J Bus Ethics (2014) 124:551–569 DOI 10.1007/s10551-013-1893-x
Environmental Mutual Funds: Financial Performance and Managerial Abilities Fernando Mun˜oz • Maria Vargas • Isabel Marco
Received: 10 October 2012 / Accepted: 5 September 2013 / Published online: 19 September 2013 Springer Science+Business Media Dordrecht 2013
Abstract This article analyzes the financial performance and managerial abilities of a sample of US and European socially responsible (SR) mutual funds. The period analyzed commences from January 1994 and concludes in January 2013 and yields 18 US and 89 European green funds. The results obtained for green fund managers are compared with those achieved for conventional and other forms of SR mutual fund managers. We control for the mutual fund investment objective (distinguishing between domestic and global portfolios) and for the effect of crisis market periods. For US SR funds, partitioning the data into crisis and normal periods reveals that SR funds obtain statistically insignificant performance in crisis periods but underperform relative to the market in normal periods. Furthermore, the findings indicate that green funds do not perform worse than other forms of SR mutual funds. For European SR funds partitioning the data into crisis and normal periods reveals that SR funds obtain statistically insignificant performance irrespective of market conditions. Similar to the US findings, green Europe SR funds do not perform worse than other forms of SR mutual funds. Managerial abilities are not evident in the findings though unsuccessful timing of the market is revealed for both Europe and US global green funds. When analyzing managerial abilities in crisis and non-crisis market periods, US green fund managers achieve better results in crisis market periods and the opposite occurs for green fund managers in European market. F. Mun˜oz (&) Centro Universitario de la Defensa de Zaragoza, Academia General Militar, Ctra. de Huesca s/n, 50090 Saragossa, Spain e-mail:
[email protected] M. Vargas I. Marco Departamento de Contabilidad y Finanzas, Universidad de Zaragoza, C/Gran Vı´a 2, 50005 Saragossa, Spain
Keywords Environmental mutual funds Financial performance Green investment Market-timing Stock-picking Style-timing JEL Classification
G11 G23 Q56
Abbreviations ECB European Central Bank ESG Environmental, Social, and Governance EU European Union Eurosif The European Sustainable Investment Forum GW Gregory and Whittaker (2007) TM Treynor and Mazuy (1966) TNAs Total net assets SR Socially responsible SRI Socially responsible investment US United States US SIF United States Social Investment Forum
Introduction Issues such as global warming, the destruction of ecosystems, the depletion of certain natural resources, and disease generated by pollution—among others—have raised the consciousness of many investors around the world. More and more investors are concerned about the environmental impact of their investments, and they seek to obtain a good financial performance while avoiding the destruction of the environment. Green investment could be considered a subset of Socially Responsible Investment. According to the European Sustainable Investment Forum (Eurosif), Socially Responsible Investment [also called Sustainable and Responsible Investing] (SRI) is ‘‘a generic term covering
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any type of investment process that combines investors’ financial objectives with their concerns about Environmental, Social and Governance (ESG) issues’’ [2010 SRI study]. In this vein, we may consider that green investment consists of taking into account in the investing process not only financial criteria but also environmental issues. According to Kelly (2010) ‘‘Green investing is mainly focused in companies and technologies that are deemed to be good for the environment’’. One financial product that investors can use to meet their twofold investment aim (financial and environmental) is the environmental mutual fund (also known as green funds). The managers of such portfolios consider both financial and environmental criteria when making their investment decisions. The socially responsible (SR) mutual fund industry has experienced significant growth in recent decades, especially in the US. According to the United States Social Investment Forum (US SIF), in 2012 there were 333 SR mutual funds in the US market, managing assets worth $640.5 billion. (For comparison, in 1995 the number of SR mutual funds was 55 and the assets managed were around $12 billion).1 According to Morningstar the number of SR mutual funds with an environmental focus in the US was 7 in 1995. These funds managed $211.5 million. In 2012, there were 18 green funds managing $1.8 billion. In view of these numbers, it is understandable that the financial literature has paid great attention to this kind of investment product. Specifically, the majority of studies of SR mutual funds have analyzed the financial performance of these portfolios, in comparison with that obtained by their conventional peers. To date, the empirical evidence is mixed, but in general terms the conclusion is that there are no significant differences between conventional and SR mutual funds.2 However, many of these studies suffer from an important bias: they consider SR mutual funds as a homogenous group, but SR mutual funds can follow a variety of strategies that could lead to them showing different financial performance results. Moreover, when analyzing mutual fund managers’ financial performance, it is very important to control the results for managerial abilities. Managerial abilities have been broadly studied for conventional funds, but have usually been overlooked in the articles focused on SR mutual funds’ financial performance. Managerial abilities, that is, stock-picking, market-timing, and style-timing imply carrying out an active management strategy, which requires the implementation of a 1
http://www.ussif.org/. Renneboog et al. (2008a) and Chegut et al. (2011) carry out a full review of the relevant literature.
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very detailed monitoring of the stocks that make up the investor universe of a specific mutual fund, in addition to the use of a number of resources. Thus, in order to carry out a valid analysis, it is necessary to concentrate on specific market segments. SR mutual fund managers could have an advantage over their conventional counterparts in implementing an active management strategy. That is, they focus on subsets of companies based on SR criteria. Focusing on a subset of the market could lead to a greater knowledge of the stocks that compose the investor universe of the fund, and this, in turn, may facilitate the implementation of an active management strategy. Following this notion, we carry out a comparative analysis of the managerial abilities of both conventional and SR mutual fund managers, in order to determine whether any significant differences exist. In addition, crisis market periods could influence the difference between the financial performance of conventional and SR mutual fund managers. Varma and Nofsinger (2012) show how, in non-crisis market periods, conventional mutual fund managers outperform SR managers. However, in times of crisis, SR mutual fund managers perform better than conventional managers. Taking this empirical evidence into account, it is necessary to control our analysis for times of crisis. In this article, we examine the financial performance of a sample of US and European green mutual funds from a comparative point of view, with a matched-pair sample of conventional mutual funds. In addition, we compare the results for green funds with those attained for other kinds of SR mutual funds [religious and Environmental, social, and governance (ESG) mutual funds]. For this purpose, we use multifactor performance models as in some of the most recent and important works on SR mutual fund financial performance [see Climent and Soriano (2011) or Renneboog et al. (2011), among others]. We analyze the managerial abilities of green funds, that is, we study the stock-picking, market-timing, and styletiming abilities of green mutual fund managers. In addition, we control our analysis for crisis market periods. Specifically, we establish controls for the technology bubble, and for the recent global financial crisis. Finally, for European funds, we also control for the current sovereign risk crisis. We contribute to the literature in several ways. First, we extend the prior empirical evidence of green mutual fund financial performance by studying a broader sample of green funds (green funds from both the US and European markets) and a more recent period (January 1994–2013). In addition, we provide new empirical evidence on issues hitherto neglected green funds. The rest of the paper is structured as follows: ‘‘Literature Review’’ section provides a literature review; ‘‘Data’’ section describes the data used in the analysis; ‘‘Methodology’’
Environmental Mutual Funds
section explains the methodology; ‘‘Empirical Results’’ section presents our empirical findings, and we close with the main conclusions of our study.
Literature Review Most papers studying the financial performance of SR mutual funds consider them as a homogenous group. However, the investment strategies implemented by various SR funds are very different. That is, a religious mutual fund that avoids investing in companies from industries that are considered sinful or unethical (alcohol or gambling, for example) is different from a green fund that seeks to invest in companies with good records on environmental issues. In this framework, recent empirical articles of SR mutual fund financial performance have established controls for a range of ethical strategies. Thus, we can find papers studying the specific case of religious mutual funds (Abdullah et al. 2007; Hoepner et al. 2011; Ferruz et al. 2012, among others), while other works control for the effect of different types of screening (positive and negative), [Renneboog et al. (2008b)]. Finally, there are studies controlling for the intensity of the screens (Barnett and Salomon 2006; Lee et al. 2010). Green investment has been widely studied in the financial literature, usually addressed from a firm perspective; thus, there is a significant number of works studying the linkage between corporate environmental behavior and corporate financial performance [see among others, Lakonski (2000), Heinkel et al. (2001), and Lakonski (2006)]. Although at first glance it may appear that companies applying measures to improve their environmental performance could suffer from an additional cost that would reduce their financial results, there is also reason to think that exhibiting good environmental behavior could lead to better financial performance. In this vein, Ambec and Lanoie (2008) outline seven arguments put forward in the financial literature on how companies with good environmental records can increase their income or reduce their costs. Specifically, their revenues could be increased through three sources: better access to certain markets; differentiating products; and selling pollution-control technology. At the same time, a better environmental performance is supposed to produce cost reductions through four ways: risk management and relations with external stakeholders; costs of material, energy, and services; cost of capital; and cost of labor. Ambec and Lanoie (2008) set out an economic reasoning for each of these seven arguments and provide empirical evidence for each.
