Journal of Islamic Economic Laws Vol. 4, No. 2, July 2021: 137-176 137 Shariah Compliant Macaulay’s Duration Model Testing: Evidence from Islamic banks in Indonesia Syed Alamdar Ali Shah1, Raditya Sukmana1, Bayu Arie Fianto1 1Universitas Airlangga email: alamdar2000pk@yahoo.com, raditya-s@feb.unair.ac.id, bayu.fianto@feb.unair.ac.id ABSTRACT The purpose of this research is to test Shariah compliant duration models on Islamic banks in Indonesia. This will be achieved using data of earning assets and risk bearing liabilities of Indonesian Islamic banks from 2009 to 2019. Using multiple regressions the results suggest that Shariah compliant duration models are robust to calculate duration of earning assets, return bearing liabilities and Islamic banks. This research adds to the previous research of testing Shariah compliant duration model. Ultimately, it will improve profitability, risk efficiency and Shariah efficiency by improved Shariah compliant measures of risk management. This will ultimately improve market capitalization and returns stability in the long run. A major limitation of the study is very short length of data of Islamic banks. Still another limitation is difference in commencement of business of various Islamic banks that makes length of data unequal. Key words: Islamic Banks, Earning Assets, Return Bearing Liabilities, Duration Model, Maturity Gap Risk Management model testing INTRODUCTION The focus of developments in Islamic financial services industry is Islamic banking. Islamic banking shares a common platform with conventional banks in overwhelming majority of the countries making them face similar risks with different impact (Archer and Karim, 2019). This different impact is also evident mailto:alamdar2000pk@yahoo.com mailto:raditya-s@feb.unair.ac.id mailto:bayu.fianto@feb.unair.ac.id 138 Afifah, Nurul Alfiah Kurniawati in their respective balance sheets (Chattha, 2013; Chattha et al., 2020). The activities of Islamic banks are exposed to a variety of risks such as credit risk, counterparty risk, equity investment risk, market risk, rate of return risk and liquidity risk (IFSB, 2005; Chattha, 2013; Archer and Karim, 2019). A major adverse affect of such risks is reduced market value of equity (Bierwag and Kaufman, 1992; Bierwag et al., 2000; Entrop et al., 2009; Chattha and Alhabshi, 2018). ROR risk is similar to interest rate risk in Islamic financial institutions (Chattha et al., 2020). It is also sometime referred to as “benchmark rate risk” Chattha and Alhabshi (2018) and has the very much potential to affect the net worth of Islamic financial institution alongwith their off-balance sheet positions, in case not properly managed (Archer and Karim, 2019; Chattha et al., 2020). Islamic Financial Services Board (IFSB) has stressed to guard against the pitfalls of ROR risk in pillar II using duration gap approach. Duration is the most common measure of risk management introduced by Macaulay (1938) and used for sensitivity against yield curve movements by Hicks (1939). Hicks (1939) work extends the application of duration into estimation of interest rate risk (Radermacher and Recht, 2020). Fisher and Weil (1971) extend the duration for portfolio immunization and Ho (1992) leads duration for non-parallel shifts of yield curve by introducing duration based on some key rates. Bierwag et al. (1978) identifies an important consideration in the development of duration models that the choice of weights in a duration model is arbitrary and is dependent on its use. It has been established over the period that Islamic bank balance sheets are structurally different from conventional banks (Chattha et al., 2020). This requires them to develop their own risk management models and other measures to tackle their risk exposures (Shah et al., 2021a&b). However, research over the period of time reveals that most of the research in Islamic context is primarily based on applying conventional tools of financial risk modeling and management in Islamic context. Application of the concept of duration in Islamic banks has also received similar Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 139 treatment (Chattha and Bacha, 2010; Chattha and Alhabshi, 2017; Chattha and Alhabshi, 2018 and Chattha et al., 2020). Addressing the issue Shah et al. (2020a) proposes a Shariah compliant duration model that requires comprehensive testing. The purpose of this study is to test the Shariah compliant duration models of Shah et al. (2020a) following the theme of implementing the durations models under the theory of Macaulay’s duration Shah et al. (2020b). This study firstly develops a framework of testing a financial model and proceeds by developing a methodology for testing the Shariah compliant duration models. It collects maturity wise data relating to return bearing assets and liabilities of Islamic banks from Pakistan. The model of Shah et al. (2020a) has been tested by developing an alternative duration models excluding the principal amounts from the Shariah compliant duration model. The purpose is to examine the effect of changes in returns on earnings assets and returns paid on return bearing liabilities on the maturity gap risk management of Islamic banks in short run and long run. This research uses multiple regression analysis, Johansen co-integration, error correction model, vector error correction model and threshold vector error correction model. LITERATURE REVIEW Literature on Islamic Banks Discussing the impact of changes in monetary policy on financial institutions it has been found that Islamic banks respond to monetary policy similar to large conventional banks (Zaheer et al., 