




































INDIAN JOURNAL OF FINANCE AND BANKING 9(1) (2022), 230-239 

 

230 

 

 

                   FINANCE AND BANKING 

                                                                    IJFB VOL 9 NO 1 (2022) P-ISSN 2574-6081  E-ISSN 2574-609X 
                                                  

        Available online at https://www.cribfb.com 

                                                                                                                                           Journal homepage: https://www.cribfb.com/journal/index.php/ijfb 

                                                                                                                                                                                                   Published by CRIBFB, USA 

MAKING A COMPELLING CASE FOR ESG & ISLAMIC FUNDS: 

AN EMPIRICAL INVESTIGATION IN COMPARISON WITH 

CONVENTIONAL FUNDS        

 
 Aasim Abdullah (a)   Ullas Rao (b)1   

 

(a)  Bachelor of Business Administration, Edinburgh Business School, Heriot-Watt University Dubai, United Arab Emirates; E-mail: aa141@hw.ac.uk 
(b) Assistant Professor of Finance, Edinburgh Business School, Heriot-Watt University Dubai, United Arab Emirates; E-mail: u.rao@hw.ac.uk 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 28 January 2022  
Accepted: 27 March 2022 

Online Publication: 31 March 2022 

 
Keywords: 

 
ESG Investing, Fama-French Factor Model 

Islamic Mutual Funds, Mutual Funds  

Socially Responsible Funds 

 
JEL Classification Codes: 

 

B26, G11, G15, G23, M14 

 

 

   
   

 
A B S T R A C T 

 
The purpose of this research is to analyze and evaluate the performance of ESG funds and Islamic 

funds vis-à-vis conventional mutual funds, whereby ESG funds and Islamic funds take into account 
environmental, social, governance and Shariah-based factors into account during portfolio 

structuring. To conduct this study, the approach primarily employed the publicly available data of 

thirty funds from each aforementioned category, calculated their logarithmic returns based on closing 

prices and subsequently ranked the funds according to the returns. Ten of the top-ranking funds were 

then selected (owing to some limitations of market data availability) for the methodology to calculate 

performance using descriptive statistics, one-sample t-tests, portfolio performance measures (Sharpe 

ratio, Treynor ratio, Jensen’s Alpha) and the well renowned Fama-French three-factor model. The 

results show that much of the excess returns across a majority of the funds (in all categories) are largely 
explained by the market premium, while the fund manager skill, SMB and HML factors do not lend 

much weight in explaining the excess returns attributable to the funds. Furthermore, a considerable 

finding of this study is that ESG and Islamic funds are not underperforming, but exhibit resilience, and 

has the potential to evolve and become mainstream options for investments. 

 
 

© 2022 by the authors. Licensee CRIBFB, USA. This article is an open access article  distributed 
under the terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/).  

                                                     

 

INTRODUCTION 
The Chief Executive Officer of the CFA Institute, Smith (2019), delivers a holistic outlook on the future of ESG investments. 

He finds that “The client of the future cares passionately about ESG. Much more passionately than we appear to do as 

investment professionals.” 

Given the above from the perspective of a practitioner of investments, it can be seen that the interest and passion 

for the likes of social inclusion, social impact and even the minimizing of negative environmental impacts is a growing 

concern for the investors of the future. The future of investing hence is being geared towards the emphasis on ESG and other 

ethical investments. Given that the demand for such investment vehicles is set to increase, it would only be reasonable that 

the mutual funds of today begin to shift focus to the environmental, social and governance factors of their investment 

philosophy. 

 

Background to Mutual Funds 
There has been significant growth in mutual fund investment vehicles, especially on a global scale. These types of 

investments are very attractive to many investors, and also have the potential to make an impact on a country’s economic 

development. Moreover, today’s age of investing strategies are complex and versatile, with many investors integrating the 

use of technology and other sophisticated trading disciplines to get a better edge on the competition to extract competitive 

                                                      
1Corresponding author: ORCID ID: 0000-0002-5524-805X 
© 2022 by the authors. Hosting by CRIBFB. Peer review under responsibility of CRIBFB, USA.  

https://doi.org/10.46281/ijfb.v9i1.1683 

 
 

To cite this article: Abdullah, A., & Rao, U. (2022). MAKING A COMPELLING CASE FOR ESG & ISLAMIC FUNDS: AN EMPIRICAL 

INVESTIGATION IN COMPARISON WITH CONVENTIONAL FUNDS. Indian Journal of Finance and Banking, 9(1), 230-239. 
https://doi.org/10.46281/ijfb.v9i1.1683 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/ijfb.v9i1.1683
https://orcid.org/0000-0001-6088-1645
https://orcid.org/0000-0002-5524-805X


Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

231 
 

returns on investments. Some of the strategies can include and are not limited to goal-based strategies, faith-oriented 

strategies and ethical strategies. Considering that there are many more strategies mutual funds employ and with many varied 

and different types of mutual funds in existence, especially with the growth of fund-of-funds and real-estate investment 

trusts (REITs), it has only led to a rise in the interest of a large number of researchers and academics to examine fund returns 

and behavior. Much of this research has covered ground using basic econometric models, performance measures using 

single-factor and multi-factor variations, meta-analyses and more. 

Mutual funds are some of the fastest-growing players in the financial industry (In et al., 2014). The mutual fund 

assets under management have grown at a rate of 16% per year between 1980 and 2008, with the total net assets of the 

worldwide regulated funds reaching over $49 trillion. Along with this growth, the ESG and Islamic funds have also been 

growing at a very quick pace, having about $60 trillion of assets under management by the signatories of the PRI (Principles 

for Responsible Investment) (Friede et al., 2015). Islamic funds are also a fast-growing sector representing $1033 billion of 

Islamic assets under management (Abdelsalam et al., 2014). When taking into account the larger world of finance, 

investment allocation into Islamic equity is a recent phenomenon that began in 1994, when new legislation was issued that 

allowed the Muslim investors to trade in international equity under specific restrictions (Hayat & Kraeussl, 2011). Having 

absorbed this development, many conventional fund entities embraced the world of Islamic investments by offering various 

Islamic instruments in their portfolio offerings and compiling indices that include Islamic investment vehicles, namely the 

Dow Jones Islamic Market Index, FTSE Shariah index, MSCI Islamic, and S&P 500 Shariah indices. 

Many investors have gravitated towards the ESG funds and Islamic funds mainly due to the recent scandals in 

ethics literature, and with much focus, due to the financial crisis and the subsequent negative impact on conventional funds. 

This also led to the rise in the price of oil, leaving a good number of Islamic investors with high liquidity to invest. Regarding 

this trend, the Muslim investors were hence left with investment options in Islamic funds, thereby increasing the demand 

for these fund types. In addition to this, the Muslim population is growing at a steady pace which can imply continuing 

growth in demand, and subsequently continued growth and appeal of Islamic funds towards the future. For instance, the 

global population of Muslims is expected to grow to 2.2 billion in 2030, from the 2010 figure of 1.6 billion. This figure is 

approximated to be 26.4% of the total projected global population of 8.3 billion people in 2030 (Pew Research Centre, 

2011). Furthermore, the Islamic investment vehicles displayed considerable strength and resilience in the face of the global 

financial crisis, hence adding to the popularity of the Islamic fund type. 