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Green mutual funds usually invest in companies with good records on environmental issues; however, they can follow different strategies in order to incorporate the environmental dimension in the investment process (see Appendix 1). Given that this kind of company could have opportunities to generate a superior financial performance, an investment in this type of mutual fund may lead investors to obtain good financial results without harming the environment. Considering this reasoning, it is interesting to analyze the financial performance of green funds from a comparative point of view, with their conventional counterparts and other kinds of SR mutual fund. Although SR mutual fund financial performance is a well-analyzed topic, and recent papers have studied some specific cases of SR mutual funds, such as religious mutual funds and SR mutual funds implementing positive or negative screens, green mutual funds have been somewhat neglected. To the best of our knowledge, there are only three articles that have addressed this issue to date. White (1995) is the first to study the specific case of green funds, analyzing the financial performance of green funds from the US and German markets. The results obtained differ according to the market considered; US green funds underperform the overall US market, while, in Germany, green funds do not perform differently from the German stock market as a whole. More recently, Climent and Soriano (2011) examine the financial performance of a sample of US green mutual funds during the 1987–2009 period, comparing the results with a sample of conventional mutual funds and find that, for the full period analyzed (1987–2009), green funds underperform their conventional peers. However, when analyzing the 2001–2009 sub-period, both types of fund do not perform differently. Chang et al. (2012) show results similar to those obtained by Climent and Soriano (2011).3 Despite that the above-mentioned studies provide interesting empirical evidence about the financial performance of green funds, they all overlook a very important issue; i.e., they do not consider the ability of the portfolio managers to obtain an abnormal performance, which could be biasing the environmental screening effect. Traditionally, it has been supposed that the results of a mutual fund manager depend on stock-picking and markettiming skills. Successful stock-picking lies in selecting stocks that outperform other securities with a similar level of non-diversifiable risk. Successful market-timing lies in 3 Derwall et al. (2005) analyze the financial performance of two portfolios; the first includes companies occupying high positions in environmental rankings, and the second contains low-ranked companies. Although it is an interesting analysis of the influence of environmental issues on financial performance, it does not analyze green funds.
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changing the exposure to the market at the right moment; i.e., in order to improve performance, a mutual fund manager should increase portfolio exposure to the market when it rises, and reduce it when the market falls. In addition, mutual fund managers attempt to predict the movement of certain market segments, focusing on one or several specific kinds of stocks (small cap stocks, large cap stocks, value stocks, or growth stocks, for example). This strategy is known as style-timing. In other words, the mutual fund manager should predict which investment style will provide the best performance and increase the portfolio exposure to this specific style. Stock-picking and market-timing skills have been widely analyzed in the financial literature, especially in the case of conventional mutual funds. In this framework, the empirical evidence obtained is mixed, depending on the market or period analyzed. Wermes (2000) finds that US equity mutual funds in the period 1975–1994 pick stocks well enough to cover their costs. However, Romacho and Cortez (2006) find that Portuguese mutual fund managers do not exhibit good selectivity and timing abilities. Rompotis (2007) finds a lack of stock-picking skills for Greek mutual fund managers, and also that Greek mutual fund managers time the market incorrectly. Focusing on market-timing studies, certain papers provide empirical evidence of a lack of ability to time the market; this is the case of Knigge et al. (2004), Christensen (2005), and Woodward and Brooks (2006), among others. Other articles find that mutual fund managers are able to correctly time the market; for example, Jiang et al. (2007), Glassman and Riddick (2006), and Chen (2007). Style-timing abilities have also been analyzed in the literature, although to a lesser extent than market-timing abilities. Examples of works addressing this issue for conventional funds are Daniel et al. (1997), Chan et al. (2002), and Swinkels and Tjong-a-Tjoe (2007), among others. Studies analyzing the managerial abilities of SR mutual fund managers are few and far between. In fact, the bulk of works that study the financial performance of SR mutual funds do not tackle this aspect of the field. Some of the papers that study market-timing abilities for SR mutual funds are those by Schro¨eder (2004) and Kreandert et al. (2005). Schro¨eder (2004) finds a perverse timing ability for SR funds from Germany and Switzerland, and a null ability for mutual funds from the US market. Kreandert et al. (2005) conclude that SR mutual fund managers from several European markets are unable to successfully time the market. Style-timing abilities are studied by Gregory and Whittaker (2007) and Ferruz et al. (2012). The former find that the managers of domestic SR funds of the UK show poor market- and momentum-timing skills, as well as a
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lack of ability to time the size style and a positive ability to time the book-to-market style. Ferruz et al. (2012) study the specific case of religious mutual fund managers in the US, concluding that they do not show ability to time either the market, or the size, book-to-market, and momentum styles. In addition, these managers exhibit poor stockpicking ability.
Data The data used in this study has been provided by Morningstar. This database identifies up to 3,591 ‘‘Socially Conscious Funds’’, defined as ‘‘Any fund that invests according to non-economic guidelines. Such funds may make investments based on such issues as environmental responsibility, human rights, or religious views. A socially conscious fund may take a pro-active stance by selectively investing in, for example, environmentally-friendly companies, or firms with good employee relations. This group also includes funds that avoid investing in companies involved in promoting alcohol, tobacco, or gambling, or in the defense industry’’.4 Morningstar classifies the Socially Conscious funds in four categories, according to their ‘‘Ethical issue strategy focus’’: environmental, ESG focus, religious, and Sharia. In order to create our sample of green funds we select all the funds designated by Morningstar as Socially Conscious and with an environmental focus. We focus on mutual funds that invest mainly in equity. We split the sample into two groups; mutual funds domiciled in the US market, and mutual funds domiciled in European market. We consider the different share classes of a mutual fund as a single mutual fund. In order to do this, we implement the procedure of Renneboog et al. (2011), by aggregating the different share classes for a given fund into one observation, using a two-step method: first, we aggregate the different share classes for a given fund, and second, for fund returns, we take the weighted average of this variable using the 1-month lagged total net assets (TNAs) of the individual share classes as the weights. Following this, we obtain 18 green funds domiciled in the US market (reported in Appendix 2) and 89 green funds domiciled in European countries (reported in Appendix 3).5 4
This figure is obtained by considering the different share classes as different mutual funds. 5 For each market, the green funds have been classified according to the investment aim. We split each sample into two groups, funds with a domestic investment aim, and funds with a global investment aim. In the US market, there are six funds with a domestic investment aim and 12 funds with a global investment aim. In the European market, there are 20 funds with a domestic investment aim and 69 funds with a global investment aim.
Environmental Mutual Funds
For these funds, the data consist of the monthly returns (net of fees) and the monthly TNAs. The sample period runs from January 1994 to January 2013. From this universe, we build four portfolios of green funds. The first (‘‘green US’’) is formed by the green funds from the US market designated by Morningstar as US Equity (six funds in total). The second portfolio is formed by the green funds from the US market whose global investment category is not limited to the US market (12 funds in total). The third portfolio (‘‘green Europe’’) is composed of those green European funds that invest mainly in European stocks according to Morningstar (20 funds in total). The fourth portfolio (‘‘green Europe global’’) is formed by those green funds from European market that invest in a global area (69 funds in total). In order to compare the results obtained by the green portfolios with other kinds of mutual funds, we construct— for each of these portfolios—others formed by conventional mutual funds and other kinds of Socially Conscious mutual funds. With regard to conventional mutual fund portfolios, we build a matched sample considering the investment objective, the inception date, and the TNAs under management. The procedure followed is similar to those used by Varma and Nofsinger (2012) and Climent and Soriano (2011). First, for each green fund, we select the conventional funds with the same investment objective according to Morningstar. Second, we restrict this sample by choosing only those conventional funds with an inception date within a year of the green fund’s inception date. Finally, for each green fund, we select the three conventional funds most similar in size to it.6 By this procedure, we obtain four matched-conventional portfolios, one for each of the green portfolios described above. Specifically, we obtain 18 matched conventional funds for the first portfolio (‘‘conventional green US’’), 36 matched conventional funds for the second portfolio (‘‘conventional green US global’’), 60 matched conventional funds for the third portfolio (‘‘conventional green Europe’’), and 207 matched conventional funds for the fourth portfolio (‘‘conventional green Europe global’’). In order to compare the results obtained for green funds with those obtained for other kinds of socially Conscious mutual funds, we construct portfolios of funds that Morningstar classifies as SR, but with other Ethical issue strategy focus. Thus, in the case of the ‘‘green US’’ portfolio, we construct two SR portfolios. The first consists of religious mutual funds (‘‘Religious US’’). Morningstar
6
Although this is the procedure followed for most of the green funds, in some cases we had to relax the inception date restriction in order to find conventional peers.
