S ock P ices as a Leading Indica o o he Eas
Asian Financial C isis
Simon B oome
Economics Depa men
Na ional Uni e si y o I eland, Maynoo h
and
B uce Mo ley*
Economics G oup
Uni e si y o Wales, Abe ys wy h
Sep embe 2003
Abs ac : Using a basic cu ency c isis model, we assess he e ec i eness o s ock
p ices as a leading indica o o he Eas Asian cu ency c isis in 1997 and 1998. S ock
p ices a e inco po a ed in o a basic mone a y model, h ough he weal h e ec
pos ula ed by F iedman (1988). In addi ion o he domes ic s ock p ice, we also
inco po a e he s ock p ices o Hong Kong, China and Japan o de e mine hei abili y
o p edic he c isis. Using mon hly da a, he esul s indica e ha he domes ic s ock
p ice is a signi ican leading indica o , howe e he main s ock p ices indica o o he
c isis is he Hong Kong s ock p ice. In addi ion he US p ice le el is also a highly
signi ican p edic o o he c isis. Causali y es s sugges e idence o bi-causali y
be ween he s ock ma ke s and o eign exchange ma ke s.
JEL. F30, E44
Key Wo ds: Cu ency C isis, S ock P ices, Mone a y Model.
* Add ess o co espondence: D B.Mo ley, Economics G oup, SMB, UW Abe ys wy h,
Abe ys wy h, SY23 3DD, UK. Tel. +(01970) 622522, E-mail: [email p o ec ed], Fax + (01970)
622740.
I In oduc ion
The aim o his pape is o p ima ily de e mine whe he he domes ic s ock ma ke
can be used as a leading indica o du ing a egional cu ency c isis, as in Eas Asia
du ing 1997 and 1998. Fu he we in es iga e whe he he majo s ock ma ke s wi hin
Eas Asia had any e ec on he cu encies su e ing he c isis and can also be used as
an ea ly wa ning sys em. A pa icula ea u e o he Eas Asian c isis was he almos
simul aneous decline in asse p ices and cu encies, as in e na ional in es o s mo ed
hei capi al ou o he espec i e domes ic ma ke s. This esul ed in a subsequen
dep ecia ion o he exchange a e as he domes ic cu ency was sold. Howe e he
deg ee o se e i y o he c isis a ied ac oss Eas Asia, as did he ex en o he decline
in he domes ic s ock ma ke s.
To da e mos models o p edic ing cu ency c ises ha e concen a ed on leading
indica o s om ei he he banking sec o o he cu en accoun (e.g., Kaminsky e al.,
1998, Kwack, 2001). When s ock p ices ha e been included, i has been limi ed o
only domes ic s ock p ices. In his pape we sugges a simple mone a y based model,
in which s ock p ices can be inco po a ed as a leading indica o o cu ency c ises.
We also in es iga e whe he o eign s ock p ices a e a signi ican leading indica o ,
based on h ee heo ies conce ning he o igins o he Sou h Eas Asian cu ency c isis.
When in es iga ing he ela ionship be ween s ock p ices and exchange a es, he
main conce n is usually o e he di ec ion o causali y be ween hese a iables. The e
a e heo e ical easons o causali y o un in bo h di ec ions, as sugges ed by
Bahmani-Oskooee and Soh abian (1992) and G ange e al (2000). The empi ical
2
e idence is equally ambiguous, al hough G ange e al (2000) inds e idence o
causali y unning om s ock ma ke s o exchange a es du ing a cu ency c isis, bu
hei s udy uses daily da a a he han mon hly da a. In his s udy we oo assume
causali y is om s ock p ices o exchange a es.
Following he in oduc ion, we assess he in e ela ionship be ween s ock p ices and
exchange a es du ing a cu ency c isis. We hen de i e a simple model o cu ency
c ises, in which s ock ma ke s a e inco po a ed h ough he demand o money
unc ion. The nex sec ion desc ibes he da a and assesses he esul s om he
empi ical models. Finally we gi e ou conclusions and sugges some implica ions o
u u e policies.
