The Risk Analysis of Ṣukūk: An Empirical Evidence from Pakistan

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The Risk Analysis of Ṣukūk: An Empirical Evidence from Pakistan

Ejaz Aslam

Assistant Professor and researcher at the School of Islamic Economics Banking & Finance, Minhaj University Pakistan

Khuram Mobusher Azam

Credit Manager, Habib Bank Ltd., Pakistan

Anam Iqbal

PhD scholar at IIUM Institute of Islamic Banking and Finance International Islamic University Malaysia

ABSTRACT. Ṣukūk is an innovative financial instrument with a flexible structure based on Sharīʿah, unlike a bond which is based on an interest-based structure. With the notion that ṣukūk contracts are significantly different from ordinary bonds, it is in high demand especially in Muslim countries to overcome liquidity problems. Ṣukūk has a key importance in the financial market, and literature is lacking on how to predict the trend and volatility of ṣukūk in the case of Pakistan, where debt instruments are high in demand. Thus, this investigation intends to inspect the volatility and trends analysis of the ṣukūk industry in Pakistan. The study sample consists of six ṣukūk issued in Pakistan, for which the daily data was collected. For this purpose, this study employed the ARCH, GARCH, EGARCH, and TGARCH models to analyze the risk behavior of the ṣukūk industry in Pakistan. Results revealed that Engro Corporation ṣukūk yield is higher and less volatile among other ṣukūk returns. The results testify that there is volatility in all corporate ṣukūk returns of different maturities. Additionally, it is found that smaller tenure ṣukūk had high volatility as compared to larger tenure ṣukūk, and that bad news and events have larger effects on volatility of the ṣukūk return than good news. The findings of this study shall be beneficial for investors, portfolio managers, and decision-making authorities to invest in the low-risk profile ṣukūk as debt instruments in Pakistan.

KEYWORDS: ARCH, GARCH, Islamic finance, Ṣukūk, Volatility.

JELCLASSIFICATION: G02, G14, P51 KAUJIECLASSIFICATION: K16, I10

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1. Introduction

Shortage of money is the major issue faced by gov- ernments and corporate bodies all over the globe. To overcome the issue of shortage of money, the financial bodies massively borrow to amass their required capital expenditures (Shiau, Chang, & Yang, 2018, p.

176). Since the last two decades, Islamic certificates have been used extensively as a prolific alternative to conventional bonds, especially in Muslim majority countries because of its unique nature and resilience to alleviate liquidity problems. Thus, Islamic certifi- cates (ṣukūk) are based on Islamic rules, which pro- hibit ribā, gharar, and other attributes that exploit and/or undermine the rights of any party involved (Salman, Amjad, & Aslam, 2017, p. 8; Smaoui, Mimouni, & Temimi, 2020, p. 807).

The development of ṣukūk in financial markets was seen as an opportunity to provide new financing and investing dimension for corporates and investors, respectively. Thus, ṣukūk was considered as an alter- native to other long-term funding and investing op- tions (Nasir & Farooq, 2017, p. 375). Ṣukūk’s struc- ture is based on Sharīʿah, and it could be used for the establishment of Islamic economies in society (Alam, Bhatti, & Wong, 2018, p. 665). Usmani (2007, p. 3) documented that there is a need to strictly evaluate the development of ṣukūk structure in concurrence with the fundamental principles of the Islamic economic system which distinguish it from the conventional system.

Ṣukūk is a financial instrument which represents the ownership of an underlying real/tangible asset to its holder and is considered as an alternative for traditional bonds. It is based on Islamic law which allows the sale or lease of an actual asset; and the generated income is considered a form of profit on sale or rent- als for a lease on assets (Smaoui & Ghouma, 2020, p.

807). Additionally, “Investment Sukuk are 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 or special investment activity” (AAOIFI, 2015, p.

468).

The basic concept behind the issuance of ṣukūk is to enable the holders of ṣukūk to share in the profits

and revenues of large enterprises, and not just act as the lender of the fund and collect fix interest pay- ments. Thus, ṣukūk provides an opportunity to invest in a Sharīʿah compliant manner and facilitate the institutions to meet their liquidity problems without resorting to speculation and resource exploitation as well as to get an equitable return (Hassan, 2012, p. 1).

Apart from Sharīʿah compliance, Islamic financial instruments also fascinate as an active business op- portunity. Therefore, ṣukūk is attracting both Mus- lims and non-Muslims as a financing and investment source despite the fact that ṣukūk markets are facing economic, financial, legal, and regulatory challenges (Jobst, Kunzel, Mills, & Sy, 2008, p. 341). Perhaps, ṣukūk has a vital role to play in the development of the real Islamic banking system, and this will con- tribute to the achievement of the noble objectives sought by the Sharīʿah (Usmani, 2007, p. 2).

