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Walk Forward Optimization - Can we have this too?

Walk Forward Optimization is an optimization process that addresses the issue of curve fitting in strategy development.

Walk Forward Optimization segregates the data series into multiple segments, and each segment is divided into an in-sample (IS) portion and an out-of-sample (OOS) portion.

Parameter optimization for the strategy is performed using the IS portion of the first segment. The same parameters are then used to back test the strategy on the OOS portion of the same segment. The process is repeated for the remaining segments.

The OOS performance results from each of the segments are considered "real" instead of "curve-fit" because the parameters that produced the OOS results were generated from IS data.
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It shouldn't be too hard once we're launched the optimization features. Will keep it in mind for the planning. If you have other feature requests please file them in github - https://github.com/QuantConnect/Lean/issues
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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.


any updates on walk forward, or are there any optimization features releases?

thanks
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And, another update check :) ?

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Also curious on the status. It would definitely be something worth paying more for!

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Anyone following the other thread concerning optimization will know, if you can run your backtests through Lean rather than the QC terminal, there is now a genetic optimizer available here:

https://github.com/jameschch/LeanOptimization

This has fairly rudimentary features and requires some effort to get started, but at this stage is quite stable and is being actively supported.

If you're interested in walk forward optimization, this is currently being alpha tested in this pre-release branch:

https://github.com/jameschch/LeanOptimization/tree/batcher

Please feel free to clone these branches, try to get it running and provide feedback. Any features requests and bug reports will be greatly appreciated.

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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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