Modeling the volatility insurance time series data using Wavelet transform

Authors

  • Ahmed Atallah Alsaraireh The University of Jordan - Department of Computer Information Systems
  • Mohammad Salameh Almasarweh The University of Jordan - Department of Business Administration
  • S. Al Wadi The University of Jordan - Department of Risk Management and Insurance
  • Mahmoud Barakat Alnawaiseh The University of Jordan - Department of Business Administration

Keywords:

volatility, insurance time series data, wavelet transform

Abstract

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.

Cover of n°42 Italian Journal of Pure and Applied Mathematics

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Published

2019-07-30

How to Cite

Alsaraireh, A. A., Almasarweh, M. S., Al Wadi, S., & Alnawaiseh, M. B. (2019). Modeling the volatility insurance time series data using Wavelet transform. Italian Journal of Pure and Applied Mathematics, 42, 965–970. Retrieved from https://journals.uniurb.it/index.php/ijpam/article/view/7158

Issue

N°42 - July 2019

Section

Articoli - Forum Editrice

License

Copyright (c) 2019 Ahmed Atallah Alsaraireh, Mohammad Salameh Almasarweh, S. Al Wadi, Mahmoud Barakat Alnawaiseh

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

L'opera è pubblicata sotto  Licenza Creative Commons Attribuzione 4.0 Internazionale (CC-BY)

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