all-in and got three callers. “How am I doing?” he excitedly asked Dan. “You might be third best “, replied the professional. In fact, he was fourth best, beaten by a set of 9s, a set of 10s and a straight that held up.

As Harrington explains, “His hand (top pair, top kicker), which is an excellent hand in most tournament situations, is a relatively weak hand in a deep-stack cash game when all the money goes in.”

Having said that, we have to accept this particular cash-game novice was at least a little unfortunate.

Take now a different example, of another novice being dealt a pair of sparkling Aces in the big blind. He raises, and is called by a couple of early limpers who have position on him. The flop comes down 10 spades – 8 clubs – 6 diamonds. He makes a robust bet with the overpair and is called again by both opponents. The Queen of Clubs comes down on the turn and he bets again, and is called again. The river reveals the 2 of spades, he bets and is called all-in. How good are the sparkling Aces likely to be here? Well, our novice may be up against a player excited by a pair of Queens, or perhaps by a sophisticated bluff, but then again he may be up against two pair or better, and it’s (just) possible that he’s sophisticated enough to be able to judge the difference. In all probability, though, he’s beat. Yet many players clutching the Aces would call instantly in this situation, and most of the time they’d lose at least a good part of their stack. As did our novice, to a Queen-high straight!

The problem is that the player holding the big pair knew he was once ahead, and it’s part of the human condition that we generally fail to fully, or at least sufficient quickly, adjust to revised circumstances, especially when those circumstances mean we should revise downward.

What was the information our novice failed to adjust to properly? First, he failed to adjust to the fact that an overpair is a big hand before the flop, while an overpair in a game which has reached the river after a sequence of raised pots is at best a mediocre hand. He also failed on this occasion to fully adjust to the behaviour of the other participants in the market.

James Surowiecki, in his book, ‘The Wisdom of Crowds’, identifies ‘independence’, which he defines as a situation where “people’s opinions are not determined by the opinions of those around them,” as an important condition for group accuracy, and therefore for the accuracy of a prediction market.

So why does the poker market differ from the prediction market? Or does it? Any thoughts?

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

Tags: leighton vaughan williams, poker, Prediction Market Theory, Prediction Markets, the betfair prof Posted in Betfair Prof, Blog, Prediction Market Theory, Prediction Markets |

Prediction Market Theory: If crowds are so wise, why can’t they solve a million dollar maths challenge?

By Leighton Vaughan-Williams
May 8th, 2009

On 24 May, 2000, during a meeting held at the College de France in Paris, the challenge was made. A million dollars would be paid to anyone offering a proof or a counterexample to any of seven mathematical conjectures.

The offer was made by Arthur Jaffe, co-founder (with Landon Clay) of the Clay Mathematics Institute. In the same year, British publisher Tony Faber offered a million dollars to anyone who could prove that every even integer greater than 2 can be expressed as the sum of two (not necessarily different) prime numbers, e.g. 74 can be expressed as the sum of the prime numbers 31 and 43. This is the ‘Goldbach Conjecture’, first formally proposed in a letter dated 7 June, 1742, from Prussian mathematician Christian Goldbach to Leonhard Euler. The purpose of the Faber offer was to publicize ‘Uncle Petros and Goldbach’s Conjecture’, a novel on the Faber and Faber publishing list by Apostolos Doxiadis.

What is especially interesting about all these million dollar prizes is that they have the potential to incentivize and focus the minds of a diverse set of amateur and professional mathematicians around the world. In other words, to tap into the wisdom of the crowd.

So nine years later, where are we with Goldbach and his primes? Faber and Faber have sold quite a few books. That much is known and could have been predicted. It has also been shown by computer that Goldbach’s Conjecture is true for all even numbers up to 1,200,000,000,000,000,000. Even so, we are no closer to a formal proof than we were when the prize was announced.

How about the conjectures identified by the Clay Mathematics Institute? Better news here. Of the seven one has been proved, the one that states in simple terms that ‘a sphere is a sphere is a sphere’, i.e. no matter what you do to it other than tearing it (punch it, pinch it, kick it, twist it, squeeze it, squash it, poke it, inflate it, deflate it), it remains a sphere, even when the surface of the sphere is in three dimensions (the surface of an ordinary sphere is two-dimensional, of course, though it encloses a three-dimensional volume). Put more rigorously, the conjecture can be expressed as ‘Every simple connected, compact three-dimensional manifold (without a boundary) is a three-dimensional sphere.’ Got it?

