Causal impact of stock price crash risk on cost of equity: Evidence from Chinese markets

Zonon, Baba ounde I ed Pa e ne; Wang, Xianzhi; Chen, Chuang; Bou aima,
Mouhamed Bayane
A icle
Causal impac o s ock p ice c ash isk on cos o equi y:
E idence om Chinese ma ke s
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Zonon, Baba ounde I ed Pa e ne; Wang, Xianzhi; Chen, Chuang; Bou aima,
Mouhamed Bayane (2025) : Causal impac o s ock p ice c ash isk on cos o equi y: E idence om
Chinese ma ke s, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 6, pp. 1-24,
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Ci a ion: Zonon, B. I. P., Wang, X.,
Chen, C., & Bou aima, M. B. (2025).
Causal Impac o S ock P ice C ash
Risk on Cos o Equi y: E idence om
Chinese Ma ke s. Economies,13(6), 158.
h ps://doi.o g/10.3390/
economies13060158
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A icle
Causal Impac o S ock P ice C ash Risk on Cos o Equi y:
E idence om Chinese Ma ke s
Baba ounde I ed Pa e ne Zonon 1,* , Xianzhi Wang 2, Chuang Chen 3and Mouhamed Bayane Bou aima 4
1School o Economics and Managemen , Sou hwes Jiao ong Uni e si y, Chengdu 610031, China
2Facul y o A s and Social Sciences, Hong Kong Bap is Uni e si y, Hong Kong SAR 999077, China;
[email p o ec ed]
3School o Business, Uni e si y o New Sou h Wales, Sydney, NSW 2052, Aus alia; [email p o ec ed]
4
Sichuan College o A chi ec u al Technology, Deyang 618000, China; [email p o ec ed]
*Co espondence: [email p o ec ed]
Abs ac : This s udy in es iga es he causal impac o s ock p ice c ash isk on he cos
o equi y (COE) in China’s segmen ed A- and B-sha e ma ke s wi h an emphasis on own-
e ship s uc u es and ma ke egimes. Employing a boo s ap panel G ange causali y
amewo k, Ma ko -swi ching dynamic eg ession, and panel h eshold eg ession mod-
els, he analysis e eals ha heigh ened c ash isk signi ican ly inc eases COE, wi h he
e ec s being mo e p onounced o A-sha es because o domes ic in es o s’ heigh ened
isk sensi i i y. This ela ionship u he in ensi ies in bull ma ke s, whe e in es o op i-
mism ampli ies downside isk pe cep ions. Owne ship segmen a ion plays a c i ical ole,
as o eign in es o s in B-sha es exhibi weake eliance on i m-le el alua ion me ics,
a o ing b oade isk-di e si ica ion s a egies. These indings o e ac ionable insigh s
in o co po a e isk managemen , in es o decision making, and policy o mula ion in
segmen ed and eme ging equi y ma ke s.
Keywo ds: cos o equi y; s ock p ice c ash isk; causali y; bull ma ke ; bea ma ke
JEL Classi ica ion: G10; G15; G32
1. In oduc ion
The ela ionship be ween s ock p ice c ash isk and he cos o equi y (COE) has
ga ne ed subs an ial a en ion in he inance li e a u e because o i s signi ican implica-
ions o in es men decisions, co po a e go e nance, and ma ke s abili y. S ock p ice
c ash isk, cha ac e ized by ab up and signi ican declines in s ock p ices, ypically a ises
om delayed disclosu es and accumula ion o nega i e in o ma ion wi hin i ms. Recen
s udies highligh a ious de e minan s o c ash isk, including manage ial oppo unism,
opaque inancial epo ing, go e nance mechanisms, and ex e nal ac o s such as in es o
sen imen , ca bon isks, ope a ing le e age, and s ock liquidi y (Jin & Mye s,2006;Hu on
e al.,2009;Pio oski e al.,2014;An e al.,2020;Ren e al.,2023;Qian e al.,2025;Bose e al.,
2024;Zhu & Zang,2024;Nguyen e al.,2025). Despi e ex ensi e esea ch, mos s udies
ha e u ilized co ela ion-based me hodologies, limi ing hei capaci y o es ablish clea
causal links be ween c ash isks and COE. This c i ical gap mo i a es he cu en s udy,
which igo ously in es iga es he causal ela ionships linking s ock p ice c ash isk o
COE, explici ly di e en ia es be ween ma ke -wide and i m-speci ic sou ces, and explo es
in es o esponses wi hin segmen ed ma ke s h ough ad anced econome ic echniques.
Economies 2025,13, 158 h ps://doi.o g/10.3390/economies13060158
Economies 2025,13, 158 2 o 24
In es o sensi i i y o c ash isk depends signi ican ly on manage ial anspa ency
and he go e nance s uc u e. In en i onmen s wi h high in o ma ion asymme y, in es o s
ace subs an ial unce ain y ega ding i m-speci ic isks, leading o highe isk p emiums
and COE (Diamond & Ve ecchia,1991;Chen & Chen,2024). Recen s udies sugges
ha equi y-based compensa ion o ou side di ec o s educes c ash isk by mi iga ing
inancial mis epo ing and bad news hoa ding (Qian e al.,2025). Addi ionally, ex e nal
ac o s, including i a ional in es o sen imen and emo ional panic, exace ba e s ock p ice
ola ili y and c ash isk (Fan & Gao,2024;Saleem e al.,2023). Howe e , he li e a u e a ely
di e en ia es explici ly how hese dis inc ypes o c ash isk in luence in es o beha io
ac oss di e en ma ke s uc u es o egimes. Recognizing hese di e ences is c ucial, as
in es o s’ abili ies o di e si y o hedge such isks signi ican ly in luence hei isk p icing
and esul an inancing cos s.
This s udy u he dis inguishes i sel by examining hese dynamics wi hin China’s
segmen ed A- and B-sha e ma ke s, whe e domes ic and o eign in es o s di e ma kedly
in hei sophis ica ion, di e si ica ion capabili ies, and isk-assessmen s a egies. Al hough
he exis ing li e a u e acknowledges he impo ance o in es o sophis ica ion and ma ke
segmen a ion, ew s udies ha e explici ly analyzed how hese ac o s in luence he causal
ela ionship be ween c ash isk and COE unde a ying ma ke condi ions. Domes ic
in es o s in A-sha es, ypically less globally di e si ied and mo e elian on i m-speci ic
in o ma ion, may exhibi heigh ened sensi i i y o i m-speci ic c ash isks compa ed
wi h o eign in es o s in B-sha es, who gene ally bene i om global di e si ica ion (He
e al.,2021). This s udy explici ly in es iga es hese in es o cha ac e is ics and ma ke
segmen a ion e ec s o p o ide no el insigh s in o he condi ions unde which c ash isk
signi ican ly a ec s in es o s’ expec a ions and i ms’ inancing cos s.
Me hodologically, his s udy ad ances he li e a u e by employing obus econome ic
echniques, speci ically boo s ap panel G ange causali y models and Ma ko -swi ching
dynamic eg essions. These me hods explici ly add ess econome ic challenges such as
c oss-sec ional dependence, i m-speci ic he e ogenei y, and egime-dependen in es o
beha io , which a e inadequa ely cap u ed by simple me hodologies. Addi ionally, a
h eshold eg ession was employed o ein o ce he indings om he Ma ko -swi ching
models by explici ly iden i ying he c i ical b eakpoin s. Thus, his s udy inco po a es
panel h eshold eg ession analysis o enhance empi ical obus ness.
By in eg a ing explici heo e ical easoning wi h igo ous me hodologies, his s udy
subs an ially enhances ou unde s anding o he nuanced ela ionship be ween c ash
isk and COE. I mo es beyond exis ing co ela ions, cla i ies causal mechanisms, and
demons a es how dis inc ma ke egimes and in es o sophis ica ion shape inancial
ou comes. These indings o e ac ionable guidance o in es o s, policymake s, and
co po a e manage s aiming o mi iga e inancial isks and op imize i m inancing s a egies
in segmen ed ma ke s.
