Are SRI Funds More Resilient towards the
Global Financial Crisis?
Miwa Nakai ∗Keiko Yamaguchi †Kenji Takeuchi ‡May 19, 2011

Abstract
This paper compares the resilience of Socially Responsible Investment (SRI) funds with that of conventional funds towards the global
ﬁnancial crisis by using an event study methodology. Taking thebankruptcy of Lehman Brothers as the particular event, we estimatedthe average cumulative abnormal returns of both SRI funds and conventional funds. Our results show that SRI funds are more resilient
to such a shock. Similar results are obtained by an estimation with amarket model that accounts for ARCH eﬀects.

Keywords SRI; Event study; Financial crisis
JEL Classiﬁcation A13; G01; M14∗

Graduate School of Economics, Kobe University
Graduate School of Humanities and Social Sciences, Okayama University‡
Graduate School of Economics, Kobe University takeuchi@econ.kobe-u.ac.jp
†

1

1

Introduction

The global recession after the subprime crisis has dealt a crippling blow tothe economy not only in the United States but all over the world. Since 2007,
the potential global writedowns on loans and securities due to this ﬁnancial
crisis were estimated to be 4.1 trillion US dollars (IMF, 2009). The falls
in GDP from 2008 to 2009 were -2.6%, -4.1%, -5.2% and -4.9% in the US,
Euro Area, Japan and the UK, respectively (IMF, 2010). Major economic
indicators show the seriousness of the impact of the ﬁnancial crisis: without
doubt it has been the worst economic downturn since the Great Depression
in 1929.
One of the causes of the economic crisis was subprime lending, which wasintended for low-income households or subprime borrowers and which would
inevitably lead to defaults. The loans were securitized into wide-ranging ﬁnancial commodities not to be able to track who should be responsible fordefaults. Investment behaviour focusing extensively on short-term economic
gains has compounded the problem. While there are calls for remedying thesituation by tightening regulation of, and governance over ﬁnancial institutions, there already exists a self-regulation mechanism in the market that is
potentially eﬀective in enhancing corporate activity for social proﬁt: that is,Socially Responsible Investments (hereafter SRI).
Socially Responsible Investment is an investment process using positiveor negative screening that takes into account not only ﬁnancial performancebut also the value of Corporate Social Responsibility (hereafter CSR), suchas voluntary activities for environmental or social issues, before making investment decisions. SRI has grown rapidly throughout the world over recent2decades. At the end of 2007, Eurosif (2008) reported the EU had the biggest
SRI market in the world with 3,922 billion US dollars (calculated at the exchange rate on 31st of December, 2007) and the US followed the second with
2,711 billion US dollars (Social Investment Forum, 2010).
Even though the performance of SRI might go down because of the ﬁnancial crisis, the degree of fall in the return of SRI would be lower compared
to conventional investments if CSR activity were evaluated positively by themarket and investors in SRI funds were more resistant to the shock. On
the other hand, should investors consider CSR as merely a cost that make acompany’s economic situation worse, SRI performed more poorly than conventional investment.
Previous studies have compared SRI funds and conventional funds withrespect to their economic performance (Hamilton et al., 1993; Bauer et al.,2005; Jones et al., 2008; Climent and Soriano, forthcoming) and investment behaviour (McLachlan and Gardner, 2004; Bollen, 2007; Benson andHumphrey, 2008). However, their resilience to a large-scale shock to theeconomy has not been examined enough. Consequently, an investigation of
their resilience would help towards a truer evaluation of the performance ofthe self-regulation mechanism that the ﬁnancial market has developed.
This study aims to examine the resilience of SRI funds compared to thatof conventional funds towards the global ﬁnancial crisis in one of the biggest
ﬁnancial markets, Japan using the event study methodology. Based on theassumption of an eﬃcient market, an event study casts light on the impactof an unanticipated event on changes in stock prices. For this purpose, thebankruptcy of Lehman Brothers was chosen as the event to be studied, since3

it triggered the ﬁnancial crisis.
The main ﬁnding of this study is that the abnormal negative impact of
the global ﬁnancial crisis on SRI funds was less than that on conventional
funds. The Average Cumulative Abnormal Return (ACAR) of SRI funds
was -0.0034 and that of conventional funds was -0.0112. They are both
statistically signiﬁcant at the 1% level, and the diﬀerence between the ACAR
of SRI funds and that of conventional funds is also statistically signiﬁcant at
the 1% level.
The rest of this paper is composed as follows. Previous studies that compared SRI funds with conventional funds are reviewed in Section 2. Section 3
describes the data. Section 4 introduces the event study methodology alongwith a market model that accounts for ARCH eﬀects. Estimated results are
summarized in Section 5. The implication of results are discussed in Section
6. The Section 7 summarizes our ﬁndings.

