As a purely speculative exercise on the accuracy of my model, I'd like to publish this idea.
The model tries to identify pressure points in any given market. The pressure points themselves identify the breadth and strength of the move to come. It exists in all time frames and can be applied to any market. The targets are printed as data is fed into the algorithm. The further away from the pressure point, the lower probability it has of attaining such levels and the higher the probability of a correction/reversal.
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Here we go.
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TG1 and TG2 hit. Next highest probability target is TG 3 @ $114.6.
Haven't programmed it yet. It is not self learning, unfortunately. I do not have a background in machine learning and have only just begun learning code.
By algorithm I simply mean a mathematical formula.
UnknownUnicorn14656390
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This could pick up even greater momentum. Also don't forget tomorrow is earnings!
@padawanjunior, I chose to omit TG 4 as it would not make sense in this context. The activity on AMC is unusual, hence the unusual targets being produced.