Open Access Journal Article

Quantifying the connectedness and portfolio implications between Islamic and conventional bonds: Evidence from global and GCC regions

by Md. Ruhul Amin a orcid ,  Md. Abdul Hakim b orcid ,  Md. Mamunur Rashid c,* orcid  and  Shaikh Masrick Hasan c orcid
a
Department of Finance and Banking, Islamic University, Kushtia, Bangladesh
b
Department of Business Administration, Notre Dame University, Dhaka, Bangladesh
c
Department of Finance, Jagannath University, Dhaka, Bangladesh
*
Author to whom correspondence should be addressed.
JEA  2022 1(2):9; https://doi.org/10.58567/jea01020001
Received: 25 November 2022 / Accepted: 8 December 2022 / Published Online: 15 December 2022
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Abstract

We explore the connectedness and portfolio implications between Islamic and conventional bonds in global and GCC regions. We also compare which bonds performed better during our sample period. Unlike previous studies, we focus on Islamic bond markets compared to their conventional counterparts and highlight the GCC bonds (Islamic and conventional) in respect of global bonds. We apply the DCC-GJR-GARCH (1,1) method, the Sharpe ratio, and the portfolio implications strategy over the period from September 1, 2013, to February 23, 2022. Our time-varying results suggest that the relationship among all variables varies over time, but most of them are positive, suggesting that there are fewer diversification opportunities between Islamic and conventional bonds. Hedging and diversification benefits are found only in the limited period among these variables, especially between GCC bonds and global bonds, and global Sukuk and GCC Sukuk. The findings of risk-adjusted returns reveal that Islamic bonds outperform their conventional counterparts. Moreover, mixed results are found in the case of hedging costs, and the majority of the fund, based on optimal weights, should be invested in Islamic bonds. Our study endows investors and regulators in the global and GCC markets with new insights on how to shield their investments and the financial system from financial crises through a hedging strategy with Islamic finance.

Keywords: Conventional bonds; Sukuk; Time-varying analysis; Portfolio implications;
Copyright: © 2022 by Amin, Hakim, Rashid and Hasan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

