RESEARCH ARTICLE
Low ca bon ansi ion isk in mu ual und po olios:
Manage ial in ol emen and pe o mance e ec s
Juan C. Rebo edo
1
| Luis A. O e o González
2
1
Depa men o Economics, Uni e sidade de
San iago de Compos ela, San iago de
Compos ela, Spain
2
Depa men o Finance and Accoun ing,
Uni e sidade de San iago de Compos ela,
San iago de Compos ela, Spain
Co espondence
Luis A. O e o González, Depa men o
Finance and Accoun ing, Uni e sidade de
San iago de Compos ela, A da. Xoán XXIII,
s/n, 15782 San iago de Compos ela, Spain.
Email: [email p o ec ed]
Funding in o ma ion
Spanish Agencia Es a al de In es igacion,
G an /Awa d Numbe : RTI2018-100702-B-
I00; Xun a de Galicia, G an /Awa d Numbe s:
ED431C 2019/11, ED431C 2020/18
Abs ac
T ansi ioning o a low-ca bon economy o mi iga e he e ec s o clima e change
in ol es isks. We in es iga e he e ec s o manage ial owne ship and
managemen on he low ca bon ansi ion isk o mu ual und po olios and he
e ec s o low ca bon ansi ion isk on mu ual und pe o mance and lows.
Using low ca bon ansi ion isk a ings based on he unmanaged ca bon isk o
he companies included in und po olios, we ind ha manage ial owne ship and
he socially esponsible ocus o he und educe und po olio exposu e o
ca bon isk, whe eas ac i e managemen has he opposi e e ec . Fu he mo e,
we ind ha unds wi h low ca bon ansi ion isk p oduce a be e isk-adjus ed
pe o mance a e mo e sensi i e o ail isks and exhibi a be e und low
pe o mance.
KEYWORDS
ca bon ansi ion isk, manage owne ship, mu ual und lows, mu ual und pe o mance,
mu ual unds, socially esponsible in es men
1|INTRODUCTION
Mi iga ing he ad e se e ec s o clima e change equi es he ansi-
ion o a low-ca bon economy which, in u n, con eys speci ic isks
ha a e acqui ing p io i y in manage ial decision-making by ins i u-
ional in es o s (K uege e al., 2020; Mo nings a , 2018).
1
Manage s
a e acing p essu e om s akeholde s o ackle und po olio
exposu e o he long- e m en i onmen al and egula o y isks implied
by he ansi ion o a deca bonized economy.
2
In his a icle, we examine how he in ol emen o manage s—as
owne s and decision-make s—a ec s he ca bon isk embedded in
mu ual und po olios and how, in u n, his low ca bon ansi ion isk
exposu e impac s mu ual und pe o mance and lows. Examining he
d i e s behind, and impac o , mu ual und exposu e o low ca bon
ansi ion isks is o in e es o wo main g oups: (a) in es o s in e -
es ed in esilien in es men s, who, in he ace o long- e m shi s o a
deca bonized economy, equi e in o ma ion ha adequa ely e lec s
1
Se e al ini ia i es ha e ecen ly been launched in o de o achie e a g ea e commi men o
low-ca bon in es men by ins i u ional in es o s. The Po olio Deca boniza ion Coali ion
(PDC) was co- ounded in 2014 by he Uni ed Na ions En i onmen P og amme (UNEP), he
UNEP Finance Ini ia i e (UNEP FI), AP4, Amundi and CDP. Likewise, he Mon eal Ca bon
Pledge, launched in 2014, aims o encou age ins i u ional in es o s o commi o he
measu emen and disclosu e o hei ca bon oo p in , p omo e po olio deca boniza ion and
epo ca bon in o ma ion in po olio design as a means o acili a e in es men s a he
se ice o he ansi ion o a low-ca bon economy.
2
Those isks include, among o he s, ail isks om na u al disas e s ela ed o clima e change
(e.g. loods, d ough s and s o ms, ising sea le els and inc easing empe a u es) as well as he
isk o s anded asse s. A ound 1300 mu ual und amilies a e exposed o asse s anding isk,
ep esen ing a ound 24% o he ne asse alue o mu ual unds domiciled in he
Uni ed S a es (Shakdwipee, 2017). Pension unds a e also e y exposed on he asse side
because hei holdings a e in es ed in long-du a ion po olios wi h impo an weigh ings in
ca bon-in ensi e indus ies (Messe y, 2016).
Recei ed: 15 July 2021 Re ised: 28 Sep embe 2021 Accep ed: 12 Oc obe 2021
DOI: 10.1002/bse.2928
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s use, dis ibu ion and ep oduc ion in any medium,
p o ided he o iginal wo k is p ope ly ci ed.
© 2021 The Au ho s. Business S a egy and The En i onmen published by ERP En i onmen and John Wiley & Sons L d.
950 Bus S a En . 2022;31:950–968.wileyonlinelib a y.com/jou nal/bse
clima e isks and oppo uni ies a ec ing asse alloca ion, and
(b) policymake s conce ned wi h he ealloca ion o p i a e and public
unds o low-ca bon economic ac i i ies.
3
We i s examine he ela ionship be ween manage ial issues and
und po olio low ca bon isk, speci ically whe he manage ial co-
in es men a ec s he low ca bon isk le el o he und po olio.
Jensen and Meckling (1976), Smi h and S ulz (1985) and Ma and
Tang (2019) show ha manage ial owne ship is a mechanism ha alle-
ia es agency con lic s, leading o a lowe le el o po olio isk when
manage s a e isk-a e se. In in es ing hei weal h, he e o e, we can
expec such manage s o lowe all kinds o und isks—including ca -
bon isk, ha is, i manage s a e isk-a e se, we can expec a nega i e
ela ionship be ween manage ial owne ship and po olio ca bon isk.
We also explo e wha ole managemen eam size plays in shaping he
po olio ca bon isk, as Pa el and Sa kissian (2017) show ha eam-
managed unds a e less exposed o isk han single-managed unds. In
addi ion, we analyse he ela ionship be ween he ca bon isk expo-
su e and he social conce ns o und manage s, as e lec ed in socially
esponsible in es men (SRI). Al hough p e ious s udies (e.g. Bo ge s
e al., 2015; Du an e al., 2019; El Ghoul & Ka oui, 2017; Ibikunle &
S e en, 2017; Riedl & Smee s, 2017) show mixed e ec s o SRI
impac on mu ual und pe o mance, we expec ha il ing in es -
men s using social conside a ions will ha e a posi i e e ec in educ-
ing po olio ca bon isk exposu e. Finally, since ac i e managemen
has been shown o ha e an impac on und pe o mance ha depends
on speci ic ma ke condi ions (e.g. C eme s e al., 2016; Pás o
e al., 2015), we expec ha selec i e and ac i e und managemen
will ha e po en ial e ec s on exposu e o ca bon isk. Acco ding o
Tan e al. (2019), he cons uc ion o po olios wi h a low ca bon isk
should achie e good pe o mance in he long e m once he e ec o
he isk is ecognized by he ma ke . We he e o e elucida e whe he
ac i e und managemen , which allows manage s o selec s a egies
acco ding o ca bon isk exposu e, leads o lowe o highe ca bon isk
o he und po olio.
In con as o p e ious s udies ha use ca bon emissions as a
p oxy o low ca bon isk, we use ca bon isk a ings, which a e com-
pu ed on he basis o he unmanaged ca bon isk emaining in a com-
pany a e all ac ions by he company o mi iga e ca bon isk exposu e
a e aken in o conside a ion. Those unmanaged ca bon isks a e a ed
by Sus ainaly ics wi h a ca bon isk sco e (CRS) calcula ed, om low
o high, as negligible (0), low (0–10), medium (10–30), high (30–50)
and se e e (g ea e han 50).
4
Thus, he CRS p o ides in o ma ion o
he ulne abili y o he i m's alue o ansi ion o a low-ca bon econ-
omy. On he basis o his in o ma ion, Mo nings a Di ec Mu ual
Fund
5
p o ides in es o s wi h in o ma ion on he ca bon isk
embedded in mu ual und po olios as a weigh ed sum o he
Sus ainaly ics ca bon isk a ings, wi h weigh s de e mined by he
po olio sha e o he company. The Mo nings a po olio CRS a -
ings, publicly made a ailable o in es o s on a qua e ly basis, can be
used o se a baseline o assessmen o he und's capaci y o manage
ca bon isk. Con a y o he po olio ca bon oo p in me ic, which
only assesses und exposu e o ca bon emissions, he Mo nings a
CRS me ic p o ides accu a e in o ma ion on ac ual ca bon isk expo-
su e; hus, a po olio wi h a low CRS is be e posi ioned o ansi ion
o a deca bonized economy han a po olio wi h a high CRS.