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identifies up to 34 mutual funds that invest mainly in American stocks and take into account religious issues.7 In addition, we build a portfolio composed of funds designated by Morningstar as ESG funds (‘‘ESG US’’), that is, mutual funds that consider not only financial criteria when picking stocks but also ESG issues (a combination of non-financial criteria). Morningstar identifies 52 ESG US mutual funds that invest mainly in American stocks. For the ‘‘green US global’’ portfolio, we construct one SR portfolio consisting of 13 ESG US mutual funds that invest in the global market (‘‘ESG US global’’).8 For the ‘‘green Europe’’ portfolio we create one SR portfolio composed of 112 ESG mutual funds that invest mainly in European markets (‘‘ESG Europe’’), and for the ‘‘green Europe global’’ portfolio we build a portfolio consisting of 99 ESG mutual funds (‘‘ESG Europe global’’) that invest in the global area.9 In Table 1, we report the number of funds that comprises each of the portfolios from the US market. We also report the mean and median age (years since fund inception), the average and median manager tenure, the mean monthly return, the mean and median TNAs, and the mean and median management fee charged by these funds. We can observe that, in general terms, domestic portfolios are older than global portfolios. For example, the green US portfolio contains funds that present a median age of about 15 years, whereas the green US global portfolio is younger, with a median age of about 6 years. The median manager tenure moves in a range from 3.75 years for the ESG US global portfolio to 6.25 years for the religious US portfolio. The median size is greater for domestic portfolios than for global portfolios. Thus, the green US portfolio presents a median TNA of $101.38 million and the green US global portfolio has a median TNA of $47.8 million. The mean monthly return is higher for the domestic portfolios than for the global portfolios (except for the conventional green US global portfolio), and the mean management fee ranges from 0.63 % for the green US portfolio to 0.95 % for the green US global portfolio. For the European portfolios, the descriptive statistics are reported in Table 2. 7 According to Kurtz (2008), ‘‘Religious belief was the first rationale for SRI, and remains an important force today, especially in the United States’’. 8 In the case of global equity funds, Morningstar identifies only five US religious mutual funds that invest in the global market. Besides, except for one of these funds whose inception date is 2001, the rest of the funds did not appear until 2008. This difference in the life cycle makes the results obtained for the religious ‘‘global’’ funds not comparable with those obtained for the green ‘‘global’’ funds. 9 For European market, Morningstar does not identify any socially conscious mutual fund that establishes religious screens.
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556 Table 1 Descriptive statistics for US portfolios Description
Green US
Matched sample Conventional green US
Green US global Religious US
ESG US
Matched sample Conventional green US global
ESG US global
Number of funds
6
18
34
52
12
36
13
Mean age
12.39
12.46
13.06
12.08
10.76
9.27
9.84
Median age Mean manager tenure
14.99 6.25
15.14 5.49
11.93 6.72
8.46 5.27
5.75 6.94
6.38 4.61
6.19 3.73
Median manager tenure
4.29
5.17
6.25
4.68
4.92
3.99
3.75
Mean monthly return
0.52 %
0.52 %
0.44 %
0.48 %
0.25 %
0.60 %
0.38 %
Mean TNA (#million)
$121.01
$119.29
$312.97
$243.55
$64.42
$53.29
$131.94
Median TNA (#million)
$101.38
$102.08
$107.42
$94.53
$47.8
$36.58
$72.87
Mean management fee
0.63 %
0.72 %
0.71 %
0.71 %
0.95 %
0.74 %
0.75 %
Median management fee
0.66 %
0.71 %
0.77 %
0.75 %
0.98 %
0.75 %
0.80 %
Reports the number of funds that comprises each of the US analyzed portfolios, as well as the mean and median age (years since the fund’s inception), the average and median manager tenure (in years), the mean monthly return, the mean and median TNAs (expressed in millions of dollars) and the mean and median management fee charged by these mutual funds ESG environmental, social and governance
Table 2 Descriptive statistics for European portfolios Description
Green Europe
Matched sample
Green Europe global
Matched sample
Conventional green Europe
ESG Europe
Conventional green Europe global
ESG Europe global
Number of funds
20
60
Mean age
7.14
7.09
112
69
207
99
10.12
6.95
6.46
Median age Mean manager tenure
5.66 4.44
5.68 4.86
7.76
10.12 5.29
5.84 5.67
5.42 5.42
5.68 5.45
Median manager tenure
4.25
4.86
4.96
5.25
5.17
4.92
Mean monthly return
0.34 %
0.29 %
0.21 %
0.11 %
0.31 %
0.07 %
Mean TNA (#million)
€37.20
€33.28
€97.98
€113.00
€39
€53.03
Median TNA (#million)
€16.43
€13.38
€26.47
€30.04
€18.43
€28.02
Mean management fee
1.52 %
1.56 %
1.17 %
1.46 %
1.53 %
1.22 %
Median management fee
1.50 %
1.50 %
1.25 %
1.50 %
1.50 %
1.20 %
Reports the number of funds that comprises each of the European analyzed portfolios, as well as the mean and median age (years since the fund’s inception), the average and median manager tenure (in years), the mean monthly return, the mean and median TNAs (expressed in millions of euros) and the mean and median management fee charged by these mutual funds ESG environmental, social and governance
The median age is around 5.5 years, except for the ESG Europe portfolio which is 10.12 years. The median manager tenure ranges from 4.25 to 5.25 years. The median size is greater for the global portfolios than for the domestic ones. Thus, for the green Europe portfolio, the median TNA is €16.43 million, whereas for the green Europe global portfolio this figure reaches €30.04 million. The mean monthly return is higher for the domestic portfolios than for the global portfolios (except for the conventional green Europe global), and the mean management
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fee ranges from 1.17 % for the ESG Europe portfolio to 1.56 % for the conventional green Europe portfolio. If we compare the main characteristics of the US and European portfolios, we can conclude that, in general terms, the US portfolios are older, lower fees, and larger than the European portfolios. These figures indicate that the US market is more mature than the European one. We also build ‘‘difference’’ portfolios in order to evaluate the differences (and significance of these differences) in risk and return between the green mutual fund portfolios and the
Environmental Mutual Funds
rest of portfolios. For this purpose, we follow the same procedure as some of the most recent studies on SR mutual fund financial performance [see Climent and Soriano (2011) and Varma and Nofsinger (2012), among others]. Specifically, we construct three difference portfolios for the category ‘‘green US’’ by subtracting ‘‘conventional green US’’, ‘‘Religious US’’ and ‘‘ESG US’’ returns from ‘‘green US’’ returns. We construct two difference portfolios for the category ‘‘green US global’’ by subtracting ‘‘conventional green US global’’ and ‘‘ESG US global’’ returns from ‘‘green US global’’ returns. We form two difference portfolios for the category ‘‘green Europe’’ by subtracting ‘‘conventional Europe green’’ and ‘‘ESG Europe’’ returns from ‘‘green Europe’’ returns, and we build two difference portfolios for the category ‘‘green Europe global’’ by subtracting ‘‘conventional green Europe global’’ and ‘‘ESG Europe global’’ returns from ‘‘green Europe global’’ returns. We apply multifactor models in order to analyze the financial performance and the managerial abilities of our sample of green funds and their SR and conventional peers. We use both an overall market benchmark and benchmarks representing the style factors considered by Carhart (1997): size, book-to-market, and momentum. The multifactor performance models have been used in some of the most recent and important studies of SR mutual fund financial performance [see Renneboog et al. (2008b) and Climent and Soriano (2011), among others].10 All the data on benchmarks and style factors have been taken from the Kenneth French website, which provides monthly data for the Fama–French factors, for the US market, for the European markets, for global markets, and for other countries and areas. We use the relevant benchmark for each of our portfolios.11 In addition, we control for crisis market periods. This control is important if we consider the empirical evidence provided in the literature. Varma and Nofsinger (2012) analyze the financial performance of SR mutual funds by implementing a comparative study with conventional mutual funds. These authors consider that the SR attributes of companies make them less risky in market crisis periods. They control their results for crisis and non-crisis market periods and conclude that, although in non-crisis periods conventional funds outperform SR ones, in crisis periods the reverse occurs. In this vein, we study whether the crisis/ non-crisis market periods have an impact on the issues of our study. In order to carry out this analysis, we run the four-factor Carhart model separately for the crisis and noncrisis periods in our sample. 10 Climent and Soriano (2011) conclude that multifactor models are superior in explaining mutual fund returns. 11 Data available on Kenneth French website: http://mba.tuck. dartmouth.edu/pages/faculty/ken.french/data_library.html.
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In the January 1994–2013 period, two important financial crises occurred; the technology bubble of early 2000 and the global financial crisis of 2007–2009. Varma and Nofsinger (2012) identify crisis periods for the stock market based on the peaks and troughs in the Standard and Poor’s 500 index and determine as crisis market periods the following: March 2000–October 2002 (corresponding to the technology bubble) and October 2007–March 2009 (corresponding to the recent global financial crisis).12 In addition, taking into account that we analyze European mutual funds and our sample spans up to January 2013, our data could be reflecting the sovereign risk crisis, for European funds. As reported by Inoue et al. (2013), in October 2009 investors began to question the solvency of Greece. In May 2010, the EU (European Union) implemented an institutional change in their system to provide fiscal support to EU member States. Later, Ireland (in November, 2010) and Portugal (in April, 2011) requested financial assistance from the EU. Spain and Italy also suffered from a loss of investor confidence. However, as stated by Ohno (2013), the sovereign risk crisis has not been limited only to these countries, but has spread throughout the whole Eurozone. In Fig. 1, we show the secondary market yields of government bonds with maturities of close to 10 years reported by the European Central Bank (ECB). From data reported by the ECB, we can observe how the yields of European government bonds began to suffer the effect of the sovereign risk crisis from October 2009. Thus, for European funds we consider the period from October 2009 to January 2013 to be a crisis market.