2

Previous Studies

There exist a considerable number of academic studies that compare SRI andconventional investments. These studies can be divided into two categories.
The ﬁrst category discusses whether or not SRI funds outperform or underperform funds that are not socially screened. The general ﬁnding from thosestudies is that the diﬀerence between SRI funds and conventional funds is notstatistically signiﬁcant, although it depends on the time and area analysed(Renneboog et al., 2008).
Hamilton et al. (1993) is one of the earliest studies to compare the perfor-4

mances of SRI funds and conventional funds. They used the monthly returndata of equity mutual funds in the United States from 1981 through 1990. In
order to measure the performance, they used Jensen’s alpha in their study.
Based on the Capital Asset Pricing Model (hereafter CAPM), Jensen’s alpha measures the performance of the stock relative to the market portfolio(Jensen, 1968). The mean monthly excess return of SRI funds establishedin 1985 or earlier was greater than that of conventional funds, though thediﬀerence between them was not statistically signiﬁcant. As for the funds
established after 1985, the mean excess return of SRI funds was lower thanthat of conventional funds but not at a statistically signiﬁcant level. The
results indicated that the market did not value the non-ﬁnancial beneﬁts of
SRI funds.
Although the market size of SRI is still small relative to the market in US
or Europe, SRI has been developing in the emerging market, too. Cheung etal. (2010) obtained that the average CSR scores among ﬁrms in the Asianmarket such as China, Hong Kong, India and Indonesia has increased over2001 to 2004, which indicates ﬁrms in those countries have exhibited greaterattention to CSR. Moreover, they found positive and statistically signiﬁcantrelationships between CSR score and ﬁrm’s market value in terms of Tobin’s
Q and market-to-book ratio.
For developed countries, similar results were obtained. Bauer et al. (2005)
investigated the performance of SRI funds and that of conventional funds inGermany, the UK, and the US for the 1990 through 2001 period. Unlike
the earlier studies, they included dead funds in the sample. If dead funds
were disregarded in the estimation, the results would be overestimated: this5

is called survivorship bias (Brown et al., 1992). They therefore added deadfunds to the sample in order to mitigate the survivorship bias. They used the
CAPM model and found that, in all regions, there was no statistically significant diﬀerence in performance between SRI funds and conventional funds,
even though most SRI funds outperformed conventional funds in value. In
terms of diﬀerences in exposure to market risk, SRI funds were signiﬁcantly
less sensitive than conventional funds except in the case of the US international mutual funds. They used the multi-factor model introduced by
Carhart (1997) that was developed from the 3-factor model of Fama andFrench (1993). Although SRI funds outperformed to conventional funds inall areas (except Germany) in value, there was again no statistically significant diﬀerence in returns between SRI funds and conventional funds, evenafter controlling for four factors. Moreover, they analysed how people inthree countries have been pricing CSR through time by subtracting Jensen’salpha of conventional funds from that of SRI funds in these four-year periods:
1990-1993, 1994-1997, and 1998-2001. Except in the UK domestic market,
SRI funds signiﬁcantly underperformed conventional funds in the earliest period, but in the third period SRI funds in all areas outperformed conventional
funds. Given these outcomes, it seems that SRI funds have been catching up
on conventional funds, probably as a result of greater investor conﬁdence inthem.
Bollen (2007) raised the interesting question, whether investor behaviours
in SRI funds and conventional funds are diﬀerent: this brings us to thesecond category of studies on SRI. He examined the relation between fundﬂows and return for SRI funds in the US. It was found that SRI funds were6

more sensitive to lagged positive returns than conventional funds, whilst SRI
investors exhibited a smaller response to negative returns than investors inconventional funds for the period 1980 through 2002. Further, he showedthat ﬂow volatility was lower in SRI funds than in conventional funds forthe period 1991 to 2002. In other words, the frequency of SRI investors
moving money into or out of funds was lower compared to conventional fundinvestors. From this it can be concluded that SRI investors were more loyal
than investors in conventional funds.
While Bollen (2007) focused on the single relationship between past returns and money ﬂows for US SRI funds, Renneboog et al. (2006) expanded
the analysis by investigating whether or not the investment decision wasmade not only with past returns in mind but also with other factors suchas fund size, age, risk, and the fee structure. Their main ﬁndings were thatinvestors in SRI funds chased past returns, return rankings, and persistencein performance the same as conventional investors did. Just as Bollen (2007)
had found, investors in SRI funds did not mind negative returns that much
more than positive returns, unless poor performance persisted. In addition,higher money inﬂows were induced by smaller, younger funds or funds belonging to the large-fund families. They also showed that higher intensityof screenings attracted more inﬂows than otherwise: however, some typesof screenings such as environmental screens or ethical screens, lowered cash
ﬂows. On the other hand, the volatility of money ﬂows in SRI funds was
greater than that in conventional funds unless poor performance persisted.
Furthermore, they indicated smaller, younger or riskier SRI funds were associated with a higher magnitude of volatility of money ﬂows than conventional7

