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Comment by kolbe | Hacker News Reader

To me, this is the more interesting news.

"his star hire Jon Rubinstein, one of the creators of the iPod, will leave after 10 months as co-CEO."

Citadel recently got rid of Keven Turner, Microsoft's ex-COO, from the CEO position at Citadel Securities. It sounds like the experiment of hiring tech executives into asset management roles isn't producing very promising results.

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Kevin Turner isn't really a tech executive; he's a professional big company manager. Prior to MSFT, he spent 20 years at Walmart.

Turner wasn't exactly beloved at Microsoft either, at least by the field sales people who reported up to him.

Given how most 'tech' guys on sites like this think about finance, economics and markets, it's really not surprising. Trading isn't intuitive, there is no math formula that can save you (more like a thousand different formulas that maybe, just maybe can nudge you in one direction or the other), and you can't just throw money at the problem.

I beg to differ - nowadays most successful finance (Citdadel, RenCap, Susquehanna etc) are quant-driven and the primary costs are tech/research talent, data and servers - very similar to tech companies.

Don't know about quant-driven per se, all do use lots of technology and have large IT staffs, but that doesn't mean tech guys are driving trading strategy. Not much room left for making money off HFT/arbitrage, and while I do know of attempts to trade use AI driven strategy, it's not there yet.

When a tech exec transitions to successfully running a hedge fund, that'd be news.

> Citadel recently got rid of Keven Turner, Microsoft's ex-COO, from the CEO position at Citadel Securities.

I'd be careful to draw such broad conclusions as Citadel with our without Turner has extremely high staff turnover

I would argue that this is a questionable conclusion, given a sample size of 2 (or 3 or 4, for that matter)

When you're talking about executive performance at extremely large companies within specific industries in specific time frames, sample sizes are always too small to draw conclusions.

Then we are in agreement :-)

The thing is, small sample sizes, be it as they may, are still data, and drawing inferences off of them is the only thing we can do given the nature of our inability to experiment.

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