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Probabilistic Sharpe Ratio

Hello All! 

We're looking for feedback on a proposed new Alpha selection filter. The Probabilistic Sharpe Ratio would give us another way to measure the results of backtests submitted and provide funds looking to license Alphas with more information about algorithm performance beyond our current metrics. If you have suggestions please clone the notebook and attach your own suggestion! 

Thanks,

Jack

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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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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.


This would lead to higher performing Alpha Streams.  I would add it to the arsenal.

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Is this being included in the backtest metrics?

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We haven't included it yet into the backtest metrics, but it's something that we're considering as well.

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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.


Jack Simonson The Central Limit Theorem is a class of theorems in probability theory, which state that the sum of a sufficiently large number of weakly dependent random variables having approximately the same scales (none of the terms dominates, makes a decisive contribution to the sum), has a distribution close to normal.

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Since the function that characterizes the distribution of a strategy's returns is unknown, the true mean μμ, variance σ2σ2, and distribution are also unknown. Because of this, the true Sharpe ratio of the strategy cannot be known for certain. 

the actual distribution is never known, and this is precisely what the science of mathematical statistics is doing, which, according to incomplete data, tries to restore its form

 

 

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I would like to see this in the backtest metrics. This would be a quick "sanity test" when backtesting.

 

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Update Backtest





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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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