Quantopian is home to 120,000 people learning algorithmic trading, including students, data scientists, academic researchers, developers, and finance professionals.
We provide a research platform, market simulation, and data for free. We also provide tutorials, community, and lectures to teach you how to get good at it. I recommend you take a look at the Getting Started Guide (https://www.quantopian.com/tutorials/getting-started) and then start going through the Lectures (https://www.quantopian.com/lectures). The lectures cover some important statistical topics, and they get into how to apply those concepts to algorithmic trading.
Quantopian's revenue model is to build a hedge fund and charge the fund investors returns/management fees. The algorithms in the hedge fund come from the Quantopian community. We work with the best algorithm writers on our platform, negotiate compensation, and then put their code to work.
We would be crazy to charge people to use our platform. We need thousands of algorithms, and charging for the platform would be one of the faster ways to kill our business.
Yes, you can code to Interactive Broker's API. But where would you get your free minute historical data for backtesting? Or corporate fundamentals data? Or the free IPython research environment? Or the community of 60,000 quants giving each other mentoring and advice?
I work at Quantopian, so you can imagine my answer to all of those questions.
In fairness, your (commendably candid) FAQ states the precise opposite "In the future we plan to charge for live trading, when you trade your algorithms through your brokerage account"
Is Quantopian free?
Quantopian's community and backtester is free for everyone to use. There will be a charge for connecting your algorithm to your brokerage. Pricing isn't finalized, but we're considering a flat monthly fee.
There's a slightly different methodology here, but one consistent with what you're looking for.
On one line, buy-and-hold the S&P 500. Re-invest all dividends. You are 100% in the market at all times.
On the other line, buy-and-hold all companies run by female CEOs, weighted by the number of companies. Rebalance your portfolio every time a company is added or removed. You are 100% in the market at all times.
I think that if you look at the IPython notebook that the Fortune article refers to you can find the details spelled out in code.
(FWIW, the calculations are done by a she, not a he! It's my colleague Karen.)
We work very hard to make our interests aligned with our community members' interests. We don't literally make money from the algorithms in the contest. What we're doing is encouraging hundreds and thousands of new people to write algorithms. The best ones will be invited to join our hedge fund, we'll negotiate compensation with them, and we'll take investment from pension funds and endowments and the like. In that sense - yes, when our customers win, we win too.
As for the judging, I think you'll find it be very transparent. There are 6 return and risk metrics calculated for both the backtest and the paper trading. The 6 metrics are weighted equally to generate an overall score. You can see the metrics for every contestant and the combined score on the leaderboard. You can verify it all by downloading the CSV. https://www.quantopian.com/leaderboard
It's both forward-testing and backward testing. The algos have been locked since submission - some were submitted as early as 1/15, all were submitted by 2/2. That makes it both an in-sample and out-of-sample test.
Yes, the Quantopian platform includes default commissions. It also includes default slippage. No model is perfect, of course, but this is a tool that's had a lot of development.
I think you're looking at the trees, and you should step back and look at the forest.
The fraction of CEOs that are women is dramatically smaller than the fraction of the population that are women. There is no qualitative explanation as to why that should be true. So long as that remains true, it's worth looking into why it is true. The relative performance of the group is fair game for investigation.
There is no qualitative explanation as to why that should be true.
I think there are plenty of qualitative explanations especially if look back a few decades (since most CEOs are in their 50s).
Women didn't obtain the name number of university degrees as men until recently. Women often step out of the workforce in order to care for family, etc, etc.
All of these would explain where there would be a smaller pool of qualified women to take a CEO role.
It's obvious, women are better than men at certain things, such as running companies. That's what we're all trying to say here isn't it? Oh, wait, we want EQUALITY for both sexes. Well, then in that case why differentiate one sex as potentially better than the other? Why create that competition?
You retain ownership of the content you put in our system; everything you write is yours. Your intellectual property remains private and your own. You can read more about our policies in our terms and in our FAQ (https://www.quantopian.com/faq and https://www.quantopian.com/policies/terms)
Of course, there is no way that we can prove or guarantee that we're not peeking. Like anything else in the cloud, at some point it becomes a matter of trust. That's why we did our About page a bit differently (https://www.quantopian.com/about). We're all startup veterans with reputations in the industry. You can click the links there and find out who we know in LinkedIn, and see what they say about us. We hope that our good reputations make it easier for you to trust us. Of course, that is entirely up to you!
Trust can take care concerns of credit card transaction, banking, or privacy. But when it comes to trade secret, intellectual property, trust is irrelevant. If you're working on trust, you're on the wrong path.
Traders need to keep their algo close to themselves. What you can offer is not testing their algo on your platform, but separating the their critical algo from the commodity data mining then offer the latter. The latter is what most traders don't have and you can add value. The ability of separating the algo, might just be your competitive edge.
Another solution is to write the algorithm but avoid the hedge fund - lots of suits, and they take most of the money. You're better off if you trade it yourself.
People work for hedge funds because hedge funds provide mentorship and really powerful tools and lots of data to sift through. We're trying to provide all of those things, for free, at Quantopian. https://www.quantopian.com/ Check out our community (for mentorship), our backtester (very powerful, and open source), and our 11-years of minute-bar data - all for free.
We provide a research platform, market simulation, and data for free. We also provide tutorials, community, and lectures to teach you how to get good at it. I recommend you take a look at the Getting Started Guide (https://www.quantopian.com/tutorials/getting-started) and then start going through the Lectures (https://www.quantopian.com/lectures). The lectures cover some important statistical topics, and they get into how to apply those concepts to algorithmic trading.
disclosure: I work for Quantopian.