2012). A study on 128 banks finds that privately owned Islamic banks provide more protection to their shareholders’ equity as compared to state owned banks (Daher et al., 2015). In a research about volatility and persistence in Islamic and conventional banks it has been reported that Islamic banks are more resilient towards uncertainties, but their resilience varies according to the model of Islamic financial system a country has adopted (Fakhfekh et al., 2016). The results of Beltrame et al. (2016) suggest highly negative correlation between interest rates and returns of Islamic banks. However, they report that negative effect can be mitigated 140 Afifah, Nurul Alfiah Kurniawati with growth in profit sharing investment accounts. This leads us to the finding that Islamic banks also receive affect from variations in interest rates. Sadiq et al. (2017) find that Islamic banks in Pakistan are less cost efficient due to excess liquidity, inadequate support and competition from conventional banks. Addressing the financial sector of Pakistan using DEA technique in another study it has been found that insurance sector in Pakistan is more technically efficient than banking sector (Shah and Masood, 2017). Also the Islamic financial sector has done better allocation of resources than their conventional counterparts (Shah and Masood, 2017). Hamza and Saadazoui (2018) in their work on Islamic banks report that interest rate changes negatively affect the financing of Islamic banks. Although the results in performance analysis of Islamic and conventional banks are similar but discussing the usage of credit risk transfer techniques it has been discovered that implementation of credit risk management techniques are not similar in both contexts rather there exists Shariah compliance constraints in case of Islamic banks (Saeed and Ayub, 2017). The impact of credit and liquidity risk has been analyzed by a few researches where they find no relation between the two and recommend different treatment (Trad et al., 2017; Ghenimi et al., 2017). Research over the period of time finds that although size and capital expansion positively affect profitability but negatively affect liquidity. Similar results have also been reported by Shafiullah and Shamsuddin (2018) who while addressing the topic of risk management find that Islamic banks possess higher liquidity risk but lower insolvency and credit risks as compared to conventional banks. In additions, they discuss the issue of operational risk and report that it declines with increase in numbers and qualifications of members of Shariah supervisory board. The relationship between sukuk and conventional bonds has been analyzed in terms of factors that affect correlations between the two. The results suggest that money market liquidity, stock market liquidity and credit information are the factors affecting volatility in emerging and developing markets almost similarly (Bhuiyan, 2017). Nawaz and Farzana (2018) analyze management of Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 141 investment risks in Islamic and conventional banks and find that both types of banks use similar risk management practices for management of their investments. In another study on performance analysis of banking sector it has been found that profitability of banks is affected similarly in case of Islamic and conventional banks in response to changes in interest rates (Ahmed et al, 2018). Chattha and Alhabshi (2018), report that Islamic banks respond similarly to changes in interest rates because they use similar benchmark rates of interest as their conventional counterparts. Therefore, in order to disintegrate themselves they require a separate benchmark for pricing. Chattha and Alhabshi (2018) and Chattha et al. (2020) observe that Islamic banks have longer durations as compared to their conventional parts. These longer durations create a paradox. This is because longer duration means higher risk and higher risk should lead to higher profitability. Contrary to this risk- return principle a comparison of the results suggest that Islamic banks are less profitable as compared to conventional banks (Chattha and Alhabshi, 2018; Chattha et al., 2020). This Islamic- conventional bank risk-return paradox requires investigation. The impact of variations in capital adequacy has also been examined in case of Islamic and conventional banks where it has been found that highly capitalized banks react positively to changes in capital adequacy ratio while the relation reverses in cases of low capitalized banks. The study does not report any difference between Islamic and conventional banks (Narmeen et al., 2018). Shariah Review of Duration Models: Shah et al. (2021b) performs review of following duration models and regards them non Shariah compliant. 1. Additive Multiplicative Models: These include duration models of Gultekin and Rogalski (1984) examine seven models of duration proposed by Cooper (1977), Bierwag (1977), Bierwag and Kaufman (1978) and Khang (1979). 2. Stochastic Duration Models: Duration models of Cox et al. (1979) that are based on 142 Afifah, Nurul Alfiah Kurniawati stochastic nature of interest rates. 3. Duration Using Taylor Expansion and Linear Approximation: These include duration models of Livingston and Zhou (2005), Tchuindjo (2008) and Dierkes and Ortmann (2015). 4. Effective Duration These include duration models of Leland (1994) and Leland and Toft (1996). 5. Duration of Net Income of Banks These include duration models of Toevs (1983), Bierwag and Kaufman (1992) and Bierwag and Kaufman (1996). 6. Duration Using logarithmic process: This consists of duration model of Pattitoni et al. (2012). 