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And if the output is not forecast, then how?
Where did I say anything about prediction? Learning is about minimising the output error. That's the error to see if the network has learned anything.
Wrong again. How will I measure the error if the output is an erroneous entry into a trade? You can't. Because the network must have an example and it does not.
Missed again. How do I measure the error if the output is an erroneous entry into the trade? You can't. Because the network must have an example and it doesn't.
This is a 5 year sample, a learning period. Drawdown 934.87, net profit 1396.06. This is without one neuron.
Here's a normally trained network on a training sample --
You're digging somewhere in your cockroaches now, you don't want to get into it, don't get into it.
The objectives of the network are different.
Here's a normally trained network on a training sample --
What period is this?
What period is that?
I don't remember. It must be a year.
The result is good, it looks like a fit, but it's more the fault of the sample than the network. Next screen will be training with additional neuron, but it's a year. First screenshot 1.1.2008-1.1.2013. Second screenshot 1.1.2008-1.1.2009. Still learning:)