Fo a sample o 1223 US domes ic equi y mu ual unds wi h po -
olios CRS- a ed by Mo nings a Di ec Mu ual Fund each qua e
o e he pe iod Janua y 2017 (when he CRS me ic s a ed o be
compu ed) o Decembe 2018, we documen ha he po olio CRS
dec eases as manage ial owne ship inc eases; ha is, und po olios
wi h g ea e manage ial owne ship s akes a e embedded wi h lowe
po olio ca bon isk. Fu he mo e, ou empi ical es s con i m ha
eam size is no ela ed o und po olio ca bon isk; ha is, he num-
be o und manage s does no a ec in es men decisions ega ding
ca bon isk. No su p isingly, we ind ha social sc eening—as
e lec ed in he SRI ocus o he und—has a nega i e e ec on he
und po olio CRS, indica ing ha SRI p ac ices a e consis en wi h
educed exposu e o low ca bon ansi ion isks. Finally, ou e idence
indica es ha ac i e und managemen , measu ed by he in e se o R-
squa ed (Amihud & Goyenko, 2013), inc eases he CRS o he und in
he subsequen yea /qua e . This is consis en wi h he idea ha
ac i e und managemen pu sues sho - e m p o i s and, conse-
quen ly, ou weighs ca bon-in ensi e businesses in po olios, he eby
inc easing he po olio's exposu e o ca bon ansi ion isks.
We also examine whe he he CRS shapes und pe o mance and
lows by analysing how he CRS a ec s isk-adjus ed und e u ns
pe o mance. P e ious esea ch (Bo ge s e al., 2015; Ibikunle &
S e en, 2017) sugges s ha unds wi h g ea e exposu e o socially
sensi i e s ocks show a poo e isk-adjus ed pe o mance. In consid-
e ing ca bon isk managemen , ou empi ical esul s indica e ha man-
age s e ec i ely ackle ca bon isk in hei manage ial decisions in
such a way ha he CRS is nega i ely ela ed o nex -qua e isk-
adjus ed und pe o mance. This esul , which holds a e con olling
o di e en und cha ac e is ics and model speci ica ions, shows ha
unds dealing wi h low ca bon ansi ion isks a e unlikely o expe i-
ence impai ed p o i abili y. We also analyse he ela ionship be ween
he CRS and und e u ns ola ili y, inding ha unds wi h lowe CRS
a ings a e associa ed wi h signi ican ly lowe e u ns ola ili y in he
nex yea /qua e . We also ind ha unds wi h lowe CRS a ings
consis en ly display lowe le els o ma ke isk exposu e and co-skew-
ness. This e idence is in line wi h he idea ha unds conce ned wi h
isk managemen a e also ackling low ca bon ansi ion isks in hei
managemen decisions. In ega d o downside isk, howe e , we ind
ha und po olios wi h low CRS a ings a e mo e sensi i e o ma ke
3
The Uni ed Na ions Clima e Change Con e ence o Pa is 2015 speci ically d ew a en ion o
he impo ance and need o channel inancial esou ces owa ds economic ac i i ies ha
ans o m he p oduc i e s uc u e o economies in o low-g eenhouse-gas-emission
economies. The In e na ional Ene gy Agency es ima es ha , in he ene gy sec o alone,
in es men amoun ing o USD37 illion will be needed by 2035, so in es men s lows need
o be edi ec ed om high-ca bon echnologies a g ea e isk o low-ca bon echnologies
(Schmid , 2014).
4
h ps://www.sus ainaly ics.com/
5
h ps://www.mo nings a .com/
REBOREDO AND OTERO GONZ
ALEZ 951
ail isk han unds wi h po olios wi h highe CRS a ings. Thus, und
po olios wi h educed exposu e o low ca bon ansi ion isks o e
be e isk-adjus ed e u ns, bu hey do so a he cos o less p o ec-
ion agains ail isks. Finally, in line wi h Rebo edo and O e o (2021),
we examine he ela ionship be ween he CRS and lows, inding ha
he CRS o und po olios is nega i ely ela ed o und lows, which
indica es ha in es o s a e aking ca bon isk le els in o accoun in
hei in es men decisions.
Ou s udy con ibu es o se e al s ands o he ex an li e a u e
on mu ual unds. Fi s , we p o ide insigh s on manage ial owne ship
and isk- aking in he unds sec o . Kho ana e al. (2007), E ans (2008),
Fu and Wedge (2011) and Ma and Tang (2019) show ha manage ial
owne ship educes isk- aking and imp o es po olio pe o mance.
Simila ly, Ka agiannis and Tolikas (2019) show ha und manage s
who isk hei own capi al a e less likely o assume ail isk. By consid-
e ing ca bon isk managemen , ou a icle complemen s p e ious s ud-
ies ha epo ha manage ial owne ship aligns manage s' isk- aking
incen i es, as unds wi h g ea e manage ial owne ship a e associa ed
wi h mi iga ed low ca bon ansi ion isk.
Second, we con ibu e o he li e a u e ha con ends ha eam
managemen shapes po olio isk and pe o mance (Ba e al., 2011;
Bliss e al., 2008; Pa el & Sa kissian, 2017; P a he &
Middle on, 2002). Consis en wi h mos s udies epo ing ha eam-
managed unds pe o m no be e han single-managed unds, ou e i-
dence shows ha eam size is no decisi e in de e mining he ca bon
isk le el o a und po olio.
Thi d, ou s udy is b oadly ela ed o he SRI mu ual und li e a-
u e, gi en ha ca bon isk managemen in ol es he sc eening o
companies acco ding o SRI unde akings in ela ion o ca bon isk
managemen . Unlike p e ious s udies on he e ec s o SRI on und
pe o mance ha epo mixed esul s (see, among o he s,
Bollen, 2007; Jolie & Ti o a, 2018; No singe & Va ma, 2014;
Renneboog e al., 2008, 2011), in examining whe he he SRI na u e
o a und leads manage s o educe ca bon isk exposu e, we ind ha
unds commi ed o SRI also ha e po olios wi h educed low ca bon
ansi ion isks.
Fou h, we con ibu e o he li e a u e on ac i e po olio man-
agemen (Amihud & Goyenko, 2013; C eme s & Pe ajis o, 2009;
Kacpe czyk e al., 2008; Pás o e al., 2015) by epo ing e idence ha
ac i ely managed unds shape low ca bon ansi ion isks, in ha
unds wi h lowe R-squa ed alues pe o m poo ly in e ms o po o-
lio ca bon isk managemen . O e all, ou e idence shows ha mana-
ge ial ea u es a e ele an o shaping und po olio CRS.
Finally, ou s udy i s wi hin he lou ishing li e a u e on he
e ec s o low ca bon sc eening on po olio pe o mance. Se e al
s udies ha e explo ed how hedging clima e isk a ec s po olio pe -
o mance, showing ha educing ca bon exposu e does no seem o
impai po olio pe o mance (see, e.g. Ande sson e al., 2016; De
Jong & Nguyen, 2016; Ji e al., 2021; T inks e al., 2018). Ibikunle and
S e en (2017), in con as , show ha g een mu ual unds signi ican ly
unde pe o m ela i e o con en ional unds, while Rebo edo
e al. (2017) and Ma i-Balles e (2019) show ha in es o s pay a p e-
mium o going g een ia enewable ene gies. Di e ing om hose
s udies, we explo e whe he accoun ing o ca bon isk managemen
is likely o ha e de imen al e ec s on he po olio pe o mance o
mu ual unds, concluding ha a educed low ca bon ansi ion isk has
a ou able e ec s on isk-adjus ed pe o mance. This e idence is con-
sis en wi h ha o Dimson e al. (2015), who ind ha engaging in
en i onmen al o social issues enhances he accoun ing pe o mance
o US public companies.
The emainde o he pape is laid ou as ollows. Sec ion 2
desc ibes da a, a iable de ini ions and desc ip i e s a is ics. Sec ion 3
explo es he impac o manage ial a iables on he CRS o mu ual und
po olios and desc ibes a obus ness analysis. Sec ion 4 discusses he
e ec o po olio CRS on mu ual und pe o mance and lows and
he co esponding obus ness analysis. Finally, Sec ion 5 summa izes
ou esul s and concludes he pape .
2|DATA, VARIABLE DEFINITIONS AND
DESCRIPTIVE STATISTICS
This sec ion desc ibes a sample o equi y mu ual unds ha ha e po -
olios wi h CRS a ings and also he a iables used o s udy de e mi-
nan s and he e ec s o und po olio exposu e o ca bon isk.
