Umo u, Da id; Igbino ia, Beau y; Aliyu, Mohammed Fa id
A icle
Exchange a e beha iou in ASEAN coun ies: A sensi i i y
analysis
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beha iou in ASEAN coun ies: A sensi i i y analysis, The Cen al Eu opean Re iew o Economics and
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Vol. 8, No.4, Decembe 2024, 37-73
Co espondence add ess: Da id UMORU, De men o Economics, Edo S a e Uni e si y Uzai ue, Iyamho, Nige ia, E-
mail: da id.umo [email protected]. Beau y IGBINOVIA, Depa men o Economics, Edo S a e Uni e si y Uzai ue,
Iyamho, Nige ia, E-mail: beau y.igbino ia@edouni e si y.edu.ng Mohammed Fa id ALIYU, Depa men o Economics,
Edo S a e Uni e si y Uzai ue, E-mail:[email protected] © 2024 WSB MERITO UNIVERSITY WROCŁAW
Exchange a e beha iou in ASEAN coun ies – a
sensi i i y analysis
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
Edo S a e Uni e si y Uzai ue, Iyamho, Nige ia
Recei ed: 27.06.2024, Re ised: 06.10.2024, Accep ed: 19.10.2024
doi: h p://10.29015/ce em.1008
Aim: The s udy examined he beha io o exchange a e in ASEAN coun ies. This was highly
necessi a ed in o de o accoun o he s uc u al b eak in he da a se occasioned by global inancial
c isis.
Resea ch me hod: The quan ile eg ession sensi i i y analysis was pe o med on daily se ies o
exchange a e ola ili y o 8 ASEAN coun ies ha ing di ided ou sample in o wo, be o e and a e he
inancial c isis e as. Pe iods o low ma ke ola ili y (2001–2006 plus 2010–2017) and high ma ke
ola ili y (1990–2000, 2007–2009, plus 2018–2023) co ela e o he pe iods be o e and a e he inancial
c isis, espec i ely.
Findings: The empi ical inding going o wa d is ha since he global inancial c isis ook e ec ,
exchange a e ola ili y has no been e ec i ely cu ailed by he go e nmen s and mone a y au ho izes
o ASEAN coun ies especially in Thailand, Malaysia, Indonesia and Vie nam espec i ely. The e is
he e o e he need o a policy igh in a ou o s abili y o he cu ency exchange a es.
O iginali y: The o iginali y o he esea ch esides wi h he sensi i i y analysis which alida es he
p esence o high pe sis ence in he ola ili y o he Thai Bah exchange a e h oughou he quan iles.
This was ollowed on by he high pe sis ence in he exchange a e o he Malaysian inggi which began
a he 70 h quan ile in he p e- inancial c isis pe iod wi h a pe sis ence alue o 1.0097 as agains he
30 h quan ile in he pos - inancial c isis es ima ions wi h a pe sis ence alue o 1.0387. The Indonesian
Rupiah and Vie namese dong ook u ns as ega ds ola ili y pe sis ence. We also ound signi ican
ARCH e ec which ins iga ed u he es ima ions o he GARCH and FIGARCH models as obus ness
checks.
Con ibu ions: Wi h he GARCH esul s, he s udy con ibu ed o es ablishing pe sis ence o ola ili y
in he exchange a es o all ASEAN coun ies in ou sample, wi h a ying deg ees and his could be
a ibu ed ins abili ies in he economies. Explici ly, he signi icance o he FIGARCH coe icien
con i ms he pe sis ence o ola ili y o e ime wi h conside able long- e m memo y e ec . This implies
ha once he exchange a e becomes ola ile, such ola ili y las long, in luencing u u e ola ili y le els
no iceably in all he coun ies. Exchange a e ola ili y pe sis ence o he Singapo e Dolla was e y low.
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
38
Keywo ds: Exchange a e beha io , FIGARCH-DCC, ola ili y pe sis ence, RER, long- e m memo y,
ola ili y
JEL: A20, B34, C50
1. In oduc ion
Exchange a e, being he alue o one cu ency o he con e sion o ano he , is
in luenced by nume ous ac o s such as in la ion, in e es a es, oil p ice a ia ion,
g ow h o money in ci cula ion, and income g ow h a e e c. (Umo u, Abugewa-Ejegi,
E iong 2023; Umo u, Akpo i o o, E iong 2023). The s udy aimed a e alua ing he
beha iou o exchange a e in ASEAN coun ies. The membe s o he Associa ion o
Sou heas Asian Na ions (ASEAN) co e ed in his esea ch include Indonesia,
Singapo e, Philippines, Thailand, Vie nam, Cambodia, Myanma , and Malaysia. P ice
and exchange a e s abili y is he co e objec i e o he mone a y au ho i ies o hese
coun ies. Indonesia cen al bank ope a es a ee loa ing exchange a e egime.
Hence, Indonesia upiah exchange a e is s ongly swayed by capi al lows and expo s
ea nings. The mone a y policy amewo k o Singapo e is exchange a e-cen e ed.
The Singapo e dolla is egula ed agains a baske o cu encies whose composi ion is
e iewed occasionally in o de o accommoda e changes in ade pa e ns. The ade-
weigh ed exchange a e luc ua es wi hin a policy band ha is ixed nea by a a ge ed
le el and a gi en app ecia ion a e. The policy adjus men s o he pa ame e s o he
exchange a e band a e announced e e y h ee mon hs. The Philippine go e nmen
implemen s he loa ing exchange a e sys em o he Philippine Peso. Acco dingly,
any ime o eign shocks dis u b he domes ic economy, he lexible peso exchange a e
se es as an au oma ic s abilize ha egula es and p o ides a es o a ion o
mac oeconomic balance. The Bank o Thailand ope a es a managed loa exchange
a e sys em whe eby ma ke mechanism ixes he alue o he Thai bah while he
Bank o Thailand in e enes when he Thai bah exchange a e is ex emely ola ile.
