Generalized Hurst exponent approach to efficiency in MENA markets

被引：54

作者：

Sensoy, A. ^{[1
,2
]}

机构：

[1] Borsa Istanbul, Res Dept, Resitpasa Mahallesi, TR-34467 Istanbul, Turkey

[2] Bilkent Univ, Dept Math, TR-06800 Ankara, Turkey

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2013年 / 392卷 / 20期

关键词：

MENA; Generalized Hurst exponent; Rolling window; Market efficiency; LONG-RANGE DEPENDENCE; SWITCHING MULTIFRACTAL MODEL; STOCK MARKETS; VOLATILITY; BEHAVIOR;

D O I：

10.1016/j.physa.2013.06.041

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We study the time-varying efficiency of 15 Middle East and North African (MENA) stock markets by generalized Hurst exponent analysis of daily data with a rolling window technique. The study covers a time period of six years from January 2007 to December 2012. The results reveal that all MENA stock markets exhibit different degrees of long-range dependence varying over time and that the Arab Spring has had a negative effect on market efficiency in the region. The least inefficient market is found to be Turkey, followed by Israel, while the most inefficient markets are Iran, Tunisia, and UAE. Turkey and Israel show characteristics of developed financial markets. Reasons and implications are discussed. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：5019 / 5026

页数：8

共 50 条

[1] Hurst exponent behavior and assessment of the MENA stock markets efficiency
Rejichi, Imen Zgueb
Aloui, Chaker
[J]. RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2012, 26 (03) : 353 - 370
[2] CAPITAL MARKETS EFFICIENCY: FRACTAL DIMENSION, HURST EXPONENT AND ENTROPY
Kristoufek, Ladislav
Vosvrda, Miloslav
[J]. POLITICKA EKONOMIE, 2012, 60 (02) : 208 - 221
[3] The impact of 2008 financial crisis on the efficiency and contagion of Asian stock markets: A Hurst exponent approach
Jin, Xiaoye
[J]. FINANCE RESEARCH LETTERS, 2016, 17 : 167 - 175
[4] Analysis of efficiency in high-frequency digital markets using the Hurst exponent
Lopez, M.
Mansilla, R.
[J]. REVISTA MEXICANA DE FISICA, 2021, 67 (06)
[5] Time and scale Hurst exponent analysis for financial markets
Matos, Jose A. O.
Gama, Silvio M. A.
Ruskin, Heather J.
Al Sharkasi, Adel
Crane, Martin
[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2008, 387 (15) : 3910 - 3915
[6] Adjusted Hurst exponent evaluations for equity and energy markets
Cheong, Chin Wen
Isa, Zaidi
Nor, Abu Hassan Shaari Mohd
Yao, Wong Zhen
[J]. JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS, 2015, 18 (1-2): : 189 - 202
[7] Bayesian Approach to Hurst Exponent Estimation
Dlask, Martin
Kukal, Jaromir
Vysata, Oldrich
[J]. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2017, 19 (03) : 973 - 983
[8] Bayesian Approach to Hurst Exponent Estimation
Martin Dlask
Jaromir Kukal
Oldrich Vysata
[J]. Methodology and Computing in Applied Probability, 2017, 19 : 973 - 983
[9] Hurst Exponent and the Efficiency of the Czech Electricity Market
Curpek, Juraj
Vesela, Jitka
[J]. EUROPEAN FINANCIAL SYSTEMS 2019, 2019, : 90 - 97
[10] GENERALIZED HURST EXPONENT OF THE CARBON THIN FILM SURFACE
Borisyuk, V. N.
Kassi, Jassim
Holovchenko, A. I.
[J]. JOURNAL OF NANO- AND ELECTRONIC PHYSICS, 2011, 3 (04) : 20 - 26

← 1 2 3 4 5 →