1. Introduction

The unending spread of the COVID-19 pandemic has shrunk the global economic and financial markets. As the representative of this crisis, a 3% drop in the global economy has been projected by the International Monetary Fund (2020) this year. Furthermore, the rate of unemployment in the United States jumped from 3.7% to 14.8% in the early two months of the pandemic (Yarovaya et al., 2021). Recently, Sharif et al. (2020), Corbet et al. (2020), Ramelli and Wagner (2020), and Akhtaruzzaman et al. (2020) have provided evidence of the repercussions of the COVID-19 pandemic on the financial markets. Therefore, almost every corner of the financial and economic system is hit by this pandemic, causing investors worldwide to experience great uncertainty regarding portfolio diversification. It is essential to search for alternative assets that have hedging and safe-haven properties, such as gold (Baur & Lucey, 2010; Baur & McDermott, 2010) and cryptocurrencies (e.g., Aysan et al., 2018; Feng et al., 2018), to safeguard their investments from global risks caused by this ongoing pandemic. Recent studies show that traditional and potential safe-haven assets, such as gold (Hasan et al., 2021a; Cheema et al., 2022), Bitcoin (Conlon & McGee, 2020; Hasan et al., 2022c), and the Swiss Franc (Hasan et al., 2021a), fail to protect investors' portfolios from crises.
Shariah-based assets are typically regarded as safer, more stable, and less volatile due to their unique features compared to their conventional counterparts. Akhtar & Jahromi (2017) find the safe haven role of Islamic financial products due to the banning of sub-prime mortgage securities and derivatives amid the global financial crisis. Additionally, several factors, such as unwise loaning practices, accounting models, and poor risk management, influenced the global financial crisis. However, these factors did not impact the Islamic finance industry due to their prohibition under Islamic laws. Moreover, under Shariah rules, interest (riba), intentional lack of accountability (gharar), transactions containing needless complexity or uncertainty, alcohol, tobacco, and gambling (gimar) relating to short sales, arbitration, and speculation are strictly banned (Hasan et al., 2021b). All of these principles regarding Islamic assets are set by Shariah scholars worldwide.
Although the literature concerning Shariah-compliant assets is comprehensive, several factors persuade us to choose these financial markets for further investigation. Islamic finance has come into the spotlight not only for investors in Muslim countries but also for non-Muslim countries around the world, with a market capitalization of US$3.50 trillion and around 10.3% growth in 2020 (Sharif, 2020). Empirical findings are ambiguous regarding the behavior of Shariah indices and demonstrate that Islamic financial assets show better performance compared to non-Islamic financial products during crisis periods (Arouri et al., 2013; Ashraf, 2013; Akhtar & Jahromi, 2017; Boo et al., 2017). However, opposing findings are also evident in studies such as Rejeb (2017), Cevik and Bugan (2018), Mezghani and Boujelbène (2018), and Ahmad et al. (2018), among others. Similarly, Foglie and Panetta (2020) extensively reviewed the related literature in this regard, with 42 papers favoring Islamic stock indices and 27 studies opposing the hedging and safe haven nature.
In general, Sukuk is "certificates of equal value representing undivided shares in ownership of tangible assets, usufruct, and services or (in the ownership of) the assets of particular projects. The returns on the certificates are directly related to the returns generated by the underlying assets" (World Bank report, 2015)[1]. However, among the Shariah-compliant assets, Islamic bonds (Sukuk) have been established recently as an alternative to interest-bearing instruments like conventional bonds. The Sukuk markets around the world have experienced tremendous growth, with Malaysia dominating those markets, followed by the Gulf Cooperation Council (GCC) countries (Naifar & Hammoudeh, 2016). Additionally, there is significant motivation for many investors of various faiths to apply their faith in investing, especially in the GCC markets, which are extremely affluent and strongly oriented toward their own religions. Furthermore, the GCC area, along with Malaysia, dominates the worldwide Sukuk market, accounting for almost two-thirds of all Islamic financial assets in the world. Very few or no studies have focused on GCC bonds (both Islamic and conventional) compared to global ones to offer hedging opportunities.
Recently, Yarovaya et al. (2021) found that there is no safe haven property in Islamic assets except the Sukuk index. In another study, Mirza et al. (2022) found that the risk-adjusted performance of Islamic equity funds is higher than that of conventional equity funds during the COVID-19 pandemic. However, the financial markets have been seriously impacted by the pandemic in several ways, including liquidity shortages, volatility jumps, capital outflows, currency depreciation, and poor risk management. Therefore, it is timely to investigate the hedging or safe-haven status of these markets, especially global and GCC Islamic bonds, against their traditional counterparts, both pre-and post-COVID-19 pandemic.
To address the gaps in the literature, we examine the association between Islamic and conventional bonds (both global and GCC) to explore the diversification benefits and portfolio choices between Islamic and conventional bonds. We use daily closing prices of these assets from September 1, 2013, to February 23, 2022. Based on the OLS method, we find that both Islamic and conventional bonds are closely connected with each other during the sample period. However, our time-varying results suggest that the relationship among all the variables varies over time, but most of them are positive, suggesting that there is less hedging or diversification opportunity between Islamic and conventional bonds. Hedging and diversification benefits are found only in a limited period, particularly between GCC bonds and global bonds, and global Sukuk and GCC Sukuk. Our findings on risk-adjusted returns reveal that Islamic bonds outperform their conventional counterparts. Moreover, we find mixed results in the case of hedge ratio, and based on optimal weights, the majority of funds should be invested in Islamic bonds to achieve the highest hedging effectiveness. Finally, our results suggest that Islamic bonds can be used as an alternative tool to protect investors’ portfolios against future crisis events.
Our study contributes to the literature in several ways. First, unlike previous studies, we focus on Islamic bond markets compared to their conventional counterparts in the GCC and global contexts. Yarovaya et al. (2021) analyzed Shariah-compliant stocks and bonds during the pandemic crisis but did not examine GCC bonds (Islamic and conventional) in relation to global bonds. Second, our study highlights the GCC markets, which is a novel contribution, as no research has been conducted recently on the GCC bond and Sukuk markets. Furthermore, we compare the GCC markets with the global ones in terms of their hedging and diversification potentials, which will help investors construct an optimum portfolio structure to diversify portfolio risks. Third, we apply DCC-GJR-GARCH (1,1) and portfolio implications (hedge ratio, optimal weights, and hedging effectiveness), which enable us to provide a clear overview of the time-varying results and portfolio strategies. Finally, the findings of our study have implications not only for investors and regulators of Muslim countries but also for those of non-Muslim countries, since our study focuses on the world as well as GCC markets.
The rest of this study is organized as follows. Section 2 discusses the previous literature relevant to this paper. Section 3 describes the data and research methodology. Section 4 presents the empirical results and their relevant discussion. Finally, Section 5 provides the conclusions, implications, and limitations of this research.