2.1 |Da a
Since 2017, he Mo nings a Di ec Mu ual Fund da abase has p o-
ided an assessmen o he ca bon ansi ion isk embedded in a und
po olio in he o m o a CRS. This me ic is compu ed on a qua e ly
basis as an asse weigh ing o he Sus ainaly ics ca bon isk a ing o
companies included in he und po olio. Sus ainaly ics compu es his
a ing on he basis o (a) he company's exposu e o ca bon isk, de e -
mined by he kind o business, ope a ions and p oduc s and se ices
o he company; and (b) he company's ca bon isk managemen ,
which e lec s i s abili y o manage ca bon isks such as ca bon emis-
sions, ene gy e iciency and g eene p oduc s and se ices. Acco d-
ingly, Sus ainaly ics assigns ca bon isk a ings depending on
unmanageable ca bon isks ha emain a e aking in o accoun man-
agemen ac ions designed o diminish ca bon isk exposu e. As men-
ioned abo e, he CRS is based on i e ca bon isk ca ego ies, anging
om negligible isk (0) o maximum isk (g ea e han 50). On he basis
o ca bon isk in o ma ion om Sus ainaly ics, Mo nings a p o ides
in es o s wi h in o ma ion on he exposu e o a mu ual und po olio
o low ca bon ansi ion isk by epo ing he CRS, compu ed as a
weigh ed sum o a company's Sus ainaly ics CRS a ing, wi h weigh s
de e mined by he po olio sha e o he company.
6
We assemble da a o all US open-end equi y mu ual unds wi h
po olios ha a e a ed wi h a CRS each qua e by he Mo nings a
Po olio CRS. Ou sample co e s he pe iod om Janua y 2017
(when he CRS me ic s a ed o be compu ed) o Decembe 2018.
6
Fu he de ails abou he p ocedu e o compu e he CRS o mu ual unds can be ound a
h ps://www.mo nings a .com/lp/measu ing- ansi ion- isk.
952 REBOREDO AND OTERO GONZ
ALEZ
Ou su i o -bias- ee da abase includes mu ual unds wi hin he A
sha e class,
7
which— o a oid E ans' (2008) incuba ion bias—a e olde
han 2 yea s. Funds in he da abase a e ca ego ized in o one o he
ollowing nine Mo nings a equi y und ca ego ies: la ge blend (LB),
la ge g ow h (LG), la ge alue (LV), mid-cap blend (MB), mid-cap
g ow h (MG), mid-cap alue (MV), small blend (SB), small g ow h
(SG) and small alue (SV). We he e o e exclude equi y unds such as
bond unds, money ma ke unds, unds o unds, index unds and eal
es a e unds. As a esul o his il e ing p ocess, he inal sample
esul ed in 1223 mu ual unds.
Fo he unds, we also e ie e speci ic in o ma ion as ollows:
und names and icke s, incep ion da e, daily p ice in o ma ion and
qua e ly po olio CRS sco e, o al ne asse s and o al asse s, annual
in o ma ion on expense a io and u no e , manage names, manage-
ial owne ship and he SRI ocus, i any, o he und (a dummy a iable
equal o 1 i he und decla es ha i applies an SRI policy and
0 o he wise).
2.2 |Mu ual und a iable de ini ions
2.2.1 | Manage ial owne ship and decisions
Fund manage s shape a und's po olio CRS ei he h ough hei
in ol emen in owne ship o he und's po olio (Kho ana
e al., 2007; Ma & Tang, 2019) o h ough manage ial decisions aken
on he basis o hei u ili y unc ions.
F om Mo nings a Di ec Mu ual Fund, we e ie e annual in o -
ma ion on (a) he numbe o manage s in cha ge o he und; and
(b) manage owne ship s akes in he und o 2017 and 2018. Mana-
ge ial owne ship is equi ed o be disclosed by he US Secu i ies and
Exchange Commission (SEC), since 2005, using he ollowing USD
in es men anges: 0, 1–10,000; 10,001-50,000; 50,001–100,000;
100,001–500,000; 500,001-1,000,000; and abo e 1,000,000. As he
in o ma ion wi hin each in e al is no p ecise in e ms o in es ed
USD, o es ima e owne ship, we use an in e al eg ession app oach
whe eby manage ial owne ship wi hin each in es men ange is
explained as a unc ion o se e al co a ia es ha include equi y und
ca ego y, und size, annual e u n, age, u no e and he SRI dummy.
F om ha model,
8
we ob ain he annual amoun in es ed by each
manage wi hin he co esponding in e al. We hen agg ega e he
annual amoun in es ed by he manage s in cha ge o each und. The
a io be ween his amoun and he o al asse alue o he und is
aken as a qua e ly measu e o manage ial owne ship.
9
Fu he mo e, since an SRI ocus shapes manage ial decisions
acco ding o non-economic p inciples such as en i onmen al
esponsibili y, human igh s, eligious iews and good employee ela-
ions, we conside his indica o a iable o be a po en ial de e minan
o he ca bon isk exposu e o a und.
Finally, we assess he po en ial impac o ac i e managemen on
he und's exposu e o ca bon isk by conside ing he qua e ly R-
squa ed alue om he mul i ac o model in Equa ion 1, in e sely
ela ed o ac i e managemen o he und and selec i i y (see
Amihud & Goyenko, 2013).
2.2.2 | Risk-adjus ed pe o mance
We es ima e he qua e ly adjus ed pe o mance o each und as he
alpha o he i e- ac o ime se ies eg ession model, as p oposed by
Fama and F ench (2015, 2017) and augmen ed by Ca ha 's (1997)
momen um ac o :
Ri, RF, ¼αiþβi,MMKT þβi,SMBSMB þβi,HMLHML þβi,RMWRMW
þβi,CMACMA þβi,MOMMOM þεi ,
ð1Þ
whe e Ri is he daily und i's e u n a day ;R
F is he isk- ee
e u n on he 1-mon h US easu y bill a e; MKT is he excess
e u n o he ma ke po olio; SMB is he di e ence be ween
di e si ied po olio e u ns o small and la ge asse s; HML is
he di e ence be ween high book- o-ma ke and low book- o-ma ke
po olio e u ns; RMW is he di e ence be ween he e u ns o a
di e si ied po olio o obus and weak p o i abili y asse s; CMA is
he di e ence be ween po olio e u ns o low (conse a i e)
and high (agg essi e) in es men i ms; and, inally, MOM
cap u es he momen um ac o . The be a pa ame e s in Equa ion 1
cap u e he sensi i i y o excess e u ns o he six ac o s,
whe eas he alpha pa ame e αideno es he isk-adjus ed
pe o mance o und i.
Fo each yea -qua e , we es ima e he eg ession model in Equa-
ion 1 o each und iand ob ain he qua e ly und's αiusing daily
in o ma ion o ha qua e ega ding he und's p ice excess e u n
and in o ma ion o he se o p icing ac o s, as sou ced om he
Kenne h F ench da a lib a y.
10
2.2.3 | Mu ual und isk
Mu ual und isk is cha ac e ized in e ms o ola ili y and downside
isk. Fo qua e ly pe iods, mu ual und ola ili y is measu ed using
ealized ola ili y ( ola ili y) compu ed o each und ias ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
PT
¼1R2
i
q,
whe e Ri is und i's con inuous daily e u n o day o he
co esponding qua e .
Mo eo e , we accoun o he qua e ly exposu e o und i o
changes in agg ega e s ock ma ke ola ili y using he implied
ma ke ola ili y be a ob ained om he ollowing eg ession
(see Ang e al., 2006):
7
Some mu ual unds o e mul iple sha e classes, which usually di e in ee s uc u e and
clien ele (e.g. e ail unds and ins i u ional unds). We he e o e agg ega e all sha e classes
gi en ha conside ing di e en classes o he same und as sepa a e unds is misleading as
hey o e he same g oss e u n be o e expenses.
8
Resul s o he in e al eg ession a e epo ed in Appendix A.
9
Al e na i ely, manage ial owne ship can be de ined as he o al USD amoun in es ed by
he managemen o e o al ne asse s. Empi ical e idence epo ed below is no a ec ed by
his al e na i e de ini ion o manage ial owne ship.
10
h p://mba. uck.da mou h.edu/pages/ acul y/ken. ench/da a_lib a y.h ml
REBOREDO AND OTERO GONZ
ALEZ 953
Ri, RF, ¼αiþβi,MMKT þβi,VIXΔVIX þεi, ,ð2Þ
whe e ΔVIX is he change in he implied S&P 100 op ion ola ili y
index a day and βi,VIX is he implied ma ke ola ili y be a o und i,
es ima ed on a qua e ly basis using daily da a o ha qua e . Da a
o he VIX index come om he Chicago Boa d Op ions Exchange.