The go e nmen o Vie nam ope a es wo exchange a e policies, namely,
“ ollowing” he ma ke and “uni ying” he ma ke . In Cambodia, ola ili y in he
exchange a e, he Na ional Bank o Cambodia (NBC) commi ee mee s o s a egize
o b ing he exchange a e back wi hin ange. Cu en ly, he Cen al Bank o Myanma
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
39
(CBM) issues daily o icial pa allel FX a es ha ing agg ega ed ansac ions epo ed
by comme cial banks o he online o ex ading pla o m. The exchange a es a e
accessible and he CBM upholds con ol o e he a es used in hese ansac ions. In
Malaysia, he Bank Nega a Malaysia (BNM) ope a es a loa ing exchange a e sys em
since 2016. The BNM pe mi ed expo e s o exchange 75% o hei p oceeds in o he
inggi , while 25% o he p oceeds a e e ained in o eign cu ency. This p ac ice
elaxed o ex hedging es ic ions and c ea ed some libe aliza ion measu es which has
ampli ied he ola ili y o he Malaysian inggi because huge lexibili y is allowed
o expo e s. The beha io o he exchange a es o ASEAN cu encies is o policy
signi icance because inancial ade s and ma ke e s can igh ly p edic he
pe o mance o he o eign exchange ma ke in ASEAN coun ies and ac o in he
ola ili y o he exchange a e when making in es men decisions. As a esul , hese
in es o s a e guided in hei decision-making. O e all, he esea ch indings a e
ele an in ha hey p o ide policy guidelines o asse po olio decision-make s and
o ex ade s in he ASEAN inancial ma ke s. In summa y, he s abili y o he
exchange a es o all ASEAN cu encies ela i e o o eign cu encies is essen ial in
o de o achie e and main ain p ice s abili y and s abili y in he inancial ma ke . The
s udy is o immense alue o policymake s who s and o bene i p o oundly om
policy indings as ega ds he o mula ion o e ec i e egula o y policies; ideas in o
how digi al cu encies in e ac wi h adi ional economic indica o s can guide he
de elopmen o egula o y amewo ks ha os e inno a ion while mi iga ing
po en ial isks. Policymake s can use he indings o design measu es ha p omo e
inancial s abili y and ensu e he esponsible in eg a ion o o ex ma ke s wi hin he
b oade economic landscape o all ASEAN na ions. The nex sec ion e iews ela ed
and ele an li e a u e. Sec ion h ee discusses he esea ch me hodology, while
sec ion ou discusses he esul s and policy implica ions. The s udy concludes wi h
sec ion i e.
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
40
2. Li e a u e e iew
Kipko i & Mu ai (2024) ocused on he in luence o commodi y p ice
luc ua ions on he beha io o he Kenyan Shilling agains majo cu encies om
2015 o 2023. The s udy sou ced i s exchange a e and commodi y p ice da a om he
Cen al Bank o Kenya and global commodi y exchanges. Employing VECM, he
esea ch aimed o unco e how global changes in commodi y p ices, especially ea
and co ee, impac he exchange a e. The indings indica ed a signi ican and las ing
impac o commodi y p ice ola ili y on he exchange a e, wi h a signi icance le el
less han 0.05. Long- e m analysis showed a slow adjus men o equilib ium, wi h an
annual speed o 3.7%, e lec ing he p o ac ed e ec o commodi y p ice changes on
he cu ency. The s udy sugges ha Kenya’s cen al bank should enhance i s
moni o ing o commodi y ma ke s and po en ially engage in u u es con ac s o hedge
agains p edic able luc ua ions in cu ency alues. Okonkwo & Mbekeani (2023)
in es iga ed he beha io al pa e ns o he Rand agains he US Dolla du ing pe iods
o poli ical ins abili y om 2010 o 2022. Using exchange a e da a om he Sou h
A ican Rese e Bank, he s udy u ilized a combina ion o uni oo es s o ensu e
da a s a iona i y and co-in eg a ion analysis o es ablish ela ionships, ollowed by a
VECM o es ima e he dynamics. The esea ch ound ha poli ical ins abili y leads o
signi ican ola ili y in he Rand, wi h exchange a e mo emen s showing heigh ened
sensi i i y du ing elec ion cycles and majo poli ical announcemen s. The signi icance
le el o hese luc ua ions was ound o be below 0.05, indica ing a s ong
ela ionship. The s udy also e ealed ha his ela ionship pe sis s in he long un,
wi h a speed o adjus men o equilib ium o 5.4% annually. In he sho un, each 1%
inc ease in poli ical ins abili y could lead o app oxima ely a 0.12% inc ease in
exchange a e ola ili y. The s udy ecommended ha policymake s and in es o s
conside he iming o poli ical e en s when assessing cu ency isk, sugges ing ha
s a egic cu ency managemen could mi iga e he ad e se e ec s on he Rand.
Djouakaa e al. (2023) examined eal e ec i e exchange a e causes. Thei esul s
demons a ed ha money supply; di ec in es men , in la ion, impo s and in e es a e
a e he main de e minan s o he eal e ec i e exchange a e in he anc zone a e
using he D iscol-K aay me hod on panel da a. Also, he use o he Panel Co ec ed
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
41
S anda d E o me hod also e ealed he same esul s. In addi ion, he analysis o he
speci ici ies o he 15 F anc Zone coun ies made i achie able o ake in o accoun
he he e ogenei y o he panel. As a esul , he cen al banks o each o he 15 F anc
Zone coun ies mus inco po a e he consequences o he a e o exchange when
o mula ing hei mone a y policies. Mo eo e , each go e nmen , when o mula ing
i s mac oeconomic policy, mus ake in o accoun he epe cussions o he exchange
ma ke . Aizenman e al. (2023) in es iga ed he link be ween RER beha iou and
in e na ional ese e in he e a o inancial in eg a ion. They u ilized nonlinea
eg essions and panel h eshold eg essions echniques o de e mine whe he
in e na ional ese e is a de e minan o eal exchange a e. Thei s udy co e ed o e
110 coun ies making use o panel da a om 2001-2020. Some o he coun ies
include Alge ia, Bo swana, B azil, Guinea, Hondu as, Hunga y, Guinea, Hondu as,
Hunga y and o he s. The indings show ha e m o ade shocks had signi ican on
eal exchange a e. The esul s also indica e ha coun ies wi h in e media e le els o
inancial de elopmen will ha e a mo e powe ul bu e .
