Dear Label_Name,

Greetings! I hope you are well.

I am writing on behalf of an international publishing house, Science and Education Publishing, USA (http://www.sciepub.com).

Science and Education Publishing (SciEP) is a multidisciplinary open access publisher of Journals covering the fields of Science, Technology and Medicine. All SciEP publications are subject to high-quality peer review, editorial and production processes and are freely available online.

Welcome to the April, 2013 edition of SciEP newsletter, providing monthly summaries of articles on science & education related topics of interest to scientist and professionals. The mission of our journals is to provide an open access forum for publishing new findings on issues pertinent to scientific and academic field. We also invite you to submit original research papers, review articles, short reports, or case studies are considered for publication in our Multidisciplinary Journals.

American Journal of Public Health Research
DOI: 10.12691/ajphr-1-1-3

The Implementation of a Tele-Homecare System with Service Oriented Architecture and HL7 Message Transmission Standard
Ching-Sung Wang

American Journal of Medical and Biological Research
DOI: 10.12691/ajmbr-1-1-2

The Influence of Ethanol on Pyruvate Kinases Activity in Vivo, in Vitro, in Silico
Lelevich Sergey Vladimirovich, Khrustalev Vladislav Victorovich, Barkovsky Eugene Victorovich, Shedogubova Tatyana Aleksandrovna

American Journal of Medical Sciences and Medicine
DOI: 10.12691/ajmsm-1-1-1

Clinical and Histological Features in Wegener Granulomatosis
Li Cavoli Gioacchino, Passantino Rita, Bono Luisa, Tortorici Calogera, Ferrantelli Angelo, Giammarresi Carlo, Rotolo Ugo

American Journal of Infectious Diseases and Microbiology
DOI: 10.12691/ajidm-1-1-2

The Curse of Lymphatic Filariasis: Would the Continual Use of Diethylcarbamazine Eliminate this Scourge in Papua New Guinea?
Anne Lanham, Lillian Mwanri

We have released issues of some journals on February 2013.
American Journal of Public Health Research
American Journal of Medical Sciences and Medicine
American Journal of Medical and Biological Research
American Journal of Pharmacological Sciences
American Journal of Clinical Medicine Research
American Journal of Nursing Research
American Journal of Cancer Prevention
American Journal of Medicine Studies
American Journal of Infectious Diseases and Microbiology
American Journal of Cardiovascular Disease Research
American Journal of Biomedical Research
American Journal of Mechanical Engineering
American Journal of Microbiological Research
Journal of Preventive Medicine
American Journal of Food and Nutrition
American Journal of Hypertension Research
American Journal of Sports Science and Medicine
Journal of Cancer Research and Treatment
American Journal of Zoological Research
Journal of Biomedical Engineering and Technology
American Journal of Microbiological Research
Biomedical Science and Engineering

We are pleased to announce that submissions are now being accepted for peer review for all the journals across all our subject areas in SciEP.

Please submit your manuscript via our online submission system:
http://www.sciepub.com/author/signin

To unsubscribe from our mailing list, please click on the following link: unsubscribe

I am looking forward to hearing from you.

Kind regards,

David Rain
Email:join@sciepub.com
Science and Education Publishing (http://www.sciepub.com)

The Impact of Subprime Crisis on Conventional and Islamic Stock Market

Majoul Neila

Higher Institute of Management, Tunis University, Tunisia

Abstract: The aim of this paper is to examine the impact of the U.S. subprime crisis on the long-term and short-term dynamic relationships between conventional and Islamic stock markets in three sub periods. The comovements among these stock markets are examined through cointegration tests, and vector error correction model-based Granger causality tests. The sub periods studied are the pre-, post and during the recent subprime crisis. Results indicate that Islamic stock market indexes are attractive than their conventional counterparts for portfolio managers and international investors. Opportunities for potential earnings through diversification of investment portfolios are high in these markets.