Finally, we assess whe he a und ends o unde go posi i e o
nega i e de ia ions wi h he ma ke by compu ing he qua e ly co-
skewness isk measu e (see Ha ey & Siddique, 2000), which, o und
i, is gi en by
Co-Skewi, ¼
Eεi, ,MKT2
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Eε2
i,
EMKT2
,ð3Þ
whe e εi, ¼Ri, RF,
ðÞαiþβi,MMKT is he esidual o he ac o
ime se ies eg ession in Equa ion 1 conside ing a single ac o ,
namely, he excess e u ns o he ma ke po olio.
Rega ding ail isk, we conside mu ual und exposu e o agg e-
ga e ail isk in bo h he mu ual und sec o and he o e all ma ke .
Fi s , he sensi i i y o he und's e u ns o ail isk in he mu ual
und indus y is gi en by he downside be a (βi, ail) in he ollowing
eg ession model:
Ri, RF, ¼αiþβi,MMKT þβi, ailES þεi, ,ð4Þ
whe e βi, ail accoun s o he sensi i i y o und i e u ns o downside
isk in he mu ual und sec o , gi en by he expec ed sho all (ES) o
he Vangua d To al S ock Ma ke Index Fund (VTSMX) as ep esen a-
i e o he mu ual und ma ke . Fo he VTSMX e u ns index ( ), ES—
de ined as E ≤F1
qðÞ
, whe e F1
qðÞis he in e se o he e u ns
dis ibu ion unc ion o he e u ns index a ime ( he alue a isk)
o a con idence le el q—is compu ed o a s uden - e u n dis ibu-
ion as
ES qðÞ¼μ σ
qhH
1qðÞ
υþH1qðÞ
2
υ1
!
,ð5Þ
whe e h and H deno e he s anda d s uden - densi y and cumula i e
dis ibu ion unc ions wi h υdeg ees o eedom, espec i ely, and μ
and σ2
deno e he mean and a iance o he s uden - densi y,
assumed o be gi en by au o eg essi e and h eshold gene al au o-
eg essi e condi ional he e oskedas ici y (GARCH) models, espec-
i ely. On a qua e ly basis o each und i, we es ima e ail isk
loading, βi, ail, using daily in o ma ion o he co esponding qua e on
excess e u ns, excess ma ke e u ns and ES alues o a 5% con i-
dence le el.
Second, o assess he exposu e o mu ual und i o o e all down-
side isk in he s ock ma ke , we conside he exposu e o each und
o he CBOE VIX Tail Hedge (VXTH) index. The VXTH index
add esses downside isk in he s ock ma ke by acking he pe o -
mance o po olios ha buy and hold he S&P 500 index and buy
1-mon h 30-del a call op ions on he VIX index, wi h po olio weigh s
ha change on a mon hly basis depending on he likelihood o a
black-swan e en occu ing acco ding o he o wa d alue o VIX.
Falls in he index e lec inc eases in downside isk p obabili y as pe -
cei ed by he ma ke . Using in o ma ion on downside isk embedded
in he VXTH index, he exposu e o und i e u ns is de e mined using
he ollowing eg ession model:
Ri, RF, ¼αiþβi,MMKT þβi,VXTHVXTH þεi, ,ð6Þ
whe e βi,VXTH is he downside be a ha accoun s o he sensi i i y o
und i e u ns o downside isk in he s ock ma ke . Fo each und i,
he ma ke ail isk loading βi,VXTH is es ima ed on a qua e ly basis
using daily da a o he VXTH sou ced om he Chicago Boa d
Op ions Exchange.
2.2.4 | O he a iables
We conside addi ional mu ual und ea u es as gi en by he ollowing
a iables: lows, und size, und age, expense a io, u no e a io and
SRI. We measu e qua e ly und lows as
Flowsi, ¼TNAi, TNAi, 11þ i,
ðÞ
TNAi, 1
,ð7Þ
whe e TNAi, e lec s he o al ne asse s o und ia he end o qua -
e and i, is he e u n on und ia qua e . Fund size is measu ed
as he log o he ma ke alue o he und's o al asse s a he end o
he qua e . Fund age is measu ed as he yea s in exis ence o he
und a he end o he qua e calcula ed om he und's incep ion
da e. The qua e ly expense a io is ob ained as one- ou h o he
annual g oss expense a io, de ined as he pe cen age o o al ne
asse s cha ged each yea o co e all expenses incu ed by he und
(including managemen ees and adminis a i e ees). Finally, aken as
he annual u no e a io is he und's ading ac i i y, accoun ing o
ading ac i i y as he pe cen age a io o minimum o agg ega e pu -
chases and sales o e a e age mon hly ne asse s. To a oid dis o ion
e ec s om ou lie s, low and u no e a iables a e winso ized a
he 99% and 1% le els.
2.3 |Desc ip i e s a is ics
Ou sample consis s o 1223 equi y unds co e ing 9784 qua e ly
obse a ions. Panel A in Table 1 shows ha he a e age qua e ly
CRS is 11.27, wi h maximum and minimum alues o 58.38 and
0, espec i ely. The dis ibu ion o he CRS ac oss unds—depic ed in
Figu e 1—shows asymme ies, wi h a la ge (small) amoun o unds in
he lowes (highes ) quan iles and wi h mos unds (74%) a aining
CRS a ings be ween 7 and 16 and only a small p opo ion (3.4%)
a aining CRS a ings abo e 20.
A ound 68% o he sampled unds ha e co-in es ing manage s,
holding an a e age sha e o 0.37% o he o al asse s, as shown
954 REBOREDO AND OTERO GONZ
ALEZ
in Panel B in Table 1. While he a e age numbe o manage s in
he managemen eam is 2.71, he e is wide dispe sion ac oss
unds ega ding eam size. Only a ound 9% o he unds ha e an
SRI ocus. Funds also di e in e ms o selec i i y and ac i e
managemen : R-squa ed has a mean alue o 0.69, e lec ing ha a
signi ican ac ion o he und's e u ns a e explained by he
ac o model in Equa ion 1, o a maximum o 0.99 and a
minimum o 0.01.
Panel C in Table 1 shows ha he a e age isk-adjus ed e u n
pe o mance is nega i e (0.03), wi h a la ge s anda d de ia ion and a
nega i ely skewed dis ibu ion. A e age alues o he ma ke be a
pa ame e om he ac o eg ession model in Equa ion 1 indica e
ha excess equi y mu ual und e u ns mos ly co-mo e wi h excess
ma ke e u ns, wi h an a e age be a o 0.86 and a low s anda d de i-
a ion. Fo he emaining p icing ac o s, a e age alues indica e ha
equi y und excess e u ns mo e in he opposi e di ec ion o he
SMB, HML, RMW and MOM ac o s and in he same di ec ion as he
CMA ac o ; sensi i i ies o hose ac o s shows g ea dispe sion
ac oss unds.
As o und isk measu es, shown in Panel D in Table 1, he
desc ip i e s a is ics indica e ha ola ili y has an a e age qua e ly
alue o 6.94 and a y widely ac oss unds. Likewise, he sensi i i y o
und e u ns o s ock ma ke ola ili y is he e ogeneous ac oss unds,
exhibi ing bo h posi i e and nega i e sensi i i ies o s ock ma ke
TABLE 1 Summa y s a is ics
Pe cen iles
Co .