Methodology Performance Models The four-factor Carhart model (1997) is a performance measure that includes four risk factors: the three factors considered by Fama and French (1993), i.e., market, size, and book-to-market factors, plus an additional factor that represents the 1-year momentum strategy. In the following expression, this model is shown. ri;t ¼ aiT þ biT RMRFt þ siT SMBt þ hiT HMLt þ piT MOM1YRt þ eit t ¼ 1; 2; . . .; T
ð1Þ
where ri,t represents the return on a portfolio i in excess of the risk-free asset return at time t; RMRFt is the excess 12
We have analyzed the peaks and troughs from the EuroStoxx 50 Index and the crisis market periods identified are very similar to those obtained from Standard and Poor’s 500 Index.
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35 30 25 20 15 10 5
Belgium Spain Luxembourg Portugal
Managerial Abilities Models Stock-picking and market-timing abilities are the main source of success for a mutual fund manager. In the financial literature, there are several methodological approaches to analyze the presence of these skills. The most-used methodology is the Treynor and Mazuy (TM) (1966) market-timing model, based on the mutual fund manager’s ability to direct the funds toward equity or cash, depending on the market direction. In the following expression, this model is shown. ð2Þ
where aiT is the portfolio alpha, measuring the fund manager’s stock-picking ability (that is, the skill of selecting stocks that outperform other securities with a similar level of non-diversifiable risk). If this coefficient is positive and significant, the manager has this skill, but if it is negative and significant, the manager has a poor stock-picking ability. The portfolio gamma (c) informs us of the market timing. If the gamma coefficient is positive and significant, the mutual fund manager has a successful market-timing
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Ireland Italy Netherlands Slovakia
Jul-12
Jan-13
Jan-12
Jul-11
Jan-11
Jul-10
Jan-10
Jul-09
Jul-08
Jan-09
Jul-07
Jan-08
Jul-06
Jan-07
Jan-06
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Jan-05
Germany France Malta Slovenia
return on a market benchmark; SMBt, HMLt, and MOM1YRt represent the size (the differential return between a small-cap stock portfolio and a large-cap stock portfolio at time t), the book-to-market (the differential return between a value stock portfolio and a growth stock portfolio at time t) and the 1-year momentum (the differential return between the previous year’s winning stock portfolio and the losing stock portfolio at time t), respectively; aiT is the four-factor adjusted return on portfolio i, and biT ; siT ; hiT and piT are the factor loadings of the four style factors; finally, eit is the error term in portfolio i over period t.
ri;t ¼ aiT þ biT RMRFt þ ciT RMRF2t þ ei;t
Jul-04
Jan-04
Jul-03
Jul-02
Jan-03
Jul-01
Jan-02
0 Jan-01
Fig. 1 Secondary market yields of government bonds with maturities of close to 10 years. The evolution of the secondary market yields of government bonds with maturities of close to 10 years of Belgium, Germany, Ireland, Greece, Spain, France, Italy, Cyprus, Luxembourg, Malta, the Netherlands, Austria, Portugal, Slovenia, Slovakia and Finland. Source ECB. Information available at: http:// www.ecb.europa.eu/stats/ money/long/html/index.en.html
Greece Cyprus Austria Finland
ability, but if it is negative and significant, the manager times the market incorrectly. This model is based on the existence of a convex relationship between the returns on the fund and the market, so a manager should increase portfolio exposure to the market whenever the market return increases and, conversely, should reduce it whenever the market return declines. The TM model only allows us to measure-timing skills with regard to the market as a whole. However, mutual fund managers also could attempt to predict the direction of different style factors. Thus, the manager could improve the financial performance of the portfolio by increasing the exposure of the portfolio to the investment styles that apparently will show a good performance, and by reducing the sensitivity of the portfolio to the styles with a poorer predicted behavior. Lu (2005) shows how the TM and Carhart models can be combined in order to measure the mutual fund managers’ style-timing abilities. Other authors in the literature have used this approach to analyze style-timing abilities [see Gregory and Whittaker (2007), Ferruz et al. (2012), and Yu (2012), among others]. Combining TM and Carhart models leads to the following expression. ri;t ¼ aiT þ biT RMRFt þ siT SMBt þ hiT HMLt þ piT MOM1YRt þ ciT RMRF2t þ cSMBiT SMB2t þ cHMLiT HML2t þ cMOMiT MOM1YR2t þ ei;t
ð3Þ
where ciT ; cSMBiT ; cHMLiT and cMOMiT measure the ability of the mutual fund manager to time the market, size, book-tomarket, and 1-year momentum styles, respectively. A positive and significant value for these coefficients indicates proper timing ability. A negative and significant value for these parameters indicates that the mutual fund manager times the market and the styles in the wrong direction. Finally, if the estimated coefficients are
Environmental Mutual Funds
insignificant, this indicates a lack of ability to time the market and the different styles considered.
Empirical Results Performance Results Table 3 reports the estimated alpha four-factor Carhart coefficients found when expression (1) is run on the portfolios formed by the US mutual funds. The results are for the estimation of the full sample, in crisis market periods (March 2000–October 2002 and October 2007–March 2009) and in non-crisis market periods.13 Panel A reports the results for the domestic portfolios. The green US portfolio obtains a negative but non-significant alpha coefficient, indicating that green US portfolio managers do not perform significantly differently from the market. Regarding the rest of the domestic US portfolios, only the category religious US shows a negative and significant alpha coefficient, indicating that these managers underperform the market. However, when we analyze the differences between portfolios we observe that these differences are not significant. Thus, we can conclude that the green funds that invest mainly in US stocks do not perform differently from conventional, ESG, and religious mutual funds. When controlling for crisis/non-crisis market periods, the financial performance of our analyzed portfolios is different. In crisis periods, all portfolios show non-significant alpha coefficients, and there are no significant differences between them. In non-crisis periods, all portfolios underperform the market, since all present a negative and significant alpha coefficient. If we analyze the differences between the portfolios, we observe no significant difference. All portfolios are beaten by the market, that is, we reach the same conclusion as for the whole sample, i.e., green funds do not perform differently from their conventional or SR peers. Panel B shows the results for the global portfolios. The green US global portfolio presents a negative and significant alpha coefficient, indicating that this kind of fund underperform the market. Meanwhile, the conventional green US global and ESG US global portfolios show nonsignificant alpha coefficients, that is, this kind of fund does not perform differently from the market. If we analyze the difference portfolios, we observe that the green US global funds perform significantly worse than their conventional peers. 13
Table 3 is focused on the alpha coefficient since it is the parameter that tells us about financial performance. The estimated Carhart factor coefficients are available to readers upon request.
559
In crisis periods, the underperformance of the green funds disappears. All portfolios show non-significant alpha coefficients. However, in non-crisis periods, green funds underperform the market. The remaining portfolios do not perform differently from the market. When we analyze the differences between portfolios, we observe for the two difference portfolios negative and significant alpha coefficients. Thus, we can conclude that in non-crisis periods the green funds perform worse than the conventional and ESG funds. The prior evidence found for the whole sample period, regarding the underperformance of the green US global funds, is driven by the results obtained for these funds in non-crisis periods, since in crisis periods they perform similarly to their conventional and ESG peers. These findings are in part consistent with those obtained by Varma and Nofsinger (2012), who concluded that SR mutual funds perform better in crisis periods, outperforming their conventional peers. We also find that SR mutual fund managers perform better in crisis periods, but they do not outperform their conventional peers.14 Table 4 reports the estimated alpha four-factor Carhart coefficients found when expression (1) is run on the portfolios formed by the European mutual funds. It reports the results for the estimation of the full sample, in crisis market periods (March 2000–October 2002, October 2007–March 2009, and October 2009–January 2013) and in non-crisis market periods. Panel A reports the results for the domestic portfolios and Panel B shows the results for global portfolios. The results are very similar. The green Europe portfolios show a non-significant alpha coefficient, that is, these funds do not perform differently from the market. The same result is found for their conventional and ESG peers. We observe that, in crisis periods, the difference between the alpha coefficients found for green funds and for conventional funds is negative and significant. However, if we focus on the alpha coefficients obtained for each of the three analyzed portfolios, none is significant, indicating that green, conventional, and ESG funds do not perform differently from the market. Finally, in non-crisis market periods, the financial performance results are the same as those found for the whole sample period, i.e., the green funds perform similarly to the market and to their conventional and ESG peers. In short, and focusing on the green funds, the empirical evidence indicates that they do not perform worse than other forms of SR mutual funds (religious and ESG), in any market, when considering the full sample. In addition, only
14
One possible explanation for this difference could be the different period analyzed. Varma and Nofsinger (2012) analyze the period 2000–2011, whereas we study the period 1994–2013.
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F. Mun˜oz et al.