1.1 Overview of Ṣukūk Market in Pakistan As per the Securities and Exchange Commission of Pakistan (SECP)⁽¹⁾, a total of ninety-nine domestic corporate, privately placed ṣukūk had been issued as of 31^st December 2016. The total raised amount was worth about Rs. 1173.11 billion out of which ṣukūk of worth Rs. 613.78 billion had been redeemed, and total outstanding ṣukūk were worth about Rs. 559.34 billion. Among these ṣukūk, Pakistan Water and Power Development Authority (WAPDA) issued three ṣukūk till December 2016. The very first ṣukūk, worth Rs. 8 billion, was issued on 5^th January 2006 based on the ijārah ṣukūk, and was issued for a peri- od of seven years. The second WAPDA ṣukūk was issued on 13^th July 2007. This was based on the di- minishing mushārakah model, having a worth of Rs.

8 billion, and was issued for a period of ten years.

The third ṣukūk was issued in continuation of the first ijārah ṣukūk that was redeemed in January 2013.

This ṣukūk was issued on 14^th October 2013, having a worth of Rs. 10 billion, and was issued for a period of eight years. These ṣukūk were non-listed, and had an AAA rating by the Pakistan Credit Rating Agency (PACRA). The securities provided against these ṣukūk were twelve power generation turbines at the Mangla & Tarbela Power Station.

(1) www.psx.com.pk

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Karachi Electric Supply Company Limited (K- Electric) issued Pakistan’s first listed ṣukūk named AZM ṣukūk that provided a rate of return and flexible options like early purchase/redemption option, and was traded in all three stock exchanges of Pakistan.

The AZM ṣukūk had a rating of A+ by the JCR-VIS credit rating company and the Islamic International Rating Agency. This ṣukūk was utilized to meet the working capital requirement of K-Electric. The secu- rities provided against these ṣukūk were the forty- seven grid stations of the company. Moreover, Engro Corporation Ltd. issued two ṣukūk named Engro Is- lamic Rupiya-1 and Engro Islamic Rupiya-2 that had a tenure of three and five years, respectively. The instrument rating was AA and entity rating AA- issued by PACRA. The amount raised from Engro Islamic Rupiya-1 was Rs. 3 billion at 13% expected annual rate of return. While Engro Islamic Rupiya-2 raised Rs. 1 billion, with 13.5% expected annual rate of return.

The present research evaluates the risk and trend analysis of the ṣukūk market in Pakistan. The more significant part of the previous literature used theoret- ical justification and trend analysis to justify their idea. Thus, the present research tests their proposed hypotheses by using the autoregressive conditional heteroscedasticity (ARCH) and the generalized autoregressive conditional heteroskedasticity (GARCH) approaches, utilizing ṣukūk data in Pakistan.

Pakistan is a developing country, and its bond market is less productive when contrasted with its financial exchange and debt base instruments like bonds that depend on bank borrowings to fund their operations (Ghafoor, Saba, & Kouser, 2018, p. 161).

Therefore, ṣukūk is considered as the best alternative which provides more return at low risk as compared to conventional bonds. Thus, the outcome of this research can stretch positive ramifications to both the debtor and the creditor, particularly in Pakistan.

This study consists of five sections. After the introduction, the next section discusses the available literature on ṣukūk and its background in Pakistan.

The third section explores the methodology, while section four presents and discusses the results of this study. In the last section, the conclusion and limita- tions of this research are presented.

2. Literature Review

Ṣukūk has an alternate structure and arrangement from regular bonds (Abdul Rauf & Ibrahim, 2014, p.

146). It is a certificate of trust that represents the financial ownership in an underlying asset, for example, processing plant inventories, vehicles, speculation venture like property advancement projects, hydropower projects, and motorways projects (Lah- sasna & Lin, 2012, p. 496). Moreover, it gives the premise of Islamic financial framework, which de- pends on an impartial conveyance of riches, risk- reward sharing, and riches fixation (Bhuiyan, Puspa, Saiti, & Ghani, 2020, p. 1251). However, in compari- son with customary bonds, ṣukūk is considered a diverse mode of financing (Hassan, 2012, p. 4).

Some of the researchers contended that both ṣukūk and ordinary bonds are similar. For example, Miller, Challoner, and Atta (2007, p. 24) mention that ṣukūk are structured such that they offer similar prof- its as conventional bonds. Similarly, Ahmad and Abd. Rahim (2014, p. 278) believe that ṣukūk reflect ordinary bonds, particularly for financial specialists who are unfamiliar with the investment.

However, on the other hand, some researchers be- lieve that ṣukūk offer particular and interchange secu- rity to customary bonds, particularly regarding risk.

For instance, Godlewski, Turk-Ariss, and Weill (2013, p. 746) considered the declaration impacts of the issuance of Islamic and ordinary bonds. They utilized an occasion study system and inferred that the market did not respond as much towards the issuance of the traditional securities.

In this regard, Tariq and Dar (2007, p. 221) put forth their attempts to discover the risk associated with the fundamental structure of ṣukūk. They at- tempted to relieve these risks with the assistance of ideas and endorsements. They examined the develop- ment of ṣukūk, their underlying principals, structures, risks, and competitiveness versus the traditional bond framework. Thus, they found that ṣukūk provides motivating forces and strength to money related markets and result in asset deployment to both the private and public sectors.