II Cu ency C ises and S ock P ices
The main a emp o inco po a e he domes ic s ock ma ke in o empi ically based
cu ency c isis models has been Kaminsky and Reinha (1996) and Kaminsky e al
(1998). These models inco po a e a numbe o eal, inancial and poli ical a iables in
pu ely empi ical models, o iden i y which a e signi ican and also he leng h o he
signalling ho izon. They use he “signals” app oach, which in gene al in ol es a one
s ep ahead p obabili y o a de alua ion, in he con ex o a mul i a ia e p obi o logi
ype model. The domes ic s ock ma ke s a e gene ally ound o be a signi ican
leading indica o o cu ency c ises, o e a numbe o di e en cu ency c ises in he
ecen pas . In he s udy by Kaminsky e al. (1998), s ock p ices a e ound o be he
ou h bes p edic o o cu ency c ises.
3
The e has been a ce ain amoun o deba e in he li e a u e as o he di ec ion o
causali y be ween s ock p ices and exchange a es. G ange e al. (2000) show ha
causali y uns om domes ic s ock p ices o exchange a es. They o e some
heo e ical suppo o a bi-di ec ional ela ionship be ween he s ock ma ke and
o eign exchange ma ke , bu only o e he sho un. They a gue ha a change in
exchange a es would change he ma ke alue o all i ms ha ade in e na ionally.
This would depend on whe he he i ms a e ne impo e s o expo e s, such ha i in
agg ega e mos i ms we e ne expo e s, a de alua ion would ha e a bene icial a ec
on hose i ms p o i abili y and he e o e s ock ma ke alue. This causal ela ionship
is e med he adi ional app oach, al hough i does no speci y he sign o he e ec .
In con as o his app oach, bo h Bahmani-Oskooee and Soh abian (1992) and
G ange e al. (2000) s ess he impo ance o he po olio app oach o analysing he
ela ionship be ween s ock p ices and exchange a es. This sugges s ha a ise in
s ock p ices, inc eases he domes ic weal h o in es o s, acili a ing a ise in he
demand o money. Following he consequen ise in in e es a es, capi al is a ac ed
in o he domes ic economy app ecia ing he domes ic cu ency. This app oach
assumes he e is a nega i e ela ionship be ween s ock p ices and exchange a es,
wi h causali y unning om he s ock ma ke o he o eign exchange ma ke . Wu
(2001) p o ides e idence o he nega i e ela ionship be ween equi ies and exchange
a es in Sou h Eas Asia. This explana ion is he mos ele an o his ela ionship
du ing a cu ency c isis. We ha e conduc ed a se o G ange causali y es s be ween
domes ic s ock p ices and exchange a es, as wi h o he s udies, he e is e idence o
bicausali y be ween he s ock ma ke and o eign exchange ma ke s. When causali y
4
uns om s ock p ices o he exchange a e, he e is a nega i e ela ionship, which
sugges s he po olio app oach is mos impo an in Sou h Eas Asia.
Apa om he US s ock ma ke , we ha e in es iga ed whe he he c isis could ha e
o igina ed om any o he main neighbou ing s ock ma ke s, in Japan, Hong Kong
and China. Al hough he c isis began in Thailand in 1997, o he s ha e sugges ed he
c isis began ea lie han his, wi h bo h China/ Hong Kong and Japan being sugges ed
as con ende s. Fe nald e al (1999) ha e sugges ed ha he ise in China’s economic
s eng h du ing he 1990’s added o he c isis. They ocused on he 1994 de alua ion
and subsequen s ong expo pe o mance as he cause o he oubles, as China
cap u ed expo ma ke s, which had p e iously been domina ed by he Associa ion o
Sou heas Asian Na ions (ASEAN) coun ies. This acili a ed cu en accoun
p oblems, educed company p o i abili y and culmina ed in he gene al inancial
demise o he a ea. I has also been a gued ha a u he sou ce o he c isis could
ha e been Hong Kong, which in 1997 was o icially e u ned o China om he UK.