funds were.
Benson and Humphrey (2008) provided further insight into SRI investor
behaviour by incorporating both monthly and annual returns in order toinvestigate if investors react to current and/or past information, and also
by incorporating lagged ﬂow to take into account the persistence of fundﬂow. The ﬂow of SRI funds was a negative function of current, past, andlagged returns, unlike the conventional fund ﬂow. This suggested that SRI
investors cared about returns less than their conventional counterparts; thiswould accord with the hypothesis that investors in SRI funds obtain some
additional non-ﬁnancial utility. The lagged ﬂow was signiﬁcantly positiveand its coeﬃcient was larger than that of the conventional one. This meansthat SRI fund ﬂows were more persistent than conventional funds. Therefore, it seems likely that investors in SRI funds reinvest in funds they havealready owned. Benson and Humphrey also investigated the diﬀerences inthe ﬂow-performance relation for the best and worst performing funds. Whileconventional fund investors responded to a good performance greatly but reacted less to a poor performance, SRI fund investors were less sensitive toperformance than conventional fund investors were.
In summary, the earlier studies found that investors do not consider SRI
as ”costs” – at least since there is no diﬀerence in performance between SRI
funds and conventional funds. In terms of investor behaviour, SRI investors
are more loyal than conventional investors, since SRI funds are more sensitive
to lagged positive returns but less so to negative returns. Taking these results
into consideration, we would expect that, even though most countries in
the world experienced a recent signiﬁcant economic downturn, SRI investors8

might hold their funds instead of selling them oﬀ. Further, it is known thatpolitical support for environment-friendly industries has spread, mainly indeveloped countries. Thus we set up a hypothesis that SRI funds can be more
resilient towards a negative impact than conventional funds, and we examine
this hypothesis using the event study methodology. Although Curran and
Moran (2007) used an event study to investigate the impact on corporateﬁnancial performance of inclusion in or deletion from the SRI index, theirfocus was not on evaluating SRI funds compared with other funds. This
study, therefore, is the ﬁrst attempt to use the event study methodology toanalyse the impact of a speciﬁc event on SRI funds and conventional funds
and compare the results.

3

Data

The ﬁrst SRI fund in Japan was launched in 1999 and its history is much
shorter than similar funds in Europe and the US (Social Investment Forum
Japan, 2010a). While investors in SRI funds in Europe and the US arebasically institutional investors, especially in pension funds, in Japan mostinvestment is in the publicly oﬀered SRI funds targeting individual investors.
Figure 1 shows changes in the number of publicly oﬀered SRI funds in Japanand their total net assets in billion US dollars (Social Investment Forum
Japan, 2010b). In the beginning of the SRI market in Japan, there were
only a few funds. Both the number of funds and their total net assets havesteadily been growing, though there was a sudden considerable decrease in2008 due to the ﬁnancial crisis. Total net assets of the SRI funds amount9to 5.4 billion US dollars in 2010; this represents only 0.7% of the Japanesemutual fund market, a smaller share than in Europe and the US, where SRI
funds represent 10% of those mutual fund markets. The main screening has
been directed at the environmental aspect since 2007; it is reported that, asof 2009, 80% of SRI funds are environmentally screened. Although domestic
equity funds made up the mainstream of investment types for many years,
international equity funds have expanded and now account for 60% of SRI
funds in Japan as environment-related funds keep increasing. Sakuma andLouche (2008) summarise the characteristics of Japanese SRI as ”Japan has
adopted a ’soft’ version of European SRI, choosing for engagement rather
than activism, and for positive screening rather than exclusion.”
Figure 2 shows the number of conventional funds and their total net
assets in Japan (The Investment Trusts Association, Japan, 2010). While the
SRI fund market in Japan is still developing, the conventional fund market
seems to have already matured, hence there has been no rapid increase in
the number and net assets of conventional funds. The conventional funds
experienced a slight drop in total net assets, (compared to that of SRI funds),
and their number has been gradually increasing since 2004.
To conduct our analysis, we used data on the value of funds and on themarket portfolio. The daily return data of publicly oﬀered investment trusts
is available from the Investment Trusts Association Japan, which gives asample of 3,824 funds at the end of July 2010. Data on privately oﬀered
investment trusts are unavailable and therefore these were not included inour sample. We used the Social Investment Forum (SIF) Japan classiﬁcation to identify SRI funds, of which there are 89 listed for the same time.

10

Table 1: Sample Numbers
Domestic

International Total

SRI

24

38

62

Conventional

793

1343

2136

Total

817

1381

2198

An additional condition was that the funds had to be surviving during thewhole of the research period, which was from 7th of February through 17thof September in 2008. As a result, our data covers 2,136 conventional funds
62 SRI funds (for these latter, see Appendix A). Funds can be also classiﬁed into domestic or international funds. Domestic funds are mutual funds
that invest stocks and/or bonds of mainly domestic companies, whilst international funds largely invest those of companies outside the country. In
accordance with the criteria, there are 793 domestic conventional funds and
24 domestic SRI funds. International funds have 1343 conventional funds
and 38 SRI funds (See Table 1). In addition, we used the Tokyo Stock Price
Index (TOPIX) obtained from Datastream as the market index.
Table 2 gives the descriptive statistics for the fund returns of SRI andconventional funds. The fund return is calculated as Equation 1 in Section
4. Therefore, each fund has 152 returns in this period. The basic statistics
shows that the average return and standard deviation of both types of funds
were similar in the whole period.

