FORECASTING USING NEURAL NETWORKS AND STOCHASTIC MODELS ON DAY OF THE WEEK EFFECT: A CASE STUDY OF KSE 100 INDEX - Marri, Azhar Ali; Talpur, Mir G.H. (The journal of contemporary issues in business and government, 2021)
The main objective of this research was to determine the day of the week effect in Karachi stock exchange (KSE) 100 Index. The problems of financial market structure is analyzed and forecasted by many statistical models. For example Auto regressive integrated moving average (ARIMA) model and artificial neural network (ANN) models. In this research day of the week effect was investigated Wednesday found significant and Monday was noted not significant. 15 step ahead prediction of Wednesday was observed through ARIMA model and ANN models. The coefficient of correlation for actual and forecasted values was perceived 0.8871 by ARIMA model and 0.924 by ANN model. Power of accuracy was displayed 88.765% by ARIMA model and 97.18% by ANN model.