The article was written by Moises Meir, a Financial Analyst at I Know First. 
Read The Full Premium Article In this stock market forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the Aggressive stocks for long and short positions which were sent daily to our customers. Our analysis covers the period from December 20, 2019, to September 9th, 2020.
I Know First was featured on MarketWatch. This article refers Israeli News 13 TV Channel challenge: « Identifying the top Stocks to Buy Using AI » in which I Know First participated. The experiment was conducted during late August – early September 2019. This period was hardly predictable because of the US China tensions.
This MarketWatch article tells about the experiment, the Israeli News 13 TV Channel reporter structured two investment portfolios from the 20 top US stocks forecast generated by the algorithm. The first portfolio was built for passive investment which kept the same
I Know First was featured on Techaeris portal in “How tech is changing investment markets” article by Kayla Matthews Specifically, this article refers to Matthews analysis on how technology has significantly decreased the barrier to entry for those who want to get involved in stock trading whether it being through social media or simply allowing people to invest on their own.
Matthews discusses how AI Algorithms are used to make humans less and less required for investment activities. As she goes on to mention that I Know First has high accuracy rate when predicting the Nasdaq
In this forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the ETF universe, which is sent to our customers on a daily basis. Our analysis covers the time period from 1 April 2019 to 31 May 2019. We will start with an introduction to our asset picking and benchmarking methods and then apply it to the ETF universe. We will then compare returns based on our algorithm with the benchmark performance over the same period. This evaluation is part of our continuous studies of I Know First’s live AI predictive algorithm’s performance.
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.
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