Algorithmic Trading Strategies For European Stocks: Returns Up to 193%

In the following article we analyze a series of trading strategies directly adoptable by I Know First clients and which have generated returns up to 193% over the period going from August 2015 to April 2017. The strategies follow the algorithm’s signals and invest daily in the strongest ones from the package “European Stocks” hence resulting in a portfolio continuously in line with the program’s recommendations and with the evolving market.

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Algorithmic trading strategies

Algorithmic Trading Strategies For European Stocks: Returns Up to 240%

In the following article we present an analysis of a series of trading strategies directly adoptable by I Know First clients and which have generated returns up to 240% over the period going from August 2015 to April 2017. The strategies follow the algorithm’s signals and invest daily in the strongest ones from the package “European Stocks” hence resulting in a portfolio continuously in line with the program’s recommendations and with the evolving market.

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Algorithmic Trading Strategies

Stock Filtering by the I Know First Signal and Predictability Indicators

Dario Biasini is a Research Analyst at I Know First.





Summary
We expand on research performed in previous articles by further exploring the effect and interpretation of the I Know First prediction measures and how these can be used for stock filtering. We show that as predictability and signal strength increase the average trade returns based on these indicators grow in a consistent, significant, and robust manner and that by daily selecting stocks with the highest predictabilities and signals average returns significantly above those of S&P500 Index can be achieved.
  • Analysis of the Returns Generated by Filtering S&P500 Stocks using the I Know First Signal and Predictability Indicators
  • Comparison of the Compounded Returns Generated by using the I Know First Signal and Predictability Indicators against those of the whole S&P500 Stock Universe

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