Research Article
Predictive Modeling of the IT Index: An In-depth Study Using SARIMAX and Market Indicators
@INPROCEEDINGS{10.4108/eai.23-11-2023.2343256, author={Abhijeet Birari and Harshal Salunkhe and Prajakta Yawalkar and Jitendrasinh Jamadar}, title={ Predictive Modeling of the IT Index: An In-depth Study Using SARIMAX and Market Indicators}, proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India}, publisher={EAI}, proceedings_a={IACIDS}, year={2024}, month={3}, keywords={time series analysis sarimax forecasting moving averages}, doi={10.4108/eai.23-11-2023.2343256} }- Abhijeet Birari
Harshal Salunkhe
Prajakta Yawalkar
Jitendrasinh Jamadar
Year: 2024
Predictive Modeling of the IT Index: An In-depth Study Using SARIMAX and Market Indicators
IACIDS
EAI
DOI: 10.4108/eai.23-11-2023.2343256
Abstract
Using time series analysis and the SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors) model, the study intends to investigate the closing prices of the IT Index. To improve the model's predicting accuracy, variables such as moving averages, daily price disparities, the Relative Strength Index (RSI), and the Average True Range (ATR) were created using the index's closing values. The information technology index's final price is significantly influenced by the difference between the high and low prices as well as the 14-day moving average, according to the study's findings. SARIMAX is a useful tool for financial analysis and decision making as it may incorporate external variables and yield encouraging findings that closely resemble real data.