11

Figure 1: The Number of SRI Funds and Total Net Assets in Japan

Table 2: Descriptive Statistics
Observation

Mean

S.D.

Min.

Max.

SRI

9,424

-0.0009067

0.0150-0.0672

0.0661

Conventional

325,128-0.0008833

0.0135-0.1852

0.1131Market proxy152-0.0009978

0.0168-0.05190.041012Figure 2: The Number of Conventional Funds and Total Net Assets in Japan

13

4

Methodology

4.1

Event Study Methodology with OLS

Event study methodology was introduced by Fama et al. (1969) for the purpose of examining the relationship between a particular unanticipated eventand changes in the stock prices. Numerous studies have analysed whether
or not either a positive or a negative CSR-related event has an impact on a
corporation’s share price (Arora, 2001; Gupta and Goldar, 2005; Hamilton,
1995; Takeda and Tomozawa, 2006; Yamaguchi, 2008; Yamaguchi, 2009).
The validity of an event study relies on a few assumptions: the notion ofmarket eﬃciency; the unexpectedness of the event; and the nonexistence ofother events that could aﬀect the share price during the event chosen for analysis (McWilliams and Siegel, 1997). In order to conduct our event study, we
needed to deﬁne the event window, that is, the period examined for changes
in fund prices. We set three days as our event window: the day before theevent, the day of the event, and the day after the event. The event window isnormally set for a period longer than the day of the event in order to include
any changes in the fund price resulting from information leaked before theevent happened, and to include the investment action taken by latecomers
on the day following the event.
Since the Japanese market was closed on 15th September 2008 due topublic holiday, we identify the bankruptcy of Lehman Brothers on 16th of
September 2008 as the event day (designated here as T0 ), designated the lasttransaction day before the event (12th of September) as T−1 , and designatedthe transaction day following the event (17th of September) as T+1 . Ad14

ditionally, we used the fund price data for 150 transaction days before theevent window as our estimation window. Using the following formula, we
calculate the fund returns from fund prices:ri,t = log(Pi,t /Pi,t−1 ),(1)where ri,t is the fund return and Pi,t is the fund price on day t for ﬁrm i.
Next, we need to estimate the normal return, which is the counterfactual
return if the event does not occur. There is an assumption that the return ofthe market proxy (TOPIX in this study) and the return of each fund have alinear relationship. In order to calculate the normal return, αi and βi shouldbe estimated in the market model with data from the estimation window, asshown below:

ri,t = αi + βi rm,t + ϵi,t ,(2)2
where E[ϵi,t ] = 0 and V ar[ϵi,t ] = σ(ϵ; rm,t is the return of the market
i,t )index; αi and βi are unknown parameters. With estimated parameters, thenormal return for each day of the three-day event window can be estimated;
subtracting this from the realized return gives the abnormal return (AR).

ARi,t = ri,t − (α̂i + β̂i rm,t ).

(3)

The cumulative abnormal return (CAR) is calculated after adding theabnormal returns of ﬁrm i for the three-day event window.
15

CARi (T−1 , T1 ) =T1X

ARi,t .

(4)

t=T−1

The CARs can be analysed over the whole sample in the same category,called ACAR (averaged cumulative abnormal return), as follows:

ACAR(T−1 , T1 ) =N
X

CARi (T−1 , T1 )/N.

(5)

i=1

The variance of the averaged cumulative return can be obtained as follows:

V AR[ACAR(T−1 , T1 )] =N
1 Xσ̂ 2 (T−1 , T1 ).
N 2 i=1(6)

Once ACAR is obtained, we need to test the null hypothesis that theevent does not have any impact on the fund returns, by using the following
J-statistics:

J=q

ACAR(T−1 , T1 )1 PN
2
i=1 σ̂ (T−1 , T1 )N2

∼ N (0, 1).

(7)

If we cannot reject the null hypothesis, it becomes meaningless to interpretthe value of ACAR.