Keywords: cointegration, Granger causality, VECM, Islamic indices, subprime crisis

Received September 20, 2020; Revised October 22, 2020; Accepted October 29, 2020

Citation: Majoul Neila, The Impact of Subprime Crisis on Conventional and Islamic Stock Market. International Journal of Business and Risk Management, 3 (1). 1-8. January 2020. doi:10.12691/ijbrm-3-1-1

1. Introduction

The integration of the global stock markets represents an expansive area of research in financial economics and an interesting topic of several researches. Thus, Understanding the nature of stock market integration and examining the dynamic pattern of integration among Islamic and conventional financial markets has crucial implications for investors, fund managers and other market makers who are interested to diversify their portfolios across international stock markets mainly in turbulent financial context [1].

Financial theory tells us that studying the financial interdependence between stock market indices is important for international investors wishing to take advantage of diversification benefits [2]. Indeed, the low correlation between indices allows investors to minimize portfolio risks through effective international diversification. However, the strong co-movement between the conventional indices observed in recent years, explained by the integration of financial markets on the one hand and the contagion in times of crisis, on the other hand, led investors to address to Islamic markets in order to make gains. These markets can probably offer a much greater potential for diversification than conventional markets.

During the last three decades, the world economies have been increasingly globalized. As the world becomes integrated, economies tend to intensively liberalize their markets to compete for the foreign investments. Because the economic liberalization involves in the removal of capital barriers to investment, the liberalization process effectively enables one country’s capital market to be more accessible to the foreign investors. Thus, economies around the world become integrated with one another [3].

The Islamic banking and finance industry has captured substantial interests in the financial market particularly in the aftermath of the recent global financial crisis. A specific segment of the industry that has been receiving much attention following the crisis is the Islamic equity market [4].

Despite the enhanced increasing of Islamic banking and finance industry, particularly in aftermath of the recent global financial crisis, a few empirical studies have been interested to the integration among the stock markets in Islamic countries. The major difference between Islamic capital market and its conventional counterpart is that the former's activities are carried out in ways which does not conflict with the principles of Islam [1,5].

An Islamic stock market index can be defined as the index whose composition is made up with stocks that are Shariah compliant [3].

In Islamic finance, a market should be free from prohibited activities. Islamic investing is based on five main principles, which include the prohibition of interest (riba), the banning of excessive uncertainty (gharar), the interdiction of speculation (maysir), risk and return sharing, and the prohibition of investing in ‘unethical’ industries (haram) [1,6]. The modern Shariah scholars have provided general rules for Shariah-compliant investors to evaluate or screen whether a particular company is halal (lawful) or haram (unlawful) for investment. There are two types of stock screening approaches such as qualitative and quantitative screens. The first one is qualitative screen, the screening process that focuses on the activity of a company that is used as the main principle in Islamic investment criteria. The second one is quantitative screen, where Islamic scholars have applied a principle of tolerance associated with filtering criteria, namely Debt filter , liquidity filter, impure income filter [7].

Stability and resilience of Islamic finance against the global financial crisis represent an interesting topic of researches. However, few numbers of empirical studies examining the integration of Islamic and conventional stock markets and the potential benefit diversification across these markets in turbulent and stable financial context.

More specifically, the aim of this study is to examine the impact of the U.S. subprime crisis on the integration of selected Islamic and conventional stock markets. We study the co-movements of Islamic and conventional stock market indices through the application of cointegration analysis and analyze the nature of co-movements between Islamic and conventional stock markets through two sources of co-movements, namely: financial integration and contagion. We examine whether Islamic markets are exposed to the effects of global financial crisis. We further identify whether Islamic market exposure is related to pure contagion or contagion.

The rest of this study is organized as follows: the subsequent section briefly reviews the theoretical literature dealing with financial integration and the contagion effect. The third section describes the methodology and data used in this study. The fourth section reports the empirical results. The last section gives the summary and conclusions.

2. Financial Integration - Contagion Effect

As the world economies become increasingly integrated, enormous researches have been devoted to examine whether the financial crisis in one country will be spilled over to other countries [3].