7. Key Rate Duration: This consists of duration model of Ho (1992). 8. Principal Component Duration These models are based on the works of Willner (1996). 9. Polynomial Time value Duration: Such models are based on the works of Osborne (2005), Osborne (2014) and Dierkes and Ortmann (2015). 10. Approximation of duration in non-flat yield curve environment This model is an extension of Ho (1992) model of key rate duration. 11. Dedicated Duration These models consists of the works of Macaulay (1938), Redington (1952), Fisher and Weil (1971), Zaremba and Rządkowski (2016) and Zaremba (2017). 12. First-Order, Second-Order Durations and Convexities: These are present value of cash flow duration models of Alps (2017). 13. Approximating Duration Using Insurance risk Management properties These are based on the works of Möhlmann (2017) and Schlütter (2017). 14. Orthogonalising the duration Such models consist of the works of Dechow et al. (2004), Chen (2014) Weber (2017) and Chu et al. (2017). Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 143 15. Implied Duration: A measure for equity duration This mode of duration has been proposed by Dechow et al. (2004). 16. Duration of an organization This model has been forwarded by Weber (2018) using the works of Dechow et al. (2004), Campbell and Vuolteenaho (2004), Hansen et al. (2008), Lettau and Wachter (2007) and Santos and Veronesi (2010). 17. Equity Duration & Book Value Duration Mohrschladt and Nolte (2018) extend the works of Merton (1973), Sweeney and Warga (1986), Dechow et al. (2004), Lettau and Wachter (2007), van Binsbergen et al. (2012), Schröder and Esterer (2012), Weber (2018) Leibowitz (1986) and Kadiyala and Subrahmanyam (2000) to propose these models. 18. Duration Model of Accounts Receivable This model has been proposed by Xu and Ma (2018). 19. Duration of Assets and Liabilities of Insurance Company Fernándeza et al. (2018) propose such duration models for assets and liabilities of insurance companies based on expected values of cashflows, time and interest.. 20. Duration Measures for Corporate Project Valuation These are duration models of Arnold and North (2008) for evaluating corporate projects. 21. Shariah Compliant Duration Model Chattha et al. (2020) and Shah et al. (2020b) Shah et al. (2021a&b) recommend and Shah et al. (2020a) propose Shariah compliant models of duration for earning assets and return bearing liabilities of Islamic banks. These models have been tested by Shah et al. (2021b). Having reviewed the literature on Islamic banks and various duration models developed and tested so far, the objective in this research is to further test the Shariah compliant duration model of Shah et al. (2020)a and tested by Shah et al. (2021b). 144 Afifah, Nurul Alfiah Kurniawati METHODS This research uses the methodology of Shah et al. (2021b) for testing Shariah compliant duration models. Following Shah et al. (2021b) this research uses data relating to financial assets and liabilities of various maturity ladders as reported in various financial statements of Islamic banks in Indonesia Pakistan for the period 2009 to 2019. Maturities are calculated in terms of Stohs and Mauer (1996). According to them maturities of less than 1 year are taken at actual periods. Whereas maturities ranging above 1 to 2 years are taken at 1.5 years, 2 to 3 years are taken at 2.5 years, 3 to 4 years are taken at 3.5 years, 4 to 5 years are taken as 4.5 years. However, for the last category that is primarily over 5 years or 10 years, the maturities are calculated on the assumption that every following year has the same proportion of assets or liabilities as the one immediately preceding until 100% of the values are allocated. Descriptive statistics of the data consist of Mean, Variance, Skewness and Kurtosis. Skewness has been measured by the third moment from mean divided by second moment to the ½ power. Kurtosis is square root of fourth moment from mean divided by second moment. The descriptive statistic has been used to confirm the observations of Bildersee (1975) Gultekin and Rogalski (1984), Chen (2014), Weber (2017) and Chu et al. (2017) that returns are skewed leptokurtic. The research also calculates t-statistics to ensure the hypotheses that qual zero. This has been achieved by calculating the product of ’s to the square root of years in sample period and taking its ratio to the standard deviation of yearly estimates. Lastly, average of R2 and standard deviation of R2 has been presented after adjusting for degrees of freedom. These are meant to measure the dependency between risk and return. Procedure for testing a financial model has also been explained by Shah et al. (2021b). Their framework for testing the duration model has been given hereunder: Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 145 F ig ur e1 . F ra m ew or k fo r te st in g a F in an ci al M od el 146 Afifah, Nurul Alfiah Kurniawati According to them, the relationship of return with duration can be expressed using the following function: (1) Where Ri,t is the net return margin b1 is estimated coefficient and DURi,t is duration. Guletkin & Rogalski (1984) provide three hypotheses to be tested on duration models using multiple regression analysis that have been amended for use in Shariah context by Shah et al. (2021b) as under: “The relationship between returns volatility and Shariah compliant duration is linear; Shariah compliant duration translates the effect of changes in rates of return, benchmark rates and maturities on returns volatility of Islamic banks; and, the markets for Islamic banks are efficient.” All three hypotheses have been tested using the function as under: (2) In the above functions Rr,o,t is the net return margin on earning assets, are average estimated coefficients, DK(r-1)(o-1)(t-1) is the duration of kth assets calculated using return and benchmak rates of the previous period and DK2(r-1)(o-1)(t-1) is the square of duration to check linearity and lastly is the factor to check whether duration normalizes reversed present values. Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 147 The duration of earning assets have testing by regressing the independent variables on returns earned on earning assets. Similarly the duration of liabilities has been tested using the function: (3) In order to examine the relationship this research examines two models of Shariah compliant duration of Shah et al. (2020a). The model of Shah et al. (2020a) to be tested in this research for earning assets is: (4) And for return bearing liabilities is: (5) 148 Afifah, Nurul Alfiah Kurniawati This methodology complies earlier works of Lanstein and Sharpe (1978) and various subsequent studies such as Lettau and Wachter (2007), Chen (2014), Weber (2018) and Shah et al. (2021b). For the purpose of this research the changes in returns of Islamic banks have been calculated in terms of Shah et al. (2020) a as hereunder: (6) Where: ∆ = Change NI = Net income DEA = Duration of earning assets DRBL = Duration of risk bearing liabilities EA = Earning Assets RBL = Return Bearing Liabilities ∆ROREA = Change in rate of return on assets ∆IBOR = Change in interbank offered rates ∆RORRBL = Change in rate of return on liabilities ∆IBAR = Change in industry average rates of return on liabilities However, besides testing the duration of assets and liabilities it also tests the duration gap of Islamic banks. The duration gap has been calculated in terms of Shah et al . (2020) as under: Duration Gap = Duration of Earning Assets – Duration of Return Bearing liabilities (7) Regression function to be used for testing duration gap shall take the following form: Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 149 (8) RESULTS AND DISCUSSION Table 1. List of Islamic commercial banks in Indonesia and data period Sr # Name of Bank Data Period 1 PT. Bank Aceh Syariah 2016-2019 2 PT BPD Nusa Tenggara Barat Syariah 2018-2019 3 PT. Bank Muamalat Indonesia 2009-2019 4 PT. Bank Victoria Syariah 2010-2019 5 PT. Bank BRI Syariah 2009-2019 6 PT. Bank Jabar Banten Syariah 2009-2019 7 PT. Bank BNI Syariah 2009-2019 8 PT. Bank Syariah Mandiri 2009-2019 9 PT. Bank Mega Syariah 2009-2019 10 PT. Bank Panin Dubai Syariah 2010-2019 11 PT. Bank Syariah Bukopin 2010-2019 12 PT. BCA Syariah 2010-2019 13 PT. Bank Tabungan Pensiunan Nasional Syariah 2015-2019 14 PT. Maybank Syariah Indonesia 2010-2019 Data Source: Statistik Perbankan Syariah 2009-2019 150 Afifah, Nurul Alfiah Kurniawati Table 2. Summary Descriptive of Durations of Earning Assets Maturities M=Months Y=Years Variance Skewness Kurtosis Upto 3M 44.27% 0.4718 3.91 3M> to 6M ` 31.35% 0.3712 2.79 6M> to 12M 29.38% 0.3785 3.25 1Y> to 2Y 31.32% 0.5965 4.97 2Y> to 3Y 35.22% 0.4645 4.67 3Y> to 5Y 32.34% 0.3234 5.71 5Y> 49.77% 0.3436 5.78 Table 3. Summary Descriptive of Benchmark rates Earning Assets Maturities M=Months Y=Years Variance Skewness Kurtosis 1 Months 12.27% 0.4675 3.45 3 Months ` 13.35% 0.4894 3.56 6 Months 13.43% 0.6821 2.17 1 Year and Above 12.31% 0.6794 3.97 Table 4. Summary Descriptive of Rate of Return rates on Earning Assets Maturities M=Months Y=Years Variance Skewness Kurtosis Upto 3M 34.21% 0.4785 3.31 3M> to 6M ` 31.47% 0.4123 3.45 6M> to 12M 33.37% 0.4589 3.76 1Y> to 2Y 38.32% 0.4428 2.97 2Y> to 3Y 31.37% 0.4765 5.78 3Y> to 5Y 32.13% 0.4178 6.72 5Y> 30.34% 0.5176 5.22 Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 151 Table 5. Summary Descriptive of Returns earned on earning assets Maturities M=Months Y=Years Variance Skewness Kurtosis Upto 3M 12.32% 0.7425 5.37 3M> to 6M ` 19.73% -0.6145 4.91 6M> to 12M 13.78% -0.5432 4.53 1Y> to 2Y 37.43% -0.3245 3.23 2Y> to 3Y 39.32% 0.5463 3.77 3Y> to 5Y 41.32% 0.4981 3.21 5Y> 51.44% 0.4237 5.79 Table 6. Summary Descriptive of Return Bearing Liabilities Maturities M=Months Y=Years Variance Skewness Kurtosis Upto 3M 37.32% 0.4231 4.23 3M> to 6M ` 32.24% 0.7124 6.56 6M> to 12M 27.85% 0.2378 7.47 1Y> to 2Y 45.43% 0.6756 4.12 2Y> to 3Y 45.88% -0.4235 3.56 3Y> to 5Y 41.32% -0.8675 5.35 5Y> 42.57% -0.6234 5.12 Table 7. Summary Descriptive of Returns paid on Return Bearing Liabilities Maturities M=Months Y=Years Variance Skewness Kurtosis Upto 3M 18.76% 0.6215 3.21 3M> to 6M ` 21.23% 0.7237 4.23 6M> to 12M 22.24% 0.6745 4.39 1Y> to 2Y 27.83% 0.4391 6.21 2Y> to 3Y 34.88% -0.2734 5.01 3Y> to 5Y 31.32% -0.3691 5.43 5Y> 32.57% -0.2141 5.69 152 Afifah, Nurul Alfiah Kurniawati The results descriptive statistic in tables 2 to 7 conform Bildersee (1975), Gultekin and Rogalski (1984), Chen (2014), Weber (2017) and Chu et al. (2017) about confirmation of skewed and leptokurtic distribution. Besides, Various tests have been performed for implications of duration measures. The tests have been performed using maturity-wise data of Islamic banks relating to their return bearing assets and liabilities. The results of testing the duration models on earning assets, return bearing liabilities and duration of Islamic banks have been reported hereunder. The results have been presented in 4 different versions of return- duration regression equations that have been incorporated at the top of each respective table. Tables 11, 15 and 19 are based on regression equations incorporating all the respective variables. However, in rest of the tables from tables 8 to 19 excluding tables 11,15 and 19 one or more of the variables have been omitted. For each of the holding period using model expressed at the top of tables 8 to 19 there are coefficients for each of the maturity bracket as regression coefficient estimate and respective first order autocorrelation. The table also shows p-values calculated on the basis of t-statistics of This testing procedure corresponds to testing mechanism of Fama and MacBeth (1973). have been calculated across return on earning assets and duration of earning assets relationships of entire Indonesian Islamic banking sector that has helped in obtaining period by period estimated alongwith the confidence intervals of significance tests. In the final columns of tables 8 to 19 R2 and S (R2) have been presented, which are coefficient of determination and its standard deviation. Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 153 Ta bl e 8: R eg re ss io n R es ul ts D E A E qu at io n 1 + P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 30 .7 3 -0 .4 5 0. 43 0. 05 0. 07 7 0. 07 1 0. 25 0. 19 3M > to 6 M ` 31 .2 5 -0 .3 1 -0 .3 6 0. 02 0. 07 7 0. 12 7 0. 22 0. 17 6M > to 1 2M 29 .7 7 0. 33 0. 34 -0 .3 2 0. 05 2 0. 17 2 0. 20 0. 12 1Y > to 2 Y 38 .7 1 -0 .3 5 -0 .4 1 0. 02 0. 01 7* 0. 13 2 0. 50 0. 32 2Y > to 3 Y 34 .2 5 -0 .2 7 -0 .3 2 0. 02 0. 03 1* 0. 11 4 0. 40 0. 35 3Y > to 5 Y 35 .2 7 -0 .3 1 0. 21 0. 03 0. 00 4* 0. 11 7 0. 31 0. 21 5Y > 37 .4 5 -0 .5 1 0. 13 0. 01 0. 05 5 0. 32 3 0. 28 0. 19 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : i nd ic at es th e le ve l o f r at es o f r et ur n is n ot s ig ni fic an tly b et w ee n m at ur ity b ra ck et s. i n th e se co nd co lu m n is n eg at iv e an d in si gn ifi ca nt c on fo rm in g to th e ob se rv at io n of C ha tth a et a l. (2 02 0) th at I sl am ic b an ks ha ve h ig he r d ur at io n an d lo w er p ro fit ab ili ty . N on z er o se ri al c or re la tio n of i nd ic at e in te rr el at io ns hi p be tw ee n th e ra te s of re tu rn s. S er ia l c or re la tio n cl os e to z er o va lu es o f in di ca te d ur at io ns a re n ot in te rr el at ed . T he s ig ni fic an t p- va lu es o f a nd s ho w re lia bi lit y of re su lts . 154 Afifah, Nurul Alfiah Kurniawati Ta bl e 9: R eg re ss io n R es ul ts D E A E qu at io n 2 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 24 .7 0. 48 -1 .3 7 0. 38 0. 04 1 0. 02 1 0. 16 2 0. 15 2 0. 02 1* 0. 33 0. 27 3M > to 6 M ` 25 .3 0. 41 -1 .2 2 0. 02 0. 03 1 -0 .0 31 0. 03 7* 0. 04 5 0. 01 7* 0. 34 0. 29 6M > to 1 2M 35 .7 0. 34 -0 .9 3 0. 57 -0 .0 71 -0 .0 31 0. 04 2* 0. 17 1 0. 02 7* 0. 47 0. 38 1Y > to 2 Y 34 .2 0. 33 -0 .4 4 -0 .3 2 -0 .0 37 -0 .0 25 0. 03 1* 0. 13 7 0. 02 2* 0. 49 0. 41 2Y > to 3 Y 28 .1 0. 26 -0 .9 7 -0 .2 1 -0 .0 31 0. 03 5 0. 04 1* 0. 14 1 0. 03 7* 0. 41 0. 39 3Y > to 5 Y 25 .2 0. 22 0. 83 -0 .3 7 0. 03 4 0. 02 7 0. 02 1* 0. 11 7 0. 04 1* 0. 45 0. 36 5Y > 21 .7 0. 47 -0 .8 5 0. 09 0. 00 3 0. 03 3 0. 17 4 0. 21 5 0. 07 0 0. 45 0. 32 *a t 5 % le ve l o f s ig ni fic an ce E xp la na ti on : h as la rg el y re m ai ne d be tw ee n 20 a nd 3 0 in di ca tin g no b ig d iff er en ce in r at es o f re tu rn b et w ee n m at ur ity b ra ck et s. V al ue s of an d i nd ic at e no s ig ni fic an t lin ea r re la tio ns hi p be tw ee n re tu rn s on a ss et s an d du ra tio n. e xh ib its n eg at iv e si gn s to s ho w n eg at iv e an d si gn ifi ca nt s ho w in g no n lin ea r re la tio ns hi p of d ur at io n w ith r et ur ns o ve r 1 ye ar m at ur ity b ra ck et s. S er ia l c or re la tio n va lu es o f in di ca te in te rr el at io ns hi p be tw ee n th e ra te s of re tu rn s. H ow ev er , s er ia l c or re la tio n of an d th at d ur at io ns a re n ot in te rr el at ed . Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 155 Ta bl e 10 : R eg re ss io n R es ul ts D E A E qu at io n 3 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 31 .4 4 0. 51 1. 39 0. 78 0. 03 0. 01 0. 00 9* 0. 17 2 0. 03 1* 0. 67 0. 51 3M > to 6 M ` 25 .2 3 -0 .3 9 1. 53 -0 .5 4 -0 .0 5 0. 01 0. 01 2* 0. 21 3 0. 01 7* 0. 34 0. 29 6M > to 1 2M 22 .2 5 -0 .2 5 1. 78 0. 34 -0 .0 4 -0 .0 3 0. 01 8* 0. 19 2 0. 04 9* 0. 45 0. 36 1Y > to 2 Y 34 .2 5 0. 35 0. 62 -0 .5 1 -0 .0 4 -0 .0 5 0. 03 9* 0. 12 9 0. 03 2* 0. 43 0. 25 2Y > to 3 Y 19 .2 3 -0 .2 9 1. 22 -0 .4 1 0. 04 0. 03 0. 04 2* 0. 32 8 0. 04 5* 0. 32 0. 23 3Y > to 5 Y 31 .2 2 -0 .3 5 0. 22 0. 31 0. 01 0. 02 0. 03 1* 0. 41 3 0. 01 2* 0. 23 0. 26 5Y > 19 .2 5 -0 .5 2 0. 29 0. 67 0. 02 0. 01 0. 02 9* 0. 17 3 0. 04 5* 0. 41 0. 37 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : i nd ic at es n o bi g di ff er en ce o f ra te s of r et ur n be tw ee n ov er 1 y ea r m at ur ity b ra ck et s. ex hi bi t po si tiv e si gn s t o sh ow p os iti ve re la tio ns hi p w ith re tu rn s s ho w in g ra te s o f r et ur n an d be nc hm ar k ra te s s ig ni fic an tly aff ec t l on g te rm re la tio ns hi p of re tu rn w ith d ur at io n. 156 Afifah, Nurul Alfiah Kurniawati Ta bl e 11 : R eg re ss io n R es ul ts D E A E qu at io n 4 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 31 .2 4 0. 41 -1 .3 1 -0 .3 2 -0 .4 2 0. 02 0. 02 0. 02 0. 03 1* 0. 06 7 0. 03 1* 0. 01 7* 0. 62 0. 51 3M > to 6 M ` 33 .1 9 0. 78 -1 .3 4 -0 .7 4 0. 35 -0 .0 4 0. 02 0. 02 0. 04 1* 0. 15 7 0. 02 1* 0. 03 7* 0. 67 0. 42 6M > to 1 2M 37 .7 8 0. 75 -1 .6 1 0. 23 -0 .5 6 0. 02 0. 01 0. 01 0. 02 4* 0. 14 5 0. 03 7* 0. 02 4* 0. 44 0. 35 1Y > to 2 Y 25 .2 3 0. 74 -1 .3 9 -0 .4 5 0. 14 -0 .0 4 -0 .0 4 -0 .0 5 0. 01 2* 0. 11 1 0. 01 7* 0. 03 7* 0. 63 0. 51 2Y > to 3 Y 28 .2 4 0. 67 -1 .2 1 -1 .3 4 0. 12 0. 03 -0 .0 6 0. 03 0. 03 7* 0. 13 7 0. 02 2* 0. 02 0* 0. 27 0. 21 3Y > to 5 Y 25 .2 5 0. 25 -1 .2 3 -0 .7 8 -0 .2 4 0. 