The field of machine learning is a very fascinating one. And because the Greed and Fear indicator is a neural network, there's a lot to discuss about ways to apply neural networks and machine learning in trading.
If you're a software developer like me, then the phenomenon of a so-called bug is a well-known thing. The other day, I ran some tests and discovered one in my neural network which has significantly degraded the performance in the last 6 months.
Early visitors of this blog have seen my daily posts for years now with the so-called Greed and Fear indicator and to which direction it was pointing. This was my initial attempt to expose the indicator to the public. Along the way, the performance was measured of course, to see if it was any good and useful in trading. The most honest way to measure this performance was by counting index points 'it called right' subtracted by 'index points it called wrong', as I've explained here in more detail.
But during all those years, I never explained in some more detail what the Greed and Fear indicator really was, while this is probably one of the most fascinating subjects today: a neural network! The more widely known terminology would be machine learning, artificial intelligence, etc. There are subtle differences, but it all comes down to 'intelligent software'.