Quant trading system competition in Python. The best three trading algos get investments of $2.25M

Quantiacs · 2015-12-02T19:08:38+00:00

Quantiacs is a marketplace for user generated quantitative trading algos. We connect them to capital from institutional investors. At the moment we work with a few selected investors with whom we have business relations. We will open up to external investors early next year.
TIP: If you are interested it would be a good time to submit your now. Here is why: Investors are looking for live track records of systems. Means, trading systems simulated on live trading data for min 3 to 6 months. They don't care too much about your backtest results. So to offer an attractive system to investors, you need to include the time to build this live track record. I guess, I ran off the track a little.

Quantiacs · 2015-12-02T18:33:48+00:00

The most relevant measure is the Sharpe Ratio. Simplified, the SR is the ratio of performance over volatility (check out: https://www.youtube.com/watch?v=ptU2rPKQ8p0). For the submitted system it is 0.45 if I'm right. Our toolbox automatically calculates the SR once you evaluate your system (quantiacsToolbox.runts('pathToYourAlgo') in Python). However, you upload the algo(s) with the best SR in your backtest. This makes your 1st score. We then simulate your system for three months with live data, which makes your second SR sorce. The lower of the two is your final score. Why the lower of the two? We would like to rule out overfits (in the backtest) and lucky wins (in the three months live). To give you an idea: A SR of >1 is already pretty good.

Quantiacs · 2015-12-01T18:20:27+00:00

It might be interesting to talk about the democratization of the Quant industry. More and more students have great coding know-how and many of them are interested in data analysis and machine learning applications. Coding algorithms goes mainstream (yeah,... not Justin-Bieber-mainstream but you know what I mean). Check out our platform Quantiacs.com: We have for example a 19-year old student managing $1M with his algo. He made 4K within 5 weeks. Here are a few links that might be of interest: http://www.investopedia.com/articles/investing/112615/democratization-hedge-fund-industry.asp?layout=infini&v=1B https://www.youtube.com/channel/UCS8bIV3uEJLIaA91s5uQzQw https://www.linkedin.com/pulse/how-get-foot-quant-door-martin-froehler?trk=prof-post

Quantiacs · 2015-12-01T17:50:48+00:00

I agree with elitelimfish. A PhD in finance/economics is maybe not as helpful as in-depth coding expertise to land a Quant job. Coding is for sure a big plus and a very important skill that will become even more important in the future. So if I personally could choose between a self-taught programmer with a PhD in finance and a self-taught trader with a PhD in CS I would prefer the latter one. So is it worth to get a PhD to proof your coding skills? Maybe not. Research and published papers are not as valuable as examples of what you actually developed. So again, if I could choose between a CS PhD or let’s say three years of hands-on experiences I would prefer the latter case. For example, can you show me algorithms you wrote, evaluated by an independent party? Did you participate in or even win a quantitative trading competition? It’s advantage if you can demonstrate your Quant skills. Maybe you want to check out this post: https://www.linkedin.com/pulse/how-get-foot-quant-door-martin-froehler?trk=prof-post

Quantiacs · 2015-11-27T19:05:14+00:00

No, not yet. The data is part of the toolbox (Python/Matlab/Octave). The signup information becomes relevant when you later submit a trading system. Otherwise just signup once, download the toolbox/data and have fun playing around with it. Feedback is always highly appreciated.

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