Anyway, this is the Poincare conjecture, named in honour of French polymath Jules Henri Poincare, and proved in 2003 by Grigori Perelman, though he’s declared that he doesn’t want the prize. The other six conjectures remain unresolved. For the record, these relate to the Hodge Conjecture, the Birch and Swinnerton-Dyer Conjecture, the Riemann Hypothesis, Yang-Mills Theory, the Navier-Stokes Equations and the P versus NP Problem. So here we have a market the size of the world and a total of 8 million dollars worth of liquidity, and only one of the conjectures has been proved, and that by someone who shuns the crowd and hasn’t even bothered to pursue the formal conditions required to pick up the prize.

So we are left with the obvious question. If crowds are so wise, why can’t they solve a million dollar maths challenge? Any takers?

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

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The Betfair Prof: “The Angel was always going to surprise us on Easter Sunday, but not before the markets had all but lost faith!”

By Leighton Vaughan-Williams
April 14th, 2009

The statistics told us that 17 of the last 18 winners of the US Masters golf tournament had started the fourth day in the final pairing, the exception being Zach Johnson in 2007. The final pairing this time was Kenny Perry and Angel Cabrera. Perry, at 48 years of age, was bidding to become the oldest winner of a major ever, and to supplant Jack Nicklaus as the oldest winner of the Masters. As for Angel Cabrera, he was bidding to become the first South American to win the Green Jacket, although Roberto de Vicenzo came close in 1968, shooting the lowest score but failing to fill in his card correctly.

As the final day started, Cabrera was the marginal favourite, though the Betfair odds about both were close enough to the equivalent of 5 to 2, meaning the implied odds of a victory by one of the final pairing was a little but not hugely better than evens. Clearly the market was not overly impressed by the 17 out of 18 statistic.

For students of golf history, an interesting parallel to what was to happen was provided by the man who beat Perry in the play-off of the 1996 PGA Championship, Mark Brooks. What’s interesting is that the only other time I recall seeing Brooks in the play-off of a major was the time he took Retief Goosen all the way in the 2001 US Open held at Southern Hills, Tulsa. Brooks was cruising as he teed off on the seventeenth, shortening instantly from 4 to 6 into 1 to 5 when he found the green, despite being no little distance from the hole. A decent shot from Goosen and Stewart Cink later, he was out to 9 to 4, and by the time these two lined up at the eighteenth tee, Brooks was trading at 20 to 1. In the end, he lost the play-off but the point is the same, and it’s a simple one. Siding with the in-running favourite in golf tournaments appears to be very much of a fast route to the poorhouse.

So let’s bring the history up to date and check this contention. We are at the seventeenth hole of the 2009 US Masters and Perry’s nemesis, Brooks, is nowhere to be seen. With a two-shot lead on the seventeenth, the Kentuckian is trading at as low as 1.13 on Betfair. It seems all over. Yet a couple of wayward shots later and you could back him at a shade longer than 2 to 1 to win a 3-man play-off. Soon enough Chad Campbell was backable at no longer than 1.63, after hitting a fine drive down the fairway of the first play-off hole. Meanwhile, most people had written one man off. And then, on Easter Sunday, the Angel appeared and took them by surprise!

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

Tags: angel cabrera, golf betting, golf predictions, leighton vaughan williams, prediction exchange, Prediction Markets, the betfair prof, US Masters Posted in Betfair Prof, Blog, Golf, Prediction Markets |

Prediction Market Theory: What does Mon Mome have in common with Caughoo, and why is it so important for prediction markets?

By Leighton Vaughan-Williams
April 6th, 2009

Only five winners of the Aintree Grand National have been returned at a starting price of 100 to 1. The first was Tipperary Tim in 1928, followed by Gregalach in 1929, Caughoo in 1947, Foinavon in 1967 and of course Monmore on the day before Palm Sunday, 2009.

Which of these was really the longest shot at the start? Well, a comparison of the Tote odds reveals that a bet on Mon Mome in the Tote pool would have returned you odds of about 157 to 1, compared to a staggering 444 to 1 about Foinavon and 202 to 1 Caughoo. Unfortunately, we can’t extend the comparison to the first two 100 to 1 winners because horserace Tote betting didn’t get going until July 2nd, 1929. This year we have the added dimension of the Betfair SP, of course, and this returned Mon More at 142 to 1 (though a lot longer in running). Still, there’s no denying that these five horses share the distinction of being honorary members of the SP ‘ton-up’ club.

What is it, then, about Mon More and Caughoo that distinguishes these heroes of the track from the other three? The answer is betting tax!

