• Viral
• Prof. Hetal Gaudani

Stock price prediction is an important investment topic in the finance and economics. It’s applied in different fields like ‘medicine’, ‘environment’, ‘education’, ‘crime’ etc. This performs vast process of stock price prediction using the ARIMA model and time series techniques. Prediction plays a very important thing in stock market business. In literature survey ARIMA model is extensively used for brief term prediction of stock value. ARIMA model has an intense potential algorithm for short-term prediction. It would be used for time series modelling data and forecasting trends in the future. First, we are going to extract area unit from daily without relying on previous information of prediction. We are going to explore varying deep learning algorithms to improve the accuracy of prediction and comparing our result with LSTM, ARIMA and Prophet Algorithms.

Standard average and exponential moving average, Lstm, Arima, Prophet

"Stock Price Prediction using Time Series Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.66-72, May-2019, Available :http://www.jetir.org/papers/JETIR1905A09.pdf

"Stock Price Prediction using Time Series Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp66-72, May-2019, Available at : http://www.jetir.org/papers/JETIR1905A09.pdf