02 0. 04 0. 02 0. 01 7* 0. 01 6* 0. 01 5* 0. 05 4 0. 42 0. 35 5Y > 25 .2 7 0. 27 -0 .5 7 -0 .6 9 0. 23 0. 09 0. 03 0. 01 0. 01 5* 0. 14 5 0. 02 5* 0. 04 2* 0. 27 0. 19 *a t 5 % le ve l o f s ig ni fic an ce E xp la na ti on : in di ca te s no b ig d iff er en ce o f r at es o f r et ur n be tw ee n m at ur ity b ra ck et s pa rt ic ul ar ly o ve r 1 y ea r. sh ow s th at th e re la tio ns hi p be tw ee n re tu rn a nd d ur at io n is n ot li ne ar . sh ow s th at ra te s of re tu rn a nd b en ch m ar k ra te s si gn ifi ca nt ly a ff ec t l on g te rm r el at io ns hi p of r et ur n w ith d ur at io n. S er ia l c or re la tio n va lu es o f , a nd a re cl os e to z er o, w hi ch s ho w s th at d ur at io ns a re n ot in te rr el at ed . Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 157 Ta bl e 12 : R eg re ss io n R es ul ts D R B L E qu at io n 1 + P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 55 .2 3 0. 42 0. 42 0. 07 0. 03 7* 0. 14 1 0. 75 0. 67 3M > to 6 M ` 52 .4 7 0. 34 0. 37 0. 02 0. 02 4* 0. 13 8 0. 67 0. 54 6M > to 1 2M 34 .2 3 0. 42 -0 .2 3 0. 06 0. 04 1* 0. 12 1 0. 58 0. 41 1Y > to 2 Y 33 .6 7 0. 37 -0 .2 2 0. 02 0. 00 7* 0. 06 5 0. 53 0. 57 2Y > to 3 Y 47 .2 8 0. 31 0. 11 -0 .0 7 0. 06 9 0. 07 1 0. 20 0. 47 3Y > to 5 Y 43 .2 8 0. 34 0. 33 -0 .0 1 0. 12 4 0. 08 1 0. 23 0. 24 5Y > 44 .2 5 0. 42 0. 15 0. 08 0. 09 7 0. 07 6 0. 09 0. 26 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : in di ca te s th at le ve l o f r at es o f r et ur n is h et er og en eo us b et w ee n va ri ou s lia bi lit ie s br ac ke ts . V al ue s of a nd i n th e se co nd c ol um n in di ca te n o si gn ifi ca nt li ne ar r el at io ns hi p be tw ee n re tu rn b ea ri ng li ab ili tie s an d du ra tio n. N on z er o se ri al c or re la tio n va lu es o f in di ca te in te rr el at io ns hi p be tw ee n th e ra te s of r et ur ns . C lo se to ze ro s er ia l c or re la tio n va lu es o f s ho w th at d ur at io ns a re n ot in te rr el at ed . 158 Afifah, Nurul Alfiah Kurniawati Ta bl e 13 : R eg re ss io n R es ul ts D R B L E qu at io n 2 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 34 .4 7 0. 67 -1 .6 5 0. 54 0. 04 0. 06 0. 01 5* 0. 12 1 0. 06 5 0. 74 0. 41 3M > to 6 M ` 37 .5 2 0. 43 -1 .6 1 0. 31 0. 08 0. 07 0. 02 4* 0. 13 1 0. 04 1* 0. 62 0. 44 6M > to 1 2M 44 .4 7 0. 51 -1 .5 5 0. 73 -0 .0 9 -0 .0 3 0. 04 1* 0. 10 6 0. 02 5* 0. 52 0. 47 1Y > to 2 Y 45 .7 6 0. 39 -1 .4 3 -0 .6 7 -0 .0 3 -0 .0 1 0. 01 7* 0. 11 4 0. 03 7* 0. 56 0. 49 2Y > to 3 Y 32 .5 2 0. 54 -1 .2 3 -0 .8 1 0. 06 0. 03 0. 09 5 0. 13 7 0. 03 7* 0. 33 0. 21 3Y > to 5 Y 24 .6 7 0. 19 -1 .1 9 -0 .7 8 0. 04 0. 07 0. 12 3 0. 07 1 0. 12 1 0. 37 0. 27 5Y > 29 .6 2 0. 15 -1 .2 1 0. 13 0. 01 0. 06 0. 13 5 0. 08 7 0. 12 4 0. 38 0. 23 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : va lu es a re si gn ifi ca nt fr om 6 m on th s t o 3 ye ar s. T hi s s ho w s t ha t t he re la tio ns hi p of re tu rn d ur at io n is n ot li ne ar . S er ia l c or re la tio n va lu es o f ar e no n ze ro th at in di ca te in te rr el at io ns hi p be tw ee n th e ra te s of re tu rn s. H ow ev er , s er ia l c or re la tio n va lu es o f a nd a re c lo se to z er o, w hi ch s ho w s th at d ur at io ns a re n ot in te rr el at ed . Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 159 Ta bl e 14 : R eg re ss io n R es ul ts D R B L E qu at io n 3 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 29 .2 5 -0 .2 1 1. 41 0. 62 0. 06 0. 05 0. 01 2* 0. 14 1 0. 03 1* 0. 61 0. 47 3M > to 6 M ` 32 .6 7 -0 .2 7 1. 57 0. 51 -0 .0 4 0. 01 0. 03 1* 0. 11 6 0. 02 4* 0. 65 0. 58 6M > to 1 2M 35 .2 5 -0 .1 4 1. 32 0. 51 -0 .0 2 0. 02 0. 00 9* 0. 13 7 0. 03 1* 0. 65 0. 54 1Y > to 2 Y 34 .1 3 -0 .1 3 1. 45 -0 .5 1 0. 03 -0 .0 9 0. 03 5* 0. 31 7 0. 03 7* 0. 69 0. 62 2Y > to 3 Y 45 .1 4 -0 .2 7 1. 43 -0 .3 1 0. 17 -0 .1 2 0. 05 1 0. 22 2 0. 04 1* 0. 45 0. 39 3Y > to 5 Y 47 .1 2 -0 .2 9 1. 11 -0 .3 0 0. 25 0. 14 0. 04 2* 0. 14 7 0. 02 1* 0. 42 0. 37 5Y > 46 .4 4 -0 .2 3 1. 09 0. 41 0. 08 0. 74 0. 02 1* 0. 12 4 0. 04 1* 0. 29 0. 25 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : ex hi bi t p os iti ve si gn s, th is sh ow s t ha t r at es o f r et ur n an d be nc hm ar k ra te s s ig ni fic an tly a ff ec t l on g te rm re la tio ns hi p of re tu rn w ith d ur at io n. S er ia l c or re la tio n va lu es o f ar e no n ze ro th at in di ca te in te rr el at io ns hi p be tw ee n th e ra te s of r et ur ns . H ow ev er , s er ia l c or re la tio n va lu es o f an d a re c lo se to z er o, w hi ch s ho w s th at du ra tio ns a re n ot in te rr el at ed . 160 Afifah, Nurul Alfiah Kurniawati Ta bl e 15 : R eg re ss io n R es ul ts D R B L E qu at io n 4 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 13 .2 4 0. 45 -1 .2 3 -0 .3 1 0. 63 0. 01 0. 25 0. 76 0. 01 2* 0. 14 6 0. 03 1* 0. 04 7* 0. 57 0. 43 3M > to 6 M ` 13 .6 5 0. 67 -1 .3 7 -1 .3 7 -0 .5 4 0. 35 -0 .4 5 0. 81 0. 04 1* 0. 10 7 0. 02 6* 0. 02 2* 0. 45 0. 37 6M > to 1 2M 21 .2 7 0. 55 -0 .5 4 -1 .5 4 -0 .5 5 0. 32 -0 .3 4 0. 24 0. 03 2* 0. 12 2 0. 03 5* 0. 02 6* 0. 73 0. 65 1Y > to 2 Y 24 .5 5 0. 52 -0 .7 8 1. 45 0. 35 -0 .2 6 0. 34 -0 .2 5 0. 04 1* 0. 13 4 0. 02 5* 0. 02 3* 0. 55 0. 45 2Y > to 3 Y 34 .7 6 0. 61 -0 .5 7 -0 .4 7 0. 54 -0 .1 4 0. 37 -0 .6 2 0. 01 9* 0. 09 4 0. 03 2* 0. 04 2* 0. 79 0. 61 3Y > to 5 Y 33 .6 9 0. 24 -0 .5 6 -0 .5 6 -0 .1 8 0. 12 0. 76 -0 .7 7 0. 02 3* 0. 14 1 0. 03 7* 0. 03 6* 0. 24 0. 21 5Y > 33 .5 4 0. 23 -0 .9 7 -0 .5 1 0. 24 0. 25 0. 81 0. 25 0. 04 1* 0. 14 5 0. 04 6* 0. 02 5* 0. 21 0. 