4.2

Event Study Methodology with EGARCH

Most earlier studies listed in Section 4.1 used an event study methodologythat does not account for heteroskedasticity. The standard market model
assumes that the residuals of share price are simply white noise. However,16

ﬁnancial time series data such as share prices or the exchange rates generally
have nonconstant variance. An Autoregressive Conditional Heteroskedasticity (ARCH) model (Engle,1982) and a more extended version of the ARCH
model, Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
processes (Bollerslev, 1986) were introduced to account for heteroskedasticity. In several earlier studies, the GARCH model was employed to estimate
time-varying conditional variance, but it has some limitations (for example, it imposes the nonnegative restriction on the estimators). On the other
hand, the Exponential General Autoregressive Conditional Heteroskedasticity (EGARCH) model introduced by Nelson (1991) does not assume thenonnegative constraint when using a natural logarithm, so it is superior to
the GARCH model since the nonnegative conditions are often violated byestimators. We use the EGARCH (1,1) model to conﬁrm that the result
from OLS methodology is robust. In the same manner as in the OLS model,
parameters must be estimated to calculate the normal return. The error
term is divided into the independent white noise and the standard error:

ri,t = αi + βi rm,t + ϵi,t ,where ϵi,t =(8)qhi,t υi,t . The variance of the standard error, called the condi-

tional variance, can be shown as¯¯¯¯¯ ϵi,t−1 ¯ϵ¯¯ + α2,i q i,t−1 + βi log(hi,t−1 ),log(hi,t ) = ωi + α1,i ¯ q¯¯ hi,t−1 ¯hi,t−1(9)where ϵi,t |Ωt ∼ N (0, hi,t )and Ω is the information set at time t on which the
distribution of errors is assumed to be conditioned. This is well known as17the conditional variance equation in the EGARCH (1,1) model. The abnormal returns, the cumulative abnormal returns, and the averaged cumulative
abnormal returns are estimated in the same manner as in OLS.
In order to obtain the standardized residual terms, we need to calculate
the conditional variance in each three-day event window for ﬁrm i using
estimated parameters in Equation (9) and using data from the estimation
window. Once the conditional variances for each event window are calculated
for ﬁrm i, we can take the exponential for each of them and ﬁnd the averageover the three-days, and then we can obtain the averaged conditional variancefor ﬁrm i as follows:h̄i (T−1 , T1 ) =exp(ĥi,T−1 ) + exp(ĥi,T0 ) + exp(ĥi,T1 )
.
3

(10)

The variance of the averaged cumulative return can be obtained as follows:

V AR[ACAR(T−1 , T1 )] =N
1 X
h̄i (T−1 , T1 ).
N 2 i=1(11)

Finally, we need to test the null hypothesis that the event does not have
any impact on the fund returns, by using the following J-statistics:

J=q

ACAR(T−1 , T1 )1 PN
i=1 h̄i (T−1 , T1 )N2

18

∼ N (0, 1).

(12)

5

Empirical Results

5.1

Results with OLS

We estimate the ACARs for the group of SRI funds and the group of conventional funds. In this study, each ACAR shows the degree of impact of
the Lehman Brothers bankruptcy on the return. The ACAR of SRI funds is-0.0034 and that of conventional funds is -0.0112, as shown in Table 3. They
are both statistically signiﬁcant at the 1% level. Therefore, we can reject thenull hypothesis that the event did not have any eﬀect on the funds. As can beseen from the results, the Lehman Brothers collapse did have a negative impact on both types of fund. Still, SRI funds obviously have more resilience
towards the event. The diﬀerence in the ACARs between SRI funds andconventional funds is statistically signiﬁcant at the 1% level.
In order to analyse how serious this negative shock was, we would haveto compare the obtained ACARs with other event studies. Unfortunately,
there have been no other event studies using fund data that we know of.
Comparison of the impact of the ﬁnancial crisis on SRI funds with otherevents that might aﬀect the returns of SRI funds would require further study.

5.2

Results with EGARCH

If data contains an ARCH eﬀect, it means the data has heteroskedasticity. We
conducted an ARCH-LM test for all of the data and found that 34 out of 62
SRI funds and 1,003 out of 2,139 conventional funds have ARCH eﬀects. (Theresults of the ARCH-LM test for SRI funds are shown in Appendix B). Since
it is conﬁrmed that there exists an ARCH-eﬀect in a considerable number of19

Table 3: Comparisons of ACAR
The Type of FundOLS

EGARCH-0.0034*** -0.0024**(-3.0408)(-1.7236)-0.0112*** -0.0110***
Conventional Fund (-56.5757) (-41.3268)
0.0078*** 0.0086***
Diﬀerence(6.5642)(5.3272)
SRI Fund***=Signiﬁcant at 1%. **=Signiﬁcant at 5%.
Numbers in parentheses and square brackets are

J statistics and t statistics respectively.

funds, we also analysed the data using the EGARCH (1,1) model. As with the
OLS model, we estimated the ACARs for both SRI funds and conventional
funds. We found that the ACAR of SRI funds is -0.0024, which is statisticallysigniﬁcant at the 5% level. On the other hand, the ACAR of conventional
funds is -0.0110, which is statistically signiﬁcant at the 1% level. Here again,
we can reject the null hypothesis that the Lehman Brothers collapse did
not have any eﬀect on fund performance. Both SRI and conventional funds
suﬀered from that company’s bankruptcy, though the degree of impact on
SRI funds is much lower than that on conventional funds, and its diﬀerenceis statistically signiﬁcant at the 1% level.

