Disliked{quote} I am currently studying possible use of Neural Networks using MACD indicator to find a dominant pattern automatically. I found one simple way to do data scaling of that indicator. Basically I tried to divide indicator values coming from JPY by 100 to get the right scale compared to other pairsIgnored

- One may suggest that all patterns are Waves (1-2-3-4-5-A-B-C) or harmonic patterns. But I advocate differently, I say they are simply all M patterns in different fonts which makes it only logical that a 'font recognition robot' (not a trading robot, but a program that reads handwritten input from academic thesis papers by using Average-Pooling or similar Deep Learning techniques) adds as much value to it as, what you use to calculate (dividing 100). Have you ever used a font recognition program? If yes, do you see the effectiveness if used on the GBP/JPY or EUR/USD chart?

- Regarding your reply on dividing by 100. Okay, are you comparing all (major) currencies with the JPY? You mention 'dividing' in your formula, where I can only assume you would add a multiplication to your calculation as well. What do you multiply? Could you explain more about your formula as to recognize a pattern (in the MacD)?

- Neural networks, a concept where you add lotsize to probability aspects, am I summing it up correctly? Are you willing to list the different values (probability vectors and dropouts to avoid overfitting) in your concept (HWL) of pattern recognition with neural networks?

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