Implementation of the SutteARIMA method to predict short‑term cases of stock market and COVID‑19 pandemic in USA

Pawan Kumar, Singh and Anushka, Chouhan and Rajiv Kumar, Bhatt and Ravi, Kiran and Ansari Saleh, Ahmar (2022) Implementation of the SutteARIMA method to predict short‑term cases of stock market and COVID‑19 pandemic in USA. Quality & Quantity, 56.

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Abstract

The objective of this study is to compare the different methods which are effective in predicting data of the short-term effect of COVID-19 confirmed cases and DJI closed stock market in the US. Data for confirmed cases of COVID-19 has been obtained from Worldometer, the database of Johns Hopkins University and the US stock market data (DJI) was obtained from Yahoo Finance. The data starts from 20 January 2020 (first confirmed COVID-19 case the US) to 06 December 2020 and DJI data covers 21 January 2019 to 04 December 2020. COVID-19 data was tested for the period 30 November to 06 December and DJI from 25 November 2020 to 04 December. From the result, we find that the method SutteARIMA was found more suitable to calculate the daily forecasts of COVID- 29 confirmed cases and DJI in the US and this method has been used in this study. For the evaluation of the prediction methods, the accuracy measure means absolute percentage error (MAPE) has been used. The MAPE value with the SutteARIMA of 0.56 and 0.60 for COVID-19 and DJI stock respectively was found to be smaller than the MAPE value with ARIMA method.

Item Type:	Article
Subjects:	KARYA ILMIAH DOSEN Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions:	KOLEKSI KARYA ILMIAH UPT PERPUSTAKAAN UNM MENURUT FAKULTAS > KARYA ILMIAH DOSEN KARYA ILMIAH DOSEN FAKULTAS MIPA
Depositing User:	Ansari Saleh Ahmar
Date Deposited:	15 Mar 2023 12:11
Last Modified:	08 May 2023 00:56
URI:	http://eprints.unm.ac.id/id/eprint/27400

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