Dr. Lipa Roitman, a scientist with over 35 years of experience created the market prediction system.
The algorithm has been in development for over 20 years, and available for professional investors since 2010.
The algorithm is based on artificial intelligence, machine learning, artificial neural networks and genetic algorithms.
At the top, a specific asset is identified.
This indicator represents the predicted movement direction/trend; not a percentage or specific target price. The signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price.
The signal strength is the absolute value of the current prediction of the system. The signal can have a positive (predicted increase), or negative (predicted decline) sign. The heat map is arranged according to the signal strength with strongest up signals at the top, while down signals are at the bottom. The table colors are indicative of the signal. Green corresponds to the positive signal and red indicates a negative signal. A deeper color means a stronger signal and a lighter color equals a weaker signal.
Analogy with a spring: The signal strength is how much the spring is stretched. The higher is the tension the more it’ll move when the spring is released.
This measures the importance of the signal. The predictability is the historical correlation between the prediction and the actual market movement for that particular market. For each asset this indicator is recalculated daily. Theoretically the predictability ranges from minus one to plus one. The higher this number is the more predictable the particular asset is. If you compare predictability for different time ranges, you’ll find that the longer time ranges have higher predictability. This means that longer-range signals are more important and tend to be more accurate.
Signal > 10
Signal > 0
Signal < -14
Signal < 0
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