With terms to a practitioner’s perspective on the grounds of ESG investments, most investors choose to integrate 

the governance factor into their investment process, while the environmental and social factors are relatively slow in 

adoption rates, hence the need for more focus on these factors (Orsagh et al., 2019). Furthermore, ESG integration is 

observed significantly more in the equity sector as opposed to the fixed income sector, and portfolio managers are more 

frequently incorporating factors of ESG within their investment techniques and processes (Orsagh et al., 2019). 

 

LITERATURE REVIEW 
Some academics have conducted empirical investigations and yielded promising results on ESG and Islamic funds. Sauer 

(1997) assesses the impact of socially responsible stocks on investment performance by analyzing restrictions present in 

socially responsible stocks. The tests observed that social screening did not impact the investment performance adversely 

and that investors need not be concerned about any sacrifice in investment performance because of the restrictions. 

Chang and Doug Witte (2010) analyse the characteristics of socially responsible funds and observe that fixed 

income-based socially responsible investments give a better performance with lower risk and higher return. 

Tripathi and Bhandari (2016) analyze if ESG based companies can portray better performance compared to 

conventional investment based companies. They find that the ESG compliant companies outperformed the conventional 

companies, with much higher alpha values when assessed against the Fama-French three-factor model. 

In regards to Islamic funds, Mansor and Bhatti (2011) conducted an in-depth study of the funds and observed that 

the Islamic mutual funds were performing better on average as compared to the Kuala Lumpur Stock Exchange Composite 

Index. Furthermore, the Islamic mutual funds exhibited higher statistically significant returns in comparison to their 

conventional fund counterparts. 

Dah et al. (2015) analyzed Shariah impacts with reference to the Dow Jones Islamic Index (DJIM-US). The authors 

find that the Islamic funds, primarily in the Saudi Arabian market, Malaysian market and the Kuwaiti market do not 

necessarily underperform compared to the market benchmarks, rather they outperformed the DJIM-US and also the Dow 

Jones Sustainability Index of the US. 

Finally, the study by El-Masry et al. (2016) used a test to assess the performance of Islamic mutual funds in the 

GCC and the Middle East and North African region. They found that the funds outperform the conventional funds in the 

GCC region, and they are less risky and more resistant to certain forms of economic crises. 

 

OBJECTIVE OF THE STUDY 
Based on the above, the purpose of this research paper is to analyze and evaluate the performance of ESG funds and Islamic 

mutual funds vis-à-vis conventional mutual funds. This purpose will entail the use of preliminary analysis via descriptive 

statistics, one-sample t-tests and portfolio performance measures such as the Sharpe ratio (Sharpe, 1966), Treynor ratio 

(Treynor, 1965) and the Jensen’s Alpha (Jensen, 1968), along with the renowned econometric Fama-French three-factor 

model (Fama & French, 1993) to assess the factors affecting the fund performance and excess returns attributable to the 

funds. 

 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

232 
 

The main objectives, therefore, of this paper will be as follows: 

 Analyzing the fund manager’s efforts in explaining the excess returns of a fund. 

 Analyzing the impact of the market premium in explaining the excess returns of the fund. 

 Analyzing if the SMB (size factor) is significant in explaining the excess return attributable to the fund. 

 Analyzing if the HML (value factor) is significant in explaining the excess return attributable to the fund. 

Having introduced the research study and set forth the objectives, this paper will now move to discuss the 

methodology and the empirical material of the study. 

 

METHOD 

The data used for the analysis included thirty funds from each category (see appendices A, B and C), and the returns of the 

funds were analyzed based on four specific tests. The tests were the preliminary descriptive statistics (see appendices D, E, 

F, G, H and I), one-sample t-test (Tables 1, 2 and 3), portfolio performance measures (see appendix J) and the Fama-French 

three-factor model (Tables 4, 5 and 6). 

Using the preliminary descriptive statistics, the Jarque-Bera values (Jarque & Bera, 1980) were assessed across all 

the funds; the highest significance was seen in the Islamic sample, followed by the ESG fund sample, with the majority of 

the insignificance observed in the conventional fund sample (see appendices E, G and I). 

The one-sample t-test was conducted to assess preliminary significance levels that can give an initial inference into 

the return behaviour of the funds, which will be later assessed by the Fama- French three-factor model. The one-sample t-

test showed insignificance in the conventional fund portfolio, while the significance was observable for the ESG and Islamic 

fund portfolios (Tables 1, 2 and 3). 

 

Table 1. Test values for conventional fund portfolio 

 
 VANGUARD 

HORIZON FD. 

VANGD.CAP.

OPPOR.FD. 

BROWN 

CAP.MAN.S

ML.CO. 

INV.SHS. 

CLEARBRID

GE LARGE 

CAP 

GROWTH 

FD.CL.A 

COL.SELIG

MAN 

GLB.TECH.

FD.CL.C 

DODGE   

& COX 

BAL.FD. 

HARTFORD 

SMALL CAP 

GROWTH 

FUND A 

VANGUARD 

PRIMECAP 

FD. 

AB 

EQUITY 

INCOME 

FUND A 

AB SMALL 

CAP 

GROWTH 

PORTFOLI

O A 

AMERICA

N FUNDS 

GLOBAL 

GROWTH 

FUND 2 

t-Statistic  (0.1853)  (0.8355)  (0.2275)  (0.7495) (-0.0801)  (0.3802) (0.2465)  (0.9411)  (0.7213)  (0.5641) 

Source: Authors’ calculations 

 

Table 2. Test values for ESG fund portfolio 

 
 DWS 

INVEST ESG 

EURO 

BONDS 

(SHORT) FC 

DWS ESG 

EURO 

BONDS 

(LONG) LC 

DWS ESG 

EURO 

BONDS 

(MEDIUM) 

LC 

PAX ESG 

BETA 

QUALITY 

FUND 

INDIVIDUAL 

INVESTOR 

PRISMA ESG 

WORLD 

CONVERTIBLE 

BONDS 

SBI 

MAGNUM 

EQUITY 

ESG FUND-

DIVIDEND 

FIERA 

ACTIVE 

FIXED 

INCOME 

ETHICAL 

ESG FUND 

DAIWA 

DC SRI 

FUND 

NOMURA 

GLOBAL 

SRI 100 

NOMURA 

GLOBAL 

SRI 

INDEX 

FUND DC 

t-Statistic (5.1787)*** (2.6196)** (2.7291)*** (0.2317) (0.1107) (0.7527) (0.4521) (-0.3285) (-0.2517) (-0.1914) 

Source: Authors’ calculations 

 

Table 3. Test values for Islamic fund portfolio 

 
 JS 

ISLAMIC 

FUND 

MEEZAN 

ISLAMIC 

FUND 

CIMB 

ISLAMIC 

SUKUK 

AM BON 

ISLAM 

HSBC 

ISLAMIC 

GLOBAL 

EQUITY 

INDEX AD 

USD 

CIMB 

ISLAMIC 

DALI 

EQUITY 

RHB 

ISLAMIC 

BOND 

DOW 

JONES 

ISLAMIC 

FD. CL.K 

CIMB 

ISLAMIC 

DALI 

EQUITY 

GROWTH 

HSBC US 

DOLLAR 

MURABAHA 

FUND 

t-

Statistic 

(-0.6805) (-0.2260) (4.9153)*** (1.9712)* (0.5539) (0.6989) (1.1880) (0.3947) (1.3111) (11.2857)*** 

Source: Authors’ calculations 

 

The portfolio performance measures were conducted to ascertain the performance behaviour of the portfolio. 

