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Stock price prediction with LSTM model and Moving Averaging

SIU CHEUNG LAM, Suman Aich, Xiaoyu Wang, Nafis Fuad


In this project, we will analyze time-series stock price data and make short-term predictions using two methods: Time-Series Moving Averaging (TSMA) and Long Short-Term Models(LSTM). We will then compare their performances by evaluating the root-mean square error and mean absolute percentage error.

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