Abdul Rauf and Ibrahim (2014, p. 145) identified the risk embedded in ṣukūk structure and determined a positive relationship between risk and ṣukūk return.

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Similarly, Kostandyan (2015, p. 36) concludes ṣukūk to be an advantageous part of the portfolio in diversi- fying risk in the case of Bahrain, Pakistan, Qatar, Malaysia, and the UAE.

Ariff and Safari (2012, p. 101) noted that ṣukūk securities yield was different from the traditional bond yield, though the tenure of issue and issuer of securities was the same. The mean yield of ṣukūk securities was drastically different from the conventional bond, and with some exceptions, there was no causal relationship between these two debt instruments.

Abdalla and Winker (2012, p. 166) studied the trend of investment bonds (IBs) of different maturities by employing the ARCH and GARCH model to measure the volatility. They observed that investors were taking a higher profit/loss on their investment in the five years IBs due to their high volatility. Where- as ten years maturity IBs returns volatility was in between the volatility of IBs with five years and three years maturity. Al-Amine (2011, p. 344) documented that any positive change in the interest rate resulted in a decrease in the fixed return ṣukūk values. Fathu- rahman and Fitriati (2013, p. 162) studied the yields of conventional coupon payment bonds and ṣukūk listed on the Indonesian stock market. Their findings showed that the yield on ṣukūk was different from the yield of conventional bonds. Additionally, the yields on ṣukūk were more massive than the yield on tradi- tional bonds in at least three of the ten groups studied.

Similarly, Bhuiyan et al. (2020, p. 1245) documented that ṣukūk risk is lower than the risk in bond.

Raees, Raheem, and Zakir (2017, p. 103) noted that knowledge and Islamic spirit have a positive relationship with investment in ṣukūk. Nagano (2017, p. 142) stated that ṣukūk is utilized more when firms experience high data asymmetry and have a large funding demand. Zulkhibri (2015, p. 239) stated that lack of harmonization, fewer markets, non-active trading, lack of regulatory support, and different Sharīʿah interpretations are the main constraints to investment in ṣukūk. Nasreen, Naqvi, Tiwari, Ham- moudeh, and Shah (2020, p. 17) mention in their study that VAR analysis demonstrates that benefits from the Islamic assets portfolio vary within the time/scale. Al-Swaidan, Daynes, and Pasgas (2017, p. 389) documented that ṣukūk risk profiles are di- rectly related to ṣukūk structures.

Abd. Rahim and Ahmad (2015, p. 581) estimated volatility of ṣukūk using Moving Centerline Expo- nentially Weighted Moving Average (MCEWMA) volatility forecasting model applied to get the daily return information about the ijārah ṣukūk issuance from 2008 to 2011. They found that bootstrap meth- ods of MCEWMA perform better to evaluate the ṣukūk issuance volatility. Maghyereh and Awartani (2016, p. 252) compare the ṣukūk and bond based on return and volatility with equities. They observed that ṣukūk have higher returns and standard deviation as compared to world bond index. Malikov (2017, p.

34) concludes that sovereign ṣukūk issuances have a positive impact on the economic development of Malaysia and Saudi Arabia.

Ariff and Safari (2012, p. 103) examined the av- erage yields of ṣukūk and ordinary bonds traded in Malaysia and observed that yields for ṣukūk are high- er as well as that ṣukūk with low tenure maturity re- main more volatile. Likewise, Saeed and Izzeldin (2016, p. 150) inferred that dissimilar to common bonds, the exchange off among risk and proficiency does not exist in Islamic bonds, for example, ṣukūk.

Meanwhile, El Mosaid and Boutti (2014, p. 226) found that the ṣukūk index outperforms the bond and market index. The outcomes likewise affirmed a positive and noteworthy correlation among ṣukūk and bond portfolios, proposing that ṣukūk does not con- trast from regular bonds as far as their Sharīʿah structure is concerned.

As aforesaid, the discussion and/or study of the risk and return of ṣukūk is an important issue. There- fore, it is interesting to explore further the volatility and trends of the ṣukūk industry in Pakistan. Thus, the proposed research hypotheses of the present study are constructed as follows:

H1: Yield of Engro Corporation ṣukūk is higher than the yield of other ṣukūks in Pakistan.

H2: Returns of different maturities corporate ṣukūk are volatile.

H3: There exists a clustering effect in all corporate ṣukūk returns of different maturities.

H4: Corporate ṣukūk, which have a short maturity period/tenure have high volatility.

H5: GARCH effect exists in all corporate ṣukūk returns.