Ini ially his had a posi i e e ec on Hong Kong’s sha e p ices, bu as he da e o he
hando e app oached, so conce n abou in es men in Hong Kong inc eased.
Some a gue ha ano he sou ce o he c isis was Japan. Following apid ises in he
s ock ma ke du ing he 1980’s, he ea ly and mid 1990’s saw a e e sal o his end,
wi h some sha p alls. A he same ime he Japanese economy expe ienced an e a o
s agnan g ow h and lack o demand. This acili a ed a decline in demand o ASEAN
impo s and a all in in es men lows o hese coun ies. The inancial c isis in Japan
culmina ed in he ailu e o Yamaichi co po a ion in 1997, he ou h la ges inancial
ins i u ion. This in u n caused ano he la ge all in he Japanese s ock ma ke .
5

I ei he Japan o China/ Hong Kong we e he ins iga o s o his c isis, hen a
measu e o hei inancial oubles could be a use ul leading indica o o he cu ency
c ises in Eas Asia. To de e mine i his is he case, we ha e inco po a ed he s ock
ma ke indices o China, Hong Kong and Japan in o he basic mone a y based model,
along wi h he domes ic s ock ma ke index.
III Model
The ollowing model is based on he K ugman (1979) model o cu ency c isis, wi h
s ock ma ke e ec s inco po a ed h ough he money demand speci ica ion. As wi h
Edin and V edin (1993), his is only used as a basis o he empi ical in es iga ion
and as wi h he leading indica o li e a u e in gene al, o he leading indica o s a e also
inco po a ed in o he empi ical es s, wi hou speci ic heo e ic modeling. The s ock
ma ke is included in he money demand unc ion2 o h ee easons, as sugges ed by
F iedman (1988). I p ima ily ac s as a weal h e ec , as a ise in s ock p ices
inc eases nominal weal h. Addi ionally a ise in s ock p ices e lec s a ise in
expec ed e u ns om isky asse s. To o se his ise in isk, agen s swi ch away om
long- e m bonds o sa e mone a y asse s. Thi dly a ise in s ock p ices implies a ise
in inancial ansac ions and hus ansac ional demand o money. These imply a
posi i e ela ionship be ween money and s ock p ices. The e could also be a nega i e
ela ionship h ough a subs i u ion e ec . As s ock p ices ise, agen s subs i u e he
2 The s ock ma ke could ha e been ela ed o o he mac oeconomic a iables, such as consump ion,
ou pu and in es men . Howe e gi en he mone a y basis o mos cu ency c isis models, we ha e
inco po a ed i in o he money demand unc ion.
6
mo e a ac i e equi ies o money. Howe e as wi h F iedman (1988) we assume he
posi i e e ec domina es.
As wi h he con en ional mone a y model, we assume pu chasing powe pa i y
(PPP) and unco e ed in e es pa i y (UIP) 3hold;
(1) epp

*
Whe e, e is he exchange a e, p a e domes ic p ices and p* a e o eign p ices.
Ede
d ii
() *
 (2)
Whe e i a e domes ic in e es a es and i*a e o eign a es. Money demand akes he
ollowing o m:
mp y i s






(3)
Whe e m is domes ic money balances, y is domes ic income and s is a domes ic s ock
ma ke index. We ha e assumed ha he domes ic money supply is pu ely
accommoda ing. By ea anging he abo e equa ions, we ge :
3 As wi h cu ency c isis models in gene al based on he mone a y model, we ha e assumed PPP and
UIP, al hough empi ical s udies ques ion whe he he o me holds due o ade impedimen s and
anspo cos s and he la e due o he p esence o a isk p emium.
