World Cup Forecasting Challenge For Quants
databuff writes "As a break from projecting the strength of subprime mortgages, credit default swaps, and other obscure financial instruments, quantitative analysts at Goldman Sachs, JP Morgan, UBS, and Danske Bank have modeled the 2010 FIFA World Cup. Now Kaggle has set up a forecasting competition, allowing statisticians to go head-to-head with these corporate giants. The challenge is to predict how far each country will progress in the tournament."
There are numerous problems here.
Firstly is very few fans of football can truly consider themselves independent enough to do this well. I will try, but I just know my bias's will in the end have some effect on the outcome of my selections.
Secondly it isn't just about stats at something like the world cup where there are very few second chances and It is a game where you can completely dominate the opposition and still lose to a single error or bad ref decision.
For the record, quants rarely try to predict things in the market. That's left to people who work in econometrics. The main job that a quant does is to price financial instruments in a way that is consistent with the market prices of other liquidly traded assets. I'm being deliberately vague about what precisely is meant by "consistent" because that often depends on the choice of model, but there are also model-free results which require certain asset prices to obey certain relations: put-call parity, for example.
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Worse than that, JP Morgan picked Slovenia to finish fourth. Ahead of teams like Germany and Slovenia.
...that's basically how credit default swaps work.
STFU spammer !
*looks at parent's UID*
*gasps*
A 4-digit prime UID !
*slowly backs away from parent's lawn, sweating profusely*
Ha ha, my mistake, carry on...
For just $10,000 in unmarked and nonsequential bills, Vinnie "the kneecap" is willing to venture a prediction as to when any particular team is going to drop out.
"When yous got a problem, pick Vinnie. We don't predict; we Promise."