2. Literature Review

A growing number of studies (e.g., Arouri et al., 2013; Ajmi et al., 2014; Al-Khazali et al., 2014; Dewandaru et al., 2014; Ho et al., 2014; Akhtar & Jahromi, 2017; El Mehdi & Mghaieth, 2017) have investigated the performance, volatility, and co-movement between Islamic finance and its conventional counterparts, and they have all found contradictory and mixed results. Similarly, a comprehensive literature review ranging from 2009 to 2019 related to the interdependence, decoupling, and contagion of Islamic finance compared to its conventional counterparts was conducted by Foglie & Panetta (2020), uncovering mixed results. Although some studies have been performed to examine these issues, their findings are divergent, highlighting the lack of consensus on these concerns. However, in this section, we highlight some relevant papers that focus on the relationship between Islamic (Sukuk) and conventional bonds from several perspectives.
The Islamic bond (Sukuk) has come to the spotlight for its tremendous diversification or hedging role in the time of the global financial crisis. Some studies (Cakir & Raei, 2007; Alam et al., 2013; Azmat et al., 2014) attempt to differentiate Sukuk from conventional bonds, and their evidence suggests that Sukuk has dissimilarities over conventional bonds with respect to contractual arrangements. Bhuiyan et al. (2020) examine whether the Sukuk market is different from conventional bond markets based on the value-at-risk (VaR) approach. They observed that the VaR amount of Sukuk indices is comparatively much lower than the VaR of bond indices in all cases. However, this research is limited to covering only six years of data. Aloui et al. (2015) inspect whether Sukuk and Islamic stocks move in tandem in the GCC regions. They indicate that the co-movement is dominated in the long run and depends on the time and frequency. The diversification benefit is strongly evidenced, depending on the market circumstances. Maghyereh and Awartani (2016) explore the returns and volatility spillovers between Islamic bonds (Sukuk) and conventional bonds. They highlight the importance of Sukuk in the strategic asset allocation and hedging of international investors.
Recently, Shahzad et al. (2019) constructed a portfolio including the Sukuk index with major Islamic stock indexes, i.e., world, USA, UK, Canada, and Japan. Their empirical findings suggest that Sukuk provides potential hedging benefits for the largest Islamic stock indices. Both studies focus only on the portfolio formation between Islamic bonds (Sukuk) and stocks but do not focus on the comparative analysis of Sukuk and its conventional counterpart. Likewise, Ahmed and Elsayed (2019) examine the decoupling hypothesis between Islamic and conventional capital markets by analyzing the dynamic interdependencies among conventional stocks, Islamic stocks, bonds, and Sukuk markets in Malaysia. They find that the conventional stock and bond markets are regarded as the main net transmitters of spillovers toward other markets, whereas the Sukuk market is a net receiver of modest levels of return shocks from conventional, Islamic, and bond markets.
Hassan et al. (2018) adopted a multivariate GARCH framework to examine conditional correlations and volatility linkages between Sukuk (Islamic bonds) and conventional bond markets in Europe, the United States, and emerging markets. They found that Sukuk returns are much less volatile than those of U.S. and EU investment-grade bonds. They observed that during recessions, the dynamic correlation between Sukuk and bond markets tends to increase. Hossain et al. (2021) examined whether Sukuk and conventional bonds are different assets in terms of their return and risk profile. They found that Sukuk returns are insignificantly different from those of bonds but have a significantly higher risk. However, they found that Sukuk investors are not sufficiently compensated for the higher risk. Furthermore, Pirgaip et al. (2020) unveiled the diversification behavior of bond portfolios (conventional and Sukuk) in Turkey, and their results confirmed the presence of these benefits in times of economic downturns. They also constructed different risk-return patterns individually or mixed, where risk substantially differs based on the direction of the risk-return profile.
From the perspective of risk factors, Naifar and Hammoudeh (2016) analyzed the effects of various risk and uncertainty factors such as economic policy uncertainty (EPU), global financial distress (CFSI), global commodity and financial market risk indices on Sukuk markets (both global and GCC). They found that GCC Sukuk is negatively affected by all the factors they examined except the conventional bond and gold market uncertainties, while the global Sukuk is only affected by the global conventional bond uncertainty index. Their findings suggest that the effects on the GCC Sukuk markets are more pronounced compared to the global Sukuk index due to the unprecedented movement of oil prices. To date, Paltrinieri et al. (2019) uncovered a wide range of literature (80 papers) in connection with Sukuk’s research spanning the period 1950-2018, and they recommended making a comparison of the return pattern across several time frames and expanding the study on profitability, considering trading tactics on Islamic financial assets.
From the literature discussed above, several features can be drawn. First, we observe that no consensus has been reached by earlier studies regarding the connectedness between Islamic and conventional bonds in the GCC and global perspectives. Second, we notice that most of the research focuses only on the relationship between Islamic and conventional bonds in the global or country-wise context. However, no research has been performed regarding the comparative analysis of global and GCC regions in the context of Islamic and conventional bonds, except Naifar and Hammoudeh (2016), who considered various risk and uncertainty factors to explore the impact on the global and GCC Sukuk market only. Third, prior studies do not cover the COVID-19 pandemic period to see whether the relationship or connectedness between these variables differs in normal and crisis periods. Therefore, it is crucial to study the connectedness between Islamic and conventional bonds (GCC and global) to offer both investors and policymakers better investment and policy decisions. If the relationship differs between global and GCC bonds (both Islamic and conventional), stakeholders may make useful decisions in formulating or redesigning policy decisions. However, this study is attempting to fulfill the abovementioned literature gap.

