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. REFERENCES Abdelsalam, O., Fethi, M. D., Matallin, J. C., & Tortosa-Ausina, E. (2014). On the comparative performance of socially responsible and Islamic mutual funds. Journal of Economic Behavior & Organization, 103(S), S108-S128. https://doi.org/10.1016/j.jebo.2013.06.011 Chang, C. E., & Doug Witte, H. (2010). Performance Evaluation of U.S. Socially Responsible Mutual Funds: Revisiting Doing Good and Doing Well. American Journal of Business, 25(1), 9-24. https://doi.org/10.1108/19355181201000001 Dah, M., Hoque, M., & Wang, S. (2015). Constrained investments and opportunity cost – evidence from Islamic funds. Managerial Finance, 41(4), 348-367. https://doi.org/10.1108/MF-06-2014-0179 El-Masry, A. A., de Mingo-Lopez, D. V., Matallin-Saez, J. C., & Tortosa-Ausina, E. (2016). Environmental conditions, fund characteristics, and Islamic orientation: An analysis of mutual fund performance for the MENA region. Journal of Economic Behavior & Organization, 132(S), 174-197. https://doi.org/10.1016/j.jebo.2016.10.015 Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56. https://doi.org/10.1016/0304-405X(93)90023-5 Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210-233. https://doi.org/10.1080/20430795.2015.1118917 Hayat, R., & Kraeussl, R. (2011). Risk and return characteristics of Islamic equity funds. Emerging Markets Review, 12(2), 189-203. https://doi.org/10.1016/j.ememar.2011.02.002 In, F., Kim, M., Park, R. J., Kim, S., & Kim, T. S. (2014). Competition of socially responsible and conventional mutual funds and its impact on fund performance. Journal of Banking & Finance, 44, 160-176. https://doi.org/10.1016/j.jbankfin.2014.03.030 Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255-259. https://doi.org/10.1016/0165-1765(80)90024-5 Jensen, M. C. (1968). THE PERFORMANCE OF MUTUAL FUNDS IN THE PERIOD 1945-1964. The Journal of Finance, 23(2), 389 – 416. https://doi.org/10.1111/j.1540-6261.1968.tb00815.x Mansor, F., & Bhatti, I. (2011). Risk and return analysis on performance of the Islamic mutual funds: Evidence from Malaysia. Global Economy and Finance Journal, 4(1), 19-31. Retrieved from https://www.isfin.net/sites/isfin.com/files/risk_and_return_analysis_on_performance_of_the_islamic_mutual_fu nds-_evidence_from_malaysia.pdf Orsagh, M., Allen, J., Sloggett, J., Bartholdy, S., Georgieva, A., Dehman, N. A., & Sofronova, Y. (2019). ESG integration in Europe, the Middle East, and Africa: Markets, practices and data. Principles for Responsible Investment. Retrieved from https://www.unpri.org/download?ac=6036 Pew Research Centre. (2011). The Future of The Global Muslim Population. http://www.pewforum.org/The-Future-of-the- Global-Muslim-Population.aspx Sauer, D. A. (1997). The impact of social-responsibility screens on investment performance: Evidence from the Domini 400 social index and the Domini Equity Mutual Fund. Review of Financial Economics, 6(2), 137-149. https://doi.org/10.1016/S1058-3300(97)90002-1 Sharpe, W. F. (1966). Mutual fund performance. The Journal of Business, 39(1), 119-138. https://dx.doi.org/10.1086/294846 Smith, P. (2019). The client of the future cares passionately about ESG, and it needs to be incorporated into the investment process #cfapresident [Video]. LinkedIn Retrieved from https://www.linkedin.com/feed/update/urn:li:activity:6516283481318842368 Treynor, J. (1965). How to rate management of investment funds. Harvard Business Review, 43(1), 63-75. Tripathi, V., & Bhandari, V. (2016). Performance of socially responsible stocks portfolios – The impact of Global Financial Crisis. Journal of Economics and Business Research, XXII(1), 42-68. Retrieved from https://ssrn.com/abstract=2843113 https://doi.org/10.1016/j.jebo.2013.06.011 https://doi.org/10.1108/19355181201000001 https://doi.org/10.1108/MF-06-2014-0179 https://doi.org/10.1016/j.jebo.2016.10.015 https://doi.org/10.1016/0304-405X(93)90023-5 https://doi.org/10.1080/20430795.2015.1118917 https://doi.org/10.1016/j.ememar.2011.02.002 https://doi.org/10.1016/j.jbankfin.2014.03.030 https://doi.org/10.1016/0165-1765(80)90024-5 https://doi.org/10.1111/j.1540-6261.1968.tb00815.x https://www.isfin.net/sites/isfin.com/files/risk_and_return_analysis_on_performance_of_the_islamic_mutual_funds-_evidence_from_malaysia.pdf https://www.isfin.net/sites/isfin.com/files/risk_and_return_analysis_on_performance_of_the_islamic_mutual_funds-_evidence_from_malaysia.pdf https://www.unpri.org/download?ac=6036 http://www.pewforum.org/The-Future-of-the-Global-Muslim-Population.aspx http://www.pewforum.org/The-Future-of-the-Global-Muslim-Population.aspx https://doi.org/10.1016/S1058-3300(97)90002-1 https://dx.doi.org/10.1086/294846 https://www.linkedin.com/feed/update/urn:li:activity:6516283481318842368 https://ssrn.com/abstract=2843113 Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 236 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 Abdullah & Rao , Indian Journal of Finance and Banking 9(1) (2022), 230-239 239 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 Publisher’s Note: CRIBFB stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. © 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/). Indian Journal of Finance and Banking (P-ISSN 2574-6081 E-ISSN 2574-609X) by CRIBFB is licensed under a Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/) http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/