560 Table 3 Financial performance of US mutual fund portfolios Portfolio
a full sample
a of crisis market periods
a of non-crisis market periods
Panel A: domestic equity portfolios Green US (1)
-0.001 (-0.96)
0.001 (0.37)
-0.002 (-1.99)**
Conventional green US (2)
-0.001 (-1.47)
0.001 (1.13)
-0.001 (-2.27)**
Religious US (3)
-0.002 (-3.21)***
ESG US (4)
-0.001 (-1.53)
-0.001 (-0.41)
-0.002 (-4.38)***
0.001 (0.92)
-0.002 (-3.09)***
(1)–(2)
0.000 (-0.21)
(1)–(3)
0.001 (0.62)
-0.001 (-0.19) 0.001 (0.49)
-0.001 (-0.87)
(1)–(4)
0.000 (-0.29)
0.000 (0.1)
-0.001 (-0.57)
0.000 (-0.15)
Panel B: global equity portfolios Green US global (5)
-0.003 (-1.7)*
0.005 (1.53)
-0.004 (-2.17)**
Conventional green US global (6) ESG US global (7)
0.001 (0.75) -0.001 (-1.5)
0.005 (1.57) 0.001 (0.85)
0.000 (-0.38) -0.001 (-1.22)
(5)–(6)
-0.004 (-2.49)**
0.000 (-0.05)
-0.004 (-2.15)**
(5)–(7)
-0.002 (-1.19)
0.004 (1.13)
-0.003 (-1.84)*
The results found for the estimated alpha 4-factor Carhart coefficient when it is run for the US portfolios. Panel A reports the results for the domestic portfolios and panel B the results for the global portfolios. We report the estimated coefficients, along with their associated t statistic (between brackets). The a coefficient represents the financial performance of the portfolio. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return. The first column shows the results when estimating the 4-factor Carhart model in the full sample. The second column reports the results when estimating the 4-factor Carhart model during crisis market periods (March 2000–October 2002 and October 2007–March 2009). The third column shows the results when running the 4-factor Carhart model in non-crisis market periods ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
Table 4 Financial performance of European mutual fund portfolios Portfolio
a full sample
a of crisis market periods
a of non-crisis market periods
Panel A: domestic equity portfolios Green Europe (8)
0.000 (-0.16)
-0.003 (-1.13)
-0.000 (-0.06)
Conventional green Europe (9)
0.001 (0.32)
-0.000 (-0.09)
-0.000 (-0.15)
ESG Europe (10)
0.000 (-0.07)
-0.002 (-0.93)
-0.000 (-0.05)
(8)–(9)
-0.003 (-1.91)*
0.000 (0.14)
0.000 (-0.21)
-0.001 (-0.51)
-0.000 (-0.04)
Green Europe global (11)
-0.002 (-0.94)
-0.005 (-1.43)
-0.002 (-0.76)
Conventional green Europe global (12)
-0.001 (-0.27)
0.002 (0.59)
-0.005 (-1.16)
ESG Europe global (13)
-0.001 (-0.66)
-0.003 (-1.18)
-0.002 (-0.74)
(11)–(12) (11)–(13)
-0.001 (-0.59) -0.001 (-0.71)
-0.007 (-2.81)*** -0.002 (-1.14)
0.002 (0.67) -0.001 (-0.3)
(8)–(10)
-0.001 (-0.83)
Panel B: global equity portfolios
The results found for the estimated alpha 4-factor Carhart coefficient when it is run for the European portfolios. Panel A reports the results for the domestic portfolios and panel B the results for the global portfolios. We report the estimated coefficients, along with their associated t statistic (between brackets). The a coefficient represents the financial performance of the portfolio. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return. The first column shows the results when estimating the 4-factor Carhart model in the full sample. The second column reports the results when estimating the 4-factor Carhart model during crisis market periods (March 2000–October 2002, October 2007–March 2009 and October 2009–January 2013). The third column shows the results when running the 4-factor Carhart model in non-crisis market periods ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
123
Environmental Mutual Funds
in the case of the green US global funds do their conventional peers perform significantly better. Besides, in general terms, we conclude that controlling for crisis market periods does not significantly affect our findings for the whole sample period, with regard to differences in financial performance among the green funds and the conventional and other kinds of SR fund. Our results differ somewhat from those previously found by Climent and Soriano (2011), who concluded that during the 1987–2009 period, the US environmental mutual funds underperformed conventional funds. However, when they analyzed the 2001–2009 period, their results indicated that the environmental and conventional mutual funds did not perform differently. We find that only the green US global funds underperform their conventional peers (but the underperformance disappears in crisis periods). The reason for such different results could lie in the different samples of environmental funds, and in the different periods considered; Climent and Soriano (2011) analyze seven green mutual funds during the period 1987–2009, whereas we analyze 18 green funds in the period 1994–2013. Moreover, we run the analyses separately for the green funds that invest mainly in domestic stocks (six funds) and for those with a global equity investment objective (12 funds). In addition, we analyze 89 green funds from European market, whereas Climent and Soriano (2011) are focused on the US market.
Managerial Abilities Results Climent and Soriano (2011) consider that one possible explanation of the results found for the green funds they analyzed is poor fund management. In this section, we test the presence of managerial abilities among the mutual fund managers of the analyzed portfolios. Specifically, we analyze the stock-picking, market-timing, and style-timing abilities of the green fund managers, and we compare the results with those found for the managers of conventional and other types of SR mutual fund. Ferruz et al. (2012) analyze this topic for religious mutual fund managers from the US market. However, as far as we know, these issues have been neglected for green mutual funds. Green funds restrict their investor universe according to environmental issues. This reduction of the investment universe could imply an advantage for the managers of these particular portfolios. A smaller eligible universe of stocks could enable them to possess a greater knowledge about those stocks. This could make it easier to implement an effective active management strategy. In Table 5, we show the results found for the multifactor timing model applied to the US portfolios.
561
Panel A of Table 5 reports the results for the domestic portfolios. The green US portfolio shows insignificant a, c, cSMB, cHML, and cMOM parameters, indicating that the green fund managers are not able to follow successful stock-picking strategies, nor do they exhibit sufficient skills in timing either the market return or the size, book-tomarket, and momentum styles. For the other domestic US portfolios, we observe that the conventional mutual fund managers show a negative stock-picking ability and a poor ability to time the momentum style. However, they are able to successfully time the book-to-market style. The religious mutual fund managers present a negative stock-picking ability and they are not able to time any of the styles considered with any degree of success. This finding is consistent with the conclusions found by Ferruz et al. (2012) and could be the origin of the underperformance documented in Table 3 for this kind of mutual fund. Finally, the ESG mutual fund managers present a negative stock-picking ability but a successful book-to-market timing ability. Despite the empirical evidence found for each of the analyzed portfolios, when we analyze the differences between the coefficients obtained for the green funds and the rest of the portfolios, we detect no significant difference. Panel B of Table 5 shows the results for the global portfolios. None of the analyzed portfolios show successful stock-picking ability. With regard to timing, the green and ESG fund managers show a poor market-timing ability, whereas the conventional fund managers are able to time the book-to-market style. If we analyze the results for the difference portfolios, we observe that there are no significant differences between the green and ESG funds. However, the green funds show a better size timing coefficient than the conventional funds, but the latter are better at timing the book-to-market style than the former. In the previous section, we concluded that green global funds significantly underperform their conventional peers. The poor market-timing ability of green fund managers, combined with the successful book-to-market timing skills of conventional managers, could be the origin of the underperformance of green global funds. Tables 6 and 7 report the same information as Table 5, but in crisis market periods (March 2000–October 2002 and October 2007–March 2009) and in non-crisis market periods, respectively. Panels A of Tables 6 and 7 show the results for domestic US portfolios in crisis and in non-crisis market periods, respectively. In crisis periods, green portfolio managers show a poor ability to time the market, but successful timing of the size style. ESG and conventional fund managers are also able to time the size style, while
