Analysis and Forecasting of Stock Market Using Time Series Algorithm

EasyChair Preprint 10219

Abstract

Stock market is the way of investing money and making profits by it. It involves a large number of investors, buyers and sellers. India is the 2nd largest country which has more population making profits out from the stock market. As India is in 2nd place, making predictions in stock market will be a helpful one for all. Anyway, prediction in stock market is a little challenging one, since it is time fluctuating and dynamic in nature. The stock market will be changing in irregular intervals of time. So, our model makes prediction in stock market by employing both TSLM (time series linear model) and Support vector machines. By this we develop a model which is used to make the predictions for our future use. Time series play a crucial role in stock market prediction and it can be used to make short term predictions. We also use the ARIMA (Autoregressive integrated moving average) algorithm too. Finally, the forecasted values are converted to the original scale by applying Trend and Seasonality constraints back. In the paper we survey the pros and cons of using these techniques to predict values.Stock market is the way of investing money and making profits by it. It involves a large number of investors, buyers and sellers. India is the 2nd largest country which has more population making profits out from the stock market. As India is in 2nd place, making predictions in stock market will be a helpful one for all. Anyway, prediction in stock market is a little challenging one, since it is time fluctuating and dynamic in nature. The stock market will be changing in irregular intervals of time.

Keyphrases: ARIMA, LSTM, Moving Average, SESONALITY, SVM, TSLM, forecast, machine learning, time series, trend

@booklet{EasyChair:10219,
  author    = {Ananthula Jeevan Kumar and Onteddu Gangadhar Reddy and Badveli Sai Kumar Reddy and Balagonda Sandeep Kumar and Arikala Sri Hari},
  title     = {Analysis and Forecasting of Stock Market Using Time Series Algorithm},
  howpublished = {EasyChair Preprint 10219},
  year      = {EasyChair, 2023}}