Stock Market Prediction: The Predictability Signal-Weighted Strategy with the Signal Outlier Filter

I Know First Research Team LogoThis article “Stock market prediction: the predictability signal-weighted strategy with the signal outlier filter” was written by the I Know First Research Team.

Stock Market Prediction: I Know First provides investment solutions for both individual and institutional investors, utilizing an advanced AI self-learning algorithm to gain a competitive advantage. We offer a personalized approach to our institutional clients, assisting them in their investment process based on their specific needs and preferences. For more details about I Know First solutions for institutional investors, please visit our website.

Stock Market Prediction: The Predictability Signal-Weighted Strategy with the Signal Outlier Filter

The following trading strategies were developed using I Know First’s AI Algorithm daily forecasts from January 21st, 2020, to June 26th, 2023, with a focus on S&P 500 stocks selected based on predictability and signal filters. The results of these strategies serve as examples of the trading solutions that I Know First could offer to institutional clients.

The strategy involves constructing four signal-weighted portfolios by the top 20 most predictable stocks on each week of the month. At the same time, we drop duplicate stocks if these stocks have already been included in the previous portfolio this month. Also, we implement the signal outlier filter. The signal outlier filter ensures that stocks with signals outside of the chosen range, i.e., those with extreme values, are not considered. After that, we do monthly rebalancing of each portfolio separately.

The strategy provides a positive return of 90.61% which exceeded the S&P 500 return by 58.70%. Below we can notice the strategy behavior for each year.

I Know First Algorithm – Seeking the Key &  Generating Stock Market Forecast

Stock market predictions: Basic Principle of the "I Know First" Predictive Algorithm

The I Know First predictive algorithm is a successful attempt to discover the rules of the market that enable us to make accurate stock market forecasts. Taking advantage of artificial intelligence and machine learning and using insights of chaos theory and self-similarity (the fractals), the algorithmic system is able to predict the behavior of over 13,500 markets. The key principle of the algorithm lies in the fact that a stock’s price is a function of many factors interacting non-linearly. Therefore, it is advantageous to use elements of artificial neural networks and genetic algorithms. How does it work? At first, an analysis of inputs is performed, ranking them according to their significance in predicting the target stock price. Then multiple models are created and tested utilizing 15 years of historical data. Only the best-performing models are kept while the rest are rejected. Models are refined every day, as new data becomes available. As the algorithm is purely empirical and self-learning, there is no human bias in the models and the market forecast system adapts to the new reality every day while still following general historical rules.


I Know First offers investment solutions for institutional investors, leveraging our advanced self-learning algorithm to gain a competitive advantage. We provide a personalized approach for our institutional clients, enhancing their investment process according to their specific needs and preferences. In this context, we have evaluated the performance of the Predictability Signal-Weighted Strategy with the Signal Outlier Filter during the period from January 21st, 2020, to June 26th, 2023.

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Please note-for trading decisions use the most recent forecast.