Previous studies on financial integration have demonstrated the increasing increase in stock market co-movements as a major result of globalized economies [8]. In this framework, studies have suggested that financial integration between markets around the world is beneficial as it allows for better capital allocation, economic growth, and risk sharing and diversification [9]. It offers international investors new investment opportunities to diversify their portfolios and improve the risk-return profile [10]. While other studies show that the most integrated markets are more vulnerable to the effects of shocks in other countries [8,11,12].

2.1. Financial Integration

Following the collapse of the Bretton Woods system, developed countries launched the international process of financial liberalization. The latter involves the removal of barriers to capital investment [13,14]. The liberalization process effectively allows a country's capital markets to be more accessible to foreign investment. Indeed, the increased deregulation of capital movements, the reduction of transaction costs and the progress of information and communication technologies have contributed to the increase in the degree of financial integration between global stock markets [15,16].

Thus, understanding the nature of stock market integration is crucial for investors seeking to diversify their portfolios in international equity markets. It has important implications, in developing investment strategies, to take advantage of potential opportunities for portfolio diversification [4]. Indeed, the integration of stock markets has been defined in the literature from two perspectives: the asset valuation perspective and the static perspective [1].

The first perspective suggests that if stock markets are fully integrated, the returns on financial assets are determined by global risk factors. Identical financial securities must be valued identically in these markets [17]. Assets with the same risks must have the same prices [18]. Thus, no diversification benefits from a portfolio can be derived from these markets.

The second perspective suggests that highly integrated markets tend to move together and have stable long-term relationships [19]. Indeed, a long-term common relationship indicates that cross-market correlations are relatively high in the long run, reducing any potential diversification benefits over the long term.

However, the high degree of financial integration reflects an acceleration of shocks transmission movements, the vulnerability of countries integrated into financial crises and the contagion effect.

2.2. Contagion Effect

Reference [20] defined contagion as the significant increase in cross-market links after a shock from one country stock market or group of countries to another. According to this definition, contagion does not occur if two markets show a high degree of linkage during both stable and crisis periods. Contagion occurs only if cross-market linkage increases significantly after the shock.

For this, [20] has distinguished two different channels in the international transmission of financial shocks: crisis-contingent and non-crisis-contingent channels or pure contagion and fundamental contagion [21,22]. Crisis-contingent channels imply that transmission mechanisms change during a crisis (contagion exists), and non-crisis-contingent channels imply that transmission mechanisms do not change during both stable (contagion does not exist) and crisis periods.

Theoretical work on the international propagation of shocks can be broadly categorized as focusing on three different mechanisms: aggregate shocks which affect the economic fundamentals of more than one country, country-specific shocks which affect the economic fundamentals of other countries, and shocks which are not explained by fundamentals and are categorized as pure contagion

The first mechanism focuses on aggregate or global shocks which simultaneously affect the fundamentals of several economies The stock markets in any countries affected by this aggregate shock would move together (at least to some degree), so that directly after the shock, cross-market correlations between any affected countries could increase.

The second mechanism explains how a shock to one country (or group of countries) could affect fundamentals in other countries. This mechanism could work through a number of real linkages, such as trade or policy coordination. Trade could link economies because devaluation in one country would increase the competitiveness of that country's goods, potentially decreasing the competitiveness of other countries. This could not only have a direct affect on a country's sales and output, but if the loss in competitiveness is severe enough, it could increase expectations of an exchange rate devaluation and/or lead to an attack on the country's currency. Policy coordination could link economies because one country's response to an economic shock could force another country to follow similar policies.

The final international propagation mechanism, contagion, is defined as any increased market co-movement which cannot be explained by the previous two channels. Theories explaining contagion are based on multiple equilibrium, capital market liquidity, investor psychology, and/or political economy.

3. Methodology

3.1. Empirical Approach

The empirical framework in this study considers different approaches to investigate Conventional and Islamic stock markets integration before and during the global financial crisis periods. Initially, we adopt the Johansen-Juselius co-integration approach to examine the long-run relationship among the selected stock markets. Then, the VECM model is applied to explore the short-term dynamic relationship among Islamic stock markets. Finally, the granger causality test is used to analyze the causality dynamics between Conventional and Islamic stock markets.