CRSVa iables Mean
S d.
de . Max Min Skewness Ku osis 5% 25% 50% 75% 95%
Panel A. Ca bon isk measu e
CRS 11.27 5.93 58.38 0.00 2.97 18.55 4.04 8.28 10.86 13.24 17.92 1
Panel B. Manage ial owne ship and decision a iables
Owne ship (%) 0.37 2.05 54.66 0.00 15.55 321.97 0.00 0.00 0.02 0.13 1.31 0.03
Team size 2.71 1.92 21.00 1.00 3.20 19.28 1.00 2.00 2.00 3.00 6.00 0.03
SRI 0.09 0.29 1.00 0.00 2.87 9.22 0.00 0.00 0.00 0.00 1.00 0.08
R-squa ed 0.69 0.27 0.99 0.01 0.63 2.11 0.18 0.47 0.78 0.92 0.98 0.10
Panel C. Risk-adjus ed pe o mance
Alpha 0.03 0.10 0.29 1.54 3.01 25.63 0.21 0.06 0.01 0.01 0.09 0.04
βM0.86 0.28 3.15 1.36 0.77 7.49 0.37 0.71 0.92 1.02 1.22 0.09
βSMB 0.01 0.26 2.50 2.96 0.34 14.50 0.34 0.14 0.04 0.13 0.39 0.07
βHML 0.05 0.35 2.80 4.57 0.80 16.24 0.55 0.21 0.03 0.13 0.41 0.15
βRMW 0.09 0.42 4.07 8.79 2.23 36.23 0.72 0.20 0.04 0.09 0.36 0.31
βCMA 0.13 0.56 8.79 3.97 3.09 31.98 0.52 0.10 0.07 0.27 0.99 0.41
βMOM 0.03 0.25 3.64 2.31 0.21 18.19 0.42 0.13 0.02 0.10 0.31 0.22
Panel D. Risk measu es
Vola ili y 6.94 4.82 89.01 2.13 4.04 37.31 3.27 4.07 5.28 8.45 15.63 0.01
βVIX 0.04 0.16 2.90 1.76 0.79 27.71 0.27 0.09 0.02 0.02 0.18 0.01
Coskew 0.02 0.19 0.64 2.12 2.55 25.14 0.32 0.10 0.00 0.08 0.21 0.07
β ail 0.06 0.64 22.20 2.88 16.16 400.16 0.27 0.06 0.01 0.08 0.38 0.04
βVXTH 0.08 0.56 3.59 6.10 0.78 12.37 0.70 0.14 0.04 0.30 1.00 0.17
Panel E. O he a iables
Flows 0.002 0.19 1.20 0.93 3.97 22.51 0.19 0.05 0.02 0.01 0.22 0.03
Size 19.91 1.99 26.02 13.13 0.04 3.07 16.58 18.55 20.01 21.22 23.09 0.10
Age 16.73 12.04 96.61 2.13 2.53 13.74 3.33 8.69 15.30 21.66 33.41 0.05
Expense 0.31 0.09 1.24 0.06 2.92 25.72 0.19 0.26 0.30 0.34 0.42 0.10
Tu no e 63.91 65.42 507.00 2.00 3.97 25.02 8.89 27.00 49.00 80.00 154.69 0.06
No es: The able epo s summa y s a is ics o he a iables used in ou analysis, lis ed in he i s column: ca bon isk sco e (CRS), manage ial owne ship,
eam size (numbe o manage s), socially esponsible in es men (SRI), R-squa ed, isk-adjus ed e u ns (Alpha), be as o he six- ac o model, ola ili y
( ealized ola ili y), be as wi h espec o he ma ke ola ili y, co-skewness, be as wi h espec o mu ual und and ma ke downside isks; lows, und size
(log o o al asse s), age, expense a io and u no e . The sample includes 1223 equi y mu ual unds o qua e s 2017-I o 2018-IV, o alling 9784
obse a ions. Summa y s a is ics includes mean, s anda d de ia ion, maximum, minimum, skewness, ku osis and pe cen iles (5%, 25%, 50%, 75% and 95%)
o all he a iables. The las column epo s he linea Pea son co ela ion be ween CRS and he a iables indica ed in he i s column.
REBOREDO AND OTERO GONZ
ALEZ 955
ola ili y swings. Simila ly, desc ip i e e idence on co-skewness indi-
ca es he exis ence o unds ha expe ience bo h posi i e and nega-
i e de ia ions wi h he ma ke . Fu he mo e, downside be as indica e
ha und e u ns ha e simila a e age alues o downwa d mo e-
men s in he unds sec o and in he o e all s ock ma ke , wi h a e -
age alues o 0.06 and 0.08, espec i ely; howe e , he pe cen ile
in o ma ion indica es ha und e u ns may inc ease o dec ease wi h
downside isks.
Panel E in Table 1 shows ha he dis ibu ion o und lows is
decidedly skewed o he igh , wi h a mean alue nea ze o and wi h
mode a e low dispe sion among unds. Fund size on a e age is 19.9,
and dis ibu ion is app oxima ely symme ic. The mean und age is
16.7 yea s, wi h mos unds aged o e 7 yea s. The qua e ly a e age
expense a io is 0.31, wi h low dispe sion among unds. Finally, he
annual a e age alue o u no e is 63.9.
The inal column o Table 1 epo s he linea Pea son co ela-
ion coe icien s o he CRS and he a iables indica ed in he i s
column. Manage ial co-in es men and eam size a e nega i ely
associa ed wi h CRS a ings, consis en wi h he ac ha mo e ‘skin
in he game’is associa ed wi h lowe ca bon isk exposu e. Simila ly,
SRI aims and R-squa ed alues a e nega i ely ela ed wi h und CRS.
The e is a posi i e linea associa ion be ween he CRS and isk-
adjus ed e u ns ha is consis en wi h he ac ha e u ns a e
g ea e when he e is mo e exposu e o ca bon isk. Likewise, he
CRS co ela es nega i ely wi h he ma ke be a, indica ing ha unds
wi h less ca bon isk a e mo e sensi i e o mo emen s in ma ke
excess e u ns. CRS a ings mo e posi i ely wi h he SMB, HML and
CMA p icing ac o s and nega i ely wi h he RMW and MOM p ic-
ing ac o s. Re u ns ola ili y and sensi i i y o e u ns o s ock ma -
ke ola ili y a e weakly ela ed o he CRS, whe eas co-skewness is
posi i ely ela ed o he CRS. Howe e , he CRS is nega i ely associ-
a ed wi h downside be as, indica ing ha a low CRS goes hand in
hand wi h g ea e sensi i i y o downside isk. Finally, he CRS is
nega i ely associa ed wi h und lows (an inc ease in he CRS
educes und lows) and is nega i ely co ela ed wi h und size and
und age, and he highe he CRS, he highe he expense and u n-
o e a ios.
3|DO MANAGERIAL FEATURES AFFECT
THE CARBON RISK OF MUTUAL FUNDS?
In his sec ion, we i s ou line he empi ical me hods and esul s o
he impac o manage ial ea u es—such as owne ship, managemen
eam size, SRI and ac i e managemen —on he ca bon isk o
mu ual und po olios and hen check he obus ness o ou
baseline esul s.
3.1 |Manage ial in ol emen and ca bon isk
To examine he impac o manage ial in ol emen on he CRS o
mu ual und po olios, we es ima e he ollowing eg ession model:
CRSi, ¼ωþβOi, 1þγTi, 1þλSRIi, 1þφR2
i, 1þθCon olsi, 1þεi, ,
ð8Þ
whe e he dependen a iable, CRSi, , is he logi ans o ma ion o
he po olio CRS o mu ual und ia he yea -qua e :
CRSi, ¼log CRSi,
100CRSi,
.
11
The main independen a iables o in e es
a e he manage s' sha e in und owne ship (‘skin in he game’)as
gi en by he a iable Oi, , he numbe o manage s a he helm o he
und as indica ed by he a iable Ti, , he SRI ocus o he und, SRIi, ,
and, inally, ac i e und managemen as gi en by he a iable R2
i, . The
pa ame e s β,γ,λand φcap u e he ma ginal e ec s o hose a i-
ables on he alue o he logi ans o ma ion o he CRS. As o con-
ol a iables, we include a iables ela ed o he main und ea u es
and isk a iables ha may in luence he CRS. Speci ically, as ca bon
isk managemen may di e acco ding o in es men s yles, we con-
ol o ixed e ec s s yle dummies de ined acco ding o he nine
Mo nings a equi y und s yle ca ego ies desc ibed abo e. We also
con ol o expense a ios, gi en ha unds wi h high expense a ios
end o adjus isk (Kemp & Ruenzi, 2008), and we con ol o und
size, lows and u no e . As p e ious s udies (e.g. Huang e al., 2011)
sugges ha isk- aking incen i es shi acco ding o e u n pe o -
mance and und age, we also con ol o hose a iables. Included, u -
he mo e, as con ol a iables, a e unds' exposu e o isk condi ions—
as gi en by he qua e ly ola ili y and downside isk be as—and co-
skewness, gi en ha hose a iables may in luence he way he und
deals wi h ca bon isk. We include as u he con ols in o ma ion on
ac o loadings, which e lec exposu e by und s yle o di e en
sou ces o isks. Finally, we con ol o he unobse ed he e ogenei y
o CRSi, o e ime by including yea -qua e ixed e ec s. To alle ia e
po en ial e e se causali y conce ns, he alues o all independen
11
This ans o ma ion is necessa y o gua an ee ha he condi ional expec a ion unc ion
akes alues ha all wi hin he ange o he dependen a iable, which na u ally akes alues
be ween 0% and 100%. Al hough he e a e di e en app oaches o dealing wi h ac ional
dependen a iables (see, e.g. Cook e al., 2008; Papke & Woold idge, 1996), he logi
ans o ma ion is he simples bu also he mos sui able app oach o ou da a gi en ha ou
sample—as shown in Figu e 1—con ains no op bounda y obse a ions and has a negligible
p obabili y o down bounda y obse a ions (only wo equi y unds ha e CRS alues ha
equal 0).