3. Data and Methodology

3.1. Data
In this paper, we use the closing/spot price of two Islamic bonds (global and GCC Sukuk) and their conventional counterparts. The Islamic and conventional bonds carry two pairs. These are Dow Jones World Sukuk and Gulf Co-operation Council (GCC)[2] countries Sukuk and their conventional assets. The two pairs of bonds are the Dow Jones world Sukuk index, the S&P International Corporate Bond Index, GCC Sukuk, and the GCC bond index. However, for all the selected assets in this study, we gather data from S&P (http://us.spindices.com) (Ashraf & Khawaja, 2016), spanning the data period from 01 September 2013 to 23 February 2022. Based on the availability of data, we select this sample period. Our sample period covers the COVID-19 pandemic crisis, which has adversely impacted the global economic and financial system (Hasan et al., 2021a). Moreover, we estimate the daily returns of all chosen assets as the first difference in the logarithms to conduct this study. The specification for logarithmic returns can be expressed as follows:
Rt=ln⁡(PtPt-1)×100
Here, Rt refers to logarithmic returns of a given asset at period t, ln refers to natural logarithm, Pt and Pt-1 are the closing prices of the index on periods, t and t-1, respectively.
The prices and returns of Islamic and conventional bonds in the global and GCC regions are depicted in Figure 1. We notice that the prices of the global bond (reported in Panel A of Figure 1) started increasing from the beginning of the sample period and started decreasing after 2014. We also observe that there is a general upward trend in the case of the global bond after mid-2015. We further witness that the prices of Global Sukuk, GCC Sukuk, and GCC Sukuk are following the general increasing trend. However, the prices of these assets drastically reduced during early 2020, which is considered the COVID-19 pandemic period. The pandemic has had a negative impact on the global economic and financial systems, and asset prices were negatively affected by this crisis. Therefore, the prices of these assets decreased during the early COVID-19 phase. After that period, the prices of these assets started increasing and continued up to the study period. On the other hand, we find that the returns of all assets considered in this study (illustrated in Panel B of Figure 1) are more volatile during the early 2020 period when the COVID-19 pandemic occurred in the world.
3.2. Econometric methodology

3.2.1. Ordinary Least Square

We begin with the Ordinary Least Square (OLS) estimation that measures the association between Islamic and conventional bonds from global and GCC regions. This is widely used as the parameter of dependency, which shows the simple statistical link between the variables. The following is the specification of simple linear We begin with Ordinary Least Squares (OLS) estimation, which measures the association between Islamic and conventional bonds from the global and GCC regions. This is widely used as the parameter of dependency, which shows the simple statistical link between the variables. The following is the specification of simple linear regression:
R t = a 1 + β i U i t + ϵ t R t = α 1 + β i U i t + ϵ t
(1)
whereRtdenotes the returns of dependent variables. Uitindicates the vector of independent variables used in this study that are expressed as a natural logarithm as the first difference of their values. ϵt is the error term. However, this technique only captures a simple linear relationship between the variables. The simple linear estimation can lose its significance, however, when we measure the range of data beyond the mean value or in the extreme values.

