My first real experience with risk management was working as a penciller for a bookmaker during my university days. Back then, there were no laptops and the book was actually a real book, not an Excel spreadsheet. The punter would receive a ticket with a largely illegible scrawl indicating details of the wager and hope (if collecting) that the ticket could be translated.
Bookmaking and market parallels
It struck me there are many parallels between the bookmaking industry and the financial services sector. No doubt a number of participants will gasp in horror at this assertion. ‘Parallels’ may be too strong a contention but perhaps there are some things we can learn from the world of professional wagering and apply to financial services.
For each race we would frame a field with risk (loss) parameters and initially set our board with unduly ‘expensive’ odds. These odds would be adjusted on the basis of betting patterns to attract or dissuade further bets, and an ultimate percentage book set just before the start reflecting preferred risk and return (an efficient frontier maybe? – the first parallel).
For those unfamiliar with the art of bookmaking, each set of odds is converted to a theoretical win percentage, so 3/1 represents a 1 chance in 4 of winning which equals 25%. A book is the cumulative total of odds offered and the theoretical ‘win’ rate is that percentage over 100. However, this makes certain assumptions about betting trends and how the book is weighted.
Data analysis is the second parallel. If there is one place where the amount of publicly available data is close to that of financial markets, it’s the form guide. I can find out how each horse has run under various conditions, with different weights, over multiple distances (with subsequent breakdowns over and within these distances), with a variety of experienced jockeys. If horses were an asset class, I could do a plethora of relative value analyses, which is actually what the bookies do to set odds in the first place – the third parallel.
So, surely this should allow me to make a fully informed decision when betting. Quite possibly, but does fully informed mean successful? Punters (wrongly) believe so. As we’ve seen, it’s how you interpret and what you do with the numbers that matters.
Take the Melbourne Cup. The bookies love it. It is one of the most difficult races to predict as evidenced by the odds on offer. Yet annually, as surely as Xmas comes, every person becomes an expert for the day. Given the amount of (not so smart) money wagered, Xmas does indeed arrive in November for the bookies as they can work their odds far better than when ‘plunges’ or a lack of diverse bets arrive.
“But,” I hear you say. “You must overlay the data with the vagaries of animal instinct - the horse just doesn’t get it or jockey’s poor judgment.” Quite true, but is this a fourth parallel to financial services? Is that akin to when stock pickers (or economists or macro analysts etc) overlay their own expertise after analysing the multitude of data available? Tosh – such facetiousness.
So let's put odds on financial forecasts
Perhaps though, an interesting exercise could be to ask analysts to add a ‘confidence weighting’ (i.e. odds) to their price target or call. I know for certain their number will be either right or wrong (so zero or 1 probability) but the real probability of accuracy lies somewhere in between.
That however doesn’t preclude and possibly invites some neat Bayesian inputs whereby the analyst can suggest ‘odds of X’ that the price target or number will be achieved. One would intuitively think these indications should be odds on given a coin toss is an even money bet. Analysts could change their odds subject to new inputs. They already change their price targets regularly.
Why not extend this to those wonderful business news articles where a cross section of experts is asked to opine on every main economic and financial indicator in the next 12 months? Please add odds so we can see how well you rate your form.
Consider the implications. One could start to follow an expert with far more confidence based on their form. An ‘outsider’ might be considered if they show some relative movement in form and we agree that all things mean revert eventually.
Moving from parallels, here’s what I consider the main difference between the bookies and the financial experts. If the former gets his efficient frontier and relative value analysis wrong, he loses his own money. Now, I am not suggesting that the complexities of financial forecasting and analytics be subject to individual penalties for experts being wrong but conversely, shouldn’t there be some degree of accountability? Particularly if they are wrong to a very meaningful extent. Perhaps the Form Guide for Financial Expertise? We would definitely have the data.
And we should extend this discussion in “That’s Racing Part 2: Revenge of the Disaffected Banker” to the ability of asset consultants to pick the best managers for asset classes.
But such an idea would be hobbled before it reached the finishing line.
Paul Umbrazunas worked for a bookmaker whilst at university before a long career in financial markets including debt capital markets, syndicate, ALM and Chief Operating Officer roles across Goldman Sachs, BZW, Deutsche Bank and Credit Suisse.