The s udy conduc ed in SSA na ions wi h a ocus on he oil-impo ing and
expo ing na ions by Ko ley & Giou is (2022) e alua ed he in luence o oil p ice
and oil ola ili y index on he exchange a e. Thei s udy employed quan ile eg ession
and Ma ko swi ching models o e alua e hei join e ec and showed ha oil
ola ili y conside ably in luenced he exchange a e o all coun ies. They es ablished
ha he ising and alling oil p ices leads he local cu ency o de alue o app ecia e.
They submi ed ha exchange a es espond o oil p ice and oil ola ili y mos ly a
lowe quan iles o all coun ies which indica es he sensi i i y o in es o s o isks
and e u ns. Bangu a e al. (2021) aimed o in es iga e he beha io o he Leone/US
dolla exchange a e based on he in luence o global oil p ice shocks in Sie a Leone
h oughou he pos -wa pe iod om June 2002 o May 2020. Among he h ee
es ima ed models, he EGARCH (1, 1) model eme ged as he mos sui able i , wi h
all mean and a iance coe icien s deemed signi ican . The empi ical indings
indica ed ha a ise in oil p ices co esponded o a dep ecia ion o he exchange a e
in Sie a Leone amongs o he s.
Raksong & Somba hi a (2021) epo ed a posi i e impac on he REER o he
ASEAN coun ies by some a iables which include he a io o FDI o GDP and
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
42
go e nmen spending. T ade opening also had a subs an ial posi i e impac on REER
in all he ASEAN coun ies s udied excep Vie nam while e ms o ade had
signi ican impac on REER in Malaysia, Philippines and Indonesia. Fo eign di ec
in es men also had signi ican impac on REER, bu only in Vie nam. In e na ional
ese e was shown o ha e long- un impac on REER in Malaysia, Thailand and
Vie nam. Ani & Mashood (2021) unde ook a comp ehensi e analysis o e alua e he
beha iou o eal exchange a e (RER) in Nige ia o e a sample size o 60 yea s om
he pe iod o 1960-2020. The s udy u ilized a mul i a ia e co-in eg a ion es , he ADF
and KPSS s a iona i y es as well as he VECM o analyze he da a se . The esul o
he s a iona i y es showed ha he mac oeconomic a iable unde s udy had no
s ochas ic ends and we e s a ione y a all le els while he esul o he G ange
causali y es showed ha eal GDP g ow h a e, in la ion a e, money supply g ow h
a e and go e nmen expendi u e exe ed signi ican in luence on eal exchange a e
beha io .
Damayan hi & Gunawa dhana (2021) analyzed he beha io o he eal e ec i e
exchange a e in S i Lanka wi h a di ec linkage o ex e nal sec o s abili y, sampling
da a om he pe iod om 2010 o 2019. The esea ch employed he ec o au o
eg ession (VAR) model as an analy ical ool. The esul s o he s udy e ealed ha
exchange a e beha ed as heo e ically expec ed wi h changes in policy a es o Uni ed
S a es. Al hough, beha io o in la ion, domes ic in e es a es and ne expo s we e
con a y o heo e ical expec a ions. The indings show ha e en hough domes ic
cu ency dep ecia ion may lead o inc eased ne expo s, S i Lanka, being a ne
impo ing economy, had su e ed u he dep ecia ion o i s domes ic cu ency. Kalaj
& Golemi (2020) ocused hei s udy on he bases o eal exchange a e beha iou in
Albania; sing he VAR model o assess da a o he pe iod o 1995-2015. The s udy
aims o ind he long un ela ionship among a iables. The indings sugges ha eal
exchange a e beha io can be dec eased by inc easing iscal policies and dec easing
mone a y policies. Findings om he s udy also indica ed a long- un ela ionship
be ween eal exchange a e beha io and ade.
Romo & Galla do (2020) explo ed he bases o he beha io o RER beha io ,
pa icula ly analyzing he e ec o sha e o wages in ou pu on RER. The s udy
modeled he beha io RER o he domes ic cu encies o h ee coun ies: Mexico,
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
43
Ko ea and F ance agains he US dolla . The econome ic echnique, VAR model, was
speci ied o ind he long- un associa ions o he RER o each coun y. The esul s
show ha , o each coun y, he e was a nega i e ela ionship be ween he RER and
wage sha e. Findings also showed ha Real Exchange Ra e is posi i ely ela ed wi h
labo p oduc i i y in F ance and Ko ea, bu in e sely ela ed in Mexico. An
explana ion as o why RER ended o e u n o he long un no mal alue was also
gi en. To Kahsay & Pa ena (2020), es ima es om ec o e o co ec ion models
(VECMs) and ec o au o eg ession models (VARs) indica e ha he REER esponds
minimally o changes in undamen als, wi h small and delayed esponses. Th ee
ac o s a e p oposed o ha e con ibu ed o his minimal esponse: labo ma ke
condi ions, p ice managemen , and emi ance ou lows. The policy implica ions
sugges ha labo ma ke e o ms, p ice libe aliza ion, and policies encou aging
domes ic in es men could imp o e he REER’s esponse o economic undamen als.
Hien e al. (2020) unde ook a comp ehensi e analysis on how huge amoun s o
emi ance can ha e an e ec on a coun y’s Real Exchange Ra e (RER) beha io ,
he eby causing he Du ch disease. The s udy ocused on coun ies which ecei e a
qui e high alue o emi ances, speci ically on 32 Asian de eloping coun ies. Using
da a co e ing he pe iod om 2006 o 2016, he S-GMM o he linea dynamic panel
da a (DPD) was used o analyze he ela ionship be ween REER and emi ances. The
indings show ha as pe capi a emi ances inc eases by 1 pe cen , REER inc eases
by 0.103 pe cen , signi ying he exis ence o he Du ch disease. The esul s u he
indica ed ha in coun ies wi h low emi ance o G oss Domes ic P oduc ,
emi ances esul s in REER app ecia ion while o coun ies ha ing a a io highe
han 1 pe cen , highe emi ances esul s in eal e ec i e exchange a e app ecia ion.
