General comment on NN (Neural Networks).
The "typical" issue with these is not only the sheer data mining and curve fitting going on, but also the complexity. If you are not careful NN will curve fit to extreme. If you are a clever individual, you can pre-process the data inputs it is looking at which are themselves derived from the data. Example of this would be ATR, Highest High, lowest low (x bars ago)…da…da…da So in essence you tell the NN what is important to look at.
This however has its pitfalls as well, because when it is done, some results or decisions were derived by such complex rules and weightings, that it is very difficult to discern what in fact it "Did' to reach it's decisions and/or if there is any logic to it. Might sound immaterial, but it you want to risk money and have "Stick –to-it-of-ness" then it is very difficult in inevitable times of adversity, if you have no idea why it should be followed in the first place (the logic behind it all). On the flip side, if it is a very simple logic, one that is fully understood and makes sense,….well them most everyone else probably has found it and you are not alone. J
Just my 2 cents.
-S
From: amibroker@yahoogroups.com [mailto:amibroker@yahoogroups.com]
Sent: Wednesday, February 03, 2016 12:14 PM
To: amibroker@yahoogroups.com
Subject: Re: [amibroker] Artificial intelligence
Ron,
I have used NN with Amibroker, via R.
Generally, i have tried a three tier prediction classification - BUY, SHORT, DO NOTHING. If you are looking to just square off via NN, you could train the NN on SELL,COVER,DO NOTHING. You need to define the output condition that will cause a cover or sell trade. It could be a very specific condition- if the market moves 1% higher, i will COVER and if it moves 1% lower, i will SELL. I have generally found a more ambiguous condition to be easier to model - eg. if NN predicts an upbar, i will SELL and if NN predicts a downbar, i will COVER. The conditions to define the output variable are many, it is probably a function of your strategy... I have generally never achieved accuracies of >70% in prediction, which result in a 40%-45% win-ratio in real life.
Rgds,
Pankaj
On 30-Jan-16 1:26 AM, 'Ron J' ronj@san.rr.com [amibroker] wrote:
My programmer is going to apply neural networks to our systems. What I have directed him to do is to use our entries and let the AI Software come up with an exit strategy.
So far when he tried to build a trading model with AI the only outcome is his learning about them.
Has anyone tried this approach?............Since a lot more effort goes into entries than exits I figure is might be worth a try.
Regards
Ron
RonJaenisch.com
"Success is almost totally dependent upon drive and persistence. The extra energy required to make another effort or try another approach is the secret of winning."
— Denis Waitley: American motivational speaker
Posted by: "Sean ONeill" <ONeillSeanP@verizon.net>
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