123
F. Mun˜oz et al.
562 Table 5 Managerial abilities of US mutual fund managers Portfolio
a
c
cSMB
cHML
cMOM
R2
Panel A: domestic equity portfolios Green US (1)
-0.001 (-1.07)
0.106 (0.36)
-0.147 (0.17)
0.528 (1.05)
-0.122 (-0.4)
0.90
Conventional green US (2)
-0.001 (-2.23)**
0.164 (1.17)
0.332 (1.5)
0.451 (1.89)*
-0.233 (-2)**
0.98
Religious US (3)
-0.002 (-3.69)***
0.197 (1.44)
0.295 (0.94)
0.188 (0.85)
-0.185 (-1.35)
0.98
ESG US (4)
-0.001 (-2.73)***
0.166 (1.29)
0.045 (0.13)
0.468 (2.55)***
-0.058 (-0.43)
0.98
(1)–(2)
0.000 (0)
-0.058 (-0.17)
-0.479 (-0.71)
0.076 (0.14)
0.111 (0.46)
0.62
(1)–(3)
0.001 (0.62)
-0.090 (-0.38)
-0.442 (-0.72)
0.340 (0.63)
0.064 (0.27)
0.35
(1)–(4)
0.000 (0.2)
-0.060 (-0.21)
-0.192 (0.36)
0.059 (0.14)
-0.063 (-0.33)
0.46
2.575 (1.2)
0.370 (0.31)
-0.144 (-0.36)
0.81
0.296 (1.25)
0.91
0.050 (0.53)
0.97
Panel B: global equity portfolios Green US global (5) Conventional green US global (6) ESG US global (7)
-0.002 (-1.19)
-0.702 (-2.02)**
0.000 (0.05)
-0.357 (-1.24)
0.000 (-0.18)
-0.729 (-0.7)
-0.538 (-2.75)***
0.444 (0.84)
(5)–(6)
-0.002 (-1.36)
-0.344 (-1.09)
3.305 (1.68)*
(5)–(7)
-0.002 (-1.19)
-0.163 (-0.52)
2.131 (1.06)
2.502 (2.97)*** 0.339 (1.02) -2.132 (-2.72)*** 0.031 (0.02)
-0.440 (-1.11)
0.27
-0.194 (-0.49)
0.16
The results found with the multifactor timing model for the US portfolios. Panel A reports the results for the domestic portfolios and panel B those for the global portfolios. The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, bookto-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
conventional and religious portfolio managers time the momentum style incorrectly. Focusing on the difference portfolios, we observe that green fund managers are significantly better than all their peers in size style-timing, but perform worse than conventional and ESG fund managers in market-timing. In non-crisis market periods, the abilities of all portfolio managers are, in general terms, worse than in crisis periods. Green portfolio managers show a poor ability to time the size and the book-to-market styles. Conventional portfolio managers show a poor ability to time the book-to-market style. Religious and ESG portfolios managers wrongly time the size style and possess poor stock-picking ability. Focusing on our difference portfolios, green fund managers seem to underperform their conventional peers in size style-timing, and do worse than religious and ESG portfolios managers in book-to-market style-timing. These findings could explain the results found in the previous section concerning the underperformance of all US domestic portfolios in non-crisis market periods. Panels B of Tables 6 and 7 show the results for global US portfolios in crisis and in non-crisis market periods, respectively. In crisis periods, green portfolio managers show poor market-timing ability, but are successful in timing the book-to-market style; in fact, they perform significantly better than their ESG peers. Conventional portfolio managers correctly time the book-to-market style,
123
but do not do well in timing the size style. Finally, ESG portfolio managers show poor ability to time the market, but good timing skills in the size style. In non-crisis market periods, green portfolios managers show poor book-to-market timing ability, whereas conventional portfolio managers are able to time the momentum style. If we analyze the difference portfolio results, we see that green fund managers are significantly less adept than their conventional and ESG peers at timing the book-to-market style. The underperformance of green funds with regard to their conventional and ESG peers in non-crisis market periods (documented in Table 3) could be driven by this. In short, and focusing on green funds, green US fund managers do not show good timing abilities in the full sample. However, in crisis market periods, they show a negative market-timing ability but a successful ability to time the size style. In non-crisis market periods, they time the size and book-to-market styles incorrectly. Green US global fund managers show a negative market-timing ability in the full sample. In crisis market periods, these managers show a negative market-timing ability but a positive ability in timing the book-to-market style. Finally, in non-crisis market periods, they show a negative timing in the book-to-market style. In view of these findings, it appears that green fund managers in the US market possess better managerial abilities in crisis market periods (they are able to properly time some of the styles analyzed) than in non-crisis market periods.
Environmental Mutual Funds
563
Table 6 Managerial abilities of US mutual fund managers in crisis market periods Portfolio
a
c
cSMB
cHML
R2
cMOM
Panel A: domestic equity portfolios Green US (1)
0.000 (0.05)
-0.886 (-2.01)*
Conventional green US (2)
0.001 (0.39)
0.333 (1.29)
2.167 (4.61)***
0.077 (0.16)
-0.199 (-0.63)
0.954
0.534 (1.75)*
0.391 (1.18)
-0.395 (-2.03)**
0.984
Religious US (3)
0.001 (1.03)
-0.077 (-0.42)
0.340 (1.32)
0.109 (0.42)
-0.437 (-2.54)**
0.986
ESG US (4)
0.000 (0.36)
-0.035 (-0.32)
0.395 (1.98)*
0.075 (0.63)
-0.097 (-0.83)
0.994
(1)–(2)
-0.001 (-0.19)
-1.218 (-2.16)**
1.633 (3.06)***
-0.314 (-0.52)
0.196 (0.57)
0.825
(1)–(3)
-0.001 (-0.46)
-0.808 (-1.52)
1.828 (3.34)***
-0.032 (-0.06)
0.238 (0.79)
0.603
(1)–(4)
-0.000 (-0.1)
-0.850 (-1.83)*
1.773 (3.87)***
0.002 (0)
-0.102 (-0.37)
0.721
-0.412 (0.63)
0.881
0.210 (0.21)
0.934 0.986
Panel B: global equity portfolios Green US global (5)
0.007 (1.4)
-1.201 (-2.83)***
-1.818 (-0.82)
4.609 (2.24)**
Conventional green US global (6)
0.004 (1.08)
-0.543 (-1.09)
-3.632 (-1.71)*
5.057 (3.13)***
ESG US global (7)
0.001 (0.29)
-0.646 (-2.78)***
1.900 (1.91)*
0.773 (1.05)
0.082 (0.28)
(5)–(6)
0.003 (0.56)
-0.658 (-1.15)
1.814 (0.76)
-0.448 (-0.29)
-0.622 (-0.65)
0.294
(5)–(7)
0.007 (1.23)
-0.555 (-1.18)
-3.718 (-1.49)
3.835 (1.73)*
-0.494 (-0.53)
0.157
The results found with the multifactor timing model for the US portfolios in crisis market periods (March 2000–October 2002 and October 2007– March 2009). Panel A reports the results for the domestic portfolios and panel B those for the global portfolios The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, book-to-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
Table 7 Managerial abilities of US mutual fund managers in non-crisis market periods Portfolio
a
c
cSMB
cHML
R2
cMOM
Panel A: domestic equity portfolios Green US (1)
-0.001 (-0.58)
0.334 (1.27)
-1.578 (-2.28)**
-2.711 (-2.02)**
0.337 (1.03)
Conventional green US (2)
-0.001 (-1.48)
0.115 (0.7)
-0.110 (-0.39)
-0.970 (-1.69)*
0.027 (0.22)
0.980
Religious US (3)
-0.002 (-3.17)***
0.279 (1.69)*
-0.571 (-2.06)**
-0.427 (-0.88)
0.031 (0.34)
0.980
ESG US (4)
-0.001 (-2.38)**
0.160 (1.07)
-0.846 (-2.35)**
0.139 (0.23)
0.063 (0.33)
0.975
0.219 (0.72)
-1.468 (-2.48)**
-1.741 (-1.28)
0.311 (1.18)
0.527
(1)–(2)
0.000 (0.13)
0.904
(1)–(3)
0.001 (0.95)
0.055 (0.21)
-1.007 (-1.54)
-2.284 (-1.73)*
0.306 (1.07)
0.357
(1)–(4)
0.001 (0.55)
0.174 (0.57)
-0.733 (-1.47)
-2.851 (-2.48)**
0.274 (1.38)
0.380
-0.903 (-1.59)
3.830 (1.19)
-5.798 (-2.19)**
0.329 (0.93)
0.778
Panel B: global equity portfolios Green US global (5) -0.003 (-1.31) Conventional green US global (6)
-0.000 (-0.28)
-0.331 (-0.64)
-0.628 (-0.41)
-0.077 (-0.06)
0.584 (2.17)**
0.896
ESG US global (7)
-0.000 (-0.01)
-0.552 (-1.95)*
0.827 (1.26)
-0.972 (-1.07)
0.053 (0.4)
0.952
-0.255 (-0.63)
0.261
0.276 (0.76)
0.263
(5)–(6)
-0.002 (-1.24)
-0.571 (-1.1)
4.458 (1.38)
-5.721 (-2.35)**
(5)–(7)
-0.003 (-1.39)
-0.351 (-0.66)
3.003 (0.99)
-4.826 (-2)**
The results found with the multifactor timing model for the US portfolios in non-crisis market periods. Panel A reports the results for the domestic portfolios and panel B those for the global portfolios. The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, book-to-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