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3. Methodology

To achieve the objective of the study, data of the daily market prices of six ṣukūk index of different maturities is selected from the period 2006-2016 in Pakistan. This time period is selected in order to col- lect a reasonable number of ṣukūk instruments and their trading to compare the ṣukūk based on the same credit rating and maturity period of the financial instruments. Thus, the present study selected WAPDA, K-Electric and Engro Corporation ṣukūk across three years, five years, eight years, and ten years maturity periods because it is available in the Pakistan Stock Exchange (PSX) database. The choice of our sample is motivated by the availability of statistical data and the difficulty of accessing databases that provide a wide range of index types. The present study employed the Augmented Dickey-Fuller test to identify the stationarity in data and autoregressive conditional heteroscedasticity (ARCH) and its variants; generalized autoregressive conditional heteroscedasticity (GARCH); exponential generalized autoregressive conditional heteroscedasticity (EGARCH); and threshold generalized autoregressive conditional heteroscedasticity (TGARCH) model, in order to cap- ture volatility clustering, volatility persistence and asymmetric effect of ṣukūk in Pakistan (Agwu &

Godfrey, 2019, p. 268; Maqsood, Safdar, Shafi, &

Lelit, 2017, p. 373). This research used a parametric approach to measure the current period yield, which is calculated with the help of the below-mentioned equation (1).

Current yield =𝐹 × r

𝑃 (1) Where F is the face value of the ṣukūk, r is the cou- pon rate, and P is the selling price/current price in the market.

Whereas yield to maturity is calculated with the help of the below-mentioned formula. The returns are derived from the yield of ṣukūk in equation 2. The return of t day is derived from the difference in yield of t day minus the yield of t-1 day. The formula for calculation of return is given below.

Ṣ𝑢𝑘ū𝑘 Return (R_t) = Y_t - Y_t−1 (2) ARCH model was developed by Engle (1982).

ARCH models are used for financial time series with time-varying volatility, such as bond returns. For modelling the volatility, this model is very helpful

and describes volatility as a function of the error term. These errors occur due to the shocks or news by financial analysis in the financial market. These shocks may be of positive or negative nature depend- ing on the good news or bad news. According to this model, the larger the shock, the greater will be the volatility. Thus, before applying the model and its variants, there should be clustered volatility in the variance, and there should be heteroskedasticity in the residuals of the ṣukūk return data (Maqsood et al., 2017, p. 376). ARCH model is given below in equation 3.

t

2 =  + ²t-1 + t (3)

A generalized autoregressive conditional heteroscedasticity (GARCH) model was developed by Bollerslev (1986). This model captures the long- legged effects in the shocks with few parameters; this made it popular among the experts. The GARCH model is presented in equation 4.

σ²t = ω + α σ²t – 1 + β ε²t – 1 (4)

An exponential GARCH (EGARCH) model was proposed by Nelson (1991). This model was particularly formulated to allow asymmetric effect between positive and negative return. The EGARCH model is presented in equation 5.

𝑙𝑛𝜎_𝑡² = 𝜔 + ∑^𝑞_𝑖=1𝛼_𝑖[|^𝜀^𝑡−1

𝜎_𝑡−1|] + ∑^𝑝_𝑡=1𝛽_𝑖𝑙𝑛(𝜎_𝑡−1² ) + ∑^𝑞_𝑡=1𝛾_𝑖^𝜀_𝜎^𝑡−1

𝑡−1 (5)

Threshold GARCH (TGARCH) model was presented by Glosten, Jagannathan, and Runkle (1993). The equation of the TGARCH model is given in equation 6.

𝜎_𝑡²

= 𝜔

+ ∑ 𝛼_𝑖𝜀_𝑡−1²

𝑞

𝑖−1

+ ∑ 𝛼_𝑖𝜎_𝑡−1²

𝑝

𝑖−1

+ ∑ 𝛾𝑖𝜀_𝑡−1²

𝑞

𝑡=1 𝐼𝑡−1 (6) Where σ²t symbolizes the conditional variance that is the measure of volatility, conditional variance sug- gests that the forecast of variation in period t is based on the previous values of variables. ω denotes the intercept. I_t−1=1, if ε_t−1< 0, otherwise I_t−1= 0,

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and γ_i is the parameter of leverage effect. The value of conditional variance will be positive even if the parameters are negative because it models the log of conditional variance. σ²t – 1 is the GARCH term that is prior to conditional variance. ε²t – 1 is the ARCH term that is the squared error term from the previous period, whereas α and β are the coefficients.

4. Results and Discussions 4.1 Ṣukūk Yield

First and foremost, the present study graphically de- scribes the data to show the behavior of ṣukūk yield and return in Pakistan. Thus, figure 1 shows the yield of eight- and ten-year maturities of WAPDA ṣukūk, and three- and five-years maturities of K-Electric and Engro ṣukūk. There was a continuous fluctuation and downward trend in all ṣukūk except the three-year maturity Engro Corporation ṣukūk yield. Due to the changing trend, the graph is considered as nonlinear.

The downward trend can be seen from Jan 2014 to May 2015 in the yield of eight-year maturity WAPDA ṣukūk that decreased from 12% to 9%, and after that, from May 2015 to January 2016 the yield was moderately stable at 9% approximately. While the yield of ten-year maturity WAPDA ṣukūk re- mained between 10%-11% from Jan 2014 to Nov 2014, but after November 2014 till May 2015 the yield of ten-year WAPDA ṣukūk dropped to 7% and then after that from May 2015 to Jan 2016, it re- mained at 7% approximately.