3.2.2. DCC-GJR-GARCH (1,1) model

In this study, we consider the multivariate Glosten, Jagannathan, and Runkle (1993) (GJR) Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model with dynamic conditional correlation (DCC) proposed by Engle (2002), formed GJR-GARCH model.[3] The asymmetric response of volatility to positive and negative shocks can be measured using the DCC-GJR-GARCH model. This method involves adding a new term that recognizes asymmetries to the GARCH model. Furthermore, the inclusion of a leverage element to describe asymmetric volatility is one of the novel aspects of the GJR-GARCH model (Al Mamun et al., 2019). A major negative shift in the GJR-GARCH model is more likely than a large positive change to be followed by another large negative change. Recent studies (e.g., Brownlees et al., 2011; Laurent et al., 2012) suggest that GJR models outperform the GARCH specification. Some recent studies (e.g., Hassan et al., 2021; Hasan et al., 2022b) also utilize this method. The conditional return on the dependent variables follows the process:
r t = μ + ψ R t - 1 + ε t , ε t = z t h t , z t ∼ N 0 , 1
(2)
where rt=[Ri,t,…..,Rn,t] is the (n×1) vector of the returns on the Islamic and conventional bonds under consideration. μ is the vector of the constant terms, and ψ denotes the coefficient vector of the autoregressive terms. Et=Ei,t,…..,En,t represents the vector of standard residuals. In the next step, we estimate the conditional variance (conditional volatility) of the i-th element follows from the GJR-GARCH (1, 1) model as follows:
h i , t 2 = ω + ⍺ E i - 1 2 + β σ i - 1 2 + Υ E i - 1 2 I t - 1
(3)
where It-1=1 if Et-1<0, otherwise It-1=0. Υ is the leverage coefficient term to capture the asymmetric influence. WhenΥ>0, this indicates that the negative shocks impact more than the positive shocks. The parametersω,⍺, β, and Υ in Equation (3) can assure the stationarity of the conditional volatility process only when the conditions ω>0, ⍺,β,Υ≥0, and Υ+⍺+β2<1 are satisfied.
The diagnostic tests on the standardized squared residuals indicate that our selected GJR-GARCH (1, 1) model with a Student-t distribution is correctly specified because the estimated residuals are free from autocorrelation effects. The model also detects the possibility of the existence of the second or higher-order moment of the GJR-GARCH. Finally, the residuals of the marginal models adequately capture the return distributions.
We obtain the dynamic correlations between the Islamic and conventional bond markets using the Dynamic Conditional Correlation (DCC) model of Engle (2002). Assume that Et-1εt=0and Et-1εtε't=Ht, where Et. is the conditional expectation at the time t. Therefore, the conditional variance-covariance matrix (Ht) is the product of the variance and correlation matrices and can be defined as the following form:
H t = D t 1 2 D C C t D t 1 2
(4)
where DCCt is the n×n time-varying correlation matrix, while the diagonal matrix of the square roots of the variances is given byDt=diag(hi,t,K,hn,t) . Engle (2002) models the right-hand side of equation (5) rather than Ht directly by proposing the following dynamic correlation structure:
D C C t = d i a g Q t - 1 2 Q t d i a g Q t - 1 2
(5)
Q t = 1 - a - b S + a d i a g Q t - 1 1 2 ε ^ i , t - 1 ε ^ i , t - 1 ' d i a g Q t - 1 1 2 + b Q t - 1
(6)
This implies that the conditional correlation is dynamically driven by the process of Qt where S is the n×n unconditional covariance matrix for the standardized residuals ε^i,t, and a, b are non-negative scalars satisfying a+b<1 . The resulting model is called DCC-GARCH.

3.2.3. Hedge ratio, optimal portfolio weights, and hedging effectiveness

Furthermore, the hedge ratio (HR), optimal portfolio weights, and hedging effectiveness (HE) are used to offer a superior hedging strategy and portfolio implications to investors and portfolio managers with a better (Antonakakis et al., 2019). Some contemporary research (e.g., Yousaf & Yarovaya, 2021; Hasan et al., 2022a) also utilizes these calculations in their studies to do the same. However, we estimate the HR, introduced by Kroner and Sultan (1993), based on the conditional variance and covariances of the DCC-GARCH t-Copula. The HR evaluates the hedging cost of a $1 long position in asset i with a βijt USD short position in asset j, in this case, several global and GCC bonds (both Islamic and conventional). The specification is expressed as follows:
β i j t = h i j t h j j t
(7)
It indicates that higher conditional variances lead to lower hedging costs for long positions, whereas greater conditional covariance leads to higher hedging costs for long positions.
This research also estimates the optimal portfolio weights (proposed by Kroner and Ng (1998)), Wijt , based on the DCC-GARCH t-Copula approach. The optimal portfolio weights between the green bond and ESG indices pair can be estimated through the following specification:
W i j t = h j j t - h i j t h i i t - 2 h i j t + h j j t
(8)
where Wijtcould be more than one or less than zero. We establish the following constraints to capture this drawback:
W i j t = 0 , i f W i j t < 0 W i j t , i f 0 ≤ W i j t ≤ 1 1 i f W i j t > 1
Finally, Ederington’s (1979) HE approach is employed in measuring the effectiveness of hedging and different portfolio strategies between the green bond and ESG indices. It can be expressed as follows:
H E i = 1 - V r β , w V r u n h e d g e d
(9)
where the rβ,w can be computed as
r β = y i t - β i j t y j t r w = w i j t y i t + ( 1 - w i j t ) y j t
H E i denotes the percent decrease in the unhedged position's variance. The variance of the unhedged position of asset i is denoted by V r u n h e d g e d . V ( r β , w ) suggests the hedged portfolio variance either from the optimal HR or the optimal weight strategy. The higher risk reduction in the portfolio is linked with a greater H E i .

