Stock Picking Based on AI: Multi-Tier Strategy

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Stock Picking: 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.

The strategy involves trading the Level 1 Sectors including broad segments of the economy, such as technology, healthcare, finance, and consumer goods to provide a high-level view of the market. A sector ETF is a pooled investment vehicle that invests specifically in the stocks and securities of a particular industry or sector (XLK – Technology, XLF – Finance).

Also, the strategy involves trading GICS level 2 ETFs based on the majority direction. While, the Level 1 Sectors include broad segments of the economy, such as technology, healthcare, finance, and consumer goods to provide a high-level view of the market. Level 2 Industries goes deep into specific industries. For example, within the technology sector (Level 1), you might find industries like semiconductors, software, and hardware. These industries offer a more detailed perspective on the market.

The strategy involves constructing a 1-month tier-weighted portfolio with monthly rebalancing, achieved through the implementation of the signal filter. Moreover, the strategy controls the majority direction. The term “majority direction” refers to our predictions for stocks, upon which we base our position. This decision is guided by a number of long and short stock forecasts. Therefore, if the count of long stock forecasts surpasses the count of short stock forecasts, the majority direction is to go long, and we construct a long portfolio. Conversely, if the count of short stock forecasts is higher, we assume a short portfolio. Additionally, we utilize a signal outlier filter to ensure that stocks with signals outside of the selected range, i.e., those exhibiting extreme values, are not included.

In this strategy, firstly we identify a direction of our trading based on the majority direction (long/short). We allocate 60% of our portfolio to three of the most promising Level 1 ETF Sectors based on the signal forecast. Another 10% is allocated to two of the most promising Level 2 ETFs. 20% is allocated to the 5 most predictable stocks from our forecast universe. Finally, 10% is allocated to SPY (S&P500 ETF) or OEF (S&P100 ETF) based on the signal value. We rebalance our strategy on a monthly basis.

The strategy provides a positive return of 326.18% which exceeded the S&P 500 return by 264.82%. Below we can notice the strategy behavior for each year.

The I Know First strategy has an impressive Sharpe ratio (which compares the return of an investment with its risk) of 1.34 and a Sortino ratio (which compares the return of an investment with its given level of downside risk) of 1.90.

Stock Picking: 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.

Stock Picking: Conclusion

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 multi-tier strategy during the period from January 1st, 2020, to May 31st, 2024.

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