The downward trend can also be seen from Octo- ber 2014 to May 2015 in the yield of three-year ma- turity K-Electric ṣukūk that decreased from 12% to 9% approximately, and after that from May 2015 to Aug 2015, it was moderately stable at approximately 9%. From August 2015 to January 2016, it decreased to almost 8.5%. The same trend was found in the yield of five-year maturity K-Electric ṣukūk. From October 2014 till May 2015, the yield of five-year maturity K-Electric ṣukūk dropped to 9% and then, after that from May 2015 to January 2016, it re- mained at approximately 9% with minor fluctuations.

Additionally, the downward trend can be seen from October 2014 to April 2015 in yield of three- year maturity Engro ṣukūk that decreased from 12.5% to 11.75% approximately, and after that from May 2015 to January 2016, it increased and reached almost 12.25%. While the yield of five-year maturity Engro Corporation ṣukūk rose from 12.5% to 13%

from Oct 2014 to May 2015, and after May 2015 till Aug 2015 the yield dropped by approximately 1%.

However, it recovered from Aug 2015 to Dec 2015, but it again declined, and at the end of Jan 2016 the yield of five-year Engro ṣukūk was 11.25% approxi- mately. It can be seen from figure 1 that the yield of both Engro Corporation ṣukūk are higher than the yield from K-Electric and WAPDA ṣukūk due to the high rate of return offered by the organization. There- fore, we accept H1 that the Engro Corporation ṣukūk yield is higher than the other ṣukūk of the study.

Figure (1) Line Graph of Ṣukūk Yield

Line graph of ten- and eight-year WAPDA sukuk yield

0.0000 2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000

Yield

10 Year WAPDA Sukuk Yield 8 Year WAPDA Sukuk Yield

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Line graph of three- and five-year K- Electric sukuk yield

Line graph of three- and five-year Engro Corporation sukuk yield

Source: Developed by authors (results exacted from Microsoft Excel)

4.2 Ṣukūk Return

Figure 2 shows the first difference in the yield data of all six ṣukūk. It can be viewed that all ṣukūk re- turn series are stationary, while the spikes in the graph indicate the high volatility in the data. The

graphs show, as in case of WAPDA ten-year ma- turity ṣukūk, for the first 150 days, a period of low volatility, followed by a period of high volatility from 200 to 340 days, then there are periods of low volatility from 340 to 399 days, followed again by some period of high volatility and then a period of 0.0000

2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000

Yield

3 Year K- Electric- Sukuk Yield

5 Year K- Electric- Sukuk Yield

10 10.5 11 11.5 12 12.5 13 13.5

Yield

3 Year Engro Corporation Sukuk Yield

5 Year Engro Corporation Sukuk Yield

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low volatility. Hence, volatility clustering gives the reason of applying ARCH, GARCH, EGARCH, and TGARCH models. Similar is the case of the remaining ṣukūk that also show the same pattern of clustering. The graphs show that the eight-year ma- turity ṣukūk return is more volatile than any other

ṣukūk in this study. The figure also verifies the yield trend that was downward, by showing that majority of the return as negative due to the downward trend in the pricing of the instrument except for the three- year maturity Engro corporation ṣukūk.

Figure (2) Line Graph of Ṣukūk Return

-.5 -.4 -.3 -.2 -.1 .0 .1 .2 .3

50 100 150 200 250 300 350 400 450

RETURNWAPDA8

^-.5

-.4 -.3 -.2 -.1 .0 .1 .2

50 100 150 200 250 300 350 400 450

RETURNWAPDA10

-.6 -.5 -.4 -.3 -.2 -.1 .0 .1 .2

25 50 75 100 125 150 175 200 225 250 275 300

RETURNKE3

^-.6

-.5 -.4 -.3 -.2 -.1 .0 .1 .2 .3

25 50 75 100 125 150 175 200 225 250 275 300

RETURNKE5

-.20 -.15 -.10 -.05 .00 .05 .10 .15

25 50 75 100 125 150 175 200 225 250 275 300 ECL3

^-1.0

-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4

25 50 75 100 125 150 175 200 225 250 275 300 ECL5

Source: Results extracted from EViews 8 software.

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4.3 Stationarity, Autocorrelation, and Hetero- scedasticity Test

In order to analyze the volatility in ṣukūk, this study first verifies the stationary in data by using the Augmented Dickey-Fuller (ADF) test. Table 1 shows that the p-value of the ADF test is significant in all series; thus, we reject the null hypothesis of a unit root. This signifies that stationarity exists in all series of ṣukūk. In order to test the presence of auto

correlation, this study employed the Durbin Watson test, which is also presented in Table 1. All Durbin Watson values are near to 2, so there is no issue of autocorrelation (Gujarati & Porter, 2009. p. 436).