Mo eo e , he s udy co obo a es o he indings why pos ula e ha a lexible
exchange a e egime leads o he dampening o he app ecia ion o he REER caused
by inc eased emi ances.
Hassan e al. (2020) did a s udy o 22 OECD coun ies. The ixed e ec model
was he es ima ed echnique used o analyze he panel da a co e ing he pe iod 1980-
2015. Thei esea ch amongs o he esul s, e eals ha coun ies wi h a la ge sha e
o a wo king popula ion end o ha e an app ecia ing e ec on he RER because
inc ease in he wo king age popula ion leads o an inc ease in he ma ginal p oduc o
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
44
capi al which inc eases o eign di ec in es men he eby causing an inc ease in
capi al in low. The e ms o ade also had a signi ican e ec on RER. The
implica ions o he indings sugges ha o de eloping coun ies expe iencing a apid
aging popula ion, he e will be a nega i e e ec on hei in e na ional compe i i eness
due o RER app ecia ion. To coun e his, he go e nmen o hese coun ies will ha e
o adop a policy o sa ing mo e o he u u e by inc easing he e ec i e e i emen
age o h ough an inc ease in budge su plus.
A e e iewing he li e a u e, a gap is ound: many schola s ha e no el he need
o conduc an empi ical in es iga ion in o he beha io o ASEAN cu ency exchange
a es wi hin he con ex o a sensi i i y analysis ha conside s inancial c isis pe iods.
Sensi i i y analysis ecei es empi ical ocus in his s udy. Thus, us wo hy
conclusions ha di ec he decision-making p ocess ega ding i ms, in es men s, and
he en i e economy a e eached by assessing he sensi i i y o ou da a on he cu ency
exchange a es o ASEEAN na ions wi h espec o imes o high and low ola ili y.
Sensi i i y analysis o his kind o e s ac ual p oo o he alidi y o s udy
conclusions abou he beha io o exchange a es in ASEAN na ions. The cu en
s udy ocused on he ASEAN coun ies o Malaysia, Indonesia, Singapo e, he
Philippines, Thailand, Vie nam, Cambodia, Myanma , and Vie nam.
3. Me hodology
To analyze he beha io o exchange a es in ASEAN coun ies, we es ima ed
quan ile eg ession analysis on he daily se ies o exchange a e ola ili y o 8
ASEAN coun ies using daily da a. This was highly necessi a ed in o de o con ol
o he s uc u al b eak in he da a se caused by global inancial c isis. Wi hin he
scope o his esea ch, 1990 o 2023, he ollowing phases o s uc u al b eaks a e
disce nible. The pe iod om 1990 o 1991 wi nessed low ma ke ola ili y due o
poli ical s abili y ha exis ed ac oss coun ies, iscal discipline on he pa o he
go e nmen s, absence o e o ism, e c. The pe iod o 1990 o 2000 was a pe iod o
high ma ke ola ili y due o Ha shad Meh a Scam o 1992 in Indian ha c ashed he
s ock ma ke and Asian ige Financial c isis o 1997-1998 which led o he collapse
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
51
le el o ola ili y ha is signi ican gi en a z-s a is ic o 25.52022. The coe icien o
RESID(-1)^2 is -0.015426, which is s a is ically signi ican (z=-2.509593, p=0.0121),
indica ing a nega i e ela ionship be ween pas squa ed esiduals and cu en
ola ili y. This nega i e alue sugges s a mean- e e ing ola ili y beha io o
exchange a e in Singapo e; pe iods o high ola ili y end o be ollowed by lowe
ola ili y; a ypical cha ac e is ic obse ed in inancial ma ke s known as he ola ili y
clus e ing.
Table 5. ARCH esul s o Philippines
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.171417
0.187246
0.915467
0.3599
NEXC(-1)
0.979605
0.017294
56.64583
0.0000
Va iance Equa ion
C
0.083953
0.001614
52.01721
0.0000
RESID(-1)^2
-0.005885
0.000477
-12.32860
0.0000
F=1347.2 (0.0000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 5 shows ha he coe icien o eal e ec i e exchange a e is 0.979605,
which is signi ican a he 0.05 le el. Hence, eal e ec i e exchange a e in he
p e ious pe iod is a s ong p edic o o he eal e ec i e exchange a e in he cu en
pe iod, wi h a 1 uni inc ease in eal e ec i e exchange a e associa ed wi h
app oxima ely a 0.98 pe cen inc ease in he cu en NEXC, holding all o he a iables
cons an . The ARCH model esul s sugges ha he eal exchange a e in Philippines
exhibi s ime- a ying ola ili y ha can be pa ially cap u ed by i s own pas alues.
This could ha e implica ions o he demand o in Philippines.
F om Table 6, he coe icien o nominal exchange a e lagged one-pe iod is
ex emely signi ican (z-s a is ic o 59.96873) and nea uni y (0.976800), poin ing
owa ds a s ong au o eg essi e beha io whe e cu en eal e ec i e exchange a e
alues closely ollow pas alues. The a iance equa ion, which models he ola ili y
o he eal e ec i e exchange a e, ea u es a small bu highly signi ican cons an
(C=0.030006; z-s a is ic o 51.68566), indica ing a base le el o ola ili y ha is
consis en ye ela i ely low, gi en he scale o he coe icien . This sugges s ha
ex e nal shocks o inhe en economic ola ili y in Thailand’s ma ke is modes bu
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
52
pe sis en o e ime. The ARCH model’s indings shows ha eal e ec i e exchange
a e in Thailand exhibi s p edic able beha io based on i s his o ical alues, i s
ola ili y is no o e ly in luenced by i s immedia e pas , excep in he o m o mean-
e e sion in esponse o shocks. This could imply ha he Thailand exchange a e is
ela i ely s able, wi h inhe en mechanisms ha dampen he impac o la ge
luc ua ions o e ime, po en ially e lec ing e ec i e mone a y policy in e en ions
o a s able mac oeconomic en i onmen .