Regarding the Sharpe and Treynor ratio, the higher value would indicate better performance; for Jensen’s Alpha, a positive 

value for the alpha would indicate a better fund performance as opposed to a negative alpha value. The tests showed an 

equal number of high and positive values (six funds) across the conventional funds, while there were nine ESG and Islamic 

funds with a high Sharpe ratio, ten ESG and Islamic funds with a high Treynor ratio and seven ESG and Islamic funds with 

a positive alpha (see appendix J). 

The Fama-French three-factor model is conducted in tables 4, 5 and 6, showing varied observations. With reference 

to the conventional sample (Table 4), all of the t-stat values were significant with terms to the market risk coefficient, 

indicating that the excess returns attributable to the funds are explained by the market premiums alone. 

 

Table 4. Fama-French three-factor model analysis for conventional funds 

 
 VANGUARD 

HORIZON 

FD. 

VANGD.CAP

.OPPOR.FD. 

BROWN 

CAP.MAN.

SML.CO. 

INV.SHS. 

CLEARBRID

GE LARGE 

CAP 

GROWTH 

FD.CL.A 

COL.SELIGM

AN 

GLB.TECH.FD

.CL.C 

DODGE & 

COX 

BAL.FD. 

HARTFO

RD 

SMALL 

CAP 

GROWTH 

FUND A 

VANGUAR

D 

PRIMECAP 

FD. 

AB 

EQUITY 

INCOME 

FUND A 

AB SMALL 

CAP 

GROWTH 

PORTFOLI

O A 

AMERICAN 

FUNDS 

GLOBAL 

GROWTH 

FUND 2 

α -0.00292 

(-0.4732) 

0.0015 

(0.2335) 

-0.0025 

(-0.4399) 

0.0006 

(0.0939) 

-0.0042 

(-0.9085) 

-0.0014 

(-0.1895) 

-0.0024 

(-0.4409) 

0.0007 

(0.1510) 

0.0011 

(0.1569) 

-0.0006 

(-0.0989) 

RM-RF 0.0038 0.0033 0.0031 0.0041 0.0032 0.0035 0.0028 0.0026 0.0036 0.0037 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

233 
 

(2.4438)** (2.0339)** (2.2025)** (2.6589)*** (2.7391)*** (1.9348)* (2.0691)** (2.1991)** (1.9517)* (2.5917)** 

SMB -0.0007 

(-0.2383) 

-0.0006 

(-0.1836) 

-0.0013 

(-0.4604) 

-0.0014 

(-0.4666) 

-0.0009 

(-0.3958) 

0.00002 

(0.0042) 

-0.0008 

(-0.2791) 

-0.0004 

(-0.1627) 

0.0003 

(0.0829) 

-0.0023 

(-0.8222) 

HML 0.0008 

(0.3436) 

-0.0009 

(-0.3568) 

-0.0001 

(-0.0597) 

-0.0014 

(-0.5919) 

-0.0003 

(-0.1692) 

-0.0004 

(-0.1405) 

0.0011 

(0.5319) 

-0.0010 

(-0.5278) 

-0.0006 

(-0.1957) 

-0.0004 

(-0.1895) 

Adj. R2 0.0556 0.0193 0.0280 0.0475 0.0596 0.0205 0.0373 0.0270 0.022 0.0441 

Source: Authors’ calculations 

 

Regarding the ESG funds (Table 5), there are several statistical significances in regards to the alpha, SMB and 

HML factors, some of which are negative as well. This observation is also similar to the Islamic fund portfolio (Table 6). 

The inference behind these results will be discussed in the next section. 

 

Table 5. Fama-French three-factor model analysis for ESG funds 

 
 DWS 

INVEST 

ESG 

EURO 

BONDS 

(SHOR

T) FC 

DWS 

ESG 

EURO 

BONDS 

(LONG) 

LC 

DWS ESG 

EURO 

BONDS 

(MEDIUM) 

LC 

PAX ESG 

BETA 

QUALITY 

FUND 

INDIVIDUAL 

INVESTOR 

PRISMA ESG 

WORLD 

CONVERTIBLE 

BONDS 

SBI 

MAGNUM 

EQUITY 

ESG FUND-

DIVIDEND 

FIERA 

ACTIVE 

FIXED 

INCOME 

ETHICAL 

ESG FUND 

DAIWA DC 

SRI FUND 

NOMURA 

GLOBAL 

SRI 100 

NOMURA 

GLOBAL 

SRI INDEX 

FUND DC 

α -0.0002 

(0.4348) 

0.0004 

(0.3429) 

-0.0004 

(-0.4941) 

-0.0045 

(-0.9994) 

-0.0020 

(-0.5353) 

-0.0054 

(-0.6917) 

-0.0023 

(-1.7999)* 

-0.0027 

(-0.5571) 

-0.0009 

(-0.1644) 

-0.0005 

(-0.0919) 

RM-RF 0.0001 

(0.5505) 

-0.0001 

(-0.4447) 

0.0004 

(2.3484)** 

0.0086 

(7.5044)*** 

0.0015 

(2.0049)** 

0.0061 

(5.0986)*** 

0.0002 

(0.6188) 

0.0099 

(9.0178)*** 

0.0081 

(6.2672)*** 

0.0081 

(6.2670)*** 

SMB 0.0006 

(2.2429)** 
-0.0001 

(-0.1050) 

0.0010 

(2.1323)** 

0.0008 

(0.3381) 

0.0055 

(2.9063)*** 

0.0025 

(0.8843) 

0.0001 

(0.1218) 

-0.0012 

(-0.6367) 

0.0061 

(-2.7150)*** 

-0.0060 

(-2.6782)*** 

HML 0.0002 

(0.6896) 

0.0002 

(0.2281) 

-0.0001 

(-0.1507) 

-0.0038 

(-2.1144)** 

0.0006 

(0.3040) 

0.0008 

(0.2643) 

-0.0002 

(-0.2519) 

-0.0013 

(-0.6196) 

-0.0040 

(-1.5821) 

-0.0039 

(-1.5726) 

Adj. R2 0.0387 -0.0302 0.0928 0.4195 0.1212 0.2424 -0.0253 0.4853 0.3758 0.3745 

Source: Authors’ calculations 

 

Table 6. Fama-French three-factor model analysis for Islamic funds 

 
 JS 

ISLAMIC 

FUND 

MEEZAN 

ISLAMIC 

FUND 

CIMB 

ISLAMIC 

SUKUK 

AM 

BON 

ISLAM 

HSBC 

ISLAMIC 

GLOBAL 

EQUITY 

INDEX AD USD 

CIMB 

ISLAMIC 

DALI 

EQUITY 

RHB 

ISLAMIC 

BOND 

DOW JONES 

ISLAMIC FD. 

