Using Lyapunov&#39;s method for analysing of chaotic behaviour on financial time series data: a case study on Tehran stock exchange

Mohammad Reza Abbaszadeh; Mehdi Jabbari Nooghabi; Mohammad Mahdi Rounaghi; Mohammad Reza Abbaszadeh; Mehdi Jabbari Nooghabi; Mohammad Mahdi Rounaghi

doi:10.3934/NAR.2020017

National Accounting Review

2020, Volume 2, Issue 3: 297-308. doi: 10.3934/NAR.2020017

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Using Lyapunov's method for analysing of chaotic behaviour on financial time series data: a case study on Tehran stock exchange

1.
Department of Accounting, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
2.
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran
3.
Department of Accounting, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Received: 31 August 2020 Accepted: 22 September 2020 Published: 23 September 2020
JEL Codes: C01, C22, C58

In the last decade there is a constantly growing interest in application of mathematics methods and econophysics methods to solve various problems concerning finance,economics,etc. Chaos and its application are importance for most of the current financial and economic phenomena. Financial markets can potentially provide financial long-term series which can be used in analysing and forecasting. Most recent studies,shows the existence of long and short-range correlations in the financial market and economic phenomena. For testing the existence of chaotic behaviour,Lyapunov's method is one of the best methods. In the current study time-series tests of Lyapunov's method were applied,among listed companies on Tehran stock exchange over a period from 2005 to 2015. The obtained findings prove the existence multifractality process in the evolution of time series stock price.
- chaotic behaviour,
- financial time series data,
- Lyapunov's method,
- Tehran stock exchange
Citation: Mohammad Reza Abbaszadeh, Mehdi Jabbari Nooghabi, Mohammad Mahdi Rounaghi. Using Lyapunov's method for analysing of chaotic behaviour on financial time series data: a case study on Tehran stock exchange[J]. National Accounting Review, 2020, 2(3): 297-308. doi: 10.3934/NAR.2020017

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Abstract

In the last decade there is a constantly growing interest in application of mathematics methods and econophysics methods to solve various problems concerning finance,economics,etc. Chaos and its application are importance for most of the current financial and economic phenomena. Financial markets can potentially provide financial long-term series which can be used in analysing and forecasting. Most recent studies,shows the existence of long and short-range correlations in the financial market and economic phenomena. For testing the existence of chaotic behaviour,Lyapunov's method is one of the best methods. In the current study time-series tests of Lyapunov's method were applied,among listed companies on Tehran stock exchange over a period from 2005 to 2015. The obtained findings prove the existence multifractality process in the evolution of time series stock price.

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