Table 6. ARCH esul s o Thailand
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.121671
0.101827
1.194875
0.2321
NEXC(-1)
0.976800
0.016288
59.96873
0.0000
Va iance Equa ion
C
0.030006
0.000581
51.68566
0.0000
RESD(-1)^2
-0.006750
0.000206
-32.74471
0.0000
F=486.17(0.0000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 7. ARCH esul s o Vie nam
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.373365
0.209037
1.786120
0.0741
NEXC(-1)
0.967368
0.014555
66.46428
0.0000
Va iance Equa ion
C
0.608470
0.023843
25.52022
0.0000
RESID(-1)^2
-0.015426
0.006147
-2.509593
0.0121
F=3002.3(0.0000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
The ARCH model esul s o Vie nam on Table 7 shows 0.967368 coe icien o
he eal e ec i e exchange a e Lagged one pe iod. The coe icien is highly
signi ican (z-s a is ic o 66.46428) and e y close o one. This indica es ha he
cu en nexc alue is almos pe ec ly p edic i e by i s p e ious alue, e lec ing
s ong pe sis ence o ine ia in he exchange a e. This inding implies ha once he
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
53
exchange a e eaches a ce ain le el, i is likely o emain nea ha le el in he
subsequen pe iod unless signi ican economic e en s occu . The a iance equa ion is
c i ical o unde s anding he ola ili y o eal e ec i e exchange a e. The cons an
e m (C) is 0.608470, highly signi ican (z-s a is ic o 25.52022), indica ing a
subs an i e inhe en ola ili y in he nexc. This e lec s ongoing economic ola ili y
in Vie nam po en ially due o luc ua ing commodi y p ices, poli ical unce ain y, o
ex e nal economic shocks.
Table 8. ARCH esul s o Cambodia
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.095810
0.152964
0.626354
0.5311
NEXC(-1)
0.995107
0.008166
121.8662
0.0000
Va iance Equa ion
C
0.215612
0.005022
42.92938
0.0000
RESD(-1)^2
-0.013266
0.000340
-39.06671
0.0000
F-s a is ic 267.1(0.000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
In Table 8, he ARCH esul s o Nige ia show Cambodia’s one-pe iod lag o
NEXC has he coe icien o 0.995107, which is signi ican ly high wi h a z-s a is ic o
121.8662. This sugges s ha he cu en alue o eal e ec i e exchange a e is almos
en i ely de e mined by i s alue in he p e ious pe iod, highligh ing s ong con inui y
and minimal a ia ion om his o ical le els in he sho e m. The in e cep (C) in he
mean equa ion is 0.095810, which is no s a is ically signi ican (p=0.5311). This
sugges s ha he e a e no signi ican mean changes in he eal e ec i e exchange a e
independen o i s pas alues, ein o cing he idea ha he exchange a e’s mo emen s
a e p edominan ly in luenced by i s own ine ia. In he a iance equa ion, he cons an
e m (C) is 0.215612, demons a ing a signi ican le el o baseline ola ili y (z-
s a is ic o 42.92938). This indica es a ela i ely high inhe en ola ili y in he
exchange a e, po en ially e lec ing he economic luc ua ions, policy changes, o
ma ke unce ain ies p e alen wi hin Cambodia.
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
54
Table 9. ARCH esul s o Myanma
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.433092
0.072750
5.953181
0.0000
NEXC(-1)
0.965299
0.005570
173.3036
0.0000
Va iance Equa ion
C
0.066289
0.003058
21.67919
0.0000
RESD(-1)^2
2.600196
0.909884
2.857724
0.0043
F=25461.3(0.000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 9 shows nominal exchange a e coe icien in Myanma is 0.965299. The
coe icien is highly signi ican wi h a z-s a is ic o 173.3036, showing ha he
nominal exchange a e is s ongly in luenced by i s p e ious alue. This coe icien
nea ly eaching one sugges s ha he exchange a e in Myanma demons a es
subs an ial pe sis ence, meaning ha cu en nominal exchange a e alues a e almos
a di ec e lec ion o he p e ious pe iod’s alues. This le el o pe sis ence can
indica e s abili y in he cu ency bu migh also e lec a igidi y ha could impede
apid adjus men o new economic condi ions. The a iance equa ion e eals he
model's app oach o handling ola ili y. The cons an e m (C) is 0.066289, wi h a
e y high signi icance le el (z-s a is ic o 21.67919), indica ing a ela i ely mode a e
baseline ola ili y in he exchange a e. This inding sugges s ha while he e a e
luc ua ions, hey a e no excessi ely ola ile unde no mal condi ions, which is
a o able o economic planning and o eign ade nego ia ions.
Table 10. ARCH esul s o Malaysia
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.065025
0.025872
2.513322
0.0120
NEXC(-1)
0.986980
0.004727
208.7983
0.0000
Va iance Equa ion
C
0.010352
0.000206
50.13430
0.0000
RESD(-1)^2
-0.010740
0.000218
-49.29567
0.0000
F-s a is ic=1468.92(0.000)
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
55
F om he ARCH in Table 10 abo e, he coe icien o one-pe iod lag o eal
e ec i e exchange a e is ema kably high a 0.986980, wi h an excep ionally
signi ican z-s a is ic o 208.7983. This esul indica es a e y s ong pe sis ence in
he exchange a e, sugges ing ha he cu en nexc is almos en i ely p edic able by
i s immedia e pas alue. Such a high le el o pe sis ence e lec s a s able exchange
a e en i onmen , whe e changes om one pe iod o he nex a e minimal and la gely
an icipa ed. The cons an e m (C) in he mean equa ion is 0.065025, which is
s a is ically signi ican (p=0.0120). This signi ies ha he e is a small bu consis en
adjus men o he eal e ec i e exchange a e independen o i s p e ious alue,
possibly e lec ing sys ema ic in luences such as policy adjus men s o long- e m
economic ends. In he a iance equa ion, he cons an e m (C) is 0.010352,
indica ing a baseline le el o ola ili y ha is signi ican and consis en (z-s a is ic o
50.13430). This sugges s ha he unde lying ola ili y o Malaysia’s nominal
exchange a e is mode a e bu pe sis en , p o iding a ounda ional le el o exchange
a e luc ua ion ha migh be a ibu ed o egula ma ke dynamics o ex e nal
economic in luences.
