Computational World Cup

The Financial Times’s Alphaville blog recently covered a number of quantitative models for predicting World Cup outcomes – models developed by well-known “quant” desks.  Though this may seem like a waste of brains and shareholder value, World Cup outcomes are historically predictive of regional equity performance; furthermore, recent trends in securitization have not passed over sports as large as soccer.  Here are the respective desks’ picks:

  • JPM: England 1st, Spain 2nd, Netherlands 3rd (notes)
  • UBS: Brazil 1st, Germany 2nd, Italy 3rd (notes, p. 37)
  • GS: England, Argentina, Brazil, Spain (unranked) (notes, p. 71)
  • Dankse Bank: Brazil 1st, Germany 2nd (notes)

As could be expected, there is some disagreement as to the value of these predictions.  Gary Jenkins of Evolution Securities chimes in with his own thoughts:

Yes it’s that time again when analysts like me who can barely predict what is going to happen in the market the following day turn away from our area of so called expertise and instead focus our attention on who is going to win the World Cup. I first got involved in this attempt to get some publicity 8 years ago, when Goldman Sachs produced a report combining economics and the World Cup and included their predictions as to who would get to the last four (I believe they got them all wrong) and had Sir Alex Ferguson pick his all time best World Cup team. I decided to do the same thing but had to explain that we could not afford Sir Alex. Thus I got my dad to pick his all time team. It caused more client complaints than most of my research and my favourites to win the tournament got knocked out early, so I abandoned this kind of research for a while.

Again, for more interesting coverage of the real-world effects of the World Cup, see FT Alphaville’s South Africa 2010 series.  P.S. Go Azzurri this afternoon!

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