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The Dependence and Dynamic Correlation between Islamic and Conventional Insurances and Stock Market: A Multivariate Short Memory Approach

Rym Charef El Ansari
By Rym Charef El Ansari
1 month ago
The Dependence and Dynamic Correlation between Islamic and Conventional Insurances and Stock Market: A Multivariate Short Memory Approach

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  1. Theoretical and Applied Economics șă Volume XXVII (2020), No. 3(624), Autumn, pp. 213-222 The dependence and dynamic correlation between Islamic and conventional insurances and stock market: A multivariate short memory approach Rym Charef El ANSARI University of Tunis El Manar, Tunisia rym.charef@yahoo.fr Riadh El ABED University of Tunis El Manar, Tunisia riadh.abed@gmail.com Abstract. This study examines the dependence and the dynamic conditional correlation among Islamic and Conventional Insurances and Stock market with Qatar and Abu Dhabi. The main objective of this article is to study how the dynamics of correlations between the major return series evolved from January, 2006 to August, 2018. To this end, we adopt a dynamic conditional correlation (DCC) model into a multivariate GARCH with symmetric effect and the dynamic conditional correlation (DCC) model into a multivariate GJR-GARCH with asymmetric framework. Empirical results indicate the evidence of time-varying co-movement, a high and low persistence of the conditional correlation in the short run. Keywords: DCC-GARCH, DCC-GJR-GARCH, asymmetries, short memory, Islamic insurances, conventional insurances and stock market. JEL Classification: C13, C22, C32, C52.
  2. 214 Rym Charef El Ansari , Riadh El Abed 1. Introduction Modeling volatility is an important issue of research in financial markets. Leptokurtosis and volatility clustering are common observation in financial time series (Mandelbrot, 1963). It is well known that financial returns have non-normal distribution which tends to have fat-tailed. Mandelbrot (1963) strongly rejected normal distribution for data of asset returns, conjecturing that financial return processes behave like non-Gaussian stable processes (commonly referred to as “Stable Paretian” distributions). The coexistence of hybrid insurance structures, including conventional and Takaful insurance companies, is essential to provide various insurance services to Muslims and others with religious restrictions. The accessibility of conventional insurance products in predominantly Muslim countries has become questionable in the eyes of Sharia because of the ban on Riba (Interest), Gharar (Uncertainty) and Maisir (Gambling) in operations of 'insurance. Takaful insurance is an alternative to conventional insurance for insurance products to meet the needs of a growing Muslim population (Akhter et al., 2017). Practical insurance operations based on Islamic Takaful insurance refer to dual structures. On the one hand, the shareholders seek to maximize the profits and the returns on investment of the shareholder company. On the other hand, there are participants (Mushtarik) who make contributions (Ishtirak) to the Takaful community fund which led to the creation of the “subscriber fund”. In case of insufficient funds in the pool, the shareholders' fund is required to provide a loan (qard al hassan). The rapid growth of Takaful insurance companies is evident over the past two decades. Sharia-compliant stocks are considered innovations in the insurance industry because they operate differently from their conventional counterparts. Although it has overcome many challenges, opponents of Islamic finance argue that ethical investment criteria based on the Islamic principle can lead to monitoring costs, the availability of a narrower investment universe and potential limited growth and diversification. (Guyot, 2011). To determine the relationship between Islamic and conventional stock market indices, previous studies (Jawadi et al., 2014; Hammoudeh et al., 2014; Naifar, 2016; Shahzad et al., 2017) have assumed that this dependence provides mixed results. In the financial econometrics’ literature, it is well documented that assessing linkages among Islamic and conventional insurances could have crucial implications from numerous viewpoints. For example, Mohamed et al. (2016) in their study compare the dynamics of the volatility of Islamic and conventional banking indices in the GCC countries. They have developed an econometric framework suitable for studying two main properties: persistence and asymmetry. To this end, a long-memory EGARCH model was estimated and applied to recent daily Islamic and conventional banking indexes, making it possible to measure the persistence of volatility during periods of stability and crisis. Consequently, this study brings several observations. First, the analysis highlights volatility and large cluster effect, suggesting evidence of extreme financial risk. Second, volatility exhibits significant persistence which is much higher for conventional banks than for Islamic banks and is also higher during periods of crisis as
  3. The dependence and dynamic correlation between Islamic and conventional insurances and stock market215 opposed to normal periods . Third, the distribution of volatility is significantly skewed, and bad news seems to affect volatility patterns more strongly than positive news. Conventional banks also react more strongly to a negative shock than to positive news. In addition, conventional banks are more sensitive to the arrival of bad news than Islamic banks. In the other hand, Nouredine and Wael (2018) examined the volatility behavior of insurance stock returns on a sample made up of twenty Saudi insurance companies. The data are collected from Thomson Reuters and cover the period from September 10, 2010 to April 26, 2015. They studied the conditional dependencies between the stock market returns of the insurance activity sectors using the DCC-GARCH. Their results indicate a significant variability over time in the dependence structure between stock market returns. There is a positive link between Takaful and conventional equity returns, with the exception of health and life insurance. The sign and the intensity of the dependence differ according to the specific insurance activity considered. The main objective of this work is to explore the symmetric and asymmetric dynamics in the correlations among Islamic and conventional insurances and Stock market for Qatar and Abu Dhabi. From a theoretical viewpoint, Boero et al. (2011) define asymmetric dependence phenomenon as the different degrees of co-movements during periods of appreciation and depreciation. In addition, they argue that asymmetric dependence can perhaps be explained by currency portfolio rebalancing activities. The layout of the present study is as follows. Section 2 presents the empirical methodology. Section 3 provides the data and a preliminary analysis. The empirical results are displayed, analyzed and discussed in section 4, while section 5 reports the concluding remarks. 2. Econometric methodology The present study investigates the dynamics correlations among Islamic and conventional insurances and stock market from Qatar and Abu Dhabi. The period span from January, 1, 2006 to August, 26, 2018. We provide a robust analysis of dynamic linkages among stock market and each insurance that goes beyond a simple analysis of correlation breakdowns. The time-varying DCCs are captured from a multivariate student-t-GARCH-DCC model which takes into account short memory behavior and symmetric effect and the multivariate student-t-GJR-GARCH-DCC model which takes into account short memory behavior and asymmetric effect. The main objective of this article is to study the Co-movements existing between the Returns of Islamic and conventional insurance and the returns of the market from Qatar and Abu Dhabi. To do this, we use a DCC-GARCH model of symmetrical type and a DCC-GJR-GARCH model of asymmetric type in case of asymmetry. Various empirical studies state that the assumption of a constant conditional correlation is restrictive. Thus, CCC can be generalized by the instability of the conditional correlation matrix presented by the following equation:
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