Moreover, Lagrange Multiplier (LM) is used to ex- amine whether the standardized residuals show ARCH behavior. The results of the LM test, presented in table 2, evidently show that the variance of the returns of ṣukūk is non-constant for all periods specified.

Table (1) Unit Root and Autocorrelation Test

Time Series Test Statistics P-Value

Critical values Durbin

Watson test

1% 5% 10%

WAPDA 8 -24.75563 0.0000 -3.4433 -2.8671 -2.5698 2.052

WAPDA 10 -22.63298 0.0000 -3.4433 -2.8671 -2.5698 2.126

K-Electric 3 -19.41356 0.0000 -3.1212 -2.1322 -2.4321 1.953

K-Electric 5 -18.06651 0.0000 -3.2565 -2.2554 -2.5656 1.976

Engro 3 -17.95931 0.0000 -3.4570 -2.2732 -2.3214 2.043

Engro 4 -17.79921 0.0000 -3.3239 -2.4568 -2.5717 2.011

Source: Estimated by authors.

Table (2) ARCH-LM Test for Different Values of q

Time Series Arch Order 2 Test Statistics TR2 Probability

WAPDA 8 q1 156.952 0.0001

WAPDA 8 q2 226.532 0.0000

WAPDA 10 q1 196.190 0.0000

WAPDA 10 q2 283.165 0.0000

K-Electric 3 q1 166.762 0.0000

K-Electric 3 q2 240.690 0.0001

K-Electric 5 q1 141.747 0.0000

K-Electric 5 q2 204.587 0.0001

Engro 3 q1 120.485 0.0000

Engro 3 q2 173.899 0.0000

Engro 4 q1 148.197 0.0000

Engro 4 q2 213.895 0.0000

There are two preconditions to apply the ARCH model. First, there should be clustered volatility in residuals, and second, there should be an ARCH effect in the residuals. Both conditions were fulfilled in all the ṣukūk return data incorporated in this study.

Moreover, as shown in figure 3, the p-value of the heteroskedasticity test of all ṣukūk returns is 0.00, which is less than 0.05, meaning that ARCH effect exists. Thus, the ARCH model can be tested on this ṣukūk return.

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Figure (3) Residual Graph of Ṣukūk Return Wapda 8

-.6 -.4 -.2 .0 .2 .4

50 100 150 200 250 300 350 400 450

Residual Actual Fitted

Wapda 10

-.6 -.4 -.2 .0 .2

50 100 150 200 250 300 350 400 450

Residual Actual Fitted

KE3

-.6 -.4 -.2 .0 .2 .4

-.6 -.4 -.2 .0 .2

25 50 75 100 125 150 175 200 225 250 275 300 Residual Actual Fitted

KE5

-.6 -.4 -.2 .0 .2 .4

ECL3

-.20 -.15 -.10 -.05 .00 .05 .10 .15

ECL5

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4

Source: Results extracted from EViews 8 software.

In figure 4, the graphs of conditional standard devia- tion and the conditional variance of ṣukūk return are presented. The values of the conditional standard deviation are calculated by taking the square root of the conditional variance. The conditional variance spikes are lesser as compared to the conditional standard deviation graph. Thus, we accept H3

because it clearly shows the presence of variance that shows high volatility clustering in this series. The extraordinary spikes indicate the high volatile periods in the series. Further, it is noted that the values of the ARCH LM test and correlogram for all ṣukūk returns in this study showed that the GARCH (1,1) model is a good model.

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Figure (4) Plot for Conditional Standard Deviation and Conditional Variance of Ṣukūk Return

Wapda 8

.0 .1 .2 .3 .4 .5 .6 .7

50 100 150 200 250 300 350 400 450

Conditional standard deviation

.00 .05 .10 .15 .20 .25 .30 .35 .40

50 100 150 200 250 300 350 400 450

Conditional variance

Wapda 10

.0 .1 .2 .3 .4 .5 .6

50 100 150 200 250 300 350 400 450

.00 .04 .08 .12 .16 .20 .24 .28 .32

50 100 150 200 250 300 350 400 450

KE3

.0 .1 .2 .3 .4 .5 .6 .7

25 50 75 100 125 150 175 200 225 250 275 300

.0 .1 .2 .3 .4 .5

25 50 75 100 125 150 175 200 225 250 275 300

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KE5

.0 .1 .2 .3 .4 .5 .6 .7 .8

25 50 75 100 125 150 175 200 225 250 275 300

.0 .1 .2 .3 .4 .5 .6

25 50 75 100 125 150 175 200 225 250 275 300

ECL3

ECL5

4.4 Analysis and Discussion

The results of the ARCH (1) model in table 3 illus- trate that all coefficients are positive and statistically significant at the 5% level. The results indicate that every past value of ṣukūk returns significantly pre- dicts the current value of ṣukūk return. Moreover, the ARCH (1) model results of all ṣukūk are significant

as p-value is less than 0.05, except Engro 5Y, which did not give a significant result by testing the ARCH (1) model. Thus, we applied the ARCH (2) model and results are statistically significant at the 1% level, in which there are two ARCH terms that explain the varying volatility of the five years Engro Corporation

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ṣukūk return. The finding clearly establishes the pres- ence of time-varying conditional volatility of all ṣukūk returns. Thus, returns of different maturities corporate ṣukūk are volatile, supporting the findings of Abdul Rauf and Ibrahim (2014, p. 145). Moreover,

results indicate that the persistence of volatility in ṣukūk, as represented by the signs of the ARCH and GARCH parameters (α, β), is large. It denotes that the effects of today’s shock remain in the forecasts of variance for many periods in the future.