The methodology operates in four stages:

- The first step is to study the stationary of the data. We use the ADF unit root test to test the stationary of the series studied. This test consists in testing the null hypothesis of presence of unit root against the alternative hypothesis of absence of unit root and stationary of the data. The general ADF model is written as follows:

[picture] | (1)

Where is a constant, is the trend measure and p is the optimal delay number.

Indeed, Dickey Fuller [23] considers three basic measures namely a model with constant and trend, a model with constant without trend and a model without constant or trend.

- The second step is to determine the optimal delay number (p) of the VAR model. The order of delay p is determined on the basis of information criterion minimization of Akaike [24] noted AIC. This criterion can be described by the following equation:

[picture] | (2)

Where is the sampling variance of the residues.

- The third step is to conduct the cointegration test. Engel and Granger [25] point out that if two series are integrated of order 1, it is necessary to test the possibility of a long-term cointegration relation between the variables. Cointegration consists of specifying stable long-term relationships and short-run dynamics between variables. More precisely, it is about estimating the number of cointegration relation of this equation:

[picture] | (3)

Δ being the first difference, δ is the vector (n x 1) of the constant terms; is the vector (n × 1) of the white noise error terms; p the optimal delay number determined by the AIC criterion; Γ and π are two matrices (n x n) of the coefficients; Γ represents the coefficient of the of the short-term dynamics, The rank of the matrix π determines the number of cointegration relation. It contains information on the relations of LT and it is decomposed into two matrices α and β ^ 'such that π = α β ^.

In order to determine the number of cointegration vectors, Johansen and Juselius [26] and Johansen [27] develop two statistical tests namely statistical trace and static Maximal Eigenvalue. The statistical test trace is written as:

[picture] | (4)

This statistical test tests the null hypothesis that there are at most r cointegration vectors. The maximum statistic Eigenvalue tests the null hypothesis of the presence of r cointegration relation against the alternative hypothesis r + 1. It is written as:

[picture] | (5)

- The fourth step is to test the causality in the sense of granger

The bivariate granger test [28] studies the linear Granger causality between two variables X and Y, and consists in estimating a linear model VAR of order p written as follows:

[picture] | (6)

3.2. Data

This study uses daily close prices of conventional and Islamic indices from Malaysia, Indonesia, the GCC ex Saudi Arabia (GCC ex SA) region and the world index. These indices are extracted from Morgan Stanley Capital International (MSCI) database and covering the period from 26 October 2009 to 06 January 2015 comprising 2425 observations for each market. The market index is represented by the MSCI World Stock Index. All these indices are taken in USD. In order to explore the impact of the US Subprime crisis on the integration of the selected stock markets, the period of study is divided into three sub-periods: The pre-crisis period (August 10, 2006 - July 31, 2007), during the crisis (August 01, 2007 - December 31, 2008) and the period after crisis (January 01, 2009 at 26 November 2015).

4. Empirical Results

Descriptive Statistics

Table 1 presents the descriptive statistics of the data, which summarizes the basic statistical characteristics of the daily stock market indices returns for the selected stock markets, for the pre crisis and during-crisis, after crisis periods, respectively.

Table 1 lists the statistics describing the daily returns of the conventional and Islamic indices. Returns exhibit negative skewness. The series are asymmetrical spread to the left. The excess kurtosis shows a strong presence of extremes. The distribution has leptokurtic tail. The values of the test Jarque Bera are very high. These tests reject the normal distribution.

For the pre-crisis period, all returns are positive. On average, Islamic indexes posted higher returns than their conventional counterparts. Islamic indices have risen higher. This means they were more risky. While conventional indices have lower risk levels indicating that these indices are less risky.