FIGURE 1 Dis ibu ion o CRS o US equi y mu ual unds o
qua e s 2017–2018 [Colou igu e can be iewed a
wileyonlinelib a y.com]
956 REBOREDO AND OTERO GONZ
ALEZ
a iables a e aken om he p e ious qua e -end. We es ima e Equa-
ion 8 using o dina y leas squa es and s anda d e o s a e ob ained
om Whi e c oss-sec ional e o a iances, wi h pe iod clus e ing o
accoun o bo h und he e oskedas ici y and co ela ion.
The esul s o es ima ing Equa ion 8 a e p esen ed in Table 2.
Columns 1–4 epo esul s o ou speci ica ions each o he single-
managemen a iables, whe eas Column 5 p esen s e idence consid-
e ing he ou manage ial a iables oge he in he eg ession model.
TABLE 2 Manage ial in ol emen and CRS in mu ual unds
(1) (2) (3) (4) (5)
Manage ial a iables
Owne ship
1
0.008
**
(3.67) 0.007
**
(3.55)
Team size
1
0.001 (0.47) 0.002 (0.96)
SRI
1
0.071
**
(4.78) 0.071
**
(4.80)
R_squa ed
1
0.155
**
(5.28) 0.148
**
(5.04)
Con ol a iables
LG 0.595
**
(7.00) 0.605
**
(7.12) 0.594
**
(6.99) 0.623
**
(7.33) 0.602
**
(7.09)
LB 0.218
**
(2.57) 0.227
**
(2.67) 0.218
**
(2.57) 0.243
**
(2.87) 0.227
**
(2.68)
LV 0.123 (1.45) 0.132 (1.56) 0.128 (1.51) 0.144
*
(1.69) 0.132 (1.56)
MG 0.217
**
(2.51) 0.226
**
(2.61) 0.218
**
(2.53) 0.250
**
(2.90) 0.234
**
(2.71)
MB 0.044 (0.51) 0.053 (0.61) 0.048 (0.56) 0.077 (0.90) 0.064 (0.74)
MV 0.005 (0.06) 0.003 (0.03) 0.001 (0.01) 0.016 (0.18) 0.006 (0.07)
SG 0.361 (1.54) 0.368 (1.57) 0.368 (1.57) 0.429
*
(1.83) 0.413
*
(1.77)
SB 0.245
**
(2.03) 0.253
**
(2.10) 0.227
*
(1.88) 0.240
**
(1.99) 0.204
*
(1.70)
Expense
1
0.036 (0.70) 0.041 (0.78) 0.049 (0.95) 0.101
*
(1.89) 0.103
*
(1.93)
Size
1
0.001 (0.51) 0.003 (1.33) 0.003 (1.13) 0.004 (1.40) 0.000 (0.07)
Flows
1
0.050
**
(2.28) 0.049
**
(2.24) 0.054
**
(2.46) 0.047
**
(2.14) 0.053
**
(2.41)
Tu no e
1
0.000 (1.33) 0.000 (0.96) 0.000 (1.24) 0.000 (0.98) 0.000 (1.60)
Re u n
1
0.002
*
(1.68) 0.002 (1.65) 0.002
*
(1.75) 0.002 (1.38) 0.002 (1.49)
Age
1
0.001
**
(3.77) 0.001
**
(3.71) 0.001
**
(3.63) 0.001
**
(3.28) 0.001
**
(3.18)
Vola ili y
1
0.016
**
(6.18) 0.016
**
(6.08) 0.016
**
(6.26) 0.020
**
(7.31) 0.021
**
(7.40)
β ail 1 0.076
**
(9.19) 0.076
**
(9.17) 0.076
**
(9.18) 0.074
**
(8.94) 0.074
**
(8.95)
βVXTH 1 0.043
**
(4.36) 0.043
**
(4.38) 0.043
**
(4.43) 0.027
**
(2.62) 0.028
**
(2.72)
Coskew
1
0.145
**
(5.08) 0.145
**
(5.06) 0.147
**
(5.14) 0.134
**
(4.69) 0.136
**
(4.78)
βM 10.104
**
(5.35) 0.104
**
(5.35) 0.104
**
(5.34) 0.028 (1.10) 0.030 (1.18)
βSMB 1 0.275
**
(10.63) 0.274
**
(10.60) 0.274
**
(10.60) 0.288
**
(11.05) 0.288
**
(11.07)
βHML 1 0.427
**
(23.21) 0.426
**
(23.14) 0.430
**
(23.33) 0.416
**
(22.48) 0.421
**
(22.76)
βRMW 10.295
**
(21.63) 0.295
**
(21.60) 0.292
**
(21.35) 0.293
**
(21.39) 0.290
**
(21.19)
βCMA 1 0.475
**
(40.41) 0.475
**
(40.38) 0.477
**
(40.58) 0.472
**
(40.16) 0.475
**
(40.43)
βMOM 10.303
**
(13.50) 0.304
**
(13.51) 0.306
**
(13.64) 0.281
**
(12.28) 0.285
**
(12.49)
Cons an 1.748
**
(17.11) 1.787
**
(17.58) 1.770
**
(17.42) 1.685
**
(16.35) 1.631
**
(15.76)
Yea -qua e FEs Yes Yes Yes Yes Yes
# Obs. 8547 8547 8547 8547 8547
Adj. R20.55 0.55 0.56 0.56 0.57
No es: The able p esen s he leas squa es es ima ion o he pa ame e s o he eg ession be ween he ca bon isk sco e (CRS) as gi en by he log
(CRS/(100 CRS)) and manage ial in ol emen measu ed by manage ial owne ship, eam size, socially esponsible in es men (SRI) ocus and ac i e
managemen , conside ing se e al con ol a iables, including ixed e ec s (FEs) s yle und in es men (LG, LB, LV, SG, SB, SV, SG, SB), expense a io, size,
lows, u no e , g oss e u ns, age, ola ili y, co-skewness, sensi i i y o downside isk in he und ma ke (β ail) and in he s ock ma ke (βVXTH), ac o
loadings (βM,βSMB,βHML,βRMW ,βCMA and βMOM) and qua e ly ixed e ec s. T-s a is ics (in pa en hesis) a e compu ed using Whi e c oss-sec ional e o
a iances wi h pe iod clus e ing o accoun o bo h und he e oskedas ici y and co ela ion.
*Signi icance a he 10% le el.
**Signi icance a he 5% le el.
REBOREDO AND OTERO GONZ
ALEZ 957
We ind ha unds headed by co-in es ing manage s a e associa ed
wi h lowe CRS le els han unds in which manage s ha e less ‘skin in
he game’. Es ima ed coe icien s o manage ial owne ship epo ed
in Columns 1 and 5 a e nega i e and signi ican a he 1% le el, indi-
ca ing ha he ma ginal e ec s o an inc ease in owne ship has an
a e age impac o 0.007 on he dependen a iable. This e idence is
consis en wi h he hypo hesis ha manage ial owne ship dampens
manage s' incen i es o ake ca bon isks, aligning hei in e es s wi h
he sus ainabili y o he und po olio. Ou esul s a e in line wi h p e-
ious esea ch suppo ing a lowe isk associa ed wi h unds in which
he manage s a e also owne s (E ans, 2008; Fu & Wedge, 2011;
Kho ana e al., 2007; Ma & Tang, 2019), bu in ou case o he spe-
ci ic isk associa ed wi h ca bon isk exposu e in he mu ual und
po olio.
Columns 2 and 5 show ha managemen eam size has a negligi-
ble e ec on he CRS o he und. This e idence is consis en wi h he
i ele ance o using a la ge manage ial eam o ealign he und po -
olio wi h low ca bon isk exposu e. No su p isingly, empi ical e i-
dence in Columns 3 and 5 con i ms ha SRI unds go hand in hand
wi h unds wi h low CRS alues, indica ing ha SRI unds exhibi
lowe ca bon isk exposu e, which is consis en wi h he SRI aims o
unds and also wi h ecen e idence epo ed by No singe and
Va ma (2021). Finally, e idence in Columns 4 and 5 indica es ha
mo e ac i e managemen (lowe R-squa ed alues) inc eases und
exposu e o ca bon isk, as he pa ame e es ima e is nega i e and sig-
ni ican a he 1% le el. This would sugges ha manage s ha seek
o p o i om ac i e ading assume mo e ca bon isk in hei po o-
lios han is assumed by he a e age und po olio.