1.1. De e minan s o S ock P ice C ash Risk and Cos o Equi y (B ie Con ex ualiza ion)
Al hough his s udy p ima ily examines he economic consequences o s ock p ice
c ash isk, a b ie e iew o i s de e minan s p o ides he necessa y heo e ical con ex .
P io esea ch has ex ensi ely iden i ied manage ial beha io , ins i u ional amewo ks, and
ma ke condi ions as pi o al de e minan s o c ash isk. Jin and Mye s (2006) and Hu on
e al. (2009) emphasize manage ial endencies o wi hhold nega i e in o ma ion, esul ing
in a highe c ash isk. Recen s udies ha e expanded on hese de e minan s, highligh ing
he ole o o he agg ega es such as ope a ing le e age, liquidi y, and ca bon disclosu e as
c i ical ac o s in luencing c ash isk h ough inc eased in o ma ion asymme y, in es o s’
asymme ic esponses, and manage ial incen i es o wi hhold nega i e in o ma ion (Bose
Economies 2025,13, 158 3 o 24
e al.,2024;Zhu & Zang,2024;Nguyen e al.,2025). Ins i u ional in es o s may ei he
mi iga e c ash isk e ec i ely o unin en ionally exace ba e i by aligning wi h manage ial
in e es s (And eou e al.,2017). Mo eo e , heigh ened c ash isk has implica ions o co po a e
con ol, educing akeo e p emiums and lowe ing i m alua ions (Ca line e al.,2023).
While he de e minan s a e well documen ed, ew s udies ha e explici ly explo ed he
causal impac o c ash isk on COE. T anspa ency gene ally educes in o ma ion asymme y
and unce ain y, and lowe s COE (Diamond & Ve ecchia,1991). An inc eased c ash isk
e lec s g ea e in o ma ion asymme y and inc eased inancing cos s (Bo osan,1997;Liu
& Ren,2019;Liang & Mao,2019). C ash isk indi ec ly inc eases COE h ough alua ion
adjus men s, as mani es ed by highe book- o-ma ke a ios (Chen e al.,2001). Howe e ,
mos s udies ely on co ela ion-based me hodologies ha p o ide limi ed causal insigh s
o explici conside a ions o a ying ma ke condi ions. This s udy con ibu es explici ly
by in es iga ing he causal ela ionships and di e en ia ed impac s o ma ke -wide and
i m-speci ic c ash isks on he COE.
1.2. Ma ke Dynamics and Owne ship S uc u es
Ma ke segmen a ion and owne ship s uc u es c i ically shape he ela ionship be-
ween c ash isk and COE, in luencing in es o beha io , isk pe cep ions, and di e si ica-
ion oppo uni ies. P e ious s udies ecognize he mode a ing ole o in es o sophis ica-
ion, ye ew explici ly analyze how dis inc ma ke s uc u es and in es o beha io s unde
a ying ma ke egimes in luence his ela ionship. Junxia and Qinsong (2019) indica e
heigh ened in es o sensi i i y o c ash isk in bull ma ke s, al hough exis ing s udies
a ely employ me hodologies ha explici ly cap u e egime-dependen beha io . Recen
indings sugges ha in e nal (e.g., co po a e go e nance) and ex e nal (e.g., ins i u ional
in es o s and analys s) moni o ing signi ican ly alle ia e c ash isk by educing in o ma ion
asymme y (Bose e al.,2024).
Liang and Mao (2019) highligh domes ic A-sha e in es o s’ g ea e sensi i i y o c ash
isks due o limi ed di e si ica ion and eliance on i m-speci ic in o ma ion compa ed
o globally di e si ied o eign B-sha e in es o s. The exis ing li e a u e has no explici ly
es ed how hese di e ences mani es causally unde a ying ma ke condi ions. This s udy
con ibu es explici ly h ough igo ous causali y es ing and egime-swi ching analyses,
p o iding obus insigh s in o he in luence o ma ke segmen a ion and in es o beha io
on he c ash isk–COE nexus.
Owne ship s uc u e also signi ican ly impac s i m alua ion and isk exposu e.
Ca line e al. (2023) documen ed ha i ms wi h a highe c ash isk expe ience educed
akeo e p emiums, which nega i ely in luence hei alua ion and inc ease inancing
cos s. Building explici ly on hese indings, his s udy ex ends he p io li e a u e by
igo ously analyzing how ma ke segmen a ion and owne ship s uc u e in luence in es o
pe cep ions and isk p icing ac oss dis inc ma ke egimes, hus p o iding no el and
ac ionable insigh s beyond exis ing co ela ional indings.
1.3. App oach and Hypo heses De elopmen
T adi ional s udies examining he ela ionship be ween s ock p ice c ash isk and he
cos o equi y (COE) o en ely on co ela ion-based o s a ic panel eg ession models ha
do no adequa ely add ess causali y, i m-le el he e ogenei y, o c oss-sec ional dependence.
To o e come hese limi a ions, his s udy adop s a mul ime hod econome ic s a egy ha
in eg a es causali y es ing and egime-sensi i e modeling.
Fi s , we applied a boo s ap panel G ange causali y model (Kónya,2006), which
accoun s o bo h c oss-sec ional dependence and slope he e ogenei y, hus enhancing
causal iden i ica ion ac oss i m panels. This echnique is pa icula ly sui ed o eme ging
Economies 2025,13, 158 4 o 24
ma ke s, such as China, whe e s uc u al in e dependencies and i m-speci ic dynamics
can bias con en ional es ima ions.
Second, o add ess he nonlinea beha io o inancial ma ke s, we inco po a ed a
Ma ko -swi ching dynamic eg ession model (E ug ul & Oz u k,2013). This amewo k
iden i ies la en egimes, such as bull and bea ma ke s, and es ima es how he c ash isk–
COE ela ionship e ol es ac oss hese s a es. This enables us o examine whe he in es o s
espond di e en ly o c ash isk depending on he p e ailing ma ke sen imen .
Thi d, we complemen ed hese models wi h a panel h eshold eg ession (Hansen,
1999) ha es ima es obse able b eakpoin s in c ash isk measu es (e.g., NCSKEW and
DUVOL) ha igge dis inc in es o eac ions. This model explici ly cap u es nonlinea i y
and s uc u al shi s, o e ing u he insigh s in o how c ash isk a ec s COE in segmen ed
inancial en i onmen s.
This in eg a ed amewo k was applied o China’s dual-sha e s uc u e (A-sha es o
domes ic in es o s and B-sha es o o eign in es o s) o explo e how in es o sophis ica-
ion and ma ke segmen a ion in luence he c ash isk–COE ela ionship ac oss egimes.
Acco dingly, his s udy es ed he ollowing hypo heses.
H1: S ock p ice c ash isk signi ican ly inc eases equi y cos s because o heigh ened in es o
unce ain y and compensa ion equi ed o pe cei ed isks.
H2: The impac o c ash isk on COE is mo e p onounced o A-sha es han o B-sha es because
o he di e ences in in es o beha io , sophis ica ion, and di e si ica ion s a egies s emming om
ma ke segmen a ion.
H3: The ela ionship be ween c ash isk and COE a ies ac oss ma ke egimes, and is s onge
in bull ma ke s because o ampli ied in es o op imism and inc eased sensi i i y o po en ial
downside isks.
By es ing hese hypo heses h ough obus empi ical analyses, his s udy ea i ms
key heo e ical expec a ions and e ines hem h ough he lens o causali y and dynamic
ma ke beha io . I p o ides ac ionable insigh s o in es o s, egula o s, and co po a e
manage s seeking o be e unde s and and manage inancing cos s in segmen ed and
beha io ally complex inancial ma ke s.
The emainde o his pape is o ganized as ollows. Sec ion 2ou lines he ma e ials
and me hods, Sec ion 3p esen s he empi ical esul s, and Sec ion 4concludes he s udy
wi h key indings, implica ions, and ecommenda ions o u u e esea ch.
