How this work?
- You use our platform to create investment algorithms.
- We work with you in all stages of the development, from idea generation to coding to validation.
- We evaluate them. If your algorithm performs well, we will back it with capital and cover all costs.
- When your algorithm makes money, you take a cut of the profits.
Our job is to raise the capital, handle all day-to-day trading operations, provide data sets, as well as build the best research platform in the world for creating investment strategies.
What you get?
If your algorithm is selected, we will pay you a share of the profits that your algorithm earns on investor capital. Our target is to pay you 10% of the profit on your algorithm’s allocation. For example, if your algorithm has a 20% annual return and your allocation is $10 million, you would be paid $200,000 per year.
- You are not told what to do. You develop your own algorithms up to your imagination and ability.
- You don’t have to pay expenses. The data, platform, and commission fees are all covered by us.
- If you are doing a Ph.D. in quantitative finance, it is a good opportunity to monetize your research result.
- You will be paid for your algorithm’s performance, regardless of other algorithm writers’ performance.
- You don’t need to manage fund operations. We will run the algorithms.
- You don’t need to raise trading capital. We will fund your successful algorithms.
- You do not have fiduciary responsibility. All you do is research. It is essentially riskless for you to join our network.
How are we different?
First and foremost, you don’t need to work alone. Our goal is to build a community of quantitative researchers who work together and learn from each other. We want to share information (up to trade secrets). Unlike our competitors, we are not interested in just taking your (unknown) trading strategy and make money. We want to help you learn and grow to become our partners. Therefore, we will work closely with you on your algorithms. We can provide trading ideas, math modeling help and IT support. We will even share with you some information and experience on our successful algorithms. We want to work with you as a team so we all learn from each other. We want to build a long term working relationship with you.
Second, we are only interested in mathematical algorithms that can be proved. As can be seen by some of the work that we have done, all our investment strategies are pure models based on solid mathematical theories. We are not interested in technical indicators that you can always make them work in backtesting. Your algorithms must be proven both mathematically (under assumptions) and pass our suite of statistical backtesting tests.
Third, we have already a large (if not largest) collection of financial mathematics related algorithms in Java that you can simply reuse to prototype your ideas. See SuanShu and AlgoQuant for more information. You can choose to develop on top of our existing algorithms and improve them. There is always room to improve an already good investment strategy.
Forth, if for nothing else, it is always fun to work on mathematical research with a group of good people as a hobby. 🙂
Terms and Conditions
To join our community, you agree to the following terms and conditions (in plain English).
- We will give you a free license to use our technologies.
- You do not distribute or pass the materials that you receive from us to any other party, including but not limited to ideas, papers, software, data.
- You may leave the community at any time.
- We may terminate your membership and collaboration at any time.
- If we must part, both you and we (the Company) own the IP of the trading ideas and the code that you submit to us (e.g., email, code repository). This is so that we don’t sue each other over the IP. You may take the idea to another fund and continue the development, and so do we.
Simply put, it is basically saying that until the point we sign a contract to fund your algorithm, we have no commitment to each other.
- Welcome to Numerical Method!
- SuanShu in .NET environment
- Core Team Members
- Quantitative Trading
- Trading Models
- Mean Reversion
- Trend Following & Momentum
- Factor Model
- Portfolio Optimization
- Covariance Selection