CL.K 

CIMB 

ISLAMIC 

DALI EQUITY 

GROWTH 

HSBC US 

DOLLAR 

MURABAHA 

FUND 

α -0.0194 

(-1.6842)* 

-0.0118 

(-1.1897) 

-0.0003 

(-0.5360) 

-0.0014 

(-1.4164) 

-0.0027 

(-0.6802) 

-0.0053 

(-1.7814)* 

-0.0010 

(-0.5339) 

-0.0040 

(-0.9151) 

-0.0013 

(-0.4114) 

-0.0009 

(-7.4589)*** 

RM-

RF 

0.0028 

(1.6188) 

0.0027 

(1.7985)* 

0.00001 

(0.1658) 

0.00003 

(0.2208) 

0.0073 

(9.1957)*** 

0.0056 

(12.1547)*** 

-0.0002 

(-0.6949) 

0.0122 

(11.1381)*** 

0.0039 

(7.9844)*** 

0.00001 

(-0.5319) 

SMB 0.0021 

(0.5165) 

0.0039 

(1.1013) 

0.0001 

(0.2335) 

0.0004 

(1.2081) 

0.0013 

(0.6520) 

0.0036 

(3.3484)*** 

0.0001 

(0.1363) 

-0.0029 

(-1.3238) 

0.0034 

(2.9966)*** 

-0.0001 

(-1.0384) 

HML -0.0006 

(-0.1333) 

-0.0072 

(-1.7612)* 

0.0004 

(1.4954) 

0.0006 

(1.4504) 

-0.0034 

(-1.5219) 

0.0031 

(2.5461)** 

0.0002 

(0.2975) 

-0.0049 

(-2.9051)*** 

0.0020 

(1.5451) 

0.00003 

(0.4126) 

Adj. 

R2 

0.0111 0.0863 -0.0078 0.0046 0.5281 0.6749 -0.0248 0.5890 0.4927 -0.0138 

Source: Authors’ calculations 

 

RESULTS 

This section will develop a discussion based on the observations that emerged from the empirical analysis of the data. 

Beginning with the preliminary analysis conducted via the descriptive statistics of the funds – with a focus on the Jarque-

Bera values – it was observed that the significance level was most prominent for the Islamic sample of funds, which was 

followed by the ESG fund sample, and the conventional sample showing the majority of insignificance (see appendices D, 

E, F, G, H and I). 

These results indicate that the mean returns from the Islamic funds tend to dominate the ESG funds, which in turn 

dominates the conventional fund sample; the mean returns are observed to be statistically insignificant and therefore 

indifferent from zero. With terms to the grand mean assessment (see appendices E, G and I), it was seen that the conventional 

funds tend to be the most significant, which was followed by the Islamic funds, with the lowest significance for the ESG 

funds; this inference however is not a point of contention, as it shows that the Islamic funds are not underperforming their 

conventional counterparts grossly, which serves as a competitive standpoint in the investing universe. 

In reference to the one-sample t-tests, the preliminary descriptive analysis was corroborated further, as the tests 

showed considerable significance levels in Islamic funds and ESG funds, and zero significance concerning the conventional 

funds (Tables 1, 2 and 3). The significance levels show that there are factors beyond the market premium that explain the 

excess returns to the funds in the Islamic and ESG portfolio, whereas for the conventional portfolio, the insignificance shows 

that the excess returns attributable to the funds are purely explained by the market premium. This was corroborated by the 

Fama-French three-factor model, where the significance levels was present mainly for the market risk coefficient of the 

funds. 

The portfolio performance measures, which are the Sharpe ratio, Treynor ratio and the Jensen’s Alpha, when 

applied to the sample portfolio, showed a relatively mixed observation (see appendix J). These observations do not indicate 

any form of gross underperformance on part of the ESG and Islamic funds, and this test was also treated as a form of the 

preliminary analysis in advance of the Fama- French three-factor model. 

The Fama-French three-factor model gave a very descriptive result, especially considering the ESG and Islamic 

funds (Tables 4, 5 and 6). This analysis gave a confirmation of the preliminary descriptive statistics and the one-sample t-

test concerning the significant values for excess returns. The conventional funds were largely experiencing only market 

premium advantages when achieving the excess returns, and hence had no link to the size factor, value factor or the skill of 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

234 
 

the fund manager. This is in effect a rather conventional result that yields no abnormal explanation for the excess returns. 

The ESG and Islamic funds, however, exhibited several interesting observations, particularly about the SMB, HML 

and the alpha values. It was seen that some of the respective funds showed a deviation from the conventional theory of the 

SMB and HML factors whereby big stocks were dominating the small stocks (lower SMB stocks giving higher return), and 

that the growth stocks were dominating the value stocks (low book-market stocks giving higher return). Furthermore, the 

fund manager’s efforts were also analyzed, as certain funds displayed a negative and significant value; indicating that the 

fund manager could be experiencing bad luck due to the potential investment philosophy of the fund that restricts the fund 

manager to a smaller investment universe. This would indicate that although the fund manager is picking the stocks in line 

with the investment philosophy of the fund, the stocks may not necessarily be the winner stocks that can help in achieving 

a higher return. 

 

DISCUSSION 

The main inferences that could be established via the results are that the market premium is the main factor that explains 

the excess returns that are attributable to the funds. As a majority of the funds in the portfolio samples showed significance 

in the market risk coefficients, it shows that the remaining SMB and HML factors are not significant in explaining the excess 

returns. 

Although certain funds showed a significance level about the SMB and the HML, especially in the case of negative 

coefficients, by and large, these factors are not viable enough to postulate any explanations based on these factors. Finally, 

the luck and skill of fund managers do not tend to influence the excess returns to the fund. Two funds in the portfolios 

indicated negative and significant alphas, yet these observations are not viable evidence to conclude that the fund manager 

skill is required to achieve excess returns. 

The limitations of this study involved the inability to procure data for ESG and Islamic funds before the year 2005. 

Conventional fund data can, however, easily date back to the year 1990 and earlier due to these funds being going concerns 

for ages. This incongruence in data availability limits the analysis of all the categories together in the same period under 

study, therefore, to maintain time-period congruency amongst the fund categories, the monthly returns were used for the 8 

years of 2005 - 2012. Furthermore, to assess market premium returns, certain markets primarily in the GCC region do not 

have publicly available sovereign interest rates to use as a proxy for risk-free return measures. Although the Islamic fund 

market can be present in these locations, the unavailability of the risk-free rates poses a limitation to calculating the risk 

premiums. This forced the portfolio allocation to exclude some otherwise higher ranked funds due to the unavailability of 

the market data to compare against. 

Through these inferences, although the ESG and Islamic funds are not outperforming their conventional mutual 

fund counterparts, there exists no significant evidence of underperformance. This indicates that the funds are still evolving 

with time and that their full potential shall be seen as the funds evolve; the ESG and Islamic funds are here to stay and can 

be looked upon as resilient investment vehicles. This inference is largely in line with the words of Smith (2019), as the ESG 

funds are going to be the future for investors. 

 

CONCLUSION 

This study analyzed the performance of ESG funds and Islamic funds together in comparison to their conventional 

counterparts; the likes of which has not been conducted all-inclusively within the existing literature. Numerous studies 

primarily compare ESG funds with conventional funds, relatively fewer studies with regards to Islamic funds and 

conventional funds, and even fewer with regards to the comparison of all three fund categories together. Therefore, to 

contribute to this gap in the literature, this analysis was undertaken. The objective of this study was therefore to analyze the 

three-way inclusion of the fund categories using portfolio performance measures and the econometric Fama-French three-

factor model. Using these tools, an explanation for fund returns was sought based on fund manager skill, market premium, 

size and value factors (SMB & HML). 

The limitations that were experienced, were by and large based on the non-availability of specific data about the 

ESG and Islamic funds. Since these fund categories are relatively new to the financial world as opposed to the conventional 

funds that have been present since the ages, better testing and analysis can only be performed as the former funds continue 

to evolve into the future. 

