Working in my own research environment with Quantopian data?

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Working in my own research environment with Quantopian data?

Guillaume Perrault-Archambault

edited Apr 6, 2017

I recently heard of Quantopian and I'm interested in getting into quantitative finance / algorithm trading.

I have a lot of experience working in Linux / python. I also have a friend who has experience with Linux / R / Matlab, who I may collaborate with.

It strikes me that the best way to leverage our experience is probably to work in our own research environment. The advantages to using our own research environment
a) Greater flexibility in terms of python modules we can import
b) Ability to use R and Matlab
c) Ability to run on our own likely faster hardware (eg GPUs)
d) Ability to store data in databases, which are faster to access than CSVs
e) Ability to use whatever editors / IDEs we chose

So my question is, is there some way to use Quantopian's data yet use our own research environment? Can we upload our algorithm once it's all backtested?

Somehow I feel the answer must be no, since otherwise Quantopian would essentially be a free data provider. But I thought I'd ask in case I'm missing something.

3 responses

The answer is "no" if you'd like to use the data provided by Quantopian. There is an off-line zipline backtester, but you'd need to provide the data. See also alphalens.

Guillaume Perrault-Archambault

Thank you Grant. I love the community on Quantopian. It's well structured and the fact that I got a fast answer is encouraging. I'll play around on Quantopian. I think working in an active and helpful community has advantages that compete with those I listed in my original comment.

I would like to train a Naive Bayes classifier on data I get through the data. history function. I start with an empty data frame and then I get the data when the market closes on a particular day and append it to my data frame and retrain my model on the whole data. So my model learns as it trades. Is there any way I can pre-train the data before I enter paper trading? This would be like training the model in backtesting and using the trained model for paper trading where it will be trained with the new data as well as the backtesting data.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.