Data Recognition for Vehicles Insurance Data using ARIMA- Wavelet Transform

Abstract

This study aim is to examine forecasting and events insurance data in stock market in Jordan, amman stock exchange “ASE” by using mixed methods the ARIMA and wavelet transform (OWT) in order the empower active participation of the insurance market and decision-makers in a position for forecasting the marketplace. Therefore, in the current study First, the series of price indexes became decomposed by way of wavelet transform, and then the smooth series anticipated by using the ARIMA. Furthermore, the comprehensive frequency parts of the signal are used in order to explore their events through the decomposed data, also, the current study provides an appropriate model with the aid of compounding the linear approach ARIMA with using WT, the outcomes suggest superiority of the designed system in predicting charge coverage time series records the usage of Daubechies Wavelet transform and ARIMA model.