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PyStockPredict

Stock prediction powered by bollinger bands

An implementation of backpropogation algorithm to solve multi layer neural networks is used alongwith a simple standard deviation serving as an input to predict the stock prices.

Required Libraries

QSTK
numpy
pandas
matplotlib

Execution

python Dataprocess1.py or python Dataprocess.py python marketsim.py
python analyze.py GOOG

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Backprop Neural Network and bollinger bands for stock prediction

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  • Python 100.0%