Performance Report of I Know First’s AI-Predictive System for ETF Universe – Beating SPY

Early upon the launch of I Know First’s forecasting algorithm, we implemented our AI-based ranking and forecasting model for a selection of 100 ETFs in the U.S. market. Since then, I Know First began to issue ETF forecasts for our global subscribed investors.

According to our forecast evaluation results, the predictions generated returns greatly surpassing that of the benchmark we have utilized, namely, the SPDR S&P 500 Trust ETF (NYSE: SPY) which tracks the S&P 500 stock market index.

For each covered ETF, the forecasts are generated daily for 5 main time horizons, expressed in

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JNPR Stock Forecast: PTX, 400 Gig, and Contrail will Drive Juniper Networks’ Revenue

   


This article was written by Kwon Sok Oh, a Financial Analyst at I Know First.    




Summary

  • Juniper Networks Delivers Better-Than-Expected Results for Q1 2018

  • Cloud Routing is Suffering Short Term due to the Transition from MX to PTX

  • Cloud Switching has Positive Outlooks Attributable to 400 Gig Development

  • Service Provider is Looking Strong Thanks to Contrail and SD WAN

  • Valuations Methods Suggest JNPR is Currently Underpriced

  • I Know First’s Algorithm Forecast is Bullish for JNPR in the Long Run

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Artificial Intelligence in Healthcare: The Future of the Medical Industry

 

This article was written by Grant Goldstein, a Financial Analyst at I Know First

   

Highlights:

  • AI Will Revolutionize Healthcare
  • Google and IBM Lead the AI Healthcare Race
  • I Know First Ventures into Healthcare
I Know First.  

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Bayesian Inference and I Know First’s Application

   


This article was written by Kwon Sok Oh, a Financial Analyst at I Know First.    




Summary

  1. Introduction of Bayesian Inference and BAC Example
  2. Prior Distribution: Concepts and BAC Example
  3. Likelihood Function: Concepts and BAC Example
  4. Posterior Distribution: Concepts and BAC Example
  5. Posterior Predictive Distribution: Concepts and BAC Example
  6. Conclusion of Discussion and BAC Example
  7. I Know First and Bayesian Neural Networks

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Launch of I Know First’s AI-Predictive System for the Indian Stock Market – Beating the NSE Benchmark

As of May 15th, 2018, I Know First finished the implementation and the training period of its AI-based ranking and forecasting model for the main equities listed on the National Stock Exchange (NSE) of India, specifically a selection of 366 equally-weighted stocks. On this date, I Know first published the first Indian stock forecast for the subscribed investors in the local Indian market, as the timing of the data feed and the forecast generation was adjusted to the respective time zone.

According to our forecast evaluation results, the predictions generated returns greatly surpassing

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Updated Performance Report of I Know First’s AI-Predictive System for Japanese Stock Market – Continuously Beating the Nikkei 225

As of December 28th 2017, I Know First finished the implementation and the training period of its AI-based ranking and forecasting model for the main equities listed on the Tokyo Stock Exchange (TYO) specifically a selection of 1277 stocks. On this date, I Know first published the first Japanese stock forecast for the subscribed investors in the local Japanese market, as the timing of the data feed and the forecast generation was adjusted to the respective time zone.

According to our forecast evaluation results, the predictions generated returns greatly surpassing that of the benchmark

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Launch of I Know First’s AI-Predictive System for the Hong Kong Stock Market – Beating HSI

As of March 15, 2018, I Know First finished the implementation and the training period of its AI-based ranking and forecasting model for the main equities listed on the Hong Kong Stock Exchange (HKEX), specifically a selection of 640 stocks. On this date, I Know First published the first Hong Kong stock forecast for the subscribed investors in the local Hong Kong market, as the timing of the data feed and the forecast generation was adjusted to the respective time zone.

According to our forecast evaluation results, the predictions generated returns greatly surpassing that of the

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