These are the questions I ponder every day, all day. And most nights. I take great comfort knowing I’m not the only one!
Kevin Q said it well, we are betting on the community to produce quality algorithms.
For Quantopian, quality means we can have a high confidence that a strategy will have a positive Sharpe ratio and low correlation, after we allocate capital to it. Think of Quantopian as a boost algorithm in machine learning. As long as we find algos that are marginally better than random, we can combine them into something compelling. Imagine if the community produces, as I expect they will, algorithms that are much higher quality than that bare minimum – the combination will be remarkable.
We are working on guidelines for algo writers, to help translate our fund goals into more concrete direction for the community. The guidelines are a work in progress, but here are some of the key characteristics we want:
- diversified holdings
- low net market exposure (balanced short and long exposure)
- actively trading
- low beta to broad market(s) and risk factors
- low correlation to the rest of the portfolio
- low leverage (so the fund can control total leverage)
- low cash balances
My goal is for the guidelines to be concrete, but not a cook book. I want to be sure that we are leaving room for this community to do the creative work.
All of this depends on Quantopian providing the best algorithmic finance platform in the world.
For the platform, I chose a breadth-first product strategy since inception. I wanted to have the complete workflow from idea to live trading as quickly as possible. Happily, I think we hit that point this quarter — you can now research (beta), develop, backtest, forward test, and real money trade on Q.
Starting now, you’ll see us shifting focus to add depth to the platform. We’ll add more markets, more data, and flesh out our APIs. We’ll support larger portfolios, parameter optimization, and code reuse.
I’d like to address Grant’s concern that we can’t be a $10b hedge fund and a community driven fund at the same time. We will do both.
The key is that Quantopian will manage trading operations. That means our trading desk will cope with algos failing to borrow for shorts, market closures, stock halting, rebalancing among algorithms, and all the myriad daily battles to keep all our fund algos running smoothly.
That means a person can have an asynchronous relationship with the algorithm - pace your work to research and create an algo in a way that fits your life, without facing the prospect of maintaining that algorithm 252 trading days a year. Q can be your side-hustle, second career, hobby, or primary source of income. Scientists, professors, stay-at-home parents, engineers, and professional quants can all work this way. Maybe you have one idea a week, maybe you have one idea a year, but you’ll always have Q ready to back the best ideas.
The platform is there to help you create fully automated strategies. We’ll be taking the responsibility and risk for allocating to your strategy. So once it is written, why couldn’t a community algo writer have $5, $10, or $100M allocated to his/her strategies? The same argument applies to running smaller allocations - with a fully automated strategy why not run $100, $50, or $10k?
As an algo writer, you invest your time and you trust us with your ideas. In exchange, you don’t have any expenses to develop your strategy, you don’t need to take on the risks or effort associated with operating it, you don’t need to raise capital to fund it. But, by virtue of your efforts and creativity, you’ll share in the upside.
Thanks for being a part of Quantopian,