Concerning the above results and the discussion, it can be inferred that although much of the abnormal returns are 

explained mainly via the market premiums, it cannot be left unsaid that investor bias can also play a significant role in 

affecting the excess returns. This is a limiting factor in this analysis. By and large, when the choice of fund selection is left 

to the investor’s interest, then the means of how the decision is made is not entirely measurable to dictate how far the 

inherent investor bias can affect fund returns; as there is no conceivable scientific evidence to highlight any proof of the 

same, hence warranting a scope for further study in this regard. 

On this note, the point that can be taken away is that ESG and Islamic investments will remain attractive investment 

vehicles for many investors due to various reasons. In addition, the funds do not underperform their conventional 

counterparts; the absence of underperformance is a viable factor that can enable the ESG and Islamic funds to maintain their 

popularity amongst investors and other stakeholders alike. In addition, the events of the global financial crisis displayed 

weaknesses in the conventional funds’ investment philosophies, while the Islamic investments stood resilient. These pieces 

of evidence indicate that the ESG funds and Islamic funds are in for the long haul, and will maintain their allure to investors 

with sentiment towards ethics and religion. 

 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

235 
 

 

 
Author Contributions: Conceptualization, A.A. and U.R.; Data Curation, U.R.; Methodology, U.R.; Validation, U.R.; Visualization, A.A.; Formal 

Analysis, U.R.; Investigation, A.A. and U.R.; Resources, A.A. and U.R.; Writing – Original Draft, A.A.; Writing – Review & Editing, A.A. and U.R.; 
Supervision, U.R.; Software, A.A. and U.R.; Project Administration, U.R.; Funding Acquisition, U.R.. Authors have read and agreed to the published 

version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 
groups or sensitive issues. 

Funding: The authors received no direct funding for this research. 

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 
Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest.                                                                                                                                                                                                                                    
 

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APPENDICES 

Appendix A: List of the Conventional Fund Sample with Datastream Codes (Thomson Reuters) 

 
CONVENTIONAL FUNDS CODE 

AB DISCOVERY GROWTH FUND A 912676(P) 

AB EQUITY INCOME FUND A 360530(P) 

AB SMALL CAP GROWTH PORTFOLIO A 517893(P) 

ABDN.GLOBAL EQUITY FD.CLASS A 280609(P) 

ABDN.GLOBAL EQUITY FD.CLASS C 14057F(P) 

ABDN.GLOBAL EQUITY FUND INSTL.SER.CL. 280607(P) 

ALGER SML.CAP GW.FD CL.A 894459(P) 

AMER.CEN.GLB.GD.FD.A CL. 14764Q(P) 

AMER.CEN.GLB.GW. FD.A CL. 14765H(P) 

AMER.CEN.SML.CAP.GW.FD. CL.A 26753V(P) 

AMERICAN FDS TAX EX FD OF CALIFORNIA F3 9016RC(P) 

AMERICAN FUNDS GLOBAL GROWTH FUND 2 8654L3(P) 

BLACKROCK BASIC VAL.I 966644(P) 

BLACKROCK HIGH EQUITY INCOME FUND INVESTOR A 696620(P) 

BROWN CAP.MAN.SML.CO. INV.SHS. 154127(P) 

CLEARBRIDGE LARGE CAP GROWTH FD.CL.A 878407(P) 

COL.DIV.OPPOR.FD.CL.A 515043(P) 

COL.SELIGMAN GLB.TECH. FD.CL.C 286534(P) 

COLUMBIA SELECT LARGE CAP VALUE FUND A 895259(P) 

DEL.GLB.VAL.FD.CL.A 14641H(P) 

DEL.GLB.VAL.FD.CL.C 14641K(P) 

DEL.GLB.VAL.FD.CL.I 14641L(P) 

DODGE & COX BAL.FD. 513165(P) 

FIDELITY MAGELLAN 513721(P) 

HARTFORD SMALL CAP GROWTH FUND A 15194W(P) 

PACE LGE.CO.GW.EQ.INVS. CL.P 311245(P) 

TWEEDY BROWNE VAL.FD. 134272(P) 

VANGUARD BD.IDX.FD.TTL. BD.MKT.PRTF. 519793(P) 

VANGUARD HORIZON FD. VANGD.CAP.OPPOR.FD. 362943(P) 

VANGUARD PRIMECAP FD. 517699(P) 

 

Appendix B: List of the ESG Fund Sample with Data stream Codes (Thomson Reuters) 

 
ESG FUNDS CODE 

ASAHI LIFE SRI SOCIETY CONTRIBUTION FUND 92862T(P) 

C-QUADRAT ABSOLUTE RETURN ESG FUND A 27299L(P) 

C-QUADRAT ABSOLUTE RETURN ESG FUND T 27299M(P) 

DAIWA DC SRI FUND 92790E(P) 

DAVY ESG MULTI-ASSET FUND 8841K3(P) 

DNB FUND GLOBAL EMERGING MARKETS ESG A CAP 671454(P) 

DNB FUND GLOBAL ESG RETAIL A 882866(P) 

DWS ESG EURO BONDS (LONG) LC 309229(P) 

DWS ESG EURO BONDS (MEDIUM) LC 308044(P) 

DWS ESG EUROPEAN EQUITIES LC 13998H(P) 

DWS INVEST ESG EURO BONDS (SHORT) FC 25676F(P) 

DWS INVEST ESG EURO BONDS (SHORT) LC 25594X(P) 

DWS INVEST ESG EURO BONDS (SHORT) LD 25595J(P) 

DWS INVEST ESG EURO BONDS (SHORT) NC 25676E(P) 

FIERA ACTIVE FIXED INCOME ETHICAL ESG FUND 7774QX(P) 

GOLDMAN SACHS INTL EQ ESG FD A 327325(P) 

GOLDMAN SACHS INTL EQ ESG FD C 895997(P) 

GOLDMAN SACHS INTL EQ ESG FD INST 875730(P) 

GOLDMAN SACHS INTL EQ ESG FD SVC 877961(P) 

MUKAM SRI FUND 92723C(P) 

NOMURA GLOBAL SRI 100 92697Q(P) 

NOMURA GLOBAL SRI INDEX FUND DC 92708V(P) 

PAX ESG BETA QUALITY FUND INDIVIDUAL INVESTOR 674675(P) 

PIMCO LOW DURATION ESG FUND INSTITUTIONAL 894809(P) 

PIMCO TOTAL RETURN ESG FUND ADMN 879575(P) 

PIMCO TOTAL RETURN ESG FUND INSTITUTIONAL 545394(P) 

PRISMA ESG WORLD CONVERTIBLE BONDS 27639F(P) 

SBI MAGNUM EQUITY ESG FUND-DIVIDEND 8706QF(P) 

SHINKIN FUKOKU SRI FUND 92638K(P) 

SMT SRI JAPAN OPEN 92690V(P) 

 

Appendix C: List of the Islamic Fund Sample with Datastream Codes (Thomson Reuters) 

 
ISLAMIC FUNDS CODE 

AM BON ISLAM 88894X(P) 

AM ISLAMIC BALANCED 88910N(P) 

AM ISLAMIC GROWTH 88910L(P) 

CIMB ISLAMIC BALANCED 88893N(P) 

CIMB ISLAMIC BALANCED GROWTH 88902D(P) 

CIMB ISLAMIC DALI ASIA PACIFIC EQUITY GROWTH 88910Q(P) 