21 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : sh ow s th at th e re la tio ns hi p be tw ee n re tu rn a nd d ur at io n is n ot li ne ar . ex hi bi ts p os iti ve s ig ns th is sh ow s th at ra te s of re tu rn a nd b en ch m ar k ra te s si gn ifi ca nt ly a ff ec t l on g te rm re la tio ns hi p of re tu rn w ith d ur at io n. Se ri al c or re la tio n va lu es o f a re n on z er o th at in di ca te in te rr el at io ns hi p be tw ee n th e ra te s of r et ur ns . H ow ev er , se ri al c or re la tio n va lu es o f , an d a re c lo se to z er o, w hi ch s ho w s th at d ur at io ns a re n ot in te rr el at ed . Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 161 Ta bl e 16 : R eg re ss io n R es ul ts D IB s E qu at io n 1 + P er io d Y 1 Y 2 Y 3 Y 4 Y 5 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) ῤ( Y 5) p( Y 1) p( Y 2) p( Y 3) p( Y 4) p( Y 5) R 2 S( R 2 ) U pt o 3M 27 .3 4 -0 .3 9 0. 36 0. 07 0. 07 6 0. 05 8 0. 13 0. 11 3M > to 6 M ` 28 .7 4 -0 .2 7 -0 .3 3 0. 18 0. 08 2 0. 09 7 0. 15 0. 10 6M > to 1 2M 25 .2 3 -0 .2 9 -0 .3 4 -0 .2 2 0. 04 7* 0. 08 3 0. 23 0. 19 1Y > to 2 Y 28 .2 7 -0 .2 7 -0 .3 7 0. 04 0. 01 1* 0. 22 8 0. 52 0. 43 2Y > to 3 Y 31 .3 9 -0 .2 5 -0 .2 8 0. 07 0. 03 7* 0. 12 9 0. 43 0. 35 3Y > to 5 Y 32 .4 1 -0 .2 9 0. 19 0. 06 0. 01 9* 0. 14 1 0. 44 0. 33 5Y > 35 .3 7 -0 .4 3 0. 10 0. 02 0. 05 5 0. 21 4 0. 32 0. 22 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : in di ca te s ab ov e 1 ye ar ra te s of re tu rn s ar e ve ry c lo se b et w ee n m at ur ity b ra ck et s. c on fo rm s to th e ob se rv at io n of C ha tth a et a l. (2 02 0) th at I sl am ic b an ks h av e hi gh er d ur at io n an d lo w er p ro fit ab ili ty . N on z er o se ri al c or re la tio n of i nd ic at es in te rr el at io ns hi p be tw ee n ra te s of re tu rn s. S er ia l c or re la tio n va lu es o f is c lo se to ze ro , w hi ch s ho w s th at d ur at io ns a re n ot in te rr el at ed . 162 Afifah, Nurul Alfiah Kurniawati Ta bl e 17 : R eg re ss io n R es ul ts D IB E qu at io n 2 P er io d Y 1 Y 2 Y 3 Y 4 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) p( Y 1) p( Y 2) p( Y 3) p( Y 4) R 2 S( R 2 ) U pt o 3M 23 .3 3 0. 51 -1 .5 2 0. 41 0. 11 0. 04 0. 09 3 0. 07 6 0. 04 3* 0. 45 0. 39 3M > to 6 M 22 .1 9 0. 48 -1 .4 2 0. 57 0. 04 -0 .0 7 0. 04 8* 0. 08 8 0. 02 5* 0. 51 0. 45 6M > to 1 2M 28 .2 7 0. 53 -0 .8 5 0. 32 -0 .0 8 -0 .0 5 0. 03 6* 0. 14 5 0. 00 0* 0. 39 0. 28 1Y > to 2 Y 31 .2 9 0. 45 -0 .5 7 -0 .5 5 -0 .0 5 -0 .0 6 0. 02 9* 0. 12 9 0. 00 0* 0. 34 0. 27 2Y > to 3 Y 29 .2 2 0. 47 -0 .9 2 -0 .9 1 -0 .0 4 0. 04 0. 03 7* 0. 16 6 0. 03 7* 0. 55 0. 49 3Y > to 5 Y 30 .9 7 0. 46 0. 67 -0 .2 3 0. 05 0. 03 0. 04 4* 0. 06 5 0. 00 4* 0. 56 0. 51 5Y > 28 .2 5 0. 55 -0 .4 2 0. 41 0. 06 0. 04 0. 15 9 0. 19 1 0. 04 5* 0. 29 0. 25 E xp la na ti on : V al ue s of a nd n eg at e lin ea r r el at io ns hi p an d s ho w n eg at iv e lo ng ru n no n lin ea r r el at io ns hi p of du ra tio n w ith re tu rn s. C lo se to z er o se ri al c or re la tio n va lu es o f a nd s ho w th at d ur at io ns a re n ot in te rr el at ed . Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 163 Ta bl e 18 : R eg re ss io n R es ul ts D E A E qu at io n 3 P er io d Y 1 Y 2 Y 3 Y 4 Y 5 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) ῤ( Y 5) p( Y 1) p( Y 2) p( Y 3) p( Y 4) p( Y 5) R 2 S( R 2 ) U pt o 3M 25 .7 5 -0 .5 9 1. 43 1. 31 0. 78 0. 03 0. 01 0. 07 0. 00 0* 0. 08 1 0. 00 0* 0. 00 0* 0. 71 0. 65 3M > to 6 M 27 .9 3 -0 .6 5 1. 64 1. 47 -0 .5 4 -0 .0 5 0. 01 0. 12 0. 00 3* 0. 17 4 0. 00 1* 0. 00 0* 0. 53 0. 48 6M > to 1 2M 31 .4 4 -0 .4 8 1. 41 1. 32 1. 64 -0 .0 4 -0 .0 3 0. 01 0. 00 0* 0. 12 5 0. 00 4* 0. 01 7* 0. 41 0. 31 1Y > to 2 Y 33 .2 2 -0 .5 6 1. 42 1. 59 -0 .5 1 -0 .0 4 -0 .0 5 0. 13 0. 00 8* 0. 16 7 0. 01 2* 0. 04 3* 0. 39 0. 32 2Y > to 3 Y 35 .2 6 -0 .4 7 1. 67 1. 36 -0 .4 1 0. 04 0. 03 0. 14 0. 00 0* 0. 04 7* 0. 00 7* 0. 03 1* 0. 46 0. 39 3Y > to 5 Y 36 .4 7 -0 .4 9 1. 23 1. 48 0. 31 0. 01 0. 02 0. 15 0. 00 9* 0. 00 5* 0. 01 9* 0. 02 9* 0. 32 0. 25 5Y > 33 .3 9 -0 .4 2 1. 42 1. 54 0. 67 0. 02 0. 01 0. 12 0. 00 1* 0. 12 3 0. 03 4* 0. 00 0* 0. 49 0. 44 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : sh ow th at ra te s of re tu rn a nd b en ch m ar k ra te s si gn ifi ca nt ly a ff ec t l on g te rm re la tio ns hi p of re tu rn w ith d ur at io n. S er ia l co rr el at io n va lu es o f a re n on z er o th at i nd ic at e in te rr el at io ns hi p be tw ee n th e ra te s of re tu rn s. H ow ev er , s er ia l c or re la tio n va lu es o f , a re c lo se to z er o, w hi ch s ho w s th at d ur at io ns a re n ot in te rr el at ed . 164 Afifah, Nurul Alfiah Kurniawati Ta bl e 19 : R eg re ss io n R es ul ts D IB E qu at io n 4 P er io d Y 1 Y 2 Y 3 Y 4 Y 5 ῤ( Y 1) ῤ( Y 2) ῤ( Y 3) ῤ( Y 4) ῤ( Y 5) p( Y 1) p( Y 2) p( Y 3) p( Y 4) p( Y 5) R 2 S( R 2 ) U pt o 3M 33 .4 1 0. 73 -1 .4 3 -0 .5 4 -0 .5 1 -0 .4 8 0. 13 0. 04 0. 03 0. 09 0. 02 1* 0. 13 2 0. 00 0* 0. 01 7* 0. 00 4* 0. 57 0. 48 3M > to 6 M ` 32 .5 7 0. 65 -1 .5 4 -0 .4 8 -0 .5 2 0. 65 -0 .0 4 0. 06 0. 05 0. 13 0. 00 0* 0. 17 1 0. 00 2* 0. 03 7* 0. 04 3* 0. 55 0. 40 6M > to 1 2M 34 .3 2 0. 61 -1 .5 6 0. 36 -0 .4 7 -0 .5 1 0. 15 0. 07 0. 02 0. 11 0. 00 3* 0. 03 1 0. 01 8* 0. 02 4* 0. 00 2* 0. 41 0. 30 1Y > to 2 Y 37 .3 1 0. 69 -1 .6 1 -0 .4 5 -0 .4 9 0. 23 0. 04 0. 12 0. 08 0. 06 0. 00 0* 0. 13 4 0. 03 2* 0. 03 7* 0. 02 1* 0. 43 0. 31 2Y > to 3 Y 36 .2 1 0. 68 -1 .6 4 -0 .4 5 -0 .4 4 0. 29 0. 07 -0 .0 9 0. 12 0. 08 0. 01 4* 0. 02 4* 0. 00 0* 0. 02 0* 0. 03 4* 0. 39 0. 29 3Y > to 5 Y 34 .3 4 0. 55 -1 .5 8 -0 .6 9 -0 .4 2 -0 .4 3 0. 06 0. 15 0. 03 0. 15 0. 01 1* 0. 07 6 0. 04 1* 0. 05 4 0. 02 1* 0. 49 0. 38 5Y > 37 .2 2 0. 51 -1 .5 3 -0 .6 7 -0 .4 1 0. 41 0. 03 0. 12 0. 07 0. 17 0. 02 5* 0. 12 2 0. 00 1* 0. 04 2* 0. 00 0* 0. 54 0. 