During the crisis period, the returns of all Islamic and conventional stock indices are negative. Both groups of Islamic and conventional indices had negative returns during the crisis period. In terms of risk, the comparison of standard deviations for different periods indicates that stock markets tend to be riskier during the time of the crisis. This suggests that the financial crisis, which occurred in this period, affected the volatility and performance of both classes of stock indices. Islamic stock markets are as vulnerable as conventional stock markets to global financial shocks. This results in lower stock market returns and greater volatility in Islamic and conventional stock market returns in the crisis period than in the two non-crisis periods. Islamic indices performed better risks than conventional indices. They are less affected by the crisis providing, as well, a hedging alternative because of their low risk. So, the Islamic stock market index is more resilient in the crisis period. This finding can guide investors in their investment decisions by providing information on the risk - return relationship during the crisis period.

For the post-crisis period, we note that high risk is offset by higher returns. This result is in line with modern portfolio theory, which suggests that the more risky investors are willing to bear, the higher the expectation of a high return for offsetting the risk. In general, the returns of conventional indices are higher than the returns of Islamic indices and the risk of Islamic indices is higher than the conventional one. Conventional indices appear to be more efficient during this period.

Risk-averse investors seeking low risk should invest in less risky Islamic indexes that can generally meet their expectations for risk especially in times of crisis. Conventional investors may also diversify their investment portfolios in Islamic indexes consistent with Islamic law especially during times of crisis. This result is consistent with the literature that evokes the superiority of investing in Islamic assets than in conventional assets especially in the period of financial crisis.

Table 1. Descriptive Statistics

Table 2. Unit root tests: ADF Test

Unit Root Tests

For the stationary nature of the stock market indices (the natural logarithmic form) and indices returns (first difference of natural logarithmic indices multiplied by 100), Table 2 reports the unit root tests results for ADF tests during the three sub-periods.

For the three sub-periods, ADF statistics indicate that at levels all the series are no stationary. This implies that, when the market indices are at levels, the null hypothesis of a unit root cannot be rejected. On the other hand, when the series are at first difference, the null hypothesis of a unit root can be rejected. Thus, we conclude that the series are stationary at their first difference. In other words, all the data series are said to be integrated at order one, or I (1).

Before proceed with co-integration test, we need to determine ‘optimal’ order for Vector Auto Regression (VAR), that is, the number of lags to be used. In the first model, only Islamic stock market indices are included. While in the second model, both conventional and Islamic stock indices are included.

Results in Table 3 suggested that AIC favors order of 1 for the pre-crisis, 2 for during the crisis for the two models. In the post crisis period, Results suggested that AIC favors order of 4 for the first model and 2 for the second model.

We proceed to investigate the presence of long-run relationships using JJ cointegration technique. Likewise, this test is been employed on two models: For the first model, only the Islamic stock markets are included and for the second model, both conventional and Islamic stock markets are included.

Trace and Maximal Eigenvalue statistics are applied to determine the number of the cointegration vectors at 5% significance level. Because the Trace statistics are more robust than the Maximal Eigenvalue statistics, if the two statistics give contradictory results the Trace statistics should prevail [26,29].

Table 3. Optimal Lag Order

Table 4. Cointegration tests (First Model)

Table 5. Cointegration Test (Second Model)

The result of the cointegration test Johansen and Juselius is reported in Table 4 for the first model and 5 for the second model. The cointegration test was used for the three sub-periods. Indeed, the cointegration test is very important because it checks whether all the variables are theoretically linked or not. In fact, when the variables are cointegrated, it means that there is a co-movement between the variables in the long run. Proof of financial cointegration implies that all stock market indices are interdependent and integrated. As a result, portfolio diversification opportunities are limited. Meanwhile, the lack of cointegration indicates the potential for earnings gains through portfolio diversification.

Table 4 shows the absence of cointegration for the three periods studied. The results suggest that Islamic markets are independent of one another. Opportunities for potential earnings from international portfolio diversification can be drawn from these markets.