4. Analysis of Results

4.1. Summary statistics and correlation matrix
The descriptive statistics for all the variables are presented in Panel A of Table 1. The results indicate that the global Sukuk and GCC bonds have the highest mean returns, whereas the global bond has the lowest mean return and the highest volatility (measured by standard deviation) in the sample period. This result suggests that, on average, global Sukuk and GCC bonds outperform other assets. On the other hand, the global bond exhibits maximum one-day returns (2.94%) and minimum one-day losses (-4.65%). Our risk-adjusted returns, based on the Sharpe ratio, indicate that Islamic bonds (both global and GCC) reveal the highest Sharpe ratio, suggesting that Islamic bonds outperform conventional bonds (both global and GCC). This result is supported by some recent studies, such as Al-Yahyaee et al. (2020), Sherif (2020), Mirza et al. (2022), and Ashraf et al. (2022). However, negative skewness and high kurtosis values are observed for all the selected assets, indicating that the return series is symmetric with heavy fat tails or outliers. The Jarque-Bera statistic is rejected at the 1% level of significance, highlighting that the return series are abnormally distributed for all the chosen assets.
Stationarity issues are a serious problem in time series data. However, several methods are introduced to test the stationarity of financial data. The return series stationarity is tested with the augmented Dickey-Fuller (ADF) test (Dickey & Fuller, 1979) and Phillips-Perron (PP) test (Phillips & Perron, 1988). Although there are several tests for stationarity, we have used ADF and PP tests as they have some benefits compared to other tests, particularly in capturing the residuals' autocorrelation issues (Hasan et al., 2022c). The results suggest that there are no stationarity issues in the return series for all the assets in the sample period. The results of the unconditional correlation are reported in Panel B of Table 1. The correlation matrix's results suggest that all the variables, whether Islamic or conventional, are strongly and positively correlated with each other during our sample period. These findings imply that there is no diversification opportunity among the variables, as all the assets are strongly correlated.
4.2. Ordinary least square analysis
Table 2 shows the results of the OLS estimations during the whole study period. The relationship between the global bond and the global Sukuk is positive and significant. This result indicates that an increase in the returns of the global bond increases the returns of global Sukuk, and vice versa. In this case, there is no hedging or diversification opportunity between the global bond and global Sukuk, highlighting that these two assets might be equally impacted by any financial and economic crises, such as the COVID-19 crisis. On the other hand, the
association between the GCC bond and the GCC Sukuk is positive and statistically significant, implying that GCC Sukuk doesn't serve as a hedging or diversification opportunity for GCC bonds. The Durbin-Watson (DW) test statistic results indicate that the OLS estimations are free from autocorrelation problems in the datasets, as the values of DW are greater than 2.
4.3. DCC-GJR-GARCH (1, 1) estimations
Furthermore, we use Engle's (2002) dynamic conditional correlation (DCC) approach in combination with the GJR-GARCH method of Glosten et al. (1993) to capture the asymmetric time-varying dependency between Islamic and conventional bonds. Figure 2 depicts the DCC plots for the variables during our sample period. We find a consistently positive correlation between GCC bonds and GCC Sukuk throughout the entire sample period, suggesting that there is no hedging or safe-haven ability between the variables. The probable reason for these outcomes is that the economies of the GCC countries are profoundly reliant on the global oil market, which has recently experienced significant fluctuations due to the Russia-OPEC price war and the trade war between the US and China (Sharif et al., 2020). The COVID-19 pandemic caused the oil price crisis to worsen, which threw the GCC nations' financial markets into chaos. This notion is further supported by Hassan et al. (2022a).
On the other hand, we observe a mixed relationship between GCC bonds and Global bonds. For example, there is a positive correlation across most of the study period, whereas we notice a negative association in around 450 and 1000 observations. The period of these observations might correspond to late 2014 and 2016. This result implies that there is a diversification opportunity between GCC bonds and Global bonds in the late 2014 and 2016 sample period. The same phenomenon (e.g., negative relations) is further evidenced during the observations from 1600 to 1900 (corresponding to late 2019 to late 2020), which are considered as the COVID-19 pandemic periods, suggesting that there is a hedging or diversification opportunity between these variables.
We further find that the relationship between Global bonds and Global Sukuk is positive throughout the entire sample period (except in observation 1000), reflecting the non-existence of diversification opportunities. On the other hand, when we examine the connectedness between Global Sukuk and GCC Sukuk, we find that the association is positive, up to 800 observations. Then, this relation turns negative, offering the diversification benefit between Global Sukuk and GCC Sukuk. Overall, our results suggest that the Islamic and conventional bond pairs can be utilized as a hedge and safe-haven tools, depending on the time period, which is partially in line with Hasan et al. (2022a). Investors can review our findings and create several trading strategies to diversify their portfolio risk. Policymakers can also make better decisions using our findings. Since most of the variables' relations are positive, they have a high chance of being equally affected by any crisis. Therefore, policymakers should be aware of the crisis when making policy decisions.
4.4. Portfolio implications (Hedge ratio, Optimal weights, Hedging effectiveness)
Table 3 displays the hedge ratio (HR) (long/short), optimal weights, and hedging effectiveness (HE) for global and GCC bonds over the sample years. According to the HR, a $1 long position in a bond can be hedged with the average value of the hedging ratio percentage of a short position in their relative pairs. The results show that HRs are lower between Global Sukuk/Global Bond, GCC Sukuk/Global Bond, and GCC Bond/Global Bond assets, ranging from 3% to 7% across the whole sample period. These outcomes suggest that investors require investing 3-7 cents in a short position in global bonds to hedge a USD 1 long position in global Sukuk, GCC Sukuk, and GCC bonds. The HR in the remaining pairs is somewhat higher and significant in most cases, indicating that the hedging cost is higher to hedge the cross or conventional pairs. On the other hand, the optimal weights between Global Bond and Global Sukuk, GCC Bond and GCC Sukuk, GCC Bond and Global Sukuk, and Global Bond and GCC Sukuk are 0.01 and 0.04, 0.09, and 0.19, respectively, suggesting that investors should invest the majority of their funds in both the global and GCC Sukuk markets to achieve maximum HE. Furthermore, when we consider only the Sukuk portfolios, the allocation of the fund should be 55% in the global Sukuk and 45% in GCC Sukuk.

