International Journal of Neutrosophic Science IJNS 2690-6805 2692-6148 10.54216/IJNS https://www.americaspg.com/journals/show/2869 2020 2020 Applied Science Private University, Faculty of Business, Department of Finance and Banking, Amman, 11937, Jordan; The University of Jordan, School of Business, Department of Finance, Aqaba, 77110, Jordan Jamil Jamil Applied Science Private University, Faculty of Business, Department of Finance and Banking, Amman, 11937, Jordan Anwar Al Al-Gasaymeh Applied Science Private University, Faculty of Business, Department of Finance and Banking, Amman, 11937, Jordan Maha Shehadeh University of Benghazi, Faculty of Economics,Department of Finance and Banking, Libya Asma S. Alzwi This study focuses on improving the predicting accuracy of the daily ASE's weighted price index of the insurance sector (ICI) using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions, namely, Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6). Using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions—Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6)—this study aims to increase the daily ASE's weighted price index of the insurance sector's (ICI) prediction accuracy. The model utilizes a genetic fuzzy system based on Thrift's methodology (GFS.Thrift). The Amman Stock Exchange (ASE) supplied a dataset with 4,478 observations for the purpose of the study. The dataset represented daily data from January 2, 2006, to March 24, 2024.  The adaptive GFS.THRIFT model was trained with 90% of the dataset, while the remaining 10% was used to test its prediction performance. Multiple egressions and multicollinearity tests were used to select input variables such as standardized foreign direct investment (FDI), standardized value traded (VT) and consumer price index (CPI). Insights from this study indicate that all input variables are positively related to the output variable. Secondly, the proposed model (MODWT-Haar-GFS. Thrift) significantly outperforms other existing models including the GFS. Thrift model. 2024 2024 165 175 10.54216/IJNS.240412 https://www.americaspg.com/articleinfo/21/show/2869