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> I mean each day 100's of Phd's... Yes, but then... "Finance novice beats hedge fund pros, winning $100k in Quantopian trading contest" https://pando.com/201

by joeyspn 10y ago

> I mean each day 100's of Phd's... Yes, but then... "Finance novice beats hedge fund pros, winning $100k in Quantopian trading contest" https://pando.com/2015/03/05/finance-novice-beats-hedge-fund-pros-wins-100k-in-inqugural-quantopian-trading-contest/ https://pando.com/2015/03/05/finance-novice-beats-hedge-fund... Thousands of brilliant people are out there undiscovered and I think quantopian does a great job leveling the playing field.

dragonwriter 10y ago
Novices sometimes beating pros is something you'd expect to be true the more performance was due to luck rather than strategy. If it was strongly strategy-dependent, best-information would win predictably and consistently.
- lpage 10y ago
  Yup. Incidentally this is exactly the same effect that makes model selection within a portfolio challenging. Two worthwhile reads on that front: the multiple comparison problem [1] and regression towards the mean [2]. Regardless of your objective - hosting a contest like this or allocating to individual institutions and strategies - you'll always face this problem. Good allocation decisions are tactical, taking both the logic of the strategy and the broader portfolio into account. Bad allocation decisions chase returns. [1] https://en.wikipedia.org/wiki/Multiple_comparisons_problem https://en.wikipedia.org/wiki/Multiple_comparisons_problem [2] https://en.wikipedia.org/wiki/Regression_toward_the_mean https://en.wikipedia.org/wiki/Regression_toward_the_mean
gedrap 10y ago
Equally, there are many athletes that play at amateur/semi-professional level and suddenly they are top level starts (e.g. Chris Smalling, Jamie Vardy). So yes, it's possible. It's just that the odds are not in your favor :) should you keep chasing your childhood athlete dream because someone did it? Probably not :) Same rules apply to your example.
oldmartin 10y ago
"Yes, but then... "Finance novice beats hedge fund pros, winning $100k in Quantopian trading contest" Not sure if you know, but that winning algorithm was taken offline within one month for poor performance. It was probably just overoptimised on past data to win the competition and then failed miserably out in the real market.

by joeyspn 10y ago

dragonwriter 10y ago

Novices sometimes beating pros is something you'd expect to be true the more performance was due to luck rather than strategy. If it was strongly strategy-dependent, best-information would win predictably and consistently.

lpage 10y ago
Yup. Incidentally this is exactly the same effect that makes model selection within a portfolio challenging. Two worthwhile reads on that front: the multiple comparison problem [1] and regression towards the mean [2]. Regardless of your objective - hosting a contest like this or allocating to individual institutions and strategies - you'll always face this problem. Good allocation decisions are tactical, taking both the logic of the strategy and the broader portfolio into account. Bad allocation decisions chase returns. [1] https://en.wikipedia.org/wiki/Multiple_comparisons_problem https://en.wikipedia.org/wiki/Multiple_comparisons_problem [2] https://en.wikipedia.org/wiki/Regression_toward_the_mean https://en.wikipedia.org/wiki/Regression_toward_the_mean

gedrap 10y ago

Equally, there are many athletes that play at amateur/semi-professional level and suddenly they are top level starts (e.g. Chris Smalling, Jamie Vardy). So yes, it's possible. It's just that the odds are not in your favor :) should you keep chasing your childhood athlete dream because someone did it? Probably not :) Same rules apply to your example.

oldmartin 10y ago

"Yes, but then... "Finance novice beats hedge fund pros, winning $100k in Quantopian trading contest" Not sure if you know, but that winning algorithm was taken offline within one month for poor performance. It was probably just overoptimised on past data to win the competition and then failed miserably out in the real market.