Table (3) Summary of The Results of ARCH and GARCH Models

WAPDA 10Y WAPDA 8Y K-Electric 3Y K-Electric 5Y ENGRO 3Y ENGRO 5Y ARCH Effect

 0.000396 0.000478 0.003515 0.000487 0.000591 0.000306



0.384722 0.184937 0.128925 0.091033 0.4245 0.004353

(0.0000) -0.0001 -0.0471 -0.0277 -0.0003 -0.7553

0.004494

(0.0000)

GARCH Effect

 - 0.000255 - 0.000548 0.000154 0.000931

 0.009838 0. 442981 0.008152 -0.011554 -0.020148 -0.008991

(0.0000) (0.0000) (0.0000) (0.0000) (0.0000) -0.0083

β 0.990162 0.290698 0.991848 0.870366 0.745251 0.850294

(0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000)

E-GARCH Effect

 0.001713 0.004166 -0.002089 -0.000621 -0.001448 -0.007837

C4 -0.034036 0.245613 -0.471532 -0.932125 0.151768 -0.164966

-0.7098 (0.0000) (0.0000) (0.0000) -0.0086 -0.0353

T-GARCH Effect

_ 0.014506 0.107648 0.094017 1.076242 0.659524 -0.073835

-0.7722 -0.2082 -0.4117 -0.0032 -0.0012 (0.0000)

γ1

1.11083 1.094793 2.731196 1.404857 -0.017594 0.210222

(0.0000) (0.0000) (0.0000) -0.001 -0.8467 (0.0000)

It is evident from this research that volatility is found in all different maturities corporate ṣukūk returns, similar to the finding of Abdalla and Winker (2012, p. 172). This confirms our hypothesis H2 that there is volatility in all corporate ṣukūk returns of different maturities. The WAPDA ṣukūk returns are more vol- atile as compared to K-Electric and Engro Corpora- tion ṣukūk returns. The first reason for the volatility of WAPDA ṣukūk returns is that it has been in the ṣukūk market for more than a decade, implying that it is among the pioneers of this sector. Whereas, K- Electric and Engro Corporation ṣukūk are relatively new entrants in the market. Secondly, WAPDA ṣukūk is an AAA rated instrument as compared to

K-Electric, and Engro Corporation ṣukūk, which are rated AA and A+ respectively.

Furthermore, the rate of return was much higher in both K-Electric and Engro Corporation, which was the result of investors retaining their holdings and not selling their ṣukūk securities, that in turn, ultimately affects the volatility pattern. Another reason for low volatility in ṣukūk returns could be that in an Islamic secondary market, there is no speculation like deriva- tives, futures, and hedging. This means that there would be less volatility in this market. The principles of Islamic economics prohibit any speculation on the prices, which is for the benefit of the people and to save them from losses.

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Comparing the volatility of three- and five-years maturity K-Electric ṣukūk returns with three, and five-years maturity Engro Corporation ṣukūk returns, it is discovered that K-Electric ṣukūk returns are more volatile than Engro Corporation ṣukūk returns. As for the K-Electric ṣukūk, the rate of return was varying, as it was linked with the KIBOR, and it was highly traded. However, Engro Corporation ṣukūk was less volatile as compared to WAPDA and K-Electric ṣukūk, because people did not want to sell their ṣukūk due to the higher rate of return offered by the Engro Corporation in the market. Thus, Engro Corporation ṣukūk is best for risk-averse customers who want a safe investment along with high profit.

It is shown that the tenure of ṣukūk affects the volatility of its return, as ṣukūk returns of three-year maturity period are more volatile than the ṣukūk re- turns of five-year maturity. Similarly, ṣukūk returns for eight-years maturity period are more volatile than ṣukūk returns of ten-year maturity. The results sup- port the findings of Ariff and Safari (2012, p. 101), who found that short period maturity ṣukūk are more volatile. Thus, we accept H4 because the results showed that the smaller the tenure of the ṣukūk, the higher its volatility. However, other factors like credit rating of the issuer, the credit rating of the instrument, rate of return, issue amount, and other market conditions would also affect the volatility behavior of all ṣukūk.