2. Ma e ials and Me hods
2.1. Sample Selec ion
This s udy uses weekly da a om i ms lis ed on he Shanghai and Shenzhen S ock
Exchanges, sou ced om he China S ock Ma ke and Accoun ing Resea ch (CSMAR)
da abase, co e ing he pe iod 2010 o 2023. The s a ing poin o 2010 ensu ed he exclusion
o he e ec s o he 2008 global inancial c isis, ocusing on he pe iods o ela i e ma ke
s abili y. While he COVID-19 pandemic in luenced ma ke s in 2020–2021, hese yea s we e
e ained o cap u e he ull ma ke dynamics. The sample includes A-sha es (domes ic in-
es o s) and B-sha es ( o eign in es o s), acili a ing an examina ion o how he owne ship
s uc u e in luences he COE–c ash isk ela ionship.
Weekly da a a e used o he COE es ima ion because hey cap u e he sho - e m ma -
ke dynamics ha a ec in es o isk pe cep ions. Al hough COE is less ola ile han s ock
ma ke indica o s, i emains sensi i e o changes in c ash isks, mac oeconomic a iables,

Economies 2025,13, 158 5 o 24
and in es o sen imen . Weekly in e als o e a g anula iew o hese ela ionships and
imp o e causal in e ence.
Re u n on equi y (ROE), a key COE inpu , is gene ally s able o e sho pe iods bu
may a y due o ea nings o ecas s, ma ke e alua ions, o economic shocks. Cap u ing
hese nuances h ough weekly da a ensu es obus analysis o i m undamen als and
ma ke condi ions.
The s udy excludes inancially dis essed i ms ma ked as “ST” o “PT” due o illiq-
uidi y and delis ing isks (Allen e al.,2015) and omi s inancial sec o i ms because o
hei dis inc le e age s uc u es and epo ing p ac ices (Fama & F ench,1992). Fi ms wi h
posi i e book alues and consis en da a o a leas eigh yea s we e included, whe eas
c oss-lis ed i ms we e excluded o con ol o he global ma ke in luence.
This app oach ensu es a high-quali y da ase , minimizing biases while aligning wi h
p io esea ch on cap u ing g anula ma ke esponses o isk ac o s (Vo s ,2017;Liu &
Ren,2019).
2.2. Measu es o S ock P ice C ash Risk
The ou models measu e i m-speci ic c ash isk. The i s measu e, CRASHi , is a
p oxy ha equals one i du ing he iscal yea , he e is a one-week minimum a which a
i m aces a s ock p ice c ash, and ze o o he wise (Vo s ,2017). A s ock p ice c ash week
can be de ined as he week in which a i m’s speci ic weekly e u n is a leas 3.2 s anda d
de ia ions below he mean speci ic e u n. Thus, unde a no mal dis ibu ion, 0.1 pe cen
o all weeks we e de ined as c ash weeks (Hu on e al.,2009). Fi m-speci ic weekly e u ns
(Equa ion (2)) a e compu ed as he na u al loga i hm o one, which is added o he esidual
o he model below (Equa ion (1)):
i =αi+β m +εi (1)
wi =ln(1+εi )(2)
whe e
i
is i m i’s s ock e u n du ing week , m
is he ma ke e u n, and
εi
ep esen s
he p opo ion o i m i’s weekly s ock e u ns ha he agg ega e ma ke mo emen s
ail o explain.
The second measu e o c ash isk is NCSKEWi , also e e ed o as nega i e condi ional
e u n skewness, which is de i ed om he hi d momen o i m-speci ic weekly e u ns
s anda dized by hei ola ili y (Chen e al.,2001;Kim e al.,2016). Highe NCSKEW alues
co espond o an inc eased nega i e skewness, indica ing a highe p obabili y o ex eme
nega i e e u ns. This measu e has been alida ed in s udies examining in o ma ion asym-
me y and manage ial beha io (Jin & Mye s,2006;Hu on e al.,2009). This heo e ical
ounda ion is based on he agg ega ion o undisclosed nega i e in o ma ion ha ul ima ely
esul s in a sha p decline.
.NCSKEWi =−[n(n−1)3/2Σw3
i ]/[(n−1)(n−2)(∑w2
i )3/2]. (3)
NCSKEWi is compu ed as he nega i e o he hi d momen o i m-speci ic weekly
e u ns di ided by he s anda d de ia ion o i m-speci ic weekly e u ns aised o hi d
powe . In ull espec o he p io li e a u e, his s udy selec s he nega i e o he hi d
momen so ha highe alues o NCSKEWi co espond o inc eased nega i e NCSKEW,
and hence, inc eased c ash isk.
The hi d measu e o c ash isk is down- o-up ola ili y DUVOLi . I e alua es he
asymme y in ola ili y be ween weeks wi h below-a e age (down) and abo e-a e age
(up) e u ns (Chen e al.,2001). By aking he na u al loga i hm o he a io o he s anda d
de ia ion o down-week e u ns o ha o up-week e u ns, DUVOLi cap u es he likeli-
Economies 2025,13, 158 6 o 24
hood o mo e ex eme losses han gains. This me ic has been widely used o examine c ash
isk in he con ex o ma ke anspa ency and in es o sen imen (Pio oski e al.,2014;
Saleem & Usman,2021). S udies ha e con i med i s sensi i i y o ab up changes, which
makes i pa icula ly sui able o his s udy. A highe DUVOLi alue indica es inc eased
c ash isk. This equa ion is exp essed as ollows:
DUVOLi =log{(nu−1)∑
down
w2
i /"(nd−1)∑
up
w2
i #}(4)
whe e he numbe o “down/up” weeks (n
d
(n
u
)) minus one will scale he s anda d de ia-
ion o “down” (“up” up’ up’ up’)-week i m-speci ic weekly e u ns. A “down/up” week
is a week du ing which he i m-speci ic weekly s ock e u n is below/abo e he mean
weekly e u n o he iscal yea .
The ou h measu e is implied ola ili y smi k (IV_SKEW), in oduced by Kim e al.
(2011). This is an op ions-based measu e ha equa es he op ion p icing o mula wi h he
op ion ma ke p ice. This can be exp essed as ollows:
IV −SKEW =IVOTMP −IVATMC (5)
whe e IV s ands o implied ola ili y, and OTM pu s a e pu op ions wi h a del a alue
be ween
−
0.375 and
−
0.125. ATM is a call op ion wi h del a alues anging om 0.375 o
0.625. To ob ain he annual measu e o he ola ili y smi k, he daily IV-SKEW o e he
12 mon hs ending 3 mon hs a e he iscal yea -end should be a e aged.
Al hough implied ola ili y smi ks (IV_SKEW) can p o ide addi ional insigh s, hei
use was p ecluded because o he lack o a ailable op ions da a wi hin he scope o his
s udy. Consequen ly, he ou h measu e (IV_SKEW) was excluded om he analysis. Ad-
di ionally, he i s measu e (CRASHi ) was no u ilized sepa a ely because i concep ually
o e laps wi h and is embedded in he calcula ions o NCSKEW and DUVOL, bo h o which
p o ide iche heo e ical and empi ical g ounding o cap u ing c ash isk (Chen e al.,
2001;Kim e al.,2016). Al hough NCSKEW and DUVOL speci ically ocus on sudden de-
clines, aligning closely wi h heo e ical models connec ing c ash isk o delayed disclosu es
and in es o eac ions (Diamond & Ve ecchia,1991), hei widesp ead accep ance and use
in he li e a u e ensu e obus compa abili y and me hodological alidi y.
