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Published in: Quality & Quantity 4/2022

14-07-2021

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

Authors: Pawan Kumar Singh, Anushka Chouhan, Rajiv Kumar Bhatt, Ravi Kiran, Ansari Saleh Ahmar

Published in: Quality & Quantity | Issue 4/2022

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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.

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Metadata
Title
Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA
Authors
Pawan Kumar Singh
Anushka Chouhan
Rajiv Kumar Bhatt
Ravi Kiran
Ansari Saleh Ahmar
Publication date
14-07-2021
Publisher
Springer Netherlands
Published in
Quality & Quantity / Issue 4/2022
Print ISSN: 0033-5177
Electronic ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-021-01207-6

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