We’re building specialized tools & data sets that take focus and that frankly a hedge fund can’t or doesn’t want to do themselves. Those are the get rich schemes from Wall St hucksters of the past. We’re not peddling models that we say work so you should buy them too. Startups today aren’t creating simple sets of data or tools. I hear this often and the answer is because specialization matters now and alpha doesn’t equal a successful quant hedge fund. >”If it’s so great, why don’t you trade on it yourself?” That’s a marked difference from the “walled gardens” that previously dominated this industry. A user exports that data from Quandl to a high-end visualization service like ( ) or ( ) extracts subtle insights using an analytics tool like ( ) backtests an investment strategy using ( ), and then actually trades on that data using Quantopian again.Īll of these transitions are basically just a few clicks of the mouse: the integrations already exist. A data producer like ( ) publishes its social media sentiment index on ( ). One of the really neat things about this next generation of startups is how they all interact nicely with each other in an emerging “data ecosystem”.
> for non mission critical, non real time use cases? > crowdsourced “terminal” of sorts that would be reliable enough, at least
> analytic and visualization tools on top, essentially resulting in a > Once such a data platform has been built, could third party developers add Thanks very much for the mention of ( ) 🙂
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