2.3. Measu e o Cos o Equi y
This s udy ollows Ashbaugh e al. (2004) in es ima ing he cos o equi y as he
discoun a e applied o u u e cash lows o de e mine a i m’s cu en s ock p ice. We
used a a ia ion o he esidual income alua ion model (Ohlson,1995), which is equi alen
o he di idend discoun model. This app oach is ma hema ically he same as he well-
known di idend discoun model, and has been used by nume ous au ho s, including
Bo osan (1997) and Gebha d e al. (2001). In hei me hodology, R is de ined as he implied
cos o equi y and he in e nal a e o e u n, which equa es he in insic alue o he s ock
o he cu en s ock p ice by simply summing he discoun ed u u e abno mal ea nings
and cu en book alue o equi y (BE):
P =B +
∞
∑
i=1
E (ROE +1−R)B +i−1
(1+R)i(6)
whe e P
ep esen s he s ock p ice a ime , B
is he BE a ime , R is he o ecas ed cos o
equi y, ROE
+i
is he e u n on equi y in pe iod + i, and E is he expec a ion conside ing
Economies 2025,13, 158 7 o 24
he in o ma ion a ailable a ime . Since Equa ion (6) needs ea nings o ecas s o u u e
pe iods, i is u he de eloped in o a new e sion: ini e ho izon.
P =B +
T
∑
i=1
(FROE +i−R)B +i−1
(1+R)i+(FROE +T−R)B +T−1
(1+T) R(7)
whe e FROE is he o ecas e u n on equi y. To calcula e he ex an e cos o equi y, his
s udy used Gebha d e al.’s (2001) indus y me hod and Eas on’s (2004) PEG a io. The
indus y me hod assumes ha a i m’s ROE au oma ically e e s o indus y-le el ROE
when i exceeds he o ecas ho izon. The use o he PEG a io implies ha abno mal
ea nings do no inc ease when hey exceed he o ecas ho izon: Lu and Ye (2004) p o ed
ha he indus y app oach is be e o analyzing he Chinese ma ke . Howe e , Bo osan
and Plumlee (2005) concluded ha in he Ame ican capi al ma ke , he PEG a io measu e is
a be e app oach because i is consis en ly and p edic ably ela ed o a ious isk measu es,
and he e o e, p o es o be mo e eliable han o he al e na i es.
B a e al. (2003), Bo osan and Plumlee (2002a,2002b), and F ancis e al. (2004) use
di idend o ecas s and a ge p ices o de i e a measu e o expec ed e u ns o i ms based
on models ha conside hese o ecas s.
Using he CSMAR da abase, he a e ages o he high and low expec ed e u ns o
2010–2023 a e used o calcula e he COE. This app oach aligns wi h p e ious s udies (B a
e al.,2003;Bo osan & Plumlee,2002a).
2.4. Con ol Va iables
Following es ablished p ac ices in he inance li e a u e, his s udy inco po a es he
ma ke be a (BETA), book- o-ma ke a io (BM), and book alue o equi y (BE) as con ol
a iables o accoun o key ac o s in luencing he cos o equi y (COE). These a iables
ha e been widely alida ed as c i ical de e minan s o inancing cos s, in es o isk pe cep-
ions, and i m alua ion.
BETA cap u es a i m’s sensi i i y o ma ke mo emen s and sys ema ic isk, whe e
highe alues e lec g ea e exposu e o ma ke ola ili y, leading in es o s o demand
highe expec ed e u ns (Fama & F ench,1992,1993). Including BETA ensu es ha ma ke -
wide isks, a ounda ional de e minan o equi y p icing, a e p ope ly con olled o .
BM, de ined as he a io o book alue o he ma ke alue o equi y, se es as a p oxy
o bo h alua ion isk and g ow h oppo uni y. Highe BM a ios o en signal unde alua-
ion o inancial dis ess, p omp ing in es o s o equi e highe e u ns (Chen e al.,2001).
Addi ionally, BM co ela es wi h s ock p ice c ash isk (Hu on e al.,2009), ein o cing
i s ele ance in cap u ing i ms’ unde lying ulne abili y o asymme ic in o ma ion and
alua ion shi s.
The BE e lec s a i m’s inancial s eng h and s abili y. Fi ms wi h la ge book equi y
end o ace lowe pe cei ed isk om in es o s, esul ing in educed COE (Bo osan,1997;
Liang & Mao,2019). In he Chinese con ex , whe e inancial epo ing s anda ds and
go e nmen in e en ions can ampli y he signaling ole o inancial s eng h, con olling
o BE is pa icula ly impo an o isola ing i m-speci ic e ec s on COE.
Toge he , hese con ol a iables add ess sys ema ic isk, i m alua ion isk, and
inancial heal h, and a e commonly emphasized in he cos o equi y and c ash isk esea ch
(F ancis e al.,2004;Liu & Ren,2019). Mo eo e , by inco po a ing i m-le el ixed e ec s and
clus e ing s anda d e o s a he i m le el, he analysis accoun s o addi ional a iable bias
and wi hin- i m co ela ions o e ime. This ensu es ha unobse ed i m cha ac e is ics
o s uc u al di e ences ac oss i ms do no con ound he es ima ed impac o c ash isk on
he COE.
Economies 2025,13, 158 8 o 24
2.5. C oss-Sec ional Dependence Tes s
Gi en he na u e o ou panel, wi h a la ge N and small T, he F iedman, F ees, and
Pesa an es s (F iedman,1937;F ees,1995,2004;Pesa an,2020) a e well sui ed.
The Lag ange Mul iplie (LM) es was de eloped by B eusch and Pagan (1980) and is
p esen ed in Equa ion (8):
LMBP =TN−1
∑
i=1
N
∑
j=i+1
ˆ
P2
i(8)
whe e
ˆ
P2
i
is he co ela ion coe icien be ween he esiduals de i ed om panel model
es ima es. Unde he null hypo hesis (Ho), he e is an asymp o ic chi-squa e dis ibu ion
(chi2) conce ning he LM s a is ic, wi h deg ees o eedom o N (N
−
1)/2. i, j, and T a e
de i ed om he panel model equa ion wi h = 1, 2,
. . .
, T. Following his equa ion, Pesa an
(2020) p oposed ano he al e na i e:
CD =s2T
N(N−1)∑N−1
i=1∑N
j=i+1ˆ
pij(9)
Unlike he LM s a is ic, CD has a mean o exac ly ze o o ixed alues o T and N unde
an ex ensi e ange o panel da a models such as nons a iona y, dynamic, homogeneous,
and he e ogeneous models.
F iedman’s s a is ic is de i ed om he a e age Spea man’s co ela ion, and is ex-
p essed as ollows:
Ra e =2
N(N−1)∑
i+1
N
∑
j=i+1
ˆ
ij (10)
whe e
ˆ
ij
is he sample es ima e o he ank co ela ion coe icien o esiduals. A la ge
alue o R_a e indica es he p esence o non-ze o c oss-sec ional co ela ions. The p esen
model and he CD s a is ic in ol e he sum o pai wise co ela ion coe icien s a he han
he sum o squa ed co ela ions used in he LM es .
Howe e , i a check o whe he any c oss-sec ional dependence is le ou in he
dis u bance is o be conduc ed, CD and R_a e lack he powe o de ec i . Howe e , his
d awback does no a ec he F ees s a is ic. This me hod is based on he sum o he squa ed
ank co ela ion coe icien s.
R2
a e =2
N(N−1)
N−1
∑
i=1
N
∑
j=i+1
ˆ
2
ij (11)
A unc ion o his s a is ic ollows a join dis ibu ion o wo independen ly d awn
x2 a iables.
2.6. Slope Homogenei y Tes
Pesa an and Yamaga a (2008) de eloped a s anda dized dispe sion s a is ic ha co e s
a la ge spec um o analysis. Unlike Swamy’s (1970) model, which is limi ed o models in
which N is smalle han T, he Pesa an and Yamaga a models conside his and ex end i o
wide panels. The model can be ep esen ed as ollows:
∼
∆=√N N−1∼
s−k
√2k !(12)
Economies 2025,13, 158 15 o 24
The dynamic eg ession esul s p esen ed in Table A6 con i m and ex end he s a ic
analysis indings, ein o cing he signi ican in luence o s ock p ice c ash isk (measu ed by
NCSKEW and DUVOL) on he cos o equi y (COE) ac oss di e en ma ke condi ions. Con-
sis en wi h E ug ul and Oz u k (2013), who s ess he impo ance o egime-dependen
dynamics in inancial isk s udies, his analysis illus a es ha he c ash isk–COE ela ion-
ship is sensi i e o shi s be ween bull and bea ma ke s.