Table 5 shows evidence of non-cointegration for periods before and after the crisis. For the crisis period, the Trace statistic and the Maximal Eigenvalue statistic show the existence of a single cointegration vector. We find that the financial crisis eventually touched the real sphere and affected the Islamic stock market indices only in times of crisis. The increase in links and co-movements across stock markets during periods of turbulence can be interpreted as a sign of the presence of a contagion effect and systemic risk transmitted through several channels of pure contagion such as lower investor confidence and sudden change in liquidity conditions [13]. Meanwhile, Islamic stock indexes were less affected by the subprime crisis and absorbed less the impact of the crisis. The application of the principles of Islamic law mitigates the impact of the negative crisis of the subprime crisis for Islamic financial markets due to the prohibition of excessive debt on interest. Islamic teachings prohibit the sale of debt. The latter must only be exchanged at its nominal value. Similarly, derivative financial products and toxic assets, which played an important role in triggering the crisis, are non-existent in the Islamic financial sector [30]. All these contracts are prohibited by Islamic law as they contain gharar.

To explore the short- and long-term dynamic relationships of conventional and Islamic stock markets, the VECM-based causality test will be applied. Indeed, the existence of a cointegration relationship is a prerequisite for applying the VECM-based causality test. The cointegration relationship is present only for a single period of the sample which is the crisis period. As a result, the Granger causality test based on VECM is used only for this period. Table 6 summarizes the long-term and short-term relationships between Islamic and conventional equity markets during the crisis period.

To study the dynamic causal relationships between these markets, the significance of the error correction terms (ECT) indicates the presence of a long-term causal relationship between the stock markets. While the significance of F statistic from joint tests of delayed differences in each variable determines the presence of a short-term causal relationship.

For the period studied, the results presented in Table 6 reveal the existence of a short and long-term causal relationship between the Islamic and conventional stock markets. The term Error Correction (ECT) is significant for the Islamic and conventional market of the GCC ex Saudi region, but only for the Islamic market of Malaysia and world market. This suggests that when there is an imbalance in the financial system, these indices will adjust to eliminate this gap [3].

Table 6. Vector Error Correction Model Multivariate Causality Analysis

Table 7. Short term causal relationship

The insignificance of the ECT error term for Indonesia and Malaysia indicates the isolation of these stock markets from regional and global markets. The global Islamic and conventional markets are the most significant markets for the short-term fluctuations of the Islamic and conventional sample countries. The lagged difference in the global market is considered significant for all markets except for the traditional and Islamic markets of Indonesia and conventional Malaysian.

For both periods, Indonesia followed by Malaysia is considered relatively exogenous in the short term. Two-way causality relationships can be found between global and GCC ex Saudi Islamic and conventional markets. These findings suggest that there is no benefit of diversification.

Table 7 summarizes the short-term causal relationships between the various conventional and Islamic stock markets during the crisis period.

5. Conclusion

This paper attempts to examine the dynamic relationships between Islamic and conventional stock indices. The interdependence of stock markets has important implications for allowing international financial traders to make consistent decisions about risk management issues and international portfolio diversification.

The lack of evidence of cointegration and the independence between the Islamic stock markets on the one hand, and the Islamic and conventional stock markets on the other hand, indicates that Islamic stock market indexes are attractive than their conventional counterparts for portfolio managers and international investors. Opportunities for potential earnings through diversification of investment portfolios are high in these markets.