6

Discussion

Why was the impact of ﬁnancial crisis on SRI funds smaller than that onconventional funds? One possible reason is that SRI investors might havesupposed that a company aiming at CSR would be one that has a long-term

20strategy. They would then believe that such a ﬁrm could be more likely
to come through the ﬁnancial crisis. It is consistent with the idea that theactivity of CSR is a factor that could bring a stable and growing development
for ﬁrms (Scalet and Kelly, 2010). Hence, they would have been less inclined
to sell oﬀ their funds on the day of the bankruptcy of the Lehman Brothers.
This section discusses the estimated result in terms of two other aspects that
can inﬂuence the size of impact: any possible diﬀerences of estimated result
between domestic and international funds, and maturity of funds.

6.1

Domestic and International Funds

Funds can be classiﬁed into domestic or international funds. Domestic funds
are mutual funds that invest stocks and/or bonds of mainly domestic companies, whilst international funds largely invest those of companies outside
the country. If investors behave diﬀerently towards domestic SRI funds andinternational SRI funds, this might result in diﬀerent response to the shockby these funds.
As shown in Table 4, we sorted the whole sample out domestic funds
and international funds. We estimated the ACARs for the group of domestic
funds and the group of international funds since they could perform diﬀerently. For domestic funds, the ACAR of SRI funds is estimated lower thanthat of conventional funds by both of OLS and EGARCH methods although
the diﬀerence between two funds are not statistically signiﬁcant by OLS.
However, the ACAR of international SRI funds are less negatively aﬀectedby the Lehman Brother’s bankruptcy than that of international conventional
funds and their diﬀerence is statistically signiﬁcant, which is similar result
21

Table 4: Comparisons of ACAR: Domestic Funds and International Funds
Domestic
OLS

EGARCHInternational
OLS

EGARCH-0.0015*** -0.0016*** -0.0045*** -0.0003*(-2.7269)(-5.9867)(-2.5418)(-1.3304)-0.0002-0.0002* -0.0178*** -0.0175***
Conventional Fund (-1.1822)(-1.3242) (-60.7034) (42.3994)-0.0013-0.0014*0.0133*** 0.0172***
Diﬀerence(-1.1078)(-1.4190)(7.5220)(6.9517)
SRI Fund***=Signiﬁcant at 1%. **=Signiﬁcant at 5%. *=Signiﬁcant at 10%.
Numbers in parentheses and square brackets are

J statistics and t statistics respectively.

to the one estimated with the whole sample. This result might indicate that
SRI investors value CSR related strategies of foreign companies than that ofdomestic companies although it is diﬃcult to make a deﬁnitive interpretation about this result as the ratio of international stocks in the fund varies
considerably.

6.2

Fund Age

Another possibility is that investors might have been inﬂuenced by fundattributes, in particular fund age. Renneboog et al. (2006) found that moremature funds attracted less money ﬂow and also induced less volatility. The
expectations about a younger fund by a Bayesian investor would be morediversiﬁed, so the younger fund would attract a higher money ﬂow (Bollen,2007). The obvious conclusion one can come to is that fund age should betaken into account when comparing SRI funds and conventional funds. As
can been seen in Table 5, the mean age of the SRI funds in our study is
22

Table 5: Fund Age Comparison (days)
Mean

S.D.

Min

Max

Range

SRI

1819.435

893.6856

953

3998

3045

Conventional

2914.868

3616.139

906

151193150287much younger than that of the conventional funds, since the conventional
fund market has a much longer history.
Consequently, it is easy to suspect that the diﬀerence in the ACARs
result not because SRI funds are more resilient than conventional funds but
because SRI funds are younger on average than conventional funds. And
yet, there is no clear correlation between abnormal return and the maturityof fund as correlation coeﬃcient between those of SRI fund is -0.0166 andof conventional fund is 0.2094 (Figure 3 and 4). Therefore, the reason that
SRI funds were more resilient towards the ﬁnancial crisis might be because
investors evaluated the companies included in SRI funds positively, and sothey expected the funds would survive the critical situation.