CIMB ISLAMIC DALI EQUITY 88899U(P) 

CIMB ISLAMIC DALI EQUITY GROWTH 88885U(P) 

CIMB ISLAMIC EQUITY AGGRESSIVE 88886U(P) 

CIMB ISLAMIC SMALL CAP 88899R(P) 

CIMB ISLAMIC SUKUK 88910T(P) 

DOW JONES ISLAMIC FD. CL.K 263758(P) 

FAISAL ISLAMIC BANK OF EGYPT MUTUAL FUND 8937TE(P) 

GLOBAL AL-DURRA ISLAMIC 8937NE(P) 

HSBC ISLAMIC GLOBAL EQUITY INDEX AD USD 299364(P) 

HSBC US DOLLAR MURABAHA FUND 8937EV(P) 

JS ISLAMIC FUND 90599M(P) 

KENANGA ISLAMIC 88896P(P) 

KENANGA ISLAMIC BALANCED 88911F(P) 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

237 
 

KENANGA OA INV-KENANGA BON ISLAM 88908W(P) 

KENANGA OA INV-KENANGA EKUITI ISLAM 889089(P) 

MARKAZ ISLAMIC FUND 8937MV(P) 

MEEZAN ISLAMIC FUND 90592Q(P) 

MFC ISLAMIC 91484Z(P) 

MIDF AMANAH ISLAMIC 88891V(P) 

PUBLIC ISLAMIC BOND 88894L(P) 

PUBLIC ISLAMIC EQUITY 88901X(P) 

RHB DANA ISLAM 88894V(P) 

RHB ISLAMIC BOND 88893L(P) 

TA ISLAMIC 88893V(P) 

 

Appendix D: Descriptive Statistics (of logarithmic returns) – Conventional Funds 

 
Code Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations 

912676(P) 0.0009 0.0055 0.1843 -0.2436 0.0763 -0.7289 4.6136 18.9158 0.0001 0.0905 0.5533 96 

360530(P) 0.0044 0.0134 0.0896 -0.1504 0.0457 -1.0647 4.7278 30.0776 0.0000 0.4217 0.1987 96 

517893(P) 0.0053 0.0016 0.1906 -0.2516 0.0719 -0.4803 4.5000 12.6913 0.0018 0.5083 0.4914 96 

280609(P) 0.0043 0.0142 0.1783 -0.1823 0.0605 -0.4498 4.0873 7.9666 0.0186 0.4133 0.3474 96 

14057F(P) 0.0041 0.0142 0.1801 -0.1828 0.0606 -0.4409 4.1051 7.9948 0.0184 0.3888 0.3487 96 

280607(P) 0.0042 0.0000 0.4221 -0.1828 0.0660 2.2634 19.4529 1164.7607 0.0000 0.4038 0.4134 96 

894459(P) 0.0055 0.0117 0.1913 -0.2259 0.0679 -0.6257 4.6516 17.1748 0.0002 0.5301 0.4376 96 

14764Q(P) 0.0038 0.0068 0.2310 -0.2368 0.0983 -0.1919 2.7381 0.8638 0.6493 0.3659 0.9177 96 

14765H(P) 0.0024 0.0130 0.1338 -0.2136 0.0607 -0.8629 4.5726 21.8066 0.0000 0.2306 0.3498 96 

26753V(P) 0.0026 0.0159 0.1728 -0.2117 0.0715 -0.2769 3.3577 1.7387 0.4192 0.2465 0.4860 96 

9016RC(P) 0.0008 0.0006 0.0562 -0.0618 0.0167 -0.3969 6.0893 40.6969 0.0000 0.0769 0.0265 96 

8654L3(P) 0.0033 0.0121 0.1538 -0.1697 0.0565 -0.5437 4.1996 10.4856 0.0053 0.3124 0.3036 96 

966644(P) -0.0018 0.0065 0.1681 -0.2074 0.0613 -0.4930 4.5658 13.6949 0.0011 -0.1714 0.3564 96 

696620(P) 0.0047 0.0138 0.1673 -0.1998 0.0628 -0.4322 4.3072 9.8237 0.0074 0.4513 0.3741 96 

154127(P) 0.0054 0.0139 0.1686 -0.1799 0.0637 -0.3473 3.5128 2.9819 0.2252 0.5219 0.3860 96 

878407(P) 0.0013 0.0027 0.1717 -0.1742 0.0557 -0.2865 4.0654 5.8534 0.0536 0.1242 0.2949 96 

515043(P) 0.0021 0.0088 0.1535 -0.1763 0.0533 -0.5820 4.8124 18.5577 0.0001 0.2057 0.2694 96 

286534(P) 0.0046 0.0106 0.1736 -0.2050 0.0605 -0.4561 4.8041 16.3467 0.0003 0.4439 0.3472 96 

895259(P) 0.0036 0.0097 0.2482 -0.2237 0.0671 -0.3533 6.0026 38.0590 0.0000 0.3484 0.4276 96 

14641H(P) -0.0020 0.0116 0.1623 -0.1523 0.0631 -0.4212 3.4252 3.5615 0.1685 -0.1950 0.3777 96 

14641K(P) -0.0022 0.0125 0.1600 -0.1515 0.0631 -0.4023 3.4100 3.2624 0.1957 -0.2086 0.3780 96 

14641L(P) -0.0020 0.0110 0.1620 -0.1533 0.0631 -0.4267 3.4170 3.6082 0.1646 -0.1933 0.3779 96 

513165(P) -0.0004 0.0048 0.1153 -0.1481 0.0470 -0.5704 4.5925 15.3505 0.0005 -0.0368 0.2095 96 

513721(P) -0.0035 0.0042 0.2313 -0.2568 0.0700 -0.6873 6.2849 50.7216 0.0000 -0.3366 0.4651 96 

15194W(P) 0.0027 0.0120 0.1668 -0.2167 0.0702 -0.5665 4.2571 11.4564 0.0033 0.2617 0.4688 96 

311245(P) 0.0030 0.0063 0.1455 -0.1805 0.0544 -0.3652 4.2444 8.3281 0.0155 0.2920 0.2813 96 

134272(P) -0.0023 0.0045 0.1284 -0.1552 0.0470 -0.5771 4.2056 11.1423 0.0038 -0.2202 0.2103 96 

519793(P) 0.0009 0.0018 0.0286 -0.0214 0.0096 0.0020 2.8233 0.1249 0.9395 0.0877 0.0088 96 

362943(P) 0.0012 0.0068 0.1902 -0.2048 0.0621 -0.4964 4.7235 15.8244 0.0004 0.1127 0.3659 96 

517699(P) 0.0014 0.0062 0.1733 -0.1919 0.0542 -0.3844 5.0849 19.7515 0.0001 0.1308 0.2786 96 

 

Appendix E: Grand Mean Computation – Conventional Fund 

 
 Mean 0.0019 

 Median 0.0025 

 Maximum 0.0055 

 Minimum -0.0035 

 Std. Dev. 0.0026 

 Skewness -0.5173 

 Kurtosis 2.1188   

 Jarque-Bera 2.3084 

 Probability 0.3153   

 Sum 0.0584 

 Sum Sq. Dev. 0.0002   

 Observations 30 

 