123
F. Mun˜oz et al.
564 Table 8 Managerial abilities of European mutual fund managers Portfolio
a
c
cSMB
cHML
cMOM
R2
Panel A: domestic equity portfolios Green Europe (8)
0.000 (0.05)
-1.427 (-3.33)***
2.032 (1.12)
2.349 (1.64)
0.556 (1.29)
0.66
Conventional green Europe (10)
0.000 (-0.15)
-0.962 (-3.12)***
1.974 (1.22)
2.699 (2.3)**
0.473 (1.2)
0.69
-0.853 (-1.99)**
1.863 (1.11)
2.707 (1.87)*
0.254 (0.59)
0.70
(8)–(10)
ESG Europe (12)
-0.001 (-0.34) 0.000 (0.3)
-0.465 (-2)**
0.058 (0.04)
-0.350 (-0.42)
0.083 (0.43)
0.24
(8)–(12)
0.001 (0.74)
-0.574 (-2.4)**
0.170 (0.11)
-0.358 (-0.6)
0.303 (2.16)**
0.13
Panel B: global equity portfolios Green Europe global (9)
-1.433 (-2.74)***
6.252 (1.92)*
0.641 (0.36)
0.437 (0.65)
0.60
0.000 (-0.1)
-1.102 (-1.63)
4.880 (1.48)
1.106 (0.72)
-0.335 (-0.62)
0.52
ESG Europe global (13)
-0.002 (-0.74)
-0.937 (-1.81)*
1.291 (0.9)
(9)–(11) (9)–(13)
-0.003 (-0.85) -0.001 (-1.01)
-0.330 (-0.67) -0.496 (-1.94)*
1.372 (0.27) 4.961 (1.95)*
Conventional green Europe global (11)
-0.003 (-1.25)
2.044 (1.54)
0.401 (0.87)
0.68
-0.465 (-0.23) -1.402 (-1.77)
0.772 (1.46) 0.036 (0.12)
0.10 0.27
The results found with the multifactor timing model for the European portfolios. Panel A reports the results for the domestic portfolios and panel B those for the global portfolios. The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, bookto-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
Table 8 reports the results of managerial abilities for European mutual fund managers when considering the full sample (January 1994–2013). Panel A of Table 8 contains the results for domestic portfolios. Green fund managers show a poor ability to time the market. Conventional fund managers also present a negative market-timing ability, but they are able to time the book-to-market style. For ESG mutual fund managers, we find the same results as for conventional managers. Focusing on differences between portfolios, the most relevant result is that, although all portfolios show negative market-timing ability, in the case of green fund portfolios it is significantly worse. Panel B of Table 8 shows the results for global portfolios. Green fund managers time the market incorrectly, but they are able to time the size style. If we compare the results with those obtained by conventional funds, the empirical evidence indicates that there are no significant differences. However, with regard to ESG fund managers, there are differences. Specifically, green funds are significantly less skilled than ESG funds in market-timing, but better in timing size style. Tables 9 and 10 show the results of managerial abilities for European portfolio managers when controlling for crisis/non-crisis market periods. Panels A of Tables 9 and 10 report the results for domestic portfolios in crisis (March 2000–October 2002, October 2007–March 2009, and October 2009–January 2013) and in non-crisis market periods, respectively.
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In crisis market periods, we observe a poor markettiming ability for green and conventional fund managers. Analyzing the difference portfolios, green fund managers are less skilled than their conventional and ESG peers in timing the market. In non-crisis market periods, again green, conventional, and ESG managers show poor markettiming skills, although they are able to time other styles. Specifically, green, conventional, and ESG fund managers are able to time the book-to-market style. ESG fund managers are also able to time the size style. In non-crisis market periods, no significant differences between portfolios are detected. Panels B of Tables 9 and 10 show the results for global portfolios in crisis (March 2000–October 2002, October 2007–March 2009, and October 2009–January 2013) and in non-crisis market periods, respectively. In crisis market periods, green and conventional portfolio managers show negative market-timing ability, while conventional fund managers show a proper ability to time the size and book-to-market styles. Focusing on the difference portfolios, green fund managers are less skilled than ESG managers at timing the market. Finally, in non-crisis market periods, green fund managers properly time the size style, but poorly time the bookto-market style. Conventional fund managers show poor market-timing ability. When we analyze the difference portfolios, we see that conventional fund managers are less skilled at markettiming than green fund managers, while the latter are better than conventional and ESG fund managers in size style-
Environmental Mutual Funds
565
Table 9 Managerial abilities of European mutual fund managers in crisis market periods a
Portfolio
c
cSMB
cHML
R2
cMOM
Panel A: domestic equity portfolios Green Europe (8)
0.000 (0.09)
-1.350 (-3.69)***
4.453 (1.48)
0.632 (0.39)
-0.670 (-0.75)
0.821
Conventional green Europe (10)
0.002 (0.73)
-0.903 (-2.93)***
4.001 (1.43)
0.326 (0.2)
-0.820 (-1.25)
0.796
-0.433 (-1.21)
1.970 (0.82)
-0.295 (-0.17)
-1.163 (-1.46)
0.813
(8)–(10)
ESG Europe (12)
-0.002 (-0.94)
0.001 (0.23)
-0.448 (-2.22)**
0.451 (0.26)
0.305 (0.33)
0.151 (0.35)
0.405
(8)–(12)
-0.001 (-0.34)
-0.917 (-4.2)***
2.482 (1.48)
0.927 (1.05)
0.493 (1.42)
0.322
-0.856 (-0.78)
0.643
0.322 (0.21)
0.758
Panel B: global equity portfolios Green Europe global (9)
-0.001 (-0.29)
-1.815 (-2.6)**
1.363 (0.43)
4.339 (1.61)
Conventional green Europe global (11)
-0.003 (-0.75)
-1.352 (-2.4)**
7.812 (1.88)*
6.474 (3.06)***
ESG Europe global (13)
-0.001 (-0.27)
-1.065 (-1.65)
2.391 (1.07)
2.698 (1.4)
-0.967 (-1.09)
0.731
(9)–(11)
0.001 (0.35)
-0.463 (-1.07)
-6.450 (-1.27)
-2.135 (-1.48)
-1.177 (-1.02)
0.187
(9)–(13)
-0.000 (-0.17)
-0.750 (-3.89)***
-1.028 (-0.59)
1.641 (1.3)
0.111 (0.2)
0.229
The results found with the multifactor timing model for the European portfolios in crisis market periods (March 2000–October 2002, October 2007–March 2009 and October 2009–January 2013). Panel A reports the results for the domestic portfolios and panel B those for the global portfolios. The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, book-to-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
Table 10 Managerial abilities of European mutual fund managers in non-crisis market periods Portfolio
a
c
cSMB
cHML
R2
cMOM
Panel A: domestic equity portfolios Green Europe (8)
-0.001 (-0.28)
-2.385 (-2.46)**
2.555 (1.29)
8.200 (2.02)**
0.530 (0.7)
0.572
Conventional green Europe (10)
-0.001 (-0.47)
-2.233 (-2.99)***
3.447 (1.46)
6.794 (2.68)***
0.493 (0.89)
0.627
ESG Europe (12)
-0.000 (-0.14)
7.907 (2.92)***
0.414 (0.67)
0.616
(8)–(10)
0.000 (0.2)
-0.152 (-0.2)
-0.891 (-0.5)
1.405 (0.72)
0.037 (0.11)
0.202
(8)–(12)
-0.001 (-0.33)
0.646 (0.93)
-1.329 (-0.92)
0.293 (0.15)
0.116 (0.4)
0.181
-0.005 (-1.5)
-1.450 (-1.61)
9.900 (2.62)**
-4.352 (-1.75)*
1.027 (1.45)
0.578
-0.001 (-0.25)
-3.440 (-3.26)**
3.128 (0.72)
1.183 (0.22)
-0.101 (-0.14)
0.412
1.252 (0.48)
3.598 (1.32)
0.525 (0.9)
0.620
6.768 (1.73)*
-5.535 (-1.13)
1.128 (1.78)*
0.199
8.644 (3.21)***
-7.950 (-2.78)***
0.502 (1.55)
0.414
Panel B: global equity portfolios Green Europe global (9) Conventional green Europe global (11)
-3.030 (-3.53)***
ESG Europe global (13)
-0.002 (-0.69)
-1.356 (-1.55)
(9)–(11)
-0.003 (-0.77)
1.990 (2.17)**
(9)–(13)
-0.003 (-1.1)
-0.094 (-0.13)
3.884 (1.74)*
The results found with the multifactor timing model for the European portfolios on non-crisis market periods. Panel A reports the results for the domestic portfolios and panel B those for the global portfolios. The information includes the estimated coefficients, along with their associated t statistic (between brackets). a coefficient represents the stock-picking ability; c, cSMB, cHML and cMOM represent the timing ability with regard to the market return, size, book-to-market and momentum styles, respectively. R2 shows the explanatory power of the model. The difference portfolios are built by subtracting the return on each of the non-green portfolios from the green portfolio return ESG environmental, social and governance * Significant at 10 %, ** significant at 5 %, *** significant at 1 %
timing, and worse than ESG managers in timing book-tomarket style. In short, green fund managers of European domestic portfolios show poor timing ability in the full sample and
when controlling for crisis/non-crisis market periods. However, in non-crisis market periods, they are able to time the book-to-market style. Global fund managers show negative market-timing in the full sample and in crisis
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566
market periods, but they are not good at timing the bookto-market style in non-crisis market periods. They do, however, have the ability to time the size style in the full sample, and in non-crisis market periods. Given these results, it appears that green fund managers have better managerial abilities in non-crisis market periods (they are able to successfully time some of the investment styles studied) than in crisis market periods. This finding is interesting when we consider that the opposite occurs for green fund managers in US market.