Table 11. GARCH esul s o Indonesia
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.745908
0.567637
1.314058
0.1888
NEXC(-1)
0.982474
0.012734
77.15495
0.0000
Va iance Equa ion
C
1.661573
0.066105
25.13538
0.0000
RESD(-1)^2
-0.027529
0.002027
-13.57907
0.0000
GARCH(-1)
0.564221
0.003347
168.5564
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
The esul s o he GARCH in Table 11 shows ha Indonesia nominal exchange
a e wi h a coe icien o 0.982474, which is highly signi ican (z-s a is ic o
77.15495) indica es a e y s ong au o eg essi e cha ac e is ic, whe e he cu en eal
e ec i e exchange a e is almos comple ely de e mined by i s alue in he p e ious
pe iod. This high deg ee o pe sis ence sugges s ha he nominal exchange a e in
Indonesia changes g adually o e ime, p o iding a p edic able pa e n based on
his o ical alues. The a iance equa ion in he GARCH model is designed o cap u e
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
56
he ola ili y o eal e ec i e exchange a e, including e ms o bo h he RESID(-
1)^2 and he lagged condi ional a iance (GARCH(-1)). The coe icien o RESID(-
1)^2 is -0.027529, signi ican wi h a nega i e sign (z-s a is ic o -13.57907),
indica ing a mean- e e sion o ola ili y. This implies ha highe ola ili y in one
pe iod ends o be ollowed by educed ola ili y, aligning wi h ypical inancial ime
se ies beha io whe e high- ola ili y e en s o en s abilize o e ime. The GARCH(-
1) coe icien is 0.564221, signi ican ly posi i e (z-s a is ic o 168.5564), highligh ing
he pe sis ence o ola ili y. This means ha i he exchange a e was ola ile in he
pas , i is likely o emain ola ile, poin ing o a sus ained impac o pas ola ili y on
cu en ola ili y le els.
Table 12. GARCH esul s o Singapo e
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.355531
0.176263
2.017048
0.0437
NEXC(-1)
0.970111
0.012316
78.76919
0.0000
Va iance Equa ion
C
0.086710
0.037361
2.320868
0.0203
RESD(-1)^2
-0.015018
0.001411
-10.64321
0.0000
GARCH(-1)
0.864199
0.063414
13.62782
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
In Table 12, he ARCH and he GARCH coe icien s o Singapo e nominal
exchange a e shows he signi ican ola ili y i s economy has expe ienced due o
a ious economic sanc ions and commodi y p ice luc ua ions. The one-pe iod lagged
alue o exchange a e is 0.970111, which is highly signi ican (z-s a is ic o
78.76919). This sugges s ha he exchange a e om one pe iod s ongly in luences
he a e in he subsequen pe iod, indica ing a g adual adjus men o new in o ma ion
and a endency o he exchange a e o ollow a smoo h pa h o e ime. In he a iance
equa ion, he baseline ola ili y o he eal e ec i e exchange a e is cap u ed by he
cons an e m (C=0.086710), which is signi ican (p=0.0203). This sugges s a
ounda ional le el o ola ili y inhe en in he Singapo e exchange a e ma ke is
in luenced by economic policy unce ain y. The GARCH(-1) coe icien o 0.864199
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
57
is signi ican ly posi i e, indica ing ha pas ola ili y has a s ong p edic i e powe
on u u e ola ili y. This high pe sis ence in ola ili y sugges s ha shocks o he
exchange a e ha e long-las ing e ec s, which could exace ba e he impac o poli ical
e en s on he ma ke s abili y.
Table 13. GARCH esul s o Philippines
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.173271
0.192182
0.901599
0.3673
NEXC(-1)
0.979277
0.017725
55.24747
0.0000
Va iance Equa ion
C
0.037690
0.043979
0.857004
0.3914
RESD(-1)^2
-0.006025
0.001299
-4.639478
0.0000
GARCH(-1)
0.561294
0.512449
1.095317
0.2734
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
The GARCH esul s in Table 13 sugges ha he cu en nominal exchange a e
is hea ily in luenced by i s immedia e pas alue, e lec ing a s able and p edic able
beha iou in he sho e m. This le el o pe sis ence is ypical o economies wi h
s able mac oeconomic policies whe e he exchange a e adjus s g adually o changes.
The in e cep (C) o 0.173271, al hough no s a is ically signi ican (p=0.3673),
indica es a mino cons an impac on he eal e ec i e exchange a e ha is no
explained by i s his o ical pe o mance. The GARCH(-1) coe icien o 0.561294,
al hough no signi ican (p=0.2734), sugges s some deg ee o ola ili y pe sis ence.
This indica es ha while pas ola ili y in luences cu en ola ili y, he e ec is no
as s ong as i migh be in mo e ola ile o uns able economies. Fo India, he GARCH
model’s shows how pas exchange a e le els and hei ola ili y a ec cu en and
u u e a es.
The esul s o he GARCH esul in Table 14 show ha nominal exchange a e
shows a high coe icien o 0.976900 wi h a signi ican z-s a is ic o 45.54392. This
indica es ha he nominal exchange a e is hea ily in luenced by i s p e ious alues,
showcasing s ong pe sis ence. Such a high le el o au o eg ession sugges s ha
changes in he nominal exchange a e a e g adual and p edic able o e sho in e als,
ypical o an economy whe e exchange a es a e managed wi hin a policy amewo k
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
58
designed o main ain s abili y. The in e cep (C) o 0.120945, hough no signi ican
(p=0.3652), indica es a minimal baseline impac on eal e ec i e exchange a e,
which is no explained me ely by i s lagged alues. This deno es unde lying
mac oeconomic ends o policy shi s ha exe a cons an bu sub le in luence on he
eal e ec i e exchange a e. The GARCH(-1) coe icien is 0.565968, which is no
signi ican (p=0.1795). This sugges s ha pas ola ili y has a mode a e in luence on
u u e ola ili y, his ela ionship is no as s ong as migh be seen in mo e eely
loa ing cu encies.