5. Conclusions

Since the ongoing outbreak of the COVID-19 pandemic, individual investors and fund managers are still searching for resilience properties to safeguard their investments from unprecedented risks triggered by this pandemic in the global financial markets. This study is a relevant and timely assessment of financial assets, especially for the investors of Islamic finance, to safeguard their investments from pandemic risks. In this vein, we examine the relationship between Islamic bonds and conventional bonds. To do so, we utilize two (global and GCC) Islamic bond indices and their conventional opposite parts. We use several methodologies, such as ordinary least squares (OLS), DCC-GJR-GARCH (1,1) models, and portfolio implications. In addition, we also consider the Sharpe ratio. Our sample period started from September 1, 2013, to February 23, 2022, which covers the pre- and post-COVID-19 periods.
The results of our study, based on the OLS estimation, show that Islamic bond indices (both global and GCC) are highly interrelated with conventional bond indices, suggesting that Islamic bond indices are unable to provide significant diversification benefits. Some exceptions are also observed in the case of DCC estimation. The DCC estimation suggests that the Islamic and conventional bond pairs can be utilized as hedge and safe-haven tools, depending on the time period. Besides, the results of risk-adjusted (Sharpe ratios) returns unveil that the Islamic bonds outperformed compared to non-Islamic bonds during the whole sample period. However, mixed results are found in the case of hedging cost, and the majority of the fund, according to optimal weights, should be invested in Islamic bonds to gain maximum HE. Our overall finding suggests that Islamic bonds offer more resilience to the investors than other assets investigated in this study throughout the normal and financial downturn (COVID-19) periods.
The findings of this study have several implications for practice and research in the global financial system. Firstly, we provide insights regarding the trading, economic and financial reforming of faith-based sources of investments, particularly Shariah-based investments, compared with the conventional markets. Investors should invest most of their funds in Islamic bonds to achieve the highest hedging effectiveness. Secondly, our results also will be supportive in making policy evaluations for policymakers to authorize and improve the bond markets, especially during crisis periods. Lastly, this paper explores new insights for investors and regulators in the global and GCC markets about how to shield their investments and the financial system from market downfalls through a hedging and diversification strategy with Islamic finance, especially during this pandemic.
Moreover, our study opens the door for forthcoming researchers to investigate other individual country’s Islamic financial markets, sub-indices, and also the rest of the Islamic financial products, especially Islamic banks, and mutual funds. Besides, we only cover Shariah-based investments; accordingly, other faith-based investments, such as Jewish and Christian, should be incorporated by future studies.

Funding Statement

This research received no external funding.

Acknowledgments

We are grateful to Professor Yu Hao, the chief editor, and the anonymous reviewers for their kind and helpful comments, which have helped to improve the manuscript further.

Conflict of interest

All the authors claim that the manuscript is entirely original, and they declare no conflicts of interest.