C ash isk measu es signi ican ly aise COE unde bo h egimes, wi h no ably s onge
e ec s o A-sha es, e lec ing domes ic in es o s’ heigh ened ulne abili y o ma ke
ola ili y (Pio oski e al.,2014). Fan and Gao (2024) u he co obo a e his inding,
highligh ing ha Chinese domes ic in es o s exhibi disp opo iona e isk sensi i i y in
esponse o asymme ic in o ma ion shocks, pa icula ly du ing pe iods o ma ke u bu-
lence. The pe sis en di e gence be ween A- and B-sha es ac oss egimes emphasizes he
endu ing impac o ma ke segmen a ion on China’s capi al ma ke s.
Mo eo e , he esul s e eal ha COE inc eases mo e sha ply in bull ma ke s, which
is consis en wi h Junxia and Qinsong (2019), who ind ha heigh ened in es o op i-
mism ampli ies downside isk conce ns. This egime asymme y is pa icula ly p o-
nounced among A-sha es, whe e ansi ions om bull o bea ma ke s a e less equen
(p21 = 39.74%) han hose among B-sha es (p21 = 89%), sugges ing g ea e ola ili y and
as e sen imen shi s among o eign in es o s. These ansi ion p obabili ies align wi h
Liang and Mao (2019), who obse ed ha o eign in es o s adjus mo e apidly o changing
ma ke condi ions, d i en by global isk conside a ions.
These indings collec i ely alida e H3, con i ming ha heigh ened in es o op imism
in bull ma ke s in ensi ies he ela ionship be ween c ash isk and inancing cos s. This
aligns wi h he heo e ical pe spec i es p oposed by Jin and Mye s (2006) and is empi ically
consis en wi h he e idence p esen ed by Qian e al. (2025), who documen s onge
isk–p ice ela ionships du ing op imis ic ma ke phases in eme ging economies.
Sys ema ic isk, p oxied by BETA, also plays a c ucial ole in de e mining COE,
especially in bull ma ke s. I s posi i e and signi ican e ec ac oss egimes suppo s ea lie
indings by Gode e al. (2005), and is consis en wi h hose o Zhao e al. (2024), who
emphasize ha in es o s’ sensi i i y o sys ema ic ac o s s eng hens du ing pe iods o
ele a ed ma ke op imism.
The beha io o alua ion me ics e eals egime-dependen pa e ns. BM posi i ely
impac s COE in bea ma ke s o bo h sha e classes, e lec ing in es o s’ heigh ened isk
a e sion du ing down u ns (Chen e al.,2001). Howe e , o A-sha es, he BM’s e ec
u ns nega i e in bull ma ke s, sugges ing ha domes ic in es o s in e p e unde alua ion
as a a o able signal du ing op imis ic pe iods. This di e en ia ed beha io is consis en
wi h Fan and Gao (2024), who show ha A-sha e in es o s exhibi s onge alua ion ocus
unde posi i e ma ke sen imen . In con as , B-sha e in es o s’ alua ion esponses emain
ela i ely mu ed, consis en wi h hei b oade in e na ional di e si ica ion s a egies.
The book alue o equi y (BE) also demons a es segmen ed e ec s. Fo A-sha es, he
BE consis en ly lowe s he COE ac oss egimes, unde sco ing he s abilizing in luence o
inancial s eng h and he ole o implici go e nmen p o ec ion in he domes ic ma ke
(Chen e al.,2023). Con e sely, o B-sha es, BE posi i ely impac s COE in bea ma ke s,
sugges ing ha o eign in es o s may in e p e inc eases in book equi y as signals o hidden
isks o ine iciencies (Saleem & Usman,2021).
O e all, he Ma ko -swi ching dynamic eg ession esul s indica e ha he ela ion-
ship be ween c ash isk and COE is no s a ic, bu highly egime-dependen . In es o
beha io , owne ship s uc u e, and ma ke segmen a ion signi ican ly in luence how c ash
isk is p iced in bull-and-bea ma ke s. This con i ms ha i ms mus adop egime-speci ic

Economies 2025,13, 158 16 o 24
isk managemen s a egies o mi iga e he inancial consequences o c ash isks, especially
du ing pe iods o ele a ed op imism when downside isks a e o en unde p iced.
Unlike adi ional s udies ha ocus solely on s a ic ela ionships, his analysis high-
ligh s he necessi y o dynamic modeling app oaches o ully cap u e he nuances o inanc-
ing cos s unde ma ke segmen a ion (Liang & Mao,2019;Qian e al.,2025). By in eg a ing
c ash isk exposu e, in es o beha io , and ma ke egime dynamics, his s udy o e s
ac ionable insigh s in o capi al managemen s a egies o i ms ope a ing in segmen ed
and ola ile inancial en i onmen s.
3.3.2. Th eshold Model
Gi en he panel s uc u e o ou da ase and he likelihood o i m-speci ic he e o-
genei y, we employed he panel h eshold eg ession (PTR) model de eloped by Hansen
(1999), which is speci ically designed o sho - and la ge-N panels. This app oach al-
lows us o es ima e he h eshold le el o s ock p ice c ash isk p oxied by NCSKEW
and DUVOL a which he ma ginal e ec on he cos o equi y (COE) shi s signi ican ly.
The model accoun s o i m-le el ixed e ec s o con ol o unobse ed he e ogenei y,
and allows egime-dependen slope coe icien s. To ensu e obus ness, s anda d e o s
a e he e oscedas ici y-consis en and clus e ed a he i m le el o add ess wi hin- i m
au oco ela ion o e ime.
Panel h eshold eg ession (PTR) analysis u he alida es he nonlinea ela ionship
be ween s ock p ice c ash isk and cos o equi y (COE), complemen ing he egime-
dependen dynamics iden i ied by he Ma ko -swi ching model. Tables A7 and A8 p esen
he PTR esul s, wi h NCSKEW and DUVOL se ing as h eshold a iables o de ine low-
and high- isk egimes.
The h eshold eg ession esul s based on NCSKEW (Table A7) e eal a clea egime
shi in he impac o c ash isk on COE o bo h A-sha es and B-sha es. Fo A-sha es, he
coe icien o NCSKEW inc eases sha ply om 1.1232 (S a e 1, low c ash isk) o 0.1021
(S a e 2, high c ash isk), and bo h a e s a is ically signi ican . This signi ican educ ion in
sensi i i y unde high-c ash- isk condi ions sugges s ha once c ash isk exceeds a c i ical
h eshold, in es o s adjus hei p icing expec a ions mo e conse a i ely, consis en wi h
isk-p icing heo ies (Jin & Mye s,2006). I also echoes he indings o Fan and Gao (2024),
who a gue ha , in high- isk en i onmen s, in es o s in eme ging ma ke s become ela i ely
less esponsi e o ma ginal inc eases in nega i e signals, e lec ing isk-sa u a ion beha io .
Simila ly, o B-sha es, al hough bo h coe icien s a e signi ican , he sensi i i y is
e e sed: NCSKEW has a la ge e ec in he high-c ash- isk egime (0.2419) han in he
low- isk egime (0.101), sugges ing ha o eign in es o s eac mo e s ongly when he
c ash isk su passes a c i ical poin . This pa e n aligns wi h Qian e al. (2025), who show
ha o eign in es o s in segmen ed ma ke s adjus mo e agg essi ely o ex eme downside
signals han domes ic in es o s do.
