Our Philosophy

Quantopian provides an opportunity for anyone, from anywhere, to get paid top-of-market rates for their intellectual property.

Your intellectual property should always be yours and no one should be allowed to profit from it without your consent.

In line with both these beliefs, we’ve created the following system to allow you to securely develop quantitative trading strategies, and get funded should they meet our criteria.

How to Get Funded

1. Research your idea on Quantopian

We’ll teach you how to work like a pro quant. Go through our getting started tutorial and learn how to use the Quantopian API. If you have developed a trading signal outside of Quantopian, upload it to Quantopian and dig deeper.

2. Get feedback on your idea by entering the Quantopian Contest.

The Contest requires strategies pass 10 structural and risk criteria. If you pass the criteria, you have passed the first step of the funding process. Enter the contest to get daily feedback on your strategy.

3. Quantopian’s automated system will evaluate your strategies.

After we have enough out of sample evidence that it meets our criteria, it will be recommended to our investment team. If it’s a good fit for our portfolio, our investment team will reach out with an offer to license your algorithm for an allocation. When a licensed algorithm generates positive returns, we split the returns between the providers of the capital, Quantopian, and the author (you!).

The Goal

Create a trading strategy on our platform which will continue to make money in the future.

The Constraints

As with any challenge, there are constraints on the problem. In our case, the constraints come from the type of strategy Quantopian would like to fund. There are many valid trading strategies out in the world that do not meet these constraints, but any strategy that gets funded by Quantopian should meet these.

To learn how to create a full strategy that meets our constraints, see the Getting Started Tutorial.

Trade liquid stocks

Strategies should have 95% or more of their invested capital in stocks in the QTradableStocksUS universe (QTU, for short).

Low position concentration

Strategies cannot have more than 5% of their capital invested in any one asset.

Long/short

Strategies should not have more than 10% net dollar exposure. This means that the long and short arms of a strategy can not be more than 10% different (measured as 10% of the total capital base). For example, if the entry has 100% of its capital invested, neither the sum value of the long investments nor the sum value of the short investments may exceed 55% of the total capital.

Turnover

Strategies should have a mean daily turnover between 5%-65% measured over a 63-trading-day rolling window. Turnover is defined as amount of capital traded divided by the actual gross book (gross market value). For algorithms that trade once per day, Turnover ranges from 0-200% (200% means the algorithm completely moved its capital from one set of assets to another).

Leverage

Strategies should maintain a gross leverage between 0.8x-1.1x. In other words entries should have between 80% and 110% of their capital invested in US equities.

Low beta-to-SPY

Strategies should have an absolute beta-to-SPY below 0.3 (low correlation to the market).

Low exposure to Quantopian risk model factors

Strategies should be less than 20% exposed to each of the 11 sectors defined in the Quantopian risk model. Strategies should also be less than 40% exposed to each of the 5 style factors in the risk model.

High Capacity

Strategies should be able to meet all constraints on backtests with starting capital values of $10M and above. We want algorithms that perform well even when trading at capacity levels typically backed by institutional capital (from $1 million to $100+ million). Capacity refers to the amount of trading capital an algorithm can manage while still generating an acceptable level of profit. At high levels of capital, many strategies will start to lose their edge due to effects known as slippage. A good way to check if your algorithm has high capacity is to backtest it with our default slippage models at increasing levels of starting capital and look at how the profits are affected. Low capacity algorithms will see rapidly declining performance at higher capital levels.

Positive returns

Strategies should have positive total returns. The return used for the Positive Returns constraint is defined as the portfolio value at the end of the backtest used to check criteria divided by the starting capital ($10M).

Strategic Intent

One of the most common ways to overfit is to just try a ton of variants until one works. We’re looking for algorithms which have a clear intent in the idea as opposed to algorithms which just happen to work with no explanation. We’d like you to be able to explain the original idea and intent of the strategy to us before we license it.

Our Process

We are building a portfolio of uncorrelated investments. Financial theory, backed by evidence in practice, shows the benefits of aggregating a large number of uncorrelated returns streams. The key is that the algorithms should be uncorrelated.

With rare exceptions described in our Terms of Use, we don't look at your algorithm code. But we do look at some of the information that comes out of your backtest. We look at things like your performance, your risk metrics, how many securities you trade, how often you trade, and what the size of your positions are.

Your Compensation

If your algorithm gets funded, we will split the returns between the investor, us, and you. Our agreement pays authors a royalty that is based on the performance of the strategy.

More specifically: funded algorithms are combined into the investment strategy operated by Quantopian. 10% of the investment strategy’s net profits are set aside in a royalty pool to align incentives for authors, Quantopian, and investors in the strategy. Each author’s share of that pool is proportional to their allocation or weight within the broader Quantopian investment strategy.

Perks Of Getting Funded

You will always own your intellectual property. Selected authors license their algorithm to Quantopian.

You don't have to pay for the platform or any of the data used in the strategy.

You have no downside risk: you do not owe anything if your strategy loses money.

You don't have to manage the algorithm operations, chained to your desk every day. We will operate the algorithm for you while you live your life and, we hope, focus on creating new strategies.

You aren't responsible for raising trading capital.

You will be paid a share of the author royalty pool, proportional to your algorithm’s weight within the total portfolio.

Our tools and data are world-class. Our open-source platform is built with the help and guidance of experts around the world.