Introduced by Chancellor of the Exchequer, Winston Churchill, on November 1st 1926, at a rate of 2 per cent on bets made on a racecourse, and 3.5 per cent on bets in registered betting offices, the Churchill betting tax was so unpopular and ineffective that less than three years later it was gone. Between the introduction of the tax and its demise, however, two horses had won the Grand National at a returned SP of 100 to 1.

Strangely enough, Caughoo’s victory marked the year that another Chancellor would decide to tinker with betting tax, as Hugh Dalton brought in a surprise tax on greyhound Tote bets and on the football pools. No matter. Backers of Caughoo were in any case returned a full 100 shillings to their shilling, and not a penny less. The first time backers of a 100 to1 Grand National winner were returned what they earned. Betting tax on horses was not to be seen again until 1966, when the Chancellor James Callaghan re-introduced it a rate of 2.5% of turnover. The dreaded turnover tax was back, just in time for Foinavon to spring his famous come-from-behind victory the following year.

It was to be another 35 years, October 6th, 2001 to be precise, before the tax on betting turnover was laid to rest and replaced with a tax on bettors’ losses, known as the ‘gross profits tax’. The effective incidence of the tax was significantly lower than the tax it replaced, and was not passed on to bettors. The ‘Golden Age’ of betting, as I have termed it, had arrived. And why was this so important for prediction markets? Because the switch from a tax on turnover (quantity) to a tax on margins (price) was critical in allowing low-margin, high-turnover, person-to-person betting exchanges like Betfair to thrive. And because the new tax regime encouraged well-informed, skilled bettors to enter, thereby creating more efficient information markets.

For these reasons, October 6th, 2001 can be seen not just as the beginning of a new Golden Age of Betting. It also marks the birth of the Golden Age of prediction markets! Note it in your diary, and celebrate!

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

Tags: Betfair Predicts, grand national, leighton vaughan williams, mon mome, prediction exchange, Prediction Markets, the betfair prof Posted in Betfair Prof, Blog, Horseracing, Prediction Market Theory, Prediction Markets |

Prediction Market Theory: “Winning Like A Longshot Shouldn’t!”

By Leighton Vaughan-Williams
March 30th, 2009

A cautionary tale from Leighton Vaughan Williams for followers of the Betfair market…

It was available at 18 to 1 at the opening of trading in the morning. The bookmakers and exchanges were more or less agreed about that. It was prominently tipped in the ‘Racing Post’ and soon shortened. By the time the on-course market opened, however, it was out to 20 to 1 and started at 22 to 1. On Betfair, meanwhile, you could get the equivalent of about 33 to 1 the win and 13 to 2 the place.

Sound attractive? Really depends on the information implied by the drift in the market. On the face of it, it doesn’t sound promising. 18 to 1 in the morning, available at as long as 33 to 1 at the off, and little support in the place market either. If a marked shortening of the odds about a horse during the course of the day can be interpreted as evidence that the probability of the horse winning is greater than that implied in the early odds, a marked lengthening would seem to indicate the opposite.

So what do you do if you’ve already grabbed a piece of the action at 18 to 1, perhaps each-way, when you spot the way the wind is blowing. Lay some of it off at 33 to 1 or so? Doesn’t sound particularly appealing, unless you’re pretty sure that the drift implies something sinister! Maybe lay off a bit in the place market?

If the market is efficient, and the new odds reflect the true probabilities, the case for laying off any of your original stake is purely a means of hedging your risk. Of course, you might well be led to believe that the horse the layers can’t seem to give away is as good as beaten before it leaves the stalls. In this case, laying back some of the stake would be a rational way of reducing your expected loss.

I’m not talking hypothetically here. I’m talking about what happened on Saturday in the William Hill Spring Mile at Doncaster. The Brian Meehan-trained ‘Manassas’ was the horse in question. Available at 18 to 1 in the morning, the four year-old bay gelding was appearing on a racecourse for just the fifth time. Off the track for no less than 337 days, and something of an unknown quantity, there was no obvious reason to explain why he should have drifted in the market. For that very reason, perhaps, many of the early morning backers could have been forgiven for taking fright and laying back a bit just before the off.

And were they right to do so?

It took this veteran of the Group 1 Jean-Luc Lagardere at Longchamp less than 1 minute 38 seconds to provide the answer. Always travelling well, he hit the front over a furlong out and won like a longshot shouldn’t.

Thanks Manassas! You made my weekend.

Professor Leighton Vaughan Williams is the Director of the Political Forecasting Unit and Betting Research Unit of Nottingham Business School, Nottingham Trent University

Tags: horseracing predictions, leighton vaughan williams, Prediction Market Theory, Prediction Markets, the betfair prof Posted in Betfair Prof, Blog, Horseracing, Prediction Market Theory, Prediction Markets |