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Stock Price Prediction using LSTM, FBProphet and ARIMA Model

Stock market being highly volatile, there is a huge amount of uncertainty and risk associated with them. For a good and successful investment, many investors are keen in knowing the future situation of the stock market. Good and effective prediction systems for stock market help traders, investors, and analyst by providing supportive information like the future direction of the stock market. Here we are presenting three innovative method to predict the future closing prices of stocks using combination of deep learning approach using Long Short-Term Memory (LSTM), Facebook prophet and Auto Regressive Integrated Moving Average (ARIMA) time series model to predict the future closing prices of stocks.

Raw Data

The historical "APPLE" stock data is collected from the link https://finance.yahoo.com/quote/AAPL/history/

References

(1). LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444, DOI: https://doi.org/10.1038/nature14539 (2005).

(2). Ghosh, A., Bose, S., Maji, G., Debnath, N. & Sen, S. Stock price prediction using lstm on indian share market. Proceedings 32nd International Conference on Computer Applications Ind. Engineering 63, 101–110, DOI: https://doi.org/10.29007/qgcz (2016).

(3). Taylor, S. J. & Letham, FB. Prophet: Forecasting at scale. DOI: https://research.fb.com/prophet-forecasting-at-scale/ (2017).

(4). Nau, R. Introduction to arima: Nonseasonal models. DOI: https://people.duke.edu/~rnau/411arim.htm (2018).

(5). Reddy, V. Data analysis course, time series analysis and forecasting. DOI: https://http://www.trendwiseanalytics.com/train ing/Timeseries_Forecasting.pdf (2018).

Link: https://drive.google.com/file/d/1mdTC6rQjc3xuCHgD5cCHSaYo2atyiXNC/view?usp=sharing here you can also see everything in more detail.

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