SutteARIMA: Short-term forecasting method, a case: Covid-19 and stock market in Spain

Ahmar, Ansari Saleh; del Val, Eva Boj

Abstract The purpose of our research is to predict the short-term of confirmed cases of covid-19 and IBEX in Spain by using SutteARIMA method. Covid-19 Spanish confirmed data obtained from Worldometer and Spain Stock Market data (IBEX 35) data obtained from Yahoo Finance. Data starts from 12 February 2020–09 April 2020 (the date on Covid-19 was detected in Spain). The data from 12 February 2020–02 April 2020 using to fitting with data from 03 April – 09 April 2020. Based on the fitting data, we can doing short forecast for 3 future period (10 April – 12 April 2020 for Covid-19 and 14 April – 16 April 2020 for IBEX). In this study, the SutteARIMA method will be used. For the evaluation of the forecasting methods we applied forecasting accuracy measures, mean absolute percentage error (MAPE). Based on the results of ARIMA and SutteARIMA forecasting methods, we conclude that the SutteARIMA method is most suitable than ARIMA to calculate the daily forecasts of confirmed cases of Covid-19 and IBEX in Spain. The MAPE value of 0.1905 (smaller than 0.04 compared to MAPE value of ARIMA) for confirmed cases of Covid-19 in Spain and 0,0202 for IBEX stock. At the end of the analysis, using the SutteARIMA method, we calculate daily forecasts of confirmed cases of Covid-19 in Spain from 10 April 2020 until 12 April 2020 and Spain Stock Market from 14 April until 16 April 2020.