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Real Money

It’s been about a month now since Quantopian opened live trading up to a public/private beta – we figured it’s about time to share an update on how things are going.

First, I’d like to say thank you to all the Quantopian community members who have joined the pilot and taken the time to provide invaluable feedback, insight and encouragement. The community is, without a doubt, the most amazing part of Quantopian – we couldn’t do this without you, and it is a privilege to work with such talented quants, hackers, scientists and analysts on a daily basis.

I’d like to share two of the key metrics we are starting to track for live trading:

              80 – Number of Quantopians who have connected their brokerage account.

              20 – Number of live (IB-backed) algorithms running today.

I'm delighted to report the first real dollars directed by Quantopian-hosted algorithms. Making the leap from simulation to real trading is a huge deal. I'm incredibly grateful that our beta group has trusted us with their capital. I'd like to congratulate each pilot trader who has launched a real-money algo and claimed their free lifetime subscription so far --  the rest of you have until March 31st to join that club.

We have also been listening closely to conversations in the larger community about live trading– it is great to see spirited and open discussions like this one unfold and evolve on the forums. My takeaway is that the key questions about live trading on Quantopian can be divided into three thematic buckets: Trust, Technology and Trading capital.

Trust: Do I trust my research and my code enough to trade? Do I trust Quantopian to protect my IP and place trades as I expect?

Technology: Are all the nuts and bolts required to implement my algorithm the way I need it in place?

Trading capital: Do I have the trading capital and the risk tolerance to live trade my algorithm?

The commonalities across these three themes are that first, the answers are personal, rather than universal and second, the answers are going to keep changing (hopefully from ‘Not yet.’ to ‘Yes!’) as we build the platform out together.

Finally I wanted to share a screenshot of my own live money algo performance (we shared the code for this a few weeks ago here). This is a conservative, market-tracking strategy that holds an equal weighted portfolio of 9 sector ETFs and rebalances as often as daily. I’ve been running this algo live since Jan 23rd when I started with a capital base of just under $30,000, I grabbed this update after the market closed yesterday.

V2 Jess live algo

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Congratulations on this huge milestone!

Lech Rzedzicki

I, for one, welcome our AI overlords 😉

Paul Mason

How is your algorithm performing relative to a Buy and Hold strategy for the same funds initial allocation?

Does its returns figure include Trading Costs?

Alisa Deychman

Hi Paul,

Here is the algorithm source code. You can try to clone it and create a strategy that buys and holds the 9 sector ETFs for comparison:

Since this is currently trading on the live market, the returns include the trading costs. When you backtest, you can set the slippage and commission costs in your algorithm to model the effects. And then when you live trade, these are handled by the broker.
For more info on these methods see:


Grant Kiehne

Hello Alisa/Fawce,

I realize that your live-running algo is an illustration, but I think that you should publish the trading costs explicitly (it would be even better if they were displayed by the Quantopian dashboard).

Also, it would be illustrative to include an estimate of the impact of anticipated Quantopian per algo per month charges on your performance.

Glad you've gotten everything running end-to-end!

Best regards,


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