References

[1]   | Abbes M B, Trichilli Y, Islamic stock markets and potential diversification benefits, Borsa _ Istanbul Review 15(2) 93-105, 2015.
[2]   | Khan T.A, Cointegration of international stock markets: an investigation of diversification opportunities, Undergraduate Economic Review, 8 (1), 2011.
[3]   | Hengchao Z et Hamid Z, The impact of Subprime crisis on Asia Pacific stock markets, Journal of Asia Pacific Business, 16 (2), 105-127, 2015.
[4]   | Kassim, S. H, Global Financial Crisis and Integration of Islamic Stock Markets in Developed and Developing Countries, V. R. F Series,461,2010.
[5]   | Dewi M., Ferdian. I. R., Islamic finance: A therapy for healing the global financial crisis, http://ebookpdf. Net/islamic-finance-a-therapy-for-healing-the- global financial- crisis.html, accessed on 10/04/2012.
[6]   | Shanmugam, B., Zahari, Z.R, A primer on Islamic finance, Research Foundation Publications of CFA Institute, Charlottesville.
[7]   | Saiti B, Cointegration of Islamic stock indices: Evidence from five ASEAN countries” International Journal of Scientific & Engineering Research, 6 (7), 1392- 1405, 2015.
[8]   | Dewandaru, G., Rizvi, S.A.R., Masih, R., Masih, M., Alhabshi, S.O, Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis, Economic Systems, 38, 553-571, 2014.
[9]   | Baele L, Ferrando A, Hordahl P, Kryova E, Monnet C, Measuring financial integration in the euro area, European central bank, occasional paper series,14, 2004.
[10]   | Gupta, R., Guidi, F., Co-integration relationship and time varying co-movements among Indian and Asian developed stock markets, International Review of Financial Analysis 21, 10-22, 2012.
[11]   | Didier T, Mauro P, Schmukler SL, Vanishing financial contagion, Journal of policy modeling, 30, 775-791, 2008.
[12]   | Agenor PR, Benefits and costs of international financial integration: theory and facts, the world economy, 26, 1089-1118, 2003.
[13]   | Saiti B, Bacha O.I, Masih M, The diversification benefits from Islamic investment during the financial turmoil: the case for the US based equity investors, Borsa Istanbul review, 14(4), pp 196-211, 2014.
[14]   | Masood O, Bellalah M, Chaudhary S, Mansour W, Teulon F, Cointegration of Baltic stock markets in the financial tsunami: Empirical Evidence, International Journal of business, 15 (1), 2010.
[15]   | Kassim SH, The global financial crisis and the integration of Islamic stock markets in developed and developing countries, Asian academy of management journal of accounting and finance, 9(2), 75-94, 2013.
[16]   | Yi Z, A time varying model to test the integration in the stock markets of East Asia, 2006.
[17]   | Naranjo, A., Aris, P, Financial market integration tests: an investigation using US equity markets, Journal of International Financial Markets, Institutions and Money, 7, 93-135, 1997.
[18]   | Bekaert, G., Harvey, C. R, Time-Varying World Market Integration, Journal of Finance, 50 (2), pp. 403-444, 1995.
[19]   | Cheng H., Cointegration Test for Equity Market Integration: The Case of the Great China Economic Area Japan and the United States, George Washington University, 2000.
[20]   | Forbes, K.J., Rigobon, R., No Contagion, Only Interdependence: Measuring Stock Market Comovements, Journal of Finance 43(5), 2002.
[21]   | Dornbusch R, Park Y.C, Classens S, Contagion: understanding how it spreads, World Bank Research Observer, 15, 177-197, 2002.
[22]   | Kaminsky, G., and C. Reinhart, On Crises, Contagion, and Confusion, Journal of International Economics, vol 51(1), pp 145-168, 2000.
[23]   | Dickey, D. A., Fuller, W. A., Likelihood ratio tests for autoregressive time series with a unit root? Econometrica, 49, 1057-1072, 1981.
[24]   | Akaike, H., A new look at the statistical model identification", IEEE Transactions on Automatic Control 19 (6), 716-723, 1974.
[25]   | Engle R.F, Granger C, Co-integration and Error Correction: Representation, Estimation and Testing, Econometrica, 55, 251-276, 1987.
[26]   | Johansen, S., Juselius, K., Maximum likelihood estimation and inference on cointegration, with applications to the demand for money, Oxford Bulletin of Economics and Statistics, 52, 169-210, 1990.
[27]   | Johansen, S., Statistical analysis of co integrating vectors, Journal of Economic Dynamics and Control, 12, 231-254, 1988.
[28]   | Granger,C.W.J, Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica. 37 (3): 424-438, 1969.
[29]   | Cheung, Y.W., Lai, K.S., Finite-sample sizes of Johansen's likelihood ratio tests for cointegration, Oxford Bulletin of Economics and Statistics, 55, 313-328, 1993.
[30]   | Haneef, R., & Smolo, E., Reshaping the Islamic Finance Industry Applying the Lessons Learnt From the Global Financial Crisis, ISRA 11/2010.