As o he con ol a iables, we ind ha he CRS is nega i ely
impac ed by und age and ola ili y, indica ing ha younge and less
ola ile unds assume g ea e ca bon isk. Fo downside isk, he
empi ical e idence shows ha und exposu e o ail isk in he mu ual
und sec o has a posi i e and signi ican impac on he CRS, meaning
ha he CRS is educed when und exposu e o ail isk inc eases.
Simila ly, und exposu e o ail isk in he inancial ma ke has a signi i-
can impac on he CRS. The e is also e idence ha co-skewness is
posi i ely ela ed o he und CRS, whe eas he g oss e u n pe o -
mance is no associa ed wi h ca bon isk. Ou empi ical es ima es u -
he mo e e eal ha p icing ac o be as, wi h he excep ion o he
ma ke isk ac o , a e ela ed o ca bon isk: Exposu es o SMB, HML
and CMA s ock po olios a e posi i ely associa ed wi h u u e alues
o he CRS, while und exposu es o di e si ied po olios and con a -
ian s ocks ha e a nega i e impac on he CRS. Fund lows a e posi-
i ely associa ed wi h he CRS, e ealing ha inc easing und's lows
aises he po olio CRS. Finally, we ind ha ce ain und ea u es,
such as und size, expense a io and u no e , ha e no signi ican
e ec s on ca bon isk.
To sum up, ou empi ical e idence on und po olio ca bon isk
poin s o he ollowing: (a) Risk is educed wi h manage s' in ol emen
h ough owne ship and he und's SRI ocus, and (b) isk is inc eased
wi h ac i e managemen , independen ly o he size o he manage-
men eam. In addi ion, he ca bon isk le el is sensi i e o ce ain
p icing ac o s and ola ili y ea u es o he und.
3.2 |Robus ness checks
We es o he obus ness o he abo e esul s in di e en ways.
Fi s , we check he sensi i i y o ou e idence o model speci ica ion,
unning he eg ession model in Equa ion 8 using gene alized leas
squa es clus e ed a he und le el and checking o he sensi i i y o
s anda d e o s o di e en a iance–co a iance ma ix speci ica ions.
Those eg essions esul in simila e idence as epo ed in Table 2.
Second, in checking he sensi i i y o he esul s o he inclusion o
di e en se s o con ol a iables, he e idence ega ding manage ial
a iables emains he same. Finally, empi ical esul s om unning he
eg ession model in Equa ion 8 using annual da a o all a iables o
he yea s 2017 and 2018 poin o simila e idence as epo ed in
Table 2.
4|DOES THE CRS AFFECT FUND
PERFORMANCE?
In his sec ion, we examine how po olio CRS migh a ec und pe -
o mance along h ee dimensions: isk-adjus ed e u ns, und isks and
und lows.
4.1 |Risk-adjus ed pe o mance and he CRS
We examine whe he he und isk-adjus ed pe o mance—as gi en
by he und alphas—is sensi i e o he und po olio CRS. Managing
ca bon isk may be a he cos o paying less a en ion o he po olio
e u n pe o mance, o , al e na i ely, i may enhance pe o mance as
he esul o a s ic sc eening p ocess ha excludes unde pe o ming
companies wi h high ca bon isk exposu e. The mu ual und li e a u e
shows ha SRI-o ien ed unds na ow he uni e se o s ocks, and his
is likely o nega i ely impac he pe o mance o hose unds
(Renneboog e al., 2008). O he esea che s ha e ound ha a i m's
en i onmen al o social commi men s enhance pe o mance (Basse &
Manda oux, 2021; Busch & Lewandowski, 2018; Dimson e al., 2015)
and lowe he cos o deb (Jung e al., 2016). We he e o e es
whe he unds wi h high o low CRS a ings imp o e o weaken u u e
isk-adjus ed und pe o mance. We es o his e ec by es ima ing
he ollowing eg ession model:
Alphai, ¼ωþβCRSi, 1þθCon olsi, 1þεi, ,ð9Þ
whe e he dependen a iable (Alpha) is he isk-adjus ed e u n mea-
su e o und ia yea -qua e ob ained om Equa ion 1. The main
independen a iable is he po olio CRS o mu ual und i. As o
con ol a iables, we include a simila se o a iables as conside ed
o Equa ion 8, as hese a e expec ed o a ec isk-adjus ed pe o -
mance: ixed e ec s s yle dummies, expense a io, und size, und
lows, u no e , und age, ola ili y, co-skewness and empo al ixed
e ec s dummies. We also con ol o pe sis ence in und pe o mance
by including lagged alues o Alpha and manage ial owne ship, eam
958 REBOREDO AND OTERO GONZ
ALEZ
in es o s a e sensi i e o he po olio ca bon ansi ion isk is cohe en
wi h e idence epo ed abo e ha poin s o he ac ha highe CRS
a ings educe isk-adjus ed e u ns and consis en ly lessen und lows.
Looking a he con ol a iables, we ind e idence o pe sis ence in und
lows as shown by he s a is ically signi ican coe icien s o lagged
lows, al hough i can be obse ed ha he sign o he lagged e ec s
changes h ough di e en speci ica ions. We also ind ha und lows
posi i ely espond o lagged und pe o mance, consis en wi h he ac
ha imp o emen s in pe o mance a ac he in e es o pe o mance-
chasing in es o s and ewa d he unds pe o ming bes in e ms o
lows. We ind ha e u ns ola ili y inc eases und lows and also ha
und lows a e nega i ely ela ed o und size, sugges ing diseconomies
o scale (i.e. unds ace di icul ies as hey g ow la ge ). Likewise, und
SRI policy has some posi i e e ec on und lows. Finally, und age has
a nega i e impac on und lows, whe eas he emaining con ol a i-
ables ha e no e ec on und lows.
4.4 |Robus ness checks
We epo a ba e y o obus ness es s o he abo e-desc ibed e i-
dence on po olio CRS and und pe o mance. We e-es ima e Equa-
ion 9 using al e na i e measu es o und e u n pe o mance, namely,
alphas om he Fama and F ench (1993) h ee- ac o model, he
Ca ha (1997) ou - ac o model and he ma ke e u n model. The
coe icien es ima es o he CRS using all hese pe o mance mea-
su es a e nega i e, signi ican and o a simila magni ude as he es i-
ma es p esen ed in Table 3. In addi ion, o und po olio aw e u ns,
coe icien es ima es o he CRS a e nega i e and signi ican ac oss all
speci ica ions, wi h he economic magni ude o he coe icien s ang-
ing om 0.07 o 0.12 and wi h obus -s a is ics o 4.24 and
8.37, espec i ely. Thus, ou inding o a de e io a ion in und e u n
pe o mance as he CRS inc eases is obus o al e na i e pe o -
mance measu es.
TABLE 9 Fund lows and CRS
(1) (2) (3) (4) (5)
CRS
1
0.001
*
(4.81) 0.001
*
(4.29) 0.001
*
(2.31) 0.001
**
(3.05) 0.001
**
(3.13)
Con ol a iables
Flows
1
0.248
**
(9.74) 0.243
**
(9.55) 0.222
**
(8.78) 0.001
**
(3.13)
Alpha
1
0.226
**
(8.88) 0.234
**
(8.95) 0.311
**
(8.85) 0.221
**
(8.74)
Vola ili y
1
0.004
**
(4.42) 0.315
**
(8.96)
Expense
1
0.158
**
(6.30) 0.004
**
(4.13)
Size
1
0.009
**
(6.78) 0.166
**
(6.42)
Age
1
0.001
**
(8.57) 0.008
**
(6.55)
Tu no e
1
0.000 (0.40) 0.001
**
(8.32)
SRI
1
0.014
*
(1.84) 0.000 (0.60)
Owne ship
1
0.003 (1.19) 0.012
*
(1.69)
Team size
1
0.004 (0.92) 0.001 (0.39)
R_squa ed
1
0.025
**
(2.59) 0.003 (0.68)
LG 0.001 (0.01) 0.026 (0.36) 0.020
**
(2.03)
LB 0.009 (0.12) 0.017 (0.24) 0.018 (0.26)
LV 0.014 (0.19) 0.011 (0.16) 0.009 (0.12)
MG 0.025 (0.34) 0.006 (0.09) 0.005 (0.06)
MB 0.024 (0.33) 0.002 (0.03) 0.001 (0.01)
MV 0.021 (0.29) 0.006 (0.09) 0.008 (0.11)
SG 0.002 (0.03) 0.057 (0.74) 0.001 (0.01)
SB 0.039 (0.52) 0.001 (0.01) 0.043 (0.56)
Cons an 0.018
**
(5.03) 0.021
**
(5.80) 0.037 (0.50) 0.221
**
(2.79) 0.015 (0.21)
Tempo al FEs Yes Yes Yes Yes Yes
# Obs. 8561 8561 8561 8561 8561
Adj. R20.001 0.08 0.09 0.11 0.11
No es: The able p esen s he gene alized leas squa es es ima ion o he pa ame e s o he eg ession model be ween ne und lows and he ca bon isk
sco e (CRS), conside ing he ollowing lagged und cha ac e is ics: CRS, ne und lows, isk-adjus ed po olio e u ns (alpha), e u n ola ili y, expense
a io, size, age, u no e , socially esponsible in es men (SRI) ocus, manage ial owne ship, eam size, ac i e managemen (R-squa ed), ixed e ec s (FEs)
s yle und in es men (LG, LB, LV, SG, SB, SV, SG, SB) and qua e ly FEs. T-s a is ics (in pa en hesis) a e compu ed using Whi e c oss-sec ional e o
a iances wi h pe iod clus e ing o accoun o bo h und he e oskedas ici y and co ela ion.