DUVOL-based h esholds (Table A8) u he con i med hese dynamics. Fo A-sha es,
DUVOL’s e ec on COE is s onge in he low- isk egime (coe icien = 10.5824) han
in he high- isk egime (coe icien = 0.2063), again consis en wi h domes ic in es o s
showing isk sa u a ion once c ash isk becomes excessi e. By con as , o B-sha es,
al hough he coe icien s emain posi i e ac oss egimes, hei ela i e magni udes a e less
p onounced (0.7013 and 0.2663, espec i ely), sugges ing mo e measu ed esponses om
o eign in es o s.
Impo an ly, he h eshold eg essions also e eal s uc u al he e ogenei y in how
he con ol a iables a ec COE ac oss egimes. Fo example, BETA exhibi s signi ican ly
s onge e ec s on COE in low- isk egimes o A-sha es (0.2291 o he NCSKEW model;
0.4181 o he DUVOL model), suppo ing he no ion ha sys ema ic isk p icing is mo e
Economies 2025,13, 158 17 o 24
p ominen when ma ke sen imen is op imis ic (Gode e al.,2005;Zhao e al.,2024), which
inc eases COE in bea ma ke s bu shows egime-dependen e e sals o A-sha es. This
ein o ces Fan and Gao’s (2024) inding ha alua ion conce ns luc ua e wi h ma ke
sen imen , and BE consis en ly exhibi s insigni ican o weak e ec s ac oss egimes o
A-sha es bu shows di e en ia ed signs o B-sha es, unde sco ing ha o eign in es o s
in e p e inancial s eng h signals di e en ly depending on c ash isk egimes (Saleem &
Usman,2021;Chen e al.,2023).
Thus, he PTR analysis s ongly suppo s H3, con i ming ha he impac o c ash
isk on inancing cos s is nonlinea and egime-dependen and shaped by bo h ma ke
segmen a ion and in es o he e ogenei y.
Mo eo e , compa ed wi h baseline panel eg essions and G ange causali y es s, he
PTR app oach o e s iche insigh s by explici ly iden i ying he h eshold le els a which
in es o beha io undamen ally shi s. This e inemen add esses he call o models
capable o cap u ing nonlinea i ies and discon inuous in es o esponses o c ash isk
(Bose e al.,2024).
O e all, he PTR esul s obus ly alida e he cen al p oposi ion ha c ash isk
signi ican ly and causally inc eases he cos o equi y in segmen ed ma ke s, wi h he e ec
a ying depending on in es o ype, owne ship s uc u e, and ma ke egime.
3.4. Implica ions o he Findings
The empi ical indings om his s udy o e impo an implica ions o co po a e
manage s, in es o s, and policymake s ope a ing in segmen ed and beha io ally di e se
capi al ma ke s such as China’s A- and B-sha e s uc u es.
Fo co po a e manage s, e idence ha c ash isk signi ican ly inc eases he cos o
equi y, especially in A-sha es domina ed by domes ic in es o s, unde sco es he necessi y
o imp o ing co po a e anspa ency, inancial disclosu es, and go e nance mechanisms.
Enhanced disclosu e p ac ices can educe in o ma ion asymme y, mi iga e in es o unce -
ain y, and lowe inancing cos s. In bull ma ke s, whe e in es o op imism can exagge a e
sensi i i y o downside isk, i ms should be especially p oac i e in s abilizing expec a ions
and managing na a i e con ol.
Fo in es o s, his s udy highligh s ha he p icing o c ash isk is highly sensi i e
o bo h ma ke egimes and in es o ypes. Domes ic in es o s in A-sha es appea mo e
sensi i e o i m-speci ic c ash signals unde bullish condi ions, whe eas o eign in es o s
in B-sha es eac mo e s ongly when isk h esholds a e su passed. These pa e ns sugges
he need o in es o s o calib a e hei isk assessmen models by inco po a ing egime
swi ches and h eshold e ec s when p icing secu i ies, pa icula ly in eme ging ma ke s,
whe e beha io al biases may be mo e p onounced.
Fo policymake s and egula o s, he esul s suppo he need o nuanced egula o y
amewo ks ha conside beha io al segmen a ion. Measu es such as p omo ing in o ma-
ion anspa ency, encou aging he di e si ica ion o domes ic po olios, and ensu ing he
consis en en o cemen o disclosu e ules can help educe sys emic ulne abili y. Addi-
ionally, unde s anding how in es o sen imen and in o ma ion low in luence p icing
unde di e en egimes can lead o mo e esponsi e and ma ke -s abilizing in e en ions.
Finally, he egime- and h eshold-dependen na u e o he c ash isk–COE ela ion-
ship implies ha adi ional linea policy and in es men models may o e look impo an
dynamics. Fu u e policy designs should in eg a e he nonlinea beha io o ma ke pa ici-
pan s, pa icula ly du ing op imis ic phases when isk misp icing is mo e likely o occu .
This unde sco es he impo ance o adop ing dynamic, beha io ally g ounded app oaches
o isk egula ion and capi al ma ke de elopmen .
Economies 2025,13, 158 18 o 24
4. Conclusions
This s udy igo ously examines he causal ela ionship be ween s ock p ice c ash isk
and cos o equi y (COE) in China’s segmen ed A- and B-sha e ma ke s by applying a
combina ion o s a ic and dynamic me hodologies. The indings consis en ly e eal ha
heigh ened c ash isk leads o a signi ican ly ele a ed COE, wi h he e ec being pa icu-
la ly p onounced in he A-sha e ma ke , whe e less globally di e si ied and domes ically
ocused in es o s domina e. The applica ion o Ma ko -swi ching dynamic eg ession
models and panel h eshold eg ession (PTR) u he e eals ha his ela ionship is egime-
dependen , in ensi ying in bull ma ke s when heigh ened in es o op imism ampli ies
sensi i i y o downside isks. These esul s unde sco e he complex in e play be ween
ma ke segmen a ion, owne ship s uc u es, in es o beha io , and ma ke egimes, which
a e pa icula ly salien in se e al ma ke con ex s.
This s udy makes h ee key con ibu ions o he li e a u e. Fi s , i mo es beyond
adi ional co ela ion-based s udies by p o iding igo ous causal e idence ha links c ash
isk o COE, u ilizing boo s ap panel G ange causali y and h eshold modeling o es ablish
di ec ionali y and obus ness. Second, i demons a es ha he c ash isk–COE ela ionship
is nonlinea and a ies sys ema ically wi h ma ke egime, a dimension la gely o e looked
in p io esea ch. The combined use o Ma ko -swi ching dynamic eg ession and panel
h eshold eg ession amewo ks mo e comp ehensi ely cap u es hese nonlinea i ies and
s uc u al shi s. Thi d, i highligh s he c i ical impo ance o owne ship segmen a ion and
in es o sophis ica ion in inancial decision making and isk p icing. The indings illus a e
ha domes ic and o eign in es o s exhibi asymme ic esponses o c ash isk ac oss
di e en ma ke condi ions, hus p o iding deepe insigh in o how s uc u al ac o s
shape capi al cos s.
The p ac ical implica ions o his s udy a e mul i- ace ed. Fo co po a e manage s,
pa icula ly hose ope a ing in he A-sha e segmen , he esul s emphasize he need o
s eng hen co po a e anspa ency, disclosu e p ac ices, and go e nance amewo ks o
mi iga e domes ic in es o s’ heigh ened c ash isk sensi i i y. In bull ma ke s, pa icula
a en ion should be paid o s abilizing in es o expec a ions o p e en disp opo iona e
inc eases in inancing cos s. Fo policymake s, e idence ad oca es e ined egula o y
s a egies ha conside segmen ed ma ke beha io . Ini ia i es p omo ing g ea e in o -
ma ion anspa ency, b oadening domes ic in es o pa icipa ion, and managing o eign
in es o sen imen du ing ma ke upswings can signi ican ly enhance ma ke esilience
and educe sys emic ulne abili y. Fo in es o s, he esul s highligh he need o adap
isk-assessmen amewo ks o accoun o bo h owne ship s uc u es and ma ke egimes.
