Open AccessOverview of the ARIMA Model Average Crude Oil Price Forecast and its Im-plications on the Indian Economy Post-Liberalization
Author(s) -
Syed Mohammad Faisal,
Ahmad Khalid Khan
Publication year - 2021
Publication title -
international journal of multidisciplinary
Language(s) - English
Resource type - Journals
ISSN - 2774-5368
DOI - 10.11594/ijmaber.02.02.06
Subject(s) - autoregressive integrated moving average , crude oil , petroleum , econometrics , economics , oil price , liberalization , time series , economy , statistics , mathematics , engineering , petroleum engineering , monetary economics , market economy , paleontology , biology
The crude oil markets have seen unpredictability over petroleum markets' good and bad times worldwide in the past few years. Various facets of the natural energy industry discuss in this research paper. The effect of the Indian ecosystem in determining oil demand and supply is vital to understand price fluctuations. Researchers in this research paper concentrates on the ARIMA model and other regression models used in the post-1991 LPG reforms to determine crude petroleum values and their primary effect on the Indian ecosystem (GDP) through time-series data from 1991 to 2019. The ARIMA model is further evidence of the validation of datasets and the potential trend in the show of global oil rates. The uncouth oil historical values prophesy the potential movement from crude oil prices, and the recommended model-based fall-outs are compelling and honest. Before applying the normality of data and unit-roots, the ARIMA model thoroughly checks at the level. If stationary is not detected, then unit-roots are suspended. The first step is to keep residuals static at the required level of significance to provide efficient forecasting using the ARIMA model used for this analysis.