7
d
de
sypime


 ** (4)
To es o he e ec s o s ock p ices on he exchange a e, we ha e chosen a s anda d
empi ical model, based on equa ion4 (4). This sugges s he c isis is a unc ion o :
),,,*,*,,,( xs es e dspiym cc




 (5)
Whe e cc is he a e o change in he exchange a e o he mon h when he exchange
a e is in a c isis condi ion,Δ m is he domes ic money supply (M1), y is ou pu , i* is
he US in e es a e, p* is he US p ice le el, ds is he domes ic s ock ma ke index,
 e is he change in he eal exchange a e, es a e o eign cu ency ese es and xs
a e he ele an o eign s ock ma ke indexes (All a iables a e in logs and in change
o m). As wi h Edin and V edin (1993) we ha e also included he eal exchange a e,
a he han he nominal exchange a e and added o eign exchange ese es. The
ele an o eign s ock ma ke indexes a e he US, Japan, Hong Kong and China. The
US s ock ma ke is included because he Eas Asian cu encies a e pegged o he
dolla , he Japanese ma ke s ha e adi ionally had a s ong e ec on he egion as a
whole. China has ecen ly unde gone impo an poli ical changes which ha e a ec ed
4 An al e na i e app oach would ha e been o include a a ie y o o he ele an a iables ela ing o
he banking sec o , cu en accoun and poli ical ac o s, as in Kaminsky e al. (1998). Howe e in
o de o p o ide a heo e ical basis o he empi ical es s, he emphasis is on a iables ela ing o he
F iedman based mone a y model. In addi ion i would no be possibl o inco po a e all he po en ial
leading indica o s in o he model, so we ha e concen a ed on he s ock ma ke a ea.
8
hei inancial ma ke s and Hong Kong has been ans e ed om UK o Chinese
con ol.
In addi ion o he main leading indica o es s, we ha e also included some G ange
Causali y es s, be ween he exchange a es and domes ic s ock p ices. In addi ion we
ha e included some causali y es s be ween he exchange a es and o eign s ock p ice
a iables. The basic es s is:
i i i
i i i
ess
usee







12110
12110




(6)
Whe e e is he exchange a e, s is he s ock p ice a iable and u and a e e o e ms.
As wi h Bloms om e al. (1996) we ha e included coun y dummy a iables and use
he -s a is ic on he lagged explana o y a iable o de e mine i he e is e idence o
causali y.
IV Da a and Resul s
The coun ies included in he in es iga ion a e hose ha expe ienced he wo s
p oblems du ing he c isis. This includes Thailand, Malaysia, Sou h Ko ea, Indonesia
and he Philippines. The da a is all mon hly, unning om Janua y 1996 o Decembe
1999, so including mon hs whe e a c isis was e iden as well as mon hs in which he
exchange a e was ela i ely s able. The exchange a e is exp essed as he domes ic
cu ency in e ms o he US dolla , he o eign explana o y a iables a e he
espec i e US a iables. This e lec s he ac ha he ele an cu encies we e
9
Kaminsky, G. and. Reinha , C.M., 1996. The win c ises: The causes o banking and
balance o paymen s p oblems. In e na ional Finance Discussion Pape 544,
Washing on: Boa d o he Go e no s o he Fede al Rese e Sys em (Ma ch).
Kaminsky, G., Lizondo, S. and Reinha , C.M., 1998. Leading indica o s o cu ency
c ises. IMF S a Pape s, 1-47.
K ugman, P., 1979. A model o balance paymen s c isis. Jou nal o Money, C edi
and Banking, 11, 311-325.
Kwack, S. Y., 2000. An empi ical analysis o he ac o s de e mining he inancial
c isis in Asia. Jou nal o Asian Economics, 11, 195-206.
Loungani, P., 2000. Com ades o compe i o s?: T ade links be ween China and o he
Eas Asian coun ies. Finance and De elopmen , 37, 1-5.
Radele , S. and Sachs, J.D., 1998 The Eas Asian inancial c isis: Diagnosis,
emedies, p ospec s. B ookings Pape s on Economic Ac i i y, 1-89.
Wu, Y. 2001., Exchange a es, s ock p ices, and money ma ke s: e idence om
Singapo e. Jou nal o Asian Economics, 12, 445-458.