Domes ic in es o s mus emain igilan du ing bullish pe iods, when op imism can
obscu e accumula ing isks, whe eas o eign in es o s should in ensi y hei moni o -
ing o i m undamen als du ing down u ns, when hidden inancial agili ies a e likely
o su ace.
Howe e , his s udy had se e al limi a ions. Focusing exclusi ely on China’s A- and
B-sha e ma ke s may cons ain he gene alizabili y o ou indings o o he ins i u ional
and egula o y con ex s. Mo eo e , al hough NCSKEW and DUVOL a e well-es ablished
p oxies o c ash isk, hey may no ully cap u e slow-building o ex ended low- e u n
scena ios. O he dimensions, such as go e nance- ela ed indica o s, sen imen indices,
and implied ola ili y skewness measu es, we e no included because o da a cons ain s.
Fu he mo e, he exclusion o inancial i ms due o hei unique egula o y and le e age
cha ac e is ics limi s he sec o al b ead h o conclusions.
Fu u e esea ch could b oaden he scope by inco po a ing al e na i e c ash isk mea-
su es such as manage ial opaci y indices (Hu on e al.,2009) o implied ola ili y skewness
me ics o be e cap u e he di e en dimensions o c ash isk. Examining mechanisms
Economies 2025,13, 158 19 o 24
such as inside ading could deepen he unde s anding o how in o ma ion asymme-
y channels in luence he c ash isk–COE nexus. Simula ion-based app oaches can be
used in pa allel wi h empi ical models o illus a e he dynamic mechanisms unde con-
olled condi ions. In eg a ing di ec sen imen measu es (e.g., su ey-based o media
one indices) would allow a mo e explici beha io al in e p e a ion o egime-dependen
e ec s. Me hodologically, u u e s udies could also conside smoo h ansi ion o mul iple-
h eshold models (e.g., STR and LSTR) o cap u e complex nonlinea dynamics mo e inely,
pa icula ly in smalle panels o mac o-le el applica ions.
Fu he mo e, in eg a ing al e na i e COE es ima ion models (e.g., Claus & Thomas,
2001) could enhance obus ness, while compa a i e c oss-coun y s udies could illumina e
how ins i u ional ma u i y and egula o y quali y shape he c ash isk–COE ela ionship.
Finally, inco po a ing beha io al inance pe spec i es could en ich u u e esea ch by
explo ing how in es o sen imen , cogni i e biases, and psychological ac o s in e ac wi h
ma ke egimes o shape capi al cos s.
Au ho Con ibu ions: Concep ualiza ion, B.I.P.Z. and X.W.; Me hodology, B.I.P.Z. and X.W.; So -
wa e, X.W. and C.C.; Valida ion, B.I.P.Z., X.W., C.C. and M.B.B.; Fo mal analysis B.I.P.Z., X.W. and
M.B.B.; In es iga ion, C.C.; Da a cu a ion, X.W. and C.C.; W i ing—o iginal d a , B.I.P.Z., X.W., C.C.
and M.B.B.; W i ing— e iew & edi ing, B.I.P.Z. and X.W.; Supe ision, B.I.P.Z.; P ojec adminis a ion,
M.B.B. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
Da a A ailabili y S a emen : The da a p esen ed in his s udy a e a ailable upon eques om he
co esponding au ho due o ongoing esea ch.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
Appendix A
Va iables’ De ini ions
Va iables De ini ion
COE
This is he measu e o he cos o equi y, which is calcula ed using di idend o ecas s and
a ge p ices o de i e an es ima e o expec ed e u n o i ms, using models o alua ion ha
in eg a e hese o ecas s. The me hod is close o he ones used by B a e al. (2003), Bo osan
and Plumlee (2002a,2002b), and F ancis e al. (2004).
NCSKEW
Sho o Nega i e Coe icien Skewness, i is he nega i e o he hi d momen o i m-speci ic
weekly e u ns o each i m and yea di ided by
he s anda d de ia ion o i m-speci ic weekly
e u ns aised o he hi d powe .
DUVOL
Sho o down- o-up ola ili y, i is he log o he a io o he s anda d de ia ion o he
“down-weeks” o e he s anda d de ia ion o he
“up-weeks”.
BETA
BETA is he ma ke be a es ima ed om CSMAR da a o e 60 mon hs be o e a i m-yea iscal
yea -end obse a ion.
BM
Book- o-ma ke alue o secu i ies published by he Shanghai Exchange and he Shenzhen
S ock Exchange, co e ing ou een yea s and calcula ed as he a io o o al asse s/ma ke
alue.
BE Book alue o equi y o secu i ies published by he Shanghai Exchange and he Shenzhen
S ock Exchange, co e ing ou een yea s.
Economies 2025,13, 158 20 o 24
Table A1. Desc ip i e s a is ics.
Va iable No o
Fi m-Yea s No o Unique Fi ms Mean S d. De . Min Max Median
A-sha es
COE 29,582 2113 0.3038 0.6839 0.0095 2.6127 0.1650
NCSKEW 29,582 2113 −0.5450 1.4560 −3.4825 2.8606 −0.5074
DUVOL 29,582 2113 −0.0735 0.3050 −0.7917 0.6691 −0.0538
BETA 29,582 2113 0.6776 0.8898 0.4629 1.4410 0.9832
BM 29,582 2113 0.5513 1.2618 0.0000 1.0802 0.5523
BE 29,582 2113 3.7238 4.7973 0.0000 26.4776 2.2487
B-sha es
COE 1512 108 0.0629 0.2713 0.0006 1.0649 0.0315
NCSKEW 1512 108 −0.2971 1.4501 −3.3712 3.0085 −0.2886
DUVOL 1512 108 −0.0474 0.2911 −0.8573 0.6133 −0.0390
BETA 1512 108 0.5020 0.7989 0.2800 1.2901 0.8075
BM 1512 108 0.5524 1.3015 0.0000 1.1128 0.5847
BE 1512 108 2.3432 3.7094 0.0000 24.3875 1.3092
No es: Table o desc ip i e s a is ics o all a iables. The sample con ains 29,582 i m-yea obse a ions o i ms
ading A-sha es and 1512 i m-yea obse a ions o B-sha es om 2010 o 2023.
Table A2. Pai wise co ela ion able o he selec ed a iables o i ms ading A- and B-sha es.
Va iables COE NCSKEW DUVOL BETA BM BE
A-sha es
COE 1.0000
NCSKEW 0.1622 ** 1.0000
DUVOL 0.0639 ** 0.7525 *** 1.0000
BETA 0.6216 ** 0.1065 *** 0.0872 *** 1.0000
BM 0.0495 *** −0.0349 *** −0.0189 *** 0.0263 *** 1.0000
BE −0.0104 * −0.0468 *** −0.0232 *** −0.0499 *** 0.1837 *** 1.0000
B-sha es
COE 1.0000
NCSKEW 0.1133 ** 1.0000
DUVOL 0.0404 * 0.7328 *** 1.0000
BETA 0.5544 ** 0.0307 * 0.0031 * 1.0000
BM 0.0277 * −0.0096 * −0.0147 * 0.0027 * 1.0000
BE −0.0338 * 0.0287 * 0.0380 * 0.0417 * −0.0642 ** 1.0000
No e: ***, **, and * indica e signi icance a he 1%, 5%, and 10% le els, espec i ely.
Table A3. Panel eg ession.