It is found that WAPDA eight and ten-year ma- turity ṣukūk has high volatility, which means that investors are more interested in this ṣukūk. Thus, investors who are willing to take a high risk in order to gain high profits can include ten and eight-year WAPDA ṣukūk in their portfolio. While the return volatility of both K-Electric ṣukūks lies between the volatility of the ṣukūk returns for the two WAPDA ṣukūks and the two Engro Corporation ṣukūks. Also, the results of ṣukūk return predicted that WAPDA ṣukūk returns with a maturity of eight years will rise more than other corporate ṣukūk returns.

The z statistic is used to test for a normal distribu- tion. As per the results, the hypothesis that the parameter coefficients are approximately zero is reject- ed; conditional variance and ARCH term are showing significant value at the 5% level. Thus, we accept H5 because it is proven that there is a GARCH effect founded in all corporate ṣukūk returns as per GARCH (1,1).

EGARCH model is the advance family member of ARCH model. Referring to the EGARCH table, the C4 coefficient is negative and significant, which clearly denotes that there is a leverage effect. The finding indicates that a negative correlation exists between the past return and the future volatility of the return. This indicates that if there is higher leverage than there is higher volatility in return. The higher leverage occurs due to the negative returns which translate to low equity prices, meaning a higher debt to equity ratio. Whereas a positive shock has less effect on conditional variance, compared to negative news. This means that good news and shock gener- ates less variance than bad news (economics conditions like inflation, unemployment, etc.) for Pakistan ṣukūk returns.

Moreover, events, news, incidents, etc., have a strong and powerful influence on the decision making of financial investors, and it has an asymmetric impact on financial markets. A standard ARCH and GARCH model treats both kinds of good and bad news symmetrically, and their impact on ṣukūk vola- tility is the same. However, as a matter of fact, the good and bad news may be asymmetric. Therefore, the threshold GARCH model captures the asymme- tries in terms of positive and negative shocks that hit the financial markets. Thus, the multiplicative dum- my variable was introduced into the variance equation to check whether there is a statistically significant difference when shocks are negative.

Lastly, the results of TGARCH show that for all ṣukūk returns, except Engro three-year ṣukūk return where γ1 is significant and positive, negative shocks have larger effects on conditional variance than positive shocks. The results indicate that news and events are very significant determinants of ṣukūk return vol- atility. The bad news has a larger effect than the good news as 1+ γ1> 1. The above finding of news and events gives useful information to investors and speculators about the risk attached with investment in ṣukūk returns.

5. Conclusions and Recommendations This research analyzes the trends and volatility of the different corporate domestic ṣukūk across various maturities. It was observed during all stages of the analysis, i.e., identification stage, estimation, diag- nostic checking, and evaluation stage, that ARCH,

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GARCH, EGARCH, and TGARCH models are best suited to identifying the trends and volatility in six ṣukūks issued in Pakistan. The yield of both the En- gro Corporation ṣukūks is higher than the K-Electric and WAPDA ṣukūks as evident from the yield curve given in the results and discussion section. The yield of Engro corporation three-year maturity ṣukūk is highest, as its yield increased when all other ṣukūk yields were decreasing.

It is evident from this research that volatility is found in all different maturities corporate ṣukūk re- turns. The WAPDA ṣukūk returns are more volatile as compared to K-Electric and Engro Corporation ṣukūk returns. While comparing the volatility of three- and five-years K-Electric ṣukūk returns with three- and five-year Engro Corporation ṣukūk returns, it is discovered that K-Electric ṣukūk returns are more volatile than Engro Corporation ṣukūk returns. This study also showed that the smaller the tenure of the ṣukūk, the higher its volatility. It was also found that WAPDA eight and ten-year maturity ṣukūk have higher volatility, meaning that investors are more interested in these ṣukūk. This indicates that investors who are willing to take a higher risk to gain higher profits should include ten and eight-year WAPDA ṣukūk in their portfolio. Moreover, TGARCH results show that for all ṣukūk returns, except Engro three- year ṣukūk, bad news will have a larger effect on the volatility of the ṣukūk return than good news.

5.1 Significance of Research and Future Outlook Volatility forecasting is a fascinating subject to both academics and practitioners for investment, security valuation, risk management, and monetary policy- making. This research shall also prove beneficial for the issuers, investors, and security managers in Paki- stan as well as abroad to identify the risk by calculat- ing the volatility of ṣukūk issued domestically. By assessing the whole situation of the risk, investors will take initiatives for safe and profit-taking invest- ments in domestic corporate ṣukūk released in Paki- stan. Besides this, it shall help portfolio managers to pick the appropriate ṣukūk by analyzing the risk ap- petite of their clients as well. In addition, the finding of this study shall help the policymakers to under- stand the ups and downs in the secondary capital market for making policies to safeguard the investment of the general public.

This research will provide a platform to the other researchers to further investigate the ṣukūk sector and bring up new concepts and elaborate upon previous ones in a more precise manner. Moreover, future studies can extend the present research by analyzing the volatility of other corporate domestic and sover- eign ṣukūk issued in Pakistan as well as around the world. In addition, future studies can also compare the ṣukūk return volatility with other fixed income securities present in the capital market. Future studies can also further extend the analysis by applying different research models.