Appendix F: Descriptive Statistics (of logarithmic returns) – ESG Funds 

 
Code Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations 

92862T(P) -0.0017 0.0067 0.0999 -0.2515 0.0591 -1.1849 5.4849 47.1636 0.0000 -0.1673 0.3315 96 

27299L(P) 0.0025 0.0027 0.0291 -0.0352 0.0105 -0.6234 5.4125 29.4976 0.0000 0.2402 0.0104 96 

27299M(P) 0.0002 0.0023 0.0295 -0.0521 0.0146 -1.3478 5.4341 52.7652 0.0000 0.0166 0.0203 96 

92790E(P) -0.0021 0.0064 0.1180 -0.2275 0.0636 -0.8804 4.0949 17.1983 0.0002 -0.2048 0.3849 96 

8841K3(P) 0.0004 0.0054 0.0551 -0.0807 0.0253 -0.7840 4.0120 13.9322 0.0009 0.0360 0.0607 96 

671454(P) 0.0068 0.0210 0.1683 -0.3412 0.0774 -1.2213 6.7774 80.9398 0.0000 0.6551 0.5695 96 

882866(P) 0.0035 0.0124 0.1405 -0.2301 0.0515 -1.2129 6.6876 77.9313 0.0000 0.3347 0.2520 96 

309229(P) 0.0031 0.0041 0.0307 -0.0296 0.0117 -0.4291 3.3066 3.3214 0.1900 0.3010 0.0131 96 

308044(P) 0.0025 0.0029 0.0237 -0.0351 0.0090 -0.5925 5.2973 26.7286 0.0000 0.2419 0.0078 96 

13998H(P) 0.0011 0.0079 0.1424 -0.2316 0.0561 -0.9950 5.3264 37.4913 0.0000 0.1073 0.2987 96 

25676F(P) 0.0023 0.0021 0.0150 -0.0114 0.0049 0.1744 3.3917 1.1002 0.5769 0.2226 0.0023 96 

25594X(P) -0.0002 0.0018 0.0150 -0.0367 0.0100 -1.9577 6.9858 124.8717 0.0000 -0.0213 0.0095 96 

25595J(P) 0.0019 0.0017 0.0145 -0.0119 0.0049 0.1584 3.3719 0.9546 0.6205 0.1832 0.0023 96 

25676E(P) 0.0026 0.0024 0.0152 -0.0112 0.0049 0.1476 3.3741 0.9083 0.6350 0.2478 0.0023 96 

7774QX(P) 0.0006 0.0009 0.0277 -0.0343 0.0123 -0.4937 3.1759 4.0240 0.1337 0.0545 0.0144 96 

327325(P) -0.0005 0.0104 0.1078 -0.2024 0.0600 -0.7743 3.5151 10.6539 0.0049 -0.0524 0.3422 96 

895997(P) -0.0004 0.0090 0.1088 -0.2017 0.0599 -0.7605 3.4984 10.2480 0.0060 -0.0414 0.3408 96 

875730(P) -0.0004 0.0093 0.1083 -0.2024 0.0599 -0.7722 3.5204 10.6253 0.0049 -0.0406 0.3412 96 

877961(P) -0.0004 0.0088 0.1091 -0.2020 0.0600 -0.7658 3.5062 10.4073 0.0055 -0.0372 0.3415 96 

92723C(P) -0.0048 0.0010 0.1343 -0.2255 0.0669 -0.8419 4.1058 16.2317 0.0003 -0.4575 0.4257 96 

92697Q(P) -0.0018 0.0120 0.1386 -0.2599 0.0683 -0.9748 4.5126 24.3565 0.0000 -0.1683 0.4426 96 

92708V(P) -0.0013 0.0122 0.1388 -0.2597 0.0682 -0.9858 4.5359 24.9847 0.0000 -0.1280 0.4422 96 

674675(P) 0.0014 0.0095 0.1148 -0.2589 0.0582 -1.5499 7.1407 107.0188 0.0000 0.1323 0.3223 96 

894809(P) 0.0000 0.0010 0.0337 -0.0577 0.0116 -1.2411 9.7691 207.9306 0.0000 -0.0030 0.0127 96 

879575(P) 0.0005 0.0030 0.0348 -0.0740 0.0145 -1.5179 9.4266 202.0706 0.0000 0.0526 0.0200 96 

545394(P) 0.0005 0.0030 0.0348 -0.0740 0.0145 -1.5179 9.4266 202.0706 0.0000 0.0526 0.0200 96 

27639F(P) 0.0004 0.0061 0.1265 -0.1823 0.0394 -1.2134 7.8462 117.4996 0.0000 0.0427 0.1472 96 

8706QF(P) 0.0066 0.0188 0.2229 -0.2798 0.0856 -0.6518 4.3252 13.8222 0.0010 0.6313 0.6962 96 



Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 

  

238 
 

92638K(P) -0.0023 0.0048 0.1193 -0.2156 0.0635 -0.9346 4.2070 19.8038 0.0001 -0.2215 0.3831 96 

92690V(P) -0.0081 0.0008 0.1252 -0.3575 0.0764 -1.4768 6.9543 97.4422 0.0000 -0.7742 0.5549 96 

 

Appendix G: Grand Mean Computation – ESG Funds 

 
Mean 0.0004 

Median 0.0004 

Maximum 0.0068 

Minimum -0.0081 

Std. Dev. 0.0029 

Skewness -0.3388 

Kurtosis 4.6869 

Jarque-Bera 4.1309 

Probability 0.1268   

Sum 0.0129 

Sum Sq. Dev. 0.0002   

 Observations 30 

 

