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Operationalizing predictive models with QuantConnect

Hello,

I'm pretty new to QuantConnect, but have been taking a deep dive for the last couple of weeks and prototyping a trading system.  I have a deep background of application development/BI with the Microsoft stack, with a relatively more recent focus on data science and machine learning, so the power and potential of QC are quite exciting to me.

However, the restrictions on whitelisting functionality of the .Net framework is of concern, and I'm trying to understand what the potential workarounds might be.  There are two main use cases I'm thinking about that I believe I'm currently restricted from implementing:

1.) Data persistance for the purpose of algorithm configuration optimization.  I want to be able to store a record for each backtest with its outcome, runtime, and user-defined configuration parameters.  I want to be able to easily query and report on these records.

2.) I want to be able to train predictive models in other tools (most likely R) and operationalize them so that my Lean algorithm can use them to make scoring decisions.  I believe the two most likely approaches for operationalizing an R model would be either use of R.Net or integration with SQL Server 2016.  If anyone has integrated a model with Lean another way, would love to hear your approach.

I can implement these use cases myself, but it will require utilization of non-whitelisted components of the .Net framework, which I understand means no use of QuantConnect for backtesting?  

If I do choose to go this route of running Lean myself for live trading, without use of the QuantConnect platform, is there anything else I should know?  Aside from QuantConnect's backtesting data and reporting UI, will I be missing any other core functionality?  Are there others that have gone this route with Interative Brokers that might want to compare notes as far issues and configurations?

Thanks, and looking forward to contributing to this community.

 

 

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Hi Nate;

 - Data persistence is something we're considering. Its an interesting feature which should help alot of people in your position.

 - We don't support R.NET yet as it was unstable; but we will check again when we next review the white listed libaries.

If you use LEAN you'll missing backtesting data, live trading data and the cloud we run on. We are working hard on bridging those gaps - you can get free fx data in the data library, live streaming delayed data via the QC API and you can now use the QC GUI in LEAN.

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Hey Nate,

Built into Lean is a pretty extensive API which allows you to create backtests on QuantConnect.com and download the results. This might serve as a way to acheive the some of the data persistance you desire while more formal Lean optimization techniques are developed.

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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 QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect 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. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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