Conclusions An increasing number of investors incorporate their environmental concerns into their investment decision process. Green funds invest in companies with good records on environmental issues. Although at first glance we may consider that sustainable companies pay a price for internalizing their environmental impact, there are also reasons to think that good environmental performance maintains a positive relationship with good financial performance. The relationship between environmental and financial performance is a topic widely analyzed in the financial literature, but it has mostly been analyzed from a firm perspective. Moreover, although there is a significant number of studies that have analyzed the financial performance of SR mutual funds, the specific case of green mutual funds has been neglected, and there exist only a very few articles on green funds. In this work, we contribute to fill this gap, and we extend the prior empirical evidence on the subject by studying a broader sample of green funds (we consider in our analyses 107 green funds from US and European markets) and an updated sample period. Furthermore, we also distinguish between green funds with a domestic equity investment aim and those with a global equity investment aim, and we control our empirical evidence for the effects of crisis market periods. Finally, we analyze the managerial abilities of green mutual fund managers. Our results indicate that green funds do not perform worse than other forms of SR mutual funds. This conclusion remains unaltered after controlling for crisis market periods. Only in the case of green US global funds do their conventional peers perform significantly better. However, this underperformance disappears when analyzing financial performance in crisis market periods. With regard to managerial abilities, we conclude that, in general terms, green fund managers are unable to successfully implement stock-picking or timing investment strategies, when considering the full sample (only for European global fund managers do we find a positive result in the ability to time the size style). In view of these
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F. Mun˜oz et al.
findings, it does not appear that SR funds take advantage of their narrower investment universe to implement active investment strategies. When controlling for crisis and non-crisis market periods, we observe a different result for green fund managers in US and European markets. In the case of the US market, green fund managers appear to have better managerial abilities in crisis market periods, but for European green fund managers the opposite is the case. More specifically, in crisis market periods, green US fund managers show successful ability to time the size style and green US global fund managers are able to time the book-to-market style. However in non-crisis market periods, green US domestic and global fund managers do not time properly any of the analyzed styles. In the case of the European market, in non-crisis market periods, green Europe fund managers are able to time properly the book-to-market style and green Europe global fund managers show positive size style timing ability. However, in crisis market periods, green Europe domestic and global fund managers are not able to time properly any of the analyzed styles. This study focuses on financial performance and the managerial abilities of green funds. However, green fund investors are also worried about the environmental impact of their investments. Thus, a relevant avenue of research for green funds could be the analysis of their environmental performance. That is, there are rating agencies providing environmental ratings for stocks and bonds issues (these agencies use a multiple environmental criteria to construct their ratings). Methodological approaches based on portfolio-holding information might allow a more in-depth study of the specific characteristics of the securities held in green portfolios. In this way, an environmental score for green funds could be calculated by matching portfolio holding information with stock and bond environmental rating information. The results from these analyses could be very interesting for investors engaged in environmental issues. Acknowledgments The authors would like to express our acknowledgements to Aragon’ Government by the funding received as Public and Official Research Group (GIECOFIN).
Appendix 1: Strategies Followed by Green Mutual Funds Green funds pursue a broad variety of strategies in order to include environmental issues in their investment decision process. We can find several examples of these strategies, from the portfolio information provided in their prospectus. Thus, we find green funds that consider positive screens, as for example the ‘‘Alger Green Fund’’, which states the following regarding its principal investment strategy:
Environmental Mutual Funds
‘‘Under normal circumstances, the Fund invests at least 80 % of its net assets, plus any borrowings for investment purposes, in equity securities of companies of any size that, in the opinion of Fred Alger Management, Inc., conduct their business in an environmentally sustainable manner, while demonstrating promising growth potential. Companies that conduct their business in an environmentally sustainable manner are companies that have developed or are developing or marketing products or services that address human needs without undermining nature’s ability to support our economy into the future, have a positive or neutral impact on the environment on a relative basis, or recognize environmental sustainability as a challenge and opportunity as demonstrated through their business strategies, practices or investments’’. Another way to tackle the environmental dimension in the investment process is to select stocks from industrial sectors considered to be ecological or environmentally friendly. This is the case for the green fund ‘‘Firsthand Alternative Energy’’. Its data sheet document states the following with regard to its investment strategy: ‘‘The Fund invests in alternative energy and energy technology companies, both U.S. and international. Alternative energy includes solar, hydrogen, wind, geothermal, hydroelectric, tidal, biofuel, and biomass. Because there are no market capitalization restrictions on the Fund’s investments, the Fund may purchase stocks of any capitalization.’’ Another example is the ‘‘New Alternatives Fund’’ which states in its prospectus, ‘‘Under normal market conditions, at least 25 % of the Fund’s total assets will be invested in equity securities of companies in the alternative energy industry. ‘‘Alternative Energy’’ means the production and conservation of energy in a manner that reduces pollution and harm to the environment, particularly when compared to conventional coal, oil or nuclear energy’’. Other funds also impose negative or exclusionary environmental screens; i.e., they avoid companies from certain sectors considered to be harmful to the environment. One example is the ‘‘Green Century Equity fund’’ that states the following in its prospectus: ‘‘…It excludes investments in companies with the worst environmental and social records on waste disposal, toxic emissions, environmental fines/penalties, recycling, waste and emissions reduction…’’.
Appendix 2: US Green Mutual Funds List of green mutual funds from US market with a domestic investment aim analyzed: Alger Green Fund, Brown Advisory Winslow Sustainability, DFA US Sustainability Core, Great-West Ariel Mid Cap Value Init, Great-West Ariel Small Cap Value and the Green Century Equity.
567
List of green mutual funds from US market with a global investment aim analyzed: Allianz Global Water, Calvert Global Alternative Energy, Calvert Global Water, Firsthand Alternative Energy, Guinness Atkinson Alternative Energy, Meeder Utilities and Infrastructure, DFA Intl Sustainability Core, Gabelli SRI Green, New Alternatives, Pax World Global Environmental, Portfolio 21 Global Equity and the Fidelity Select Envir and Alt Energy.
Appendix 3: European Green Mutual Funds List of green mutual funds from the European market that invest mainly in the European area: A Plus Environnement 10, Allianz Eco Innovation, Allianz Eure´co Equity, BMG Environnement, Echiquier Environnement, Ecureuil Be´ne´fices Environnement, EDR Ecosphere, Erste Responsible Stock Austria, Erste Responsible Stock Europe, Etoile Environnement, FCPI Innovation Pluriel, Federal Plane`te Bleue, Fructi Actions Environnement, GLG Global Sustainability Eq, LBBW Global Warming, LBPAM Responsible Actions Environnement, LGT Sustainable Equity Fd Europe, Mirova Europe Life Equity, Performance Environnement, SEB Ethical Europe and the Allianz Global Ecotrends. List of green mutual funds from the European market that invest mainly in the global area: Alta Water, Amundi FDS Equity Global Aqua, Avenir Changement Climatique, AXA WF FRM Global Environment, BGF New Energy, Bluevalor Sustainable Lifestyle Brand Eq, BNP Paribas Aqua, CFM Environnement De´veloppement Durable, Deka-Umweltinvest, DELOS Green Energy—Foreign Equity Fund, Delta Lloyd New Energy, Dexia Equity Susˆm tainable Green Planet, DNB Renewable Energy, Do Prospective C, DWS Klimawandel, DWS Zukunftsressourcen, Ecology Stock FOCUS A, EIC Renewable Energy, Entheca Rarete´, Erste WWF Stock Climate Change, Erste WWF Stock Umwelt, Evli Climate, FandC Global Climate Opp, FBG 4Elements, Green Power Eco Fund, Guinness Alternative Energy, IKANO Fds Alternative Energy and Water, Impact FDS Climate Change, Impax Environmental Markets, Invesco Umwelt-u.Nachhaltigkeits-Fonds, Jupiter JGF Climate Change Solu L €Acc, KBC Eco Alternative Energy, KBC Eco Climate Change, KBC Eco Water, KBI Alternative Energy, KBI Water, Living Planet Energy, Living Plante Global Environment, MAM Terra Nova, Nordea-1 Climate and Environment Equity, Parvest Environmental Opportunities, Pictet Clean Energy, Pictet Environment Megatrend Sel, Pictet Water, Pioneer FD Global Ecology, Polaris GEO Environmental, Prime Value Green, Provalor Cap Environnement, Quantex Environmental EUR, Quest Cleantech, RobecoSAM Smart Energy,
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568
RobecoSAM Smart Material, RobceoSAM Sustainable Climate, RobecoSAM Sustainable Water, Sarasin New Power Fund, Sarasin Sustainable Water, Swisscanto Equity Water, UBS ES Climate Change Acc, Variopartner Tareno Waterfund, Vontobel New Power, WIOF Green Energy Performance Fund, Schroder ISF Global Climate Change Equity, Schroder ISF Global Climnate CFG Equity, ACATIS Fair Value Aktien Global EUR, Ecofi De´veloppement Durable, Erste Responsible Stock Global, Inconomentric Global Valor and the Swisscanto PF Green Investment Equity.
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