Appendix H: Descriptive Statistics (of logarithmic returns) – Islamic Funds 

 
Code Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations 

88894X(P) 0.0019 0.0033 0.0306 -0.0311 0.0097 -0.4726 4.6007 13.8222 0.0010 0.1866 0.0089 96 

88910N(P) 0.0061 0.0079 0.0683 -0.0822 0.0265 -0.6896 4.5690 17.4560 0.0002 0.5860 0.0668 96 

88910L(P) 0.0069 0.0109 0.1054 -0.1152 0.0379 -0.6413 4.3765 14.1591 0.0008 0.6614 0.1363 96 

88893N(P) 0.0000 0.0066 0.0864 -0.1425 0.0342 -1.0952 5.8111 50.7987 0.0000 0.0000 0.1113 96 

88902D(P) 0.0021 0.0068 0.0633 -0.1138 0.0317 -0.7694 4.0783 14.1211 0.0009 0.2024 0.0957 96 

88910Q(P) 0.0042 0.0125 0.1180 -0.2950 0.0531 -1.9671 12.2167 401.6977 0.0000 0.4034 0.2675 96 

88899U(P) 0.0057 0.0092 0.0949 -0.1266 0.0424 -0.8649 4.4361 20.2172 0.0000 0.5441 0.1704 96 

88885U(P) 0.0036 0.0082 0.1052 -0.1956 0.0501 -1.3306 6.3156 72.3026 0.0000 0.3431 0.2384 96 

88886U(P) 0.0032 0.0057 0.1213 -0.1851 0.0497 -0.5960 4.7531 17.9761 0.0001 0.3111 0.2349 96 

88899R(P) 0.0044 0.0089 0.1407 -0.2520 0.0549 -0.9412 6.9276 75.8780 0.0000 0.4226 0.2861 96 

88910T(P) 0.0030 0.0028 0.0217 -0.0332 0.0060 -2.0477 16.1563 759.4388 0.0000 0.2912 0.0035 96 

263758(P) 0.0027 0.0154 0.0879 -0.4594 0.0659 -3.8191 26.4864 2439.8124 0.0000 0.2549 0.4126 96 

8937TE(P) -0.0029 0.0027 0.1846 -0.3368 0.0742 -1.0235 6.3277 61.0575 0.0000 -0.2741 0.5233 96 

8937NE(P) 0.0002 0.0051 0.1555 -0.4791 0.0791 -2.5650 16.1263 794.4662 0.0000 0.0174 0.5943 96 

299364(P) 0.0032 0.0101 0.0968 -0.3345 0.0568 -2.4662 14.8153 655.7253 0.0000 0.3081 0.3061 96 

8937EV(P) 0.0020 0.0022 0.0049 0.0000 0.0017 0.1898 1.4933 9.6570 0.0080 0.1894 0.0003 96 

90599M(P) -0.0077 0.0174 0.1065 -0.7096 0.1102 -3.4190 19.9874 1341.3234 0.0000 -0.7350 1.1546 96 

88896P(P) 0.0005 0.0037 0.1496 -0.1984 0.0535 -0.1918 4.6271 11.1786 0.0037 0.0494 0.2721 96 

88911F(P) -0.0014 0.0051 0.0742 -0.1571 0.0386 -1.2280 5.7947 55.3686 0.0000 -0.1316 0.1416 96 

88908W(P) 0.0031 0.0030 0.0131 -0.0152 0.0043 -0.6920 5.8582 40.3397 0.0000 0.2930 0.0017 96 

889089(P) -0.0035 0.0101 0.1082 -0.8993 0.1013 -7.3197 65.1122 16288.9519 0.0000 -0.3386 0.9754 96 

8937MV(P) 0.0003 0.0015 0.1563 -0.2569 0.0612 -0.9477 6.2427 56.4325 0.0000 0.0253 0.3560 96 

90592Q(P) -0.0023 0.0177 0.2159 -0.4785 0.0092 -1.7857 8.2918 163.0319 0.0000 -0.2196 0.9344 96 

91484Z(P) 0.0034 0.0136 0.1139 -0.2396 0.0643 -1.3721 5.5124 55.3702 0.0000 0.3270 0.3924 96 

88891V(P) -0.0021 0.0000 0.1331 -0.1475 0.0431 -0.2175 4.4480 9.1438 0.0103 -0.1990 0.1762 96 

88894L(P) 0.0013 0.0048 0.0231 -0.0570 0.0141 -2.3679 8.5653 213.6037 0.0000 0.1241 0.0189 96 

88901X(P) 0.0018 0.0084 0.0833 -0.1060 0.0396 -0.6365 3.3337 6.9274 0.0313 0.1751 0.1492 96 

88894V(P) 0.0049 0.0054 0.1147 -0.1095 0.0411 -0.2055 3.5587 1.9244 0.3820 0.4750 0.1601 96 

88893L(P) 0.0021 0.0050 0.0895 -0.1014 0.0175 -1.3684 20.9532 1319.2295 0.0000 0.2038 0.0291 96 

88893V(P) -0.0003 0.0049 0.1170 -0.1452 0.0453 -0.5456 3.9979 8.7452 0.0126 -0.0310 0.1947 96 

 

Appendix I: Grand Mean Computation – Islamic Funds 

 
Mean 0.0016 

Median 0.0020 

Maximum 0.0069 

Minimum -0.0077 

Std. Dev. 0.0032 

Skewness -0.7909 

Kurtosis 3.7709   

Jarque-Bera 3.8704 

Probability 0.1444   

Sum 0.0465 

Sum Sq. Dev. 0.0003   

 Observations 30 

 

Appendix J. Portfolio Performance Measures – Conventional, ESG and Islamic Portfolios 

 
CONVENTIONAL FUNDS CODE SHARPE TREYNOR JENSEN 

AB EQUITY INCOME FUND A 360530(P) 0.0490 0.0091 0.0024 

AB SMALL CAP GROWTH PORTFOLIO A 517893(P) 0.0437 0.0211 0.0032 

AMERICAN FUNDS GLOBAL GROWTH FUND 2 8654L3(P) 0.0196 0.0050 0.0012 

BROWN CAP.MAN.SML.CO. INV.SHS. 154127(P) 0.0516 0.0202 0.0034 

CLEARBRIDGE LARGE CAP GROWTH FD.CL.A 878407(P) -0.0154 -0.0042 -0.0008 

COL.SELIGMAN GLB.TECH. FD.CL.C 286534(P) 0.0409 0.0119 0.0026 

DODGE & COX BAL.FD. 513165(P) -0.0539 -0.0084 -0.0024 

HARTFORD SMALL CAP GROWTH FUND A 15194W(P) 0.0082 0.0038 0.0006 

VANGUARD HORIZON FD. VANGD.CAP.OPPOR.FD. 362943(P) -0.0157 -0.0044 -0.0009 

VANGUARD PRIMECAP FD. 517699(P) -0.0145 -0.0035 -0.0007 

 
ESG FUNDS CODE SHARPE TREYNOR JENSEN 

DAIWA DC SRI FUND 92790E(P) -0.0329 -0.0030 0.0000 

DWS ESG EURO BONDS (LONG) LC 309229(P) 0.2489 -0.0061 0.0027 

DWS ESG EURO BONDS (MEDIUM) LC 308044(P) 0.2546 0.0010 0.0032 

DWS INVEST ESG EURO BONDS (SHORT) FC 25676F(P) 0.4842 0.0033 0.0026 

FIERA ACTIVE FIXED INCOME ETHICAL ESG FUND 7774QX(P) -0.0695 -0.0019 -0.0016 

NOMURA GLOBAL SRI 100 92697Q(P) -0.0251 -0.0030 0.0000 

NOMURA GLOBAL SRI INDEX FUND DC 92708V(P) -0.0189 -0.0022 0.0004 

PAX ESG BETA QUALITY FUND INDIVIDUAL INVESTOR 674675(P) -0.0132 -0.0015 -0.0005 



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239 
 

PRISMA ESG WORLD CONVERTIBLE BONDS 27639F(P) 0.0191 0.0021 -0.0001 

SBI MAGNUM EQUITY ESG FUND-DIVIDEND 8706QF(P) 0.0073 0.0012 -0.0015 

 
ISLAMIC FUNDS CODE SHARPE TREYNOR JENSEN 

AM BON ISLAM 88894X(P) -0.1251 -0.0015 -0.0038 

CIMB ISLAMIC DALI EQUITY 88899U(P) 0.0084 0.0006 -0.0018 

CIMB ISLAMIC DALI EQUITY GROWTH 88885U(P) 0.0594 0.0032 -0.0001 

CIMB ISLAMIC SUKUK 88910T(P) -0.0196 -0.0001 -0.0033 

DOW JONES ISLAMIC FD. CL.K 263758(P) 0.0077 0.0009 0.0007 

HSBC ISLAMIC GLOBAL EQUITY INDEX AD USD 299364(P) 0.0527 0.0027 0.0034 

HSBC US DOLLAR MURABAHA FUND 8937EV(P) -0.4040 0.0002 -0.0188 

JS ISLAMIC FUND 90599M(P) -0.1631 -0.0517 -0.0180 

MEEZAN ISLAMIC FUND 90592Q(P) -0.1272 -0.0279 -0.0127 

RHB ISLAMIC BOND 88893L(P) -0.0588 0.1256 -0.0010 

 

 
 

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