Table 1. Causali y es s be ween S ock p ices and Exchange a es.
Δe Δds
16

Δe(-1)
Δds(-1)
ΔHKS(-1)
-0.087 (1.674)**
-0.074 (1.159)
0.182 (1.916)**
ΔUSS(-1)
ΔCHS(-1)
ΔJPS(-1)
0.070 (0.499)
-0.076 (1.683)**
-0.209 (1.927)**
No es: T-s a is ics a e in pa en heses. E and ds a e he
domes ic exchange a e and s ock p ice espec i ely.
HKS, USS, CHS and JPS and Hong Kong, US, China
and Japan’s s ock p ices espec i ely. ** indica es
signi icance a he 10% le el o signi icance. Only
lagged explana o y a iable included.
Table 2. P obi Models using panel da a om Thailand, Malaysia, Sou h Ko ea,
Philippines and Indonesia
17
Va iable 1 2 3 4
ΔM (-1)
ΔDS (-1)
ΔUSP (-1)
-1.157
(1.709)
-0.620*
(2.363)
-107.181*
(11.195)
-1.136
(1.681)
-0.585*
(2.186)
-1.3.874*
(9.488)
-1.095
(1.596)
-0.572*
(2.170)
-102.311*
(9.916)
-1.131
(1.442)
-0.320
(0.847)
-110.289*
(10.234)
ΔUSS (-1)
USi (-1)
ΔY (-1)
0.064
(0.308)
-0.608
(1.312)
-0.393
(0.615)
0.073
(0.351)
-0.629
(1.363)
0.007
(0.032)
-0.708
(1.514)
0.057
(0.240)
-0.636
(1.253)
ΔRER (-1)
ΔRES (-1)
ΔTHS(-1)
0.283
(0.807)
0.281
(0.807)
0.206
(0.577)
-0.796
(1.453)
0.090
(0.232)
-0.471
(1.651)
L-L
P obabili y
-122.031
70%
-121.841
71%
-120.956
73%
-97.229
68%
No es: -s a is ics a e in pa en heses. P obabili y is he p obabili y o a p edic ed
ou come occu ing om he 115 possible ou comes, ac ing as a pseudo-R2. M is he
money supply, DS is he domes ic s ock p ice, USP, Usi and USS a e US p ices,
in e es a es and s ock p ices espec i ely. Y is ou pu and THS a e Thailand’s s ock
p ices, RER is he eal exchange a e and RES a e ese es. L-L is he es ic ed log
likelihood A * indica es signi icance a he 5% le el.
Table 3. P obi Models using panel da a om Thailand, Malaysia, Sou h Ko ea,
Philippines and Indonesia, including o eign s ock p ices.
18
19
Va iable 1 2 3 4
ΔM (-1)
ΔDS (-1)
ΔUSP (-1)
-1.061
(1.596)
-0.445
(1.668)
-107.643*
(12.306)
-1.129
(1.665)
-0.500
(1.860)
-109.676*
(11.680)
-1.116
(1.655)
-0.594
(2.265)
-106.075*
(11.008)
-1.071
(1.609)
-0.476
(1.747)
-116.063*
(10.558)
ΔUSS (-1)
USi (-1)
ΔY (-1)
0.041
(0.188)
-0.573
(1.266)
0.082
(0.391)
-0.535
(1.150)
0.110
(0.519)
-0.683
(1.450)
1.069*
(1.224)
0.064
(0.278)
-0.578
(1.234)
ΔRER (-1)
ΔJPS (-1)
ΔCHS (-1)
0.040
(0.114)
0.175
(0.500)
-0.493*
(2.292)
0.253
(0.718)
-0.602*
(1.093)
-0.035
(0.097)
-0.512
(0.820)
-0.047
(0.164)
ΔHKS (-1)
L-L
P ob
-0.974*
(3.072)
-117.412
72%
-119.494
72%
-121.431
71%
-1.141*
(2.234)
-116.428
73%
No es: See Table 1 and 2.