> Is the bot trained to recognize these consolidations? I
Based on my understanding of how this ML is arranged, I would bet that its not. Getting the bot to recognize a consolidation structure is effectively forcing a structure onto the ML parameters, whereas the entire point of ML is for the parameters to emerge from the data itself.
But who knows – it could be possible for it to emerge.
I’d hazard a guess that because the ML is trained to perform over a 30 day period, it may be missing this almost 3 month consolidation.
“So here is how that plays out. If the Market Index correctly predicts the 30-day direction of the market, it receives a biscuit. If it doesn’t, no biscuit.”
Granted, I don’t know how the open/close signals work within the market index. Yeah, it seems that Auto-ML is a different beast than Crypto-ML.
Also, @Justin, I’m curious about this statement:
“From a machine learning perspective, Auto-ML has been running in the background since January of 2018. ”
Does this mean that it was only trained on data from January 2018? I would assume that you could feed in historical data to train – that it doesn’t necessarily need live data.