Modeling the volatility insurance time series data using Wavelet transform

被引：0

作者：

Alsaraireh, Ahmed Atallah ^{[1
]}

Almasarweh, Mohammad Salameh ^{[2
]}

Al Wadi, S. ^{[3
]}

Alnawaiseh, Mahmoud Barakat ^{[2
]}

机构：

[1] Univ Jordan, Dept Comp Informat Syst, Aqaba, Jordan

[2] Univ Jordan, Dept Business Adm, Aqaba, Jordan

[3] Univ Jordan, Dept Risk Management & Insurance, Aqaba, Jordan

来源：

ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS | 2019年 / 42期

关键词：

volatility; insurance time series data; wavelet transform;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Nowadays, the volatility of stock market data have contributed an essential section in risk study. Volatility is measured by standard deviation of the return. This study explores volatility event for the insurance time series data from Amman Stock Exchange (ASE). Wavelet models (WT) have used in order to study the events in the volatility data that collected from 2010 to 2018. Therefore, the researchers found that WT is a suitable model in studying the volatility data.

引用

页码：965 / 970

页数：6

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