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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ETF Trading Strategies Based on I Know First’s Aggregated Algorithmic Forecasts

In the following article we update a set of ETF trading strategies based on I Know First’s aggregated investment signals for the individual stocks contained within the funds. In this article, the ETF forecast is generated by using a weighted aggregation of stock-level forecasts and the performance of this method is tested on the SPDR Sector ETFs. We show that these aggregated forecasts result in ETF Trading strategies which outperform the benchmark and present excellent performance and risk statistics.

ETF Predictions Based Trading Strategies Using I Know First’s Aggregated ETF Forecast

We continue our series of articles analyzing the performance of ETF predictions computed by aggregating I Know First’s algorithmic forecasts for the individual stocks contained within the funds. In this article, a new method to generate an ETF forecast by using a weighted aggregation of stock-level predictions is presented and the performance of this method is tested using Sector ETFs. We show that the computed ETF predictions result in strategies which outperform the benchmark and present excellent performance and risk statistics both on an individual ETF level and for portfolios of ETFs.

ETF Investing by Aggregating I Know First’s Algorithmic Trading Signals

In the following article we continue our analysis on computing sector-level predictions by aggregating I Know First’s stock-level forecasts and using these aggregated predictions to build strategies for sector ETF investing. In particular we:
  1. Update previously presented strategies which compute sector-level predictions by comparing the distributions of the long and short forecasts of the stocks within each sector
  2. Present new ways of aggregating our forecasts using simpler rules and show the performance of various strategies based on these
  3. Show that both the previously developed and the new, simplified decision rules give rise to portfolios that beat the benchmark and register excellent risk statistics