S ock A S ock B
Va iables COE COE COE COE
NCSKEW 0.0455 *** - 0.0243 *** -
(17.5) - (14.92) -
DUVOL - 0.0271 ** - 0.0355 *
- (7.13) - (11.42)
BETA 0.0197 *** 0.0200 *** 0.0192 *** 0.0190 ***
(19.13) (11.14) (12.10) (12.72)
BM 0.1912 *** 0.1997 *** 0.0249 * 0.0254 *
(12.82) (13.30) (2.04) (2.05)
BE −0.0106 *** −0.0101 *** −0.0003 * −0.0004 *
(−10.35) (−9.72) (−0.19) (−0.27)
In e cep 0.1224 *** 0.1229 *** −0.0301 * −0.0213 *
(5.63) (5.61) (−0.84) (−0.59)
Obse a ions 25356 25356 1296 1296
Adj. R-squa e 0.4030 0.5325 0.3224 0.2259
No e: Table o panel eg ession esul s o (1) COE on NCSKEW, BETA, BM, and BE; (2) COE on DUVOL, BETA,
BM, and BE, o A- and B-sha es. The z- alues a e shown in pa en heses. ***, **, and * indica e signi icance a he
1%, 5%, and 10% le els, espec i ely. Fi m ixed e ec s included. S anda d e o s a e he e oscedas ici y- obus
and clus e ed a he i m le el.

Economies 2025,13, 158 21 o 24
Table A4. C oss-sec ional dependence and slope homogenei y es s.
S ock A S ock B
Equa ion (1) Equa ion (2) Equa ion (1) Equa ion (2)
Fo m Tes p-Value (a) Tes p-Value (b) Tes p-Value (a) Tes p-Value (b)
C oss-sec ional dependence
Pesa an’s es 273.4790 0.0000 290.6810 0.0000 91.3960 0.0000 158.6100 0.0000
F iedman’s es 1013.4030 0.0000 1132.4870 0.0000 278.5600 0.0000 471.7530 0.0000
F ees’ es 65.9960 0.5811 *** 83.9210 0.5811 *** 10.6680 0.5811 *** 25.3400 0.5811 ***
Slope homogenei y
∆~4.0380 0.0000 3.2280 0.0010 −4.8150 0.0000 −4.3190 0.0000
∆~adj. 6.9930 0.0000 5.5910 0.0000 −8.3400 0.0000 −7.4810 0.0000
No e: Fo s ocks A and B, Equa ion (1) ep esen s he i s equa ion as pe Table A3 (NCSKEW is he inde-
penden a iable), and Equa ion (2) ep esen s he second equa ion as pe Table A3 (DUVOL is he dependen
a iable). The null hypo hesis (Ho) o he c oss-sec ional dependence es indica es no c oss-sec ional dependence.
(a,b) The alue p esen ed in F ees’ es is he alpha om a Q dis ibu ion; *** indica es signi icance a he 1% le el.
Fo he slope homogenei y es , he null hypo hesis is ha he coe icien s a e homogeneous.
Table A5. Boo s ap panel G ange causali y es o H1 and H2.
Sha e Type Causal
Rela ionship Wald S a is ic 10%
C i ical Value
5%
C i ical Value
1%
C i ical Value
Panel A: H1—E ec o C ash Risk on Cos o Equi y (COE)
A-sha es
NCSKEW
→
COE
15.0160 ** 9.7890 13.1170 16.1560
A-sha es DUVOL →COE 24.4910 ** 14.4290 16.4210 31.2350
B-sha es
NCSKEW
→
COE
14.4010 * 13.7000 15.9010 22.1170
B-sha es DUVOL →COE 14.1470 ** 9.2670 10.4320 15.6910
Panel B: H2—E ec o Segmen a ion-Rela ed Va iables on COE (by Ma ke Type)
A-sha es BM →COE 20.3410 ** 11.1080 14.8820 27.7310
B-sha es BM →COE 10.9670 11.0070 13.1180 17.8400
No e: ** and * indica e he ejec ion o he null hypo hesis a he 5% and 10% le els, espec i ely.
Table A6. Ma ko -swi ching dynamic eg ession.
S ock A S ock B
Va iables Bea Bull Bea Bull
NCSKEW 0.0652 *** 0.1324 *** 0.0283 *** 0.0305 **
(13.68) (16.77) (17.29) (11.31)
DUVOL 0.1353 *** 0.3441 *** 0.0947 *** 0.1080 ***
(10.11) (16.22) (4.92) (11.04)
BETA 0.0027 *** 0.0401 *** 0.0063 *** 0.0606 ***
(12.03) (17.03) (12.05) (16.88)
BM 0.1322 *** −0.0980 *** 0.0223 * 0.0114
(13.07) (−5.76) (1.76) (0.24)
BE −0.0039 *** −0.0034 *** 0.0004 * −0.0001
(−5.20) (−3.57) (1.84) (−0.01)
In e cep 0.0981 *** 0.0975 *** 0.0082 −0.0273
(6.16) (4.97) (0.43) (−0.39)
Sigma 0.2730 ** 0.1121 **
p11 0.8106 ** 0.9215 **
p21 0.3974 ** 0.8900 **
No e: z- alues a e gi en in pa en heses. ***, **, and * indica e signi icance a he 1%, 5%, and 10% le els, espec-
i ely. Fi m ixed e ec s a e cap u ed h ough egime-dependen in e cep s. S anda d e o s a e he e oscedas ici y-
consis en . Sigma is he s anda d de ia ion o he en i e p ocess, and p11 and p21 a e he ansi ion p obabili ies
om one s a e o ano he . Bea s ep esen S a e 1 and bulls ep esen S a e 2.
Economies 2025,13, 158 22 o 24
Table A7. Th eshold eg ession (NCSKEW).
S ock A S ock B
Va iable S a e 1 S a e 2 Va iable S a e 1 S a e 2
NCSKEW 1.1232 ** 0.1021 *** NCSKEW 0.101 * 0.2419 *
2.37 3.31 1.94 1.74
DUVOL 4.2282 ** 1.2391 *** DUVOL 0.6687 * 0.6145 *
2.54 3.58 1.75 1.82
BETA 0.2291 *** 0.008 BETA 0.0257 *** 0.0236 *
−4.23 0.45 −2.63 1.86
BM 4.2823 *** 0.7945 BM 0.5478 *** 1.2591 ***
3.1 1.58 2.62 2.81
BE −0.1061 0.0132 BE 0.0091 −0.0074
−1.02 0.44 0.9 −0.41
In e cep 0.4496 −0.2731 In e cep −0.0906 −0.3937
0.19 −0.31 −0.49 −0.92
Th eshold −0.4515 Th eshold 0.2991
No e: Fi m ixed e ec s a e included. S anda d e o s a e he e oscedas ici y-consis en and a e clus e ed a he
i m le el. The z- alues a e gi en in he pa en heses. ***, **, and * deno e signi icance a he 1%, 5%, and 10%
le els, espec i ely. The h eshold alue ep esen s c ash isk (measu ed by he NCSKEW), sepa a ing he low-
and high- isk egimes.
Table A8. Th eshold eg ession (DUVOL).
S ock A S ock B
Va iable S a e 1 S a e 2 Va iable S a e 1 S a e 2
NCSKEW 0.3101 * 0.996 * NCSKEW 0.1029 ** 0.2065 ***
1.8 1.73 2.46 3.96
DUVOL 10.5824 * 0.2063 * DUVOL 0.7013 * 0.2663 *
1.95 1.83 1.84 1.71
BETA 0.4181 *** 0.0036 ** BETA 0.0197 * 0.0432 *
13.99 2.24 1.86 1.93
BM 5.0598 −1.3912 *** BM 0.5516 *** 1.1591 ***
3.97 −2.83 2.66 2.91
BE −0.0929 0.0042 BE 0.0109 −0.0105 *
−1.07 0.12 1.09 −1.88
In e cep 4.528 0.1336 In e cep −0.0665 −0.2906
2.29 0.24 −0.36 −0.75
Th eshold −0.0907 Th eshold 0.1235
No e: Fi m ixed e ec s a e included. S anda d e o s a e he e oscedas ici y-consis en and a e clus e ed a he
i m le el. The z- alues a e gi en in he pa en heses. ***, **, and * deno e signi icance a he 1%, 5%, and 10%
le els, espec i ely. The h eshold alue ep esen s c ash isk (measu ed by he DUVOL), sepa a ing he low- and
high- isk egimes.
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