Table 14. GARCH esul s o Thailand
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.120945
0.133560
0.905547
0.3652
NEXC(-1)
0.976900
0.021450
45.54392
0.0000
Va iance Equa ion
C
0.016618
0.016093
1.032599
0.3018
RESD(-1)^2
-0.008602
0.000392
-21.95920
0.0000
GARCH(-1)
0.565968
0.421639
1.342305
0.1795
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 15. GARCH esul s o Vie nam
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.355531
0.176263
2.017048
0.0437
NEXC(-1)
0.970111
0.012316
78.76919
0.0000
Va iance Equa ion
C
0.086710
0.037361
2.320868
0.0203
RESD(-1)^2
-0.015018
0.001411
-10.64321
0.0000
GARCH(-1)
0.864199
0.063414
13.62782
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
The GARCH model esul s o Table 15 abo e o Vie nam's NEXC lag one pe iod
shows a coe icien o 0.970111 and a z-s a is ic o 78.76919, indica ing ex emely
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
59
high s a is ical signi icance. This s ong au o eg essi e componen sugges s ha he
NEXC is highly pe sis en , wi h pas alues being a s ong p edic o o u u e a es.
Such beha io indica es a s able bu slowly adjus ing exchange a e en i onmen ,
whe e changes a e g adual and no ab up , likely e lec ing Vie nam’s mone a y
policy aimed a s abilizing he exchange a e o a oid economic shocks. The a iance
equa ion o he GARCH model shows he cons an e m o 0.086710, signi ican a
he 0.0203 le el, indica es a ounda ional le el o ola ili y inhe en o he eal
e ec i e exchange a e. This le el o baseline ola ili y is in luenced by ex e nal
economic p essu es, in e nal economic policy changes, o ma ke pe cep ions
a ec ing he Sou h A ican economy. The GARCH(-1) e m a 0.864199,
signi ican ly high (z-s a is ic o 13.62782), shows ha pas ola ili y has a s ong and
pe sis en in luence on cu en ola ili y, indica ing ha ola ili y shocks end o ha e
long-las ing e ec s.
Table 16. GARCH esul s o Cambodia
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.070835
0.157886
0.448649
0.6537
NEXC(-1)
0.996306
0.008428
118.2096
0.0000
Va iance Equa ion
C
0.074293
0.013774
5.393590
0.0000
RESD(-1)^2
-0.013525
0.002767
-4.888788
0.0000
GARCH(-1)
0.663125
0.062997
10.52629
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 16 epo ed GARCH model analysis o Nige ia’s nominal exchange a e.
The signi ican au o eg essi e componen in he mean equa ion, wi h nominal
exchange a e showing a coe icien o 0.996306 and an excep ionally high z-s a is ic
o 118.2096, demons a es ex eme pe sis ence. This implies ha he NEXC is almos
pe ec ly p edic ed by i s alue in he p eceding pe iod, sugges ing ha he exchange
a e e ol es in a highly p edic able manne wi h li le de ia ion om i s his o ical
pa h. This can be indica i e o a igh ly managed exchange a e sys em whe e policy
in e en ions ensu e s abili y and educe unp edic abili y in he o ex ma ke . The
GARCH(-1) e m a 0.663125 (signi ican wi h a z-s a is ic o 10.52629) indica es
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
60
ha p e ious pe iods’ ola ili y has a subs an ial ca yo e e ec in o cu en
ola ili y. This poin s o a scena io whe e shocks o he exchange a e can ha e
p olonged impac s, in luencing u u e ola ili y le els signi ican ly.
Table 17. GARCH esul s o Myanma
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.193976
0.162216
1.195786
0.2318
NEXC(-1)
0.988742
0.009222
107.2133
0.0000
Va iance Equa ion
C
0.049900
0.041271
1.209101
0.2266
RESD(-1)^2
-0.012306
0.003290
-3.740106
0.0002
GARCH(-1)
0.800592
0.168963
4.738260
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Table 17 epo ed GARCH esul s and shows ha he coe icien o nominal
exchange a e lagged one-pe iod is 0.988742. I is highly signi ican (z-s a is ic o
107.2133). This indica es ha he NEXC is p edominan ly in luenced by i s alue in
he p e ious pe iod, signi ying s ong con inui y and p edic abili y in exchange a e
mo emen s. Such high pe sis ence o en cha ac e izes exchange a e sys ems whe e
policy in e en ions aim o main ain s abili y o whe e economic condi ions do no
luc ua e d ama ically in he sho e m. The GARCH(-1) e m a 0.800592, wi h a
signi ican z-s a is ic o 4.738260, e lec s high ola ili y pe sis ence. This inding
sugges s ha once he nominal exchange a e exhibi s ola ili y; such luc ua ions a e
likely o con inue in o he u u e, emphasizing he impac o pas ola ili y on cu en
and u u e ola ili y le els.
The esul s o he GARCH in Table 18 o Malaysia show ha he coe icien o
one-pe iod lagged nominal exchange a e s ands a 0.986980 wi h a s ikingly high z-
s a is ic o 136.7875, indica ing an ex emely high le el o pe sis ence. This sugges s
ha he cu en nominal exchange a e is almos en i ely dependen on i s immedia e
pas alue, e lec ing a s able and p edic able exchange a e beha io o e he sho
e m. This cha ac e is ic is o en indica i e o an economy wi h e ec i e egula o y
o e sigh whe e exchange a es a e managed o ensu e g adual adjus men s a he han
ab up swings, p o iding s abili y which is c ucial o in e na ional ade and
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
67
ha e a pe sis en impac o e ime. The analysis sugges s ha he nominal exchange
a e is cha ac e ized by a high le el o pe sis ence and po en ial hea y ails in i s
dis ibu ion, bu ecen shocks and hei asymme ic impac a e no playing a
signi ican ole in o ecas ing cu en ola ili y.
