Edit: Looks like zak_mc_kracken beat me to it. Which I think just makes the point even more obvious
83 karma · joined January 12, 2012
Edit: Looks like zak_mc_kracken beat me to it. Which I think just makes the point even more obvious
But to your point, the CTO of the fund was a pure math phd who got into finance/coding when his advisors asked "Ok so now how are you going to make money". which is common for most of the heavy duty quants I know.
I'm actually in a related situation in which I'm competent in analysis (bachelors in physics) but I struggle with all the category theory inspired design patterns in functional programming.
Every book/article I've tried to read is either far too mathematical and so is disconnected from programming or is too close to programming and lacking in general foundations (ie: a monad is a burrito).
I would greatly appreciate any suggestions!
In retrospect, our sprites had their own lofi charm but yea, I never thought to just open up the WAD files.
TL;DR: Mobile web ad platform optimized through machine learning and powered by Apache Scala
Full Stack Engineer
* Polyglots and generalists preferred
* ML background a plus
* Buzzwords: Spark, Scala, Kafka, AWS, PHP, Angular, Mongo plus many more!
Kixer is a funded ad platform that helps app developers get more app installs through the use of targeted ads. It's a giant optimization feedback loop and has to be very fast as well. Small engineering team in Austin although remote is possible.
More information here: http://kixer.com/jobs/full-stack-engineer/
Mention HN!
Flash Boys however I can't even get through because the author backs an extremist negative position with completely incorrect facts. I fill with seething rage every time I realize how much more public exposure Flash Boys gets.
For a more accurate picture of the dollar I track the UUP ETF which pegs it's value to the dollars exchange rate over a basket of currencies. (Which btw has been on a steady downtrend in the past 6 months, definitely not doubling everyday)
[1]: http://www.invescopowershares.com/products/overview.aspx?tic...
I used to work in algorithmic trading (the kind which aims build consistent viable portfolios, not the HFT arms race).
This of course relies heavily on building your model, which can be anything from some simple linear regressions to more advanced techniques more commonly associated with the buzz word of machine learning, this applies to all predictive methods. You begin searching the training data to find optimal model parameters and then verifying performance on the validation set. The number ONE mistake I saw most was that when you get bad results on the CV set, going back to step 1.5 instead of just throwing the whole model out. To take your same core idea, tweak it slightly, add/remove a few parameters and restart the process. Unfortunately doing this enough times and your CV set starts to become the training set. Thus leaving your true validation set the day you turn it on live in production with real money.
It's never a good feeling to see your positively skewed returns in your training, testing and "CV" set morph into essentially a mean zero random distribution in production. This was quite an important lesson to learn for me.
I later added some other price information (gold, usd, s&p500)
I also agree FOSS is important but to 15 year old me, the fluid and polished experience of Mathematica was far more important to me than FOSS.
It was great once it finally was up and running but I'd only recommend it if you have a legitimate intellectual property concern and can't use github enterprise.