23

Figure 3: AR and Age of SRI Funds

24Figure 4: AR and Age of Conventional Funds

25

7

Conclusion

This study examined the resilience of SRI funds relative to conventional
funds towards the global ﬁnancial crisis in the Japanese market, making
use of event study methodology. We chose the bankruptcy of the Lehman
Brothers because it is known as the trigger of this greatest ﬁnancial crisis
since the Great Depression in 1929. The empirical results showed the event
signiﬁcantly had a negative impact on both groups of funds at the 1% level.
The ACAR for SRI funds was much smaller in absolute value than that of
the conventional funds and its diﬀerence is statistically signiﬁcant at the
1% level. We conﬁrmed that the results are robust by using the EGARCH
processes to account for the heteroskedasticity. These results show that the
SRI funds are more resilient than conventional funds towards the bankruptcyof the Lehman Brothers.
SRI investors might consider a corporation aiming at CSR as one with along-term management strategy. They therefore expect such ﬁrms more likely
to survive a ﬁnancial crisis than others less interested in CSR. We classiﬁed
both SRI and conventional funds into domestic and international funds andestimated the ACARs of them. In the subgroup of domestic funds, the ACAR
of SRI funds was more aﬀected by the bankruptcy of Lehman Brothers. On
the other hand, the ACAR of international SRI funds was smaller in absolutevalue than that of conventional funds, which was similar result to the wholesample. In addition, we also analysed the correlation between fund age andabnormal return, since previous studies argues that the maturity of a fundaﬀects fund ﬂow and volatility. However, abnormal return and fund age were
not correlated in the case of either type of fund.
26

In future studies, other events could be examined in order to ascertain
how serious the Lehman Brothers bankruptcy was. Comparison of the impact of the ﬁnancial crisis on SRI funds with other events, using data fromother countries as well would provide useful information. Fund data in the
United States market could be analysed with the same methodology, since
the ﬁnancial crisis was triggered by defaults on subprime loans in the US.
Such studies might lead to some interesting comparison of the level of impact
on SRI funds in Japan with SRI funds elsewhere in the world.

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31

Appendix A: The list of SRI funds used for our analysis
Fund

Name of fundStock companies

Date

ID

established1

Nikko Eco Fund

Nikko Asset Management

20 Aug 1999

2

Nenkin Tsumitate Eco Fund

Nikko Asset Management

31st Oct 2001

3

Sompo Japan Green OpenSompo Japan

30 Sep 1999

4

Eco Partners

Mitsubishi

UFJ

Trust

and

28 Jan 2000

Asahi Asset Life Management

28 Sep 2000

Banking5Asahi Life SRI Shakai Kouken FundCo., Ltd.
6

Sumishin SRI Japan OpenThe Sumitomo Trust and Banking

26 Dec 2003

Co., Ltd.
7

Sumishin DC Good Company

The Sumitomo Trust and Banking

27 Feb 2004

Co., Ltd.
8

Fukoku SRI Fund

Shinkin Asset Management Co.,

27 Feb 2004

Ltd.
9

Daiwa SRI Fund

Daiwa Asset Management

20 May 200410

DC Daiwa SRI Fund

Daiwa Asset Management

20 July 2004

11

Mitsubishi UFJ SRI Fund

Mitsubishi

UFJ

Trust

and

3 Dec 2004

Investments

Japan

18 Mar 2005

Investments

Japan

18 Mar 2005

Banking
12

SAIKYO Nihon Kabushiki CSR Fund

PineBridge
Co., Ltd.

13

Risona Japan CSR Fund

PineBridge
Co., Ltd.

14

Sompo Japan SRI OpenSompo Japan

15

PineBridge Hirogin Nihon Kabushiki

PineBridge

16

25 Mar 2005
Investments

Japan

28 Apr 2005

CSR FundCo., Ltd.

Nihon SRI OpenOkasan Asset Management Co.,

12 Aug 2005

Ltd.
17

Daiwa Eco Fund

Daiwa Asset Management

9 Mar 2006

18

Sumishin Nihon Kabushiki SRI FundThe Sumitomo Trust and Banking

12 Jun 2006

Co., Ltd.

32

19

Amundi Risona Woman J Fund

AmundiAsset

Management

30 May 2006

Chuo Mitsui Asset Management

30 Nov 2006

Japan
20

Chuo Mitsui Shakaiteki Sekinin FundCo., Ltd.
21

Shinkin SRI Fund

Shinkin Asset Management Co.,

8 Dec 2006

Ltd.
22

23

STAM SRI Japan Open (only for

The Sumitomo Trust and Banking

SMA)

Co., Ltd.

PineBridge Nihon Kabushiki SRI Fund

PineBridge

16 Feb 2007

Investments

Japan

20 Dec 2007

MitsuiAsset

31 Oct 2000

Co., Ltd.
24

Eco Balance

Sumitomo

Management Co., Ltd.
25

Nikko Global Sustainability Fund A

Nikko Asset Management

17 Nov 2000

Nikko Asset Management

17 Nov 2000

GlobalNikko Asset Management

25 Oct 2001

GlobalNikko Asset Management

25 Oct 2001

Nomura Asset Management

26 Mar 2004

Nomura Asset Management

26 Mar 2004

(without hedge)
26

Nikko Global Sustainability Fund B(with hedge)

27

NenkinTsumitate

Sustainability (without hedge)
28

NenkinTsumitate

Sustainability (with hedge)
29

World Water Fund A Course (withcurrency hedge)

30

World Water Fund B Course (without
currency hedge)

31

Nomura Global SRI 100

Nomura Asset Management

28 May 2004

32

Nomura Sekai SRI Index Fund (forNomura Asset Management

30 July 2004

Chikyu Ondanka Boushi Kanren Kabu

Shinko Asset Management Co.,

30 May 2006

Fund

Ltd.