Table 25. FIGARCH-DCC esul s o Myanma
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.136302
0.002126
64.12275
0.0000
NEXC(-1)
0.993281
3.02E-05
32924.95
0.0000
Va iance Equa ion
C
-0.187750
0.006239
-30.09357
0.0000
ARCH (-1)^2
-0.321892
0.041477
-7.760684
0.0000
GARCH (1)
0.579298
0.012131
47.75296
0.0000
d-coe icien
0.808820
0.002469
327.59011
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10
In Table 25 abo e, he coe icien 𝐶, ep esen ing he in e cep in he a iance
equa ion, is highly signi ican wi h a nea -ze o p obabili y (p- alue), indica ing a
s ong baseline le el o ola ili y in he exchange a e mo emen s. The lagged a iable
o nominal exchange a e RER(-1) wi h a e y high z-s a is ic and a p- alue o ze o
con i ms he pas nominal exchange a e alues a e ex emely p edic i e o cu en
NEXC alues, signi ying a s ong au o eg essi e cha ac e in he exchange a e se ies.
The coe icien s ARCH e m and i s esidual ep esen he sho - un componen s o
ola ili y, he ARCH e m, and he measu e o asymme y in he impac o esiduals
(le e age e ec ), espec i ely. The nega i e sign o ARCH, along wi h i s signi ican
z-s a is ic, sugges s a less han p opo ional eac ion o ola ili y o pas squa ed
esiduals, The coe icien o GARCH e m and i s high z-s a is ic and ze o p obabili y
e eal ha pas ola ili y is highly p edic i e o u u e ola ili y, signi ying a long
memo y cha ac e is ic o he ola ili y p ocess. This could mean ha ola ili y shocks
o he nominal exchange a e a e no only impac ul in he sho un bu also pe sis
o e a longe pe iod, in luencing u u e ola ili y le els. Thus, in Myanma , an
eme ging economy wi h ac i e engagemen in bi coin and o he c yp ocu encies, his
ola ili y dynamic could be c ucial. A highe pe sis ence in ola ili y indica es ha
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
68
ex e nal shocks, possibly including hose ela ed o bi coin demand luc ua ions, ha e
long-las ing e ec s on he s abili y o he eal e ec i e exchange a e. Such indings
e lec s he impac decisions ela ed o isk managemen , in es men , and economic
policy, as sus ained ola ili y in exchange a es may a ec in e na ional ade,
in es men lows, and economic s abili y.
The FIGARCH o Malaysia a e epo ed in Table 26. The FIGARCH model
esul s o Malaysia’s nominal exchange a e signi y a complex dynamic o ola ili y
in exchange a e mo emen s in luenced by Bi coin demand and o he economic
ac o s. The cons an being nega i e and signi ican indica es ha he baseline
ola ili y is subjec o mean e e sion. The ARCH coe icien is also nega i e and
signi ican ; sugges ing ha pas ola ili y has a s ong shock impac on cu en
ola ili y. This can be indica i e o a ma ke ha eac s s ongly o pas ola ili y
shocks, whe e he e ec s o la ge changes end o be ollowed by u he la ge
changes, which may emain o e long pe iods. This ai is pa icula ly impo an o
inancial isk managemen as i poin s o a po en ially highe isk en i onmen o
in es o s and policymake s. The GARCH coe icien being posi i e and signi ican
sugges s ha ola ili y shocks a e pe sis en o e ime, which aligns wi h he concep
o long memo y in ola ili y. This indica es ha he e ec s o shocks o ola ili y do
no decay quickly and ha pas pe iods o ins abili y can in luence u u e ola ili y
o e a long ho izon. The FIGARCH model indica es a complex ola ili y s uc u e in
eal e ec i e exchange a e, likely d i en by bo h ex e nal economic o ces and
in e nal policy measu es.
Table 26. FIGARCH-DCC esul s o Malaysia
Mean Equa ion
Va iable
Coe icien
S d. E o
z-S a is ic
P ob.
C
0.004035
4.41E-05
91.56762
0.0000
NEXC(-1)
0.999141
1.23E-05
81386.46
0.0000
Va iance Equa ion
C
-3.216785
0.157172
-20.46668
0.0000
ARCH(-1)^2
-0.406821
0.014469
-28.11642
0.0000
GARCH (-1)
0.250863
0.036499
6.873086
0.0000
d-coe icien
0.452890
0.001167
388.08054
0.0000
Sou ce: Au ho s’ es ima ion esul s wi h E iews 10.
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
69
Discussion
When compa ing ou esea ch indings wi h hose om o he s udies, i is
impo an o no e ha while Yuliadi e al. (2024) con i m low ola ili y in cu ency
exchange a es due o Singapo e’s managed loa ing exchange a e sys em, ou
esea ch indings which show a signi ican pe sis ence o shocks in he exchange a e
o he Singapo ean cu ency do no en i ely ag ee wi h hese indings. Ou esea ch
indings indeed co obo a ed hose o Yuliadi e al. (2024), who indica ed ha he
go e nmen should keep an eye ou o economic measu es ha would lessen he
impac o ASEAN coun ies’ exchange a e ola ili y.
In addi ion, ou esul s a e consis en wi h hose o Rossan o e al. (2023), who
ound ha cu ency exchange a e ola ili y in na ions ha adhe ed o he ee loa
egime pe sis ed e en en yea s a e he inancial c isis; Jona han (2022) ob ained
e idence o an asymme ic esponse o exchange a e luc ua ions ha co obo a es
ou s; Ain (2022) p oduced esul s om he wa ele powe spec um analysis ha a e
consis en wi h ou esul s o ASEAN na ions. Acco ding o Ain’s (2022) esea ch
indings; ou ASEAN coun ies namely, Singapo e, Thailand, Malaysia, and
Indonesia we e ound o ha e highly ola ile cu ency a es. Thailand has li le sho -
e m ola ili y and no inc eased long- e m ola ili y, in con as o he Philippines’
sligh ola ili y. Ou s udy’s ou come sugges s ha he eal exchange a e in
Philippines exhibi s ime- a ying ola ili y ha can be pa ially cap u ed by i s own
pas alues. This esea ch ou come is