*S a is ical signi icance a he 10% le el.
**S a is ical signi icance a he 5% le el.
REBOREDO AND OTERO GONZ
ALEZ 965
We epea he analysis in Table 4 using al e na i e measu es o
und e u n ola ili y, including qua e ly s anda d de ia ion o daily
e u ns and qua e ly idiosync a ic ola ili ies (see Ang e al., 2006)
compu ed as he s anda d de ia ion o he daily esiduals om he
eg ession model in Equa ion 1. Using hose measu es, es ima ed
coe icien s o he CRS a e posi i ely signi ican and o a simila mag-
ni ude as he coe icien s epo ed in Table 4.
In ela ion o he obus ness o ou e idence on he impac o he
CRS on und exposu e o ma ke ail isk, we conside di e en le els
o con idence o he ES alues in Equa ion 4, including 1% and 10%,
inding ha he impac o he CRS on ail be a loading is nega i ely
signi ican and o a simila magni ude as epo ed in Table 7. We also
e-es ima e he sensi i i y o each und o downside isk by conside -
ing he alue a isk in Equa ion 4 ins ead o he ES, e-es ima ing he
CRS coe icien s as in Table 7. The empi ical e idence con i ms ha
inc eased CRS a ings educe ail isk loading.
Finally, we es he sensi i i y o he esul s epo ed in
Tables 3–9 o model speci ica ion as ollows: (a) by unning di e en
eg essions using al e na i e speci ica ions o he a iance–
co a iance esidual ma ix; (b) by es ima ing s anda d e o s unde di -
e en speci ica ions o es o he obus ness o pa ame e signi i-
cance; and (c) by using di e en combina ions o con ol a iables.
E idence om hose es ima ions con i ms he esul s epo ed in
Tables 3–9.
5|CONCLUSIONS
Al hough he ansi ion o a deca bonized economy is likely o cause
se e e dis up ion and po en ial losses o companies ope a ing wi h
business models ha ely di ec ly o indi ec ly on ca bon-in ensi e
ac i i ies, i also b ings new in es men oppo uni ies in low ca bon
businesses. Assessing how mu ual unds a e posi ioned ela i e o his
ansi ion isk is o u mos impo ance o in es o s acing a ade-o
be ween sho - e m gains om ca bon-in ensi e businesses and
po en ial e- alua ion o low-ca bon asse s in a deca bonized econ-
omy. We in es iga e whe he manage ial owne ship, eam size, an SRI
ocus and ac i e managemen shape low ca bon isk managemen o
und po olios. We also analyse how low ca bon isks impac on und
pe o mance, including isk-adjus ed e u ns, po olio ola ili y, ail
isk and und lows.
Fo a sample o US domes ic equi y mu ual unds qua e ly a ed
wi h a CRS by Mo nings a in 2017 and 2018, we ind ha he und
po olio CRS educes wi h manage ial in ol emen h ough owne -
ship and wi h an SRI ocus. Howe e , CRS a ings a e no a ec ed by
manage ial eam size and a e in ensi ied by ac i e managemen .
Rega ding und pe o mance, isk-adjus ed e u n pe o mance is
educed, and und po olio ola ili y su ges when he po olio CRS
inc eases. Howe e , lowe CRS a ings a e also associa ed wi h highe
exposu e o ail isk. In examining he ela ionship wi h und lows,
hese a e educed when he CRS inc eases, indica ing ha in es o s
a e sensi i e o ca bon ansi ion isks. Ou esul s poin o he ac
ha und lows inc ease when he CRS alls. Fu he mo e, he und
SRI policy educes CRS, which in u n inc eases lows o SRI unds.
O e all, ou e idence indica es ha manage ial in ol emen and
decision-making shape low ca bon ansi ion isks and ha managing
hose isks has a ou able e ec s on und pe o mance and lows. Ou
indings u he highligh he ac ha he es uc u ing o und po -
olios acco ding o en i onmen al c i e ia does no ha e de imen al
e ec s on po olio pe o mance and a ac s in es men lows.
Ou empi ical e idence is egionally ci cumsc ibed o he
Uni ed S a es, whe e mu ual und manage s ha e a speci ic en i on-
men al consciousness ha migh di e om ha o manage s based
in o he egions. Examining how und manage s in o he economic
a eas such as Eu ope o Asia espond o low ca bon ansi ion isk
in o ma ion is an in e es ing opic o add ess, which we lea e o
u u e esea ch.
ACKNOWLEDGEMENTS
We hank he Edi o Sco Lam and wo anonymous e e ees o
help ul and cons uc i e commen s ha imp o ed he quali y o he
a icle. We g a e ully acknowledge inancial suppo om he
Spanish Agencia Es a al de In es igacion (Minis e io de Ciencia,
Inno acion y Uni e sidades) unde esea ch p ojec wi h e e ence
RTI2018-100702-B-I00, co- unded by he Eu opean Regional
De elopmen Fund (ERDF/FEDER). Juan C. Rebo edo acknowledges
inancial suppo p o ided by he Xun a de Galicia h ough esea ch
p ojec CONSOLIDACION 2019 GRC GI-2060 Análise Econ
omica
dos Me cados e Ins i uci
ons –AEMI (ED431C 2019/11). Luis. O e o
González acknowledges inancial suppo p o ided by he Xun a de
Galicia h ough esea ch p ojec ED431C 2020/18, co- unded by he
Eu opean Regional De elopmen Fund (ERDF/FEDER) o he pe iod
2020–2023.
ORCID
Juan C. Rebo edo h ps://o cid.o g/0000-0003-3912-9410
Luis A. O e o González h ps://o cid.o g/0000-0002-8214-6227
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APPENDIX A
This appendix shows he esul s o he in e al eg ession es ima es
o manage ial in es men o con e manage ial in es men in e als
in o a pseudo-con inuous a iable. Conside (unobse ed) manage ial
in es men yias gi en by
yi¼X0
iβþεi,ðA1Þ
whe e Xiis a ec o ha includes explana o y a iable ela ed o und
icha ac e is ics. Fo a gi en (no mal) dis ibu ion o εi, we ob ain
pa ame e es ima es by maximizing he log-likelihood unc ion:
ℓiβ,σðÞ¼lnPm
i<yi≤Mi
ðÞ¼ln ΦMiX0
iβ
σ
!
ΦmiX0
iβ
σ
!"#
,ðA2Þ
using nume ical p ocedu es. Table A1 epo s pa ame e es ima es o
di e en a iables used in he eg ession es ima es along wi h he
boo s ap s anda d e o s and -s a is ics.
TABLE A1 Es ima es o manage ial in es men
Pa ame e S d. e o T-s a is ic
LG 239631.5
**
69832.93 3.43
LB 134262.8
*
69731.66 1.93
LV 102080.2 69521.83 1.47
MG 155137.6
**
72141.31 2.15
MB 64064.76 70536.4 0.91
MV 102612.5 69439.94 1.48
SG 37339.91 71263.05 0.52
SB 190202.7
**
93706.39 2.03
SRI 3098.961 26513.51 0.12
Age 739.9285 725.1647 1.02
Tu no e 1059.083
**
185.1609 5.72
Size 84266.94
**
4135.985 20.37
Re u n
1
37.08912 443.1477 0.08
Cons an 1358170
**
108985.8 12.46
*Signi icance a he 10% le el.
**Signi icance a he 5% le el.
968 REBOREDO AND OTERO GONZ
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