34

Nikko DWS New Resource Fund

Deutsche Asset Management

20 Dec 2006

35

Global Water Fund

Nikko Asset Management

15 June 2007

36

New Generation Sekai Kankyo

United Investments Co., Ltd.

29 June 2007

defined contribution pension fund)
33

33

37

38

Chikyu Ondanka Boushi Kanren Kabu

Shinko Asset Management Co.,

Fund (3-month closing type)Ltd.

Mitsubishi UFJ Global Eco Water

Mitsubishi

UFJ

Trust

and

25 July 2005

27 July 2007

Banking
39

Nomura Aqua Toushi A Course (withNomura Asset Management

29 Aug 2007

Nomura Asset Management

29 Aug 2007

UBS Global Asset Management

31 Aug 2007

Kokusai Asset Management Co.,

31 Aug 2007

exchange hedge)
40

NomuraAqua

ToushiB

Course(without exchange hedge)
41

UBS Chikyu Ondanka Taiou Kanren
Kabu Fund

42

Ondanka Taisaku Kabushiki Open

Ltd.
43

Chikyu Ondanka Taisaku Kabushiki

Kokusai Asset Management Co.,

Open

Ltd.

44

Chikyu Kankyo Kabu Fund

Daiwa Asset Management

31 Aug 200745

DWS Shinshigen Technology Fund

Deutsche Asset Management

31 Aug 2007

46

Ondanka Boushi Kankyo Kanren Kabu

Okasan Asset Management Co.,

27 Sep 2007

Open

Ltd.

47

Fidelity Three Basic Fund

Fidelity Investments Limited

29 Oct 2007

48

Tokyo Kaijo Select Sekai Kabushiki

Tokio Marine Asset Management

6 Dec 2007

FundCo., Ltd.

Amundi Sekai Mizukanren Kabushiki

Amundi

49

50

Asset

31 Aug 2007

Management

17 Dec 2007

Fund

Japan

TA Clean Energy Fund

Toyota Asset Management Co.,

20 Dec 2007

Ltd.
51

52

Amundi

Sekai

Kankyoryoku

AmundiAsset

Management

21 Dec 2007

Kabushiki FundJapan

DIAM Koukakuzuke Income Open

DIAM Co., Ltd.

22 Dec 2005

Daiwa Asset Management

14 Mar 2006

Daiwa Asset Management

14 Mar 2006

SRI (monthly closing type)53

6

ShisanBalanceFund(distribution-type)54

6 Shisan Balance Fund (growth-type)

34

55

Shizen Kankyo Hogo Fund

DIAM Co., Ltd.

26 May 2006

56

Sekai 6Shisan Kintou Bunsan Fund

Daiwa Asset Management

28 June 2006

Daiwa Asset Management

27 Sep 2006

(monthly distribution-type)57”Shigagin” SRI 3Shisan Balance Open
(distribution-type in the odd months)

58

Amundi

Womenomics

BalanceAmundi

Kabushiki

30(monthlyJapan

Womenomics

BalanceAmundiAsset

Management

19 Jan 2007

Asset

Management

19 Jan 2007

distribution-type)
59

60

Amundi

Kabushiki 30 (active growth)Japan

Chikyu Kankyo Kabu Gaisai Balance

Daiwa Asset Management

31 Aug 2007

Shinko Asset Management Co.,

14 Dec 2007

Fund
61

Kankyo Hozen Global Balance

Ltd.
62

Amundi Risona Sekai Green Balance

Amundi

Fund

Japan

35

Asset

Management

21 Dec 2007

Appendix B: ARCH-LM Test for SRI Funds
ID

ARCH

Significance

ID

ARCH

Significance10.96606732

15.87687***

2

1.027735

33

16.22302***

32.6864634

7.315012***

4

1.402577

35

3.2449*50.01011236

1.531446

60.525505

37

16.2176***70.471471

38

5.985241**8

1.227087

39

3.641264*90.116404

405.598984**

100.087552

41

6.926547***

110.0021142

16.0997***12

1.58285743

16.04057***

13

0.94806644

19.68416***140.16351245

7.191673***

15

1.650385

46

0.436857

160.90185747

6.381472**

170.044793

48

29.76349***

18

0.061683

49

33.6517***19

0.0363450

0.752861

20

0.040993

51

24.56617***21

1.19708952

17.05208***

22

0.695522

53

3.056855*

230.66122554

0.630496

24

0.08215855

23.842152525.51617***

56

0.096191

26

25.48944***

57

9.647576***27

11.17471***

58

20.62302***28

12.13686***

595.670033**

29

5.405308**60

20.79893***

30

9.281398***61

16.46026***31

15.70286***62

24.95287*******=Significant at 1%, **=Significant at the 5%, *=Significant at 10%.

36***