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stock trend prediction
Hi everyone,
I'm trying to develop a model that optimize buy/sell signals at the end of day, in order to obtain the best gain.
Inputs are techical indicators like RSI, MACD, Stochastic and candle patterns.
At the moment I have a training set of Apple's stock in excel (that I will share when I find out the way).
In the past I have tried to build a model considering following label:
- 1 if the price variation is >0.2
- 0 if the price variation is between -0.2 and 0.2
- -1 if the price variation is <0.2
But the result accurancy is around 50% .
How can improve it?
Could you please help me?
Thanks in advance
Francesco
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Answers
I would optimize your algorithm using the Grid Operator. You can get good success when you do that.
Also, visit my site on using RapidMiner for Stock Market related things. http://www.neuralmarkettrends.com/tutorials