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New developments at spxbot.com, while the S&P 500 navigates the unknown waters of new all times highs.

pushed to the limits, the neural network output flattens to blindness

As it was implicit in the trained data, I shaped the Long Term Trend indicator, that reads the trend from current data. It is a neural indicator, meaning that it is the output of a neural network, that categorizes every past bar as belonging to a bull or a bear market. The ideal output is 1 for bull market and -1 for bear market. At the moment, on daily time frame, the indicator is firmly bullish. It is supposed that it changes very rarely. Simply put, the model looks at today’s data and says: “uh, we are in a bull market!” (or bear, in case).

Further, a few weeks ago, I wrote a code I was sniffing since long. It is my first attempt to reverse engineer the Forecast Arrays by Martin Armstrong and you may find here his description of the tool, pag. 21 and followings. All I knew is what is written there. I’ve already tried some experiments with ideas extracted from the writing, but now I wanted to strictly replicate the arrays. I read very accurately the text and tried to put myself in the original condition of a programmer in the late sixties/early seventies, using a very slow computing power and hard to learn code languages. I come out with the Highs and Lows Cycles indicator, that actually, it is in beta observation mode since inception some days ago, performs very well. It has nothing to do with neural networks and pattern recognition: it works on frequencies, algebrically. What we obtain is the marking of future days as candidates to be a high or a low. Also, it is another form of statistics available, no magic. The Highs and Lows Cycles indicator is now integrated in the standard forecast charts and under the observation of subscribers.

 

 

 

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