Author contributions

Conceptualization: Md. Ruhul Amin, Md. Mamunur Rashid; Investigation: Md. Ruhul Amin, Md Abdul Hakim, Md. Mamunur Rashid; Methodology: Md. Ruhul Amin, Md. Mamunur Rashid; Formal analysis: Md. Ruhul Amin, Md Abdul Hakim, Md. Mamunur Rashid; Writing – original draft: Md Abdul Hakim, Md. Mamunur Rashid; Writing – review & editing: Md. Ruhul Amin, Md Abdul Hakim, Shaikh Masrick Hasan.

Notes

1
The World Bank report is available at: http://www.worldbank.org/en/topic/financialsector/brief/islamic-finance.
2
There are six countries from Middle Eastern region, i.e., Saudi Arabia, Kuwait, the United Arab Emirates, Qatar, Bahrain, and Oman are included in GCC. GCC market is designed to measure the performance of these countries. This study covers the GCC region countries for Islamic and non-Islamic bond.
3
Based on the Akaike Information Criterion (AIC) and Schwarz Criterion (SC), we choose the GJR-GARCH (1, 1)model. The details frameworks are available upon request.

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figure-1
Figure 1. Price dynamics and returns of Islamic and conventional bond indices.
Figure 1. Price dynamics and returns of Islamic and conventional bond indices.
figure-1
Table 1. Descriptive statistics and correlation matrix.
Table 1. Descriptive statistics and correlation matrix.
Panel A: Descriptive statistics and unit root tests
VariablesGlobal BondGlobal SukukGCC BondGCC Sukuk
Mean0.00540.01590.01780.0157
Maximum2.94750.72932.82121.0862
Minimum-4.6551-1.3398-3.5884-1.1634
Std. Dev.0.48090.11910.24170.1230
Sharp ratio0.01120.13350.07360.1276
Skewness-0.8954-1.7571-2.4834-0.9720
Kurtosis12.929322.589258.620017.6337
Jarque-Bera9323.06***36274.82***285580.00***19958.35***
ADF-8.807***-17.048***-11.667***-17.025***
PP-15.424***-20.566***-22.025***-24.025***
Panel B: Correlation matrix
Global Bond1
Global Sukuk0.3189***1
GCC Bond0.1447***0.3760***1
GCC Sukuk0.1377***0.4644***0.7275***1
Note: The table reports the results of descriptive statistics for the return series of all selected assets. The sample period spans from September 30, 2013 to February 23, 2022. The Sharpe ratio is calculated by dividing an asset's mean returns by its standard deviation following Bouri et al. (2020). The ADF and PP tests are used to test for stationarity in the return series. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively.
Table 2. Relationship between Islamic and conventional bond.
Table 2. Relationship between Islamic and conventional bond.
Dependent Variable: Global Sukuk
VariableCoefficientStd. Errort-StatisticProb.
Global Bond0.07900.005015.76790.0000
C0.01540.00246.4178760.0000
Durbin-Watson stat2.1980
Dependent Variable: GCC Sukuk
GCC Bond0.37010.007449.69280.0000
C0.00900.00185.04080.0000
Durbin-Watson stat2.0481
Note: The table presents the linear relationship between Islamic and conventional bonds (both global and GCC) during the period of September 01, 2013, to February 23, 2022.
figure-2
Figure 2. Dynamic conditional correlation plots among the variables.
Figure 2. Dynamic conditional correlation plots among the variables.
figure-2
Table 3. Hedge Ratio and optimal portfolio weights.
Table 3. Hedge Ratio and optimal portfolio weights.
Panel A: Hedge Ratio
VariablesMeanHEp-value
Global Sukuk/Global Bond0.070.09**0.03
GCC Sukuk/Global Bond0.030.010.88
GCC Bond/Global Bond0.050.010.77
Global Bond/Global Sukuk1.230.15***0.00
GCC Sukuk/Global Sukuk0.420.24***0.00
GCC Bond/Global Sukuk0.580.22***0.00
Global Bond/GCC Sukuk0.570.020.61
Global Sukuk/GCC Sukuk0.390.30***0.00
GCC Bond/GCC Sukuk1.300.63***0.00
Global Bond/GCC Bond0.440.030.47
Global Sukuk/GCC Bond0.290.11***0.01
GCC Sukuk/GCC Bond0.530.51***0.00
Panel B: Optimal weights
Global Bond/Global Sukuk0.010.94***0.00
Global Bond/GCC Sukuk0.040.93***0.00
GCC Bond/GCC Sukuk0.090.74***0.00
GCC Bond/Global Sukuk0.190.74***0.00
Global Bond/GCC Bond0.130.79***0.00
Global Sukuk/GCC Sukuk0.550.22***0.00
Notes: The table presents the hedge ratio, optimal weights, and hedging effectiveness between the global and GCC bonds. HE represents hedging effectiveness. ***, **, * indicate the significance at the 1%, 5%, and 10% levels, respectively.