41 *a t 5 % l ev el o f s ig ni fic an ce E xp la na ti on : a nd ne ga te li ne ar r el at io ns hi p an d s ho w s th at th e re la tio ns hi p be tw ee n re tu rn a nd d ur at io n is no t lin ea r. a nd in di ca te r at es o f re tu rn a nd r el ev an t be nc hm ar ks a ff ec t re la tio ns hi p be tw ee n ne t in co m e an d du ra tio n of Is la m ic b an ks . S er ia l c or re la tio n va lu es o f , , a nd a re c lo se to z er o w hi ch s ho w s th at d ur at io ns a re no t i nt er re la te d. Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 165 Descriptive statistics tables 2 to 7 of duration of assets and liabilities show that the data has skewed and leptokurtic distributions. The results of the duration functions after incorporating into multiple regression function have been reported in tables 8 to 19. Tables 7 to 11 relate to duration of earning assets, tables 12 to 15 relate to duration of return bearing liabilities and tables 16 to 19 relate to duration of Islamic banks in Indonesia, which is calculated as duration gap. For testing the hypotheses multiple regression has been used for duration for assets and liabilities in four different combinations that have been reproduced at the top of each of the table, however, table 8 and 12 are based on full equations. The tables produce regression coefficients in columns 1 to 4, autocorrelations in columns 6 to 10, p-values in columns 11 to 14 and the last two columns report means and standard deviations of coefficient of determination. The results in tables 8, 12 and 16 do not let us accept linearity hypothesis both for duration of earning assets and return bearing liabilities. Tables 7, 13 and 17 lead us to the finding that long term relationship of duration on returns is quadratic i.e., upwards sloping. Tables 8,14 and 18 lead us to the findings that rates of return, interbank offered rates, principal sum and maturities are complete determinants of relationship between duration and returns thereby accepting our second hypothesis. Table 9,15 and 19 lead us to the finding that factor of reversed present values do have relationship with duration in original state. This can be confirmed from making a combined analysis of tables 9&10, 14&15 and 18&19 that by including reversed present value factor into regression function neither the linear relationship is effected nor non-linear relationship. These results conform to Bildersee (1975), Gultekin and Rogalski (1984), Chen (2014), Weber (2017) and Chu et al. (2017). CONCLUSION This research uses duration models testing procedures of Guletkin & Rogalski (1984) as amended by Shah et al. (2021b) using multiple regressions to test Shariah compliant duration 166 Afifah, Nurul Alfiah Kurniawati models. However, the results of this research although do not conform to all of the previous results of Guletkin & Rogalski (1984) but conform to the results of Shah et al. (2021b). The results of first hypothesis conform to Guletkin & Rogalski (1984) & Shah et al. (2021b) that duration of assets and liabilities do not have linear relationship. In case of second and third hypotheses the results although conform to Shah et a. (2021b) but do not conform to Guletkin & Rogalski (1984). This is because rate of return earned on earning assets and interbank offered rates are significant factors for determining duration of earning assets whereas rate of return return paid on return bearing liabilities and interbank average rates of deposit are significant factors in case of duration on return bearing liabilities. This research confirms the works of Shah et al. (2020a&b) and subsequently of Shah et al. (2021b). This research further confirms the nature and behavior of earning assets and return bearing liabilities of two distinct Islamic countries due to existence of a common feature of Shariah compliance. Furthermore, it answers the observation of Chattha and Alhabshi (2018) and Chattha et al. (2020) that Islamic banks have longer durations with low profitability. This is because Islamic banks have earning assets of longer maturity at similar rates of returns; and on the liabilities they have to offer higher rates of return for liabilities of similar maturities when compared to conventional banks. This makes them bear more risk due to longer duration gap at lower profitability. Limitations & Future Research Directions The study mainly focuses duration of earning assets and return bearing liabilities and their relationship with earnings of Islamic banks. Furthermore, as the study is only conducted on Islamic banks of Indonesia, therefore a larger sample and testing in various other banks operating in non-Muslim countries is also recommended to validate the model. Lastly, The study only deals with assets and liabilities that have maturities alongwith return characteristics. As Islamic banks have various assets and liabilities that do not have returns and maturities therefore a study encompassing such assets and Journal of Islamic Economic Laws-July, Vol. 4, No. 2, 2021 167 liabilities will yield more comprehensive results regarding duration of a Islamic banking organization. The study also severely suffers from availability of data. As most of the Islamic banks do not have long histories, alongwith difference in year of commencement of business therefore the length of data is not enough and is unbalanced. The models proposed in this study therefore require continuous testing over the period to better analyze the respective models. This research has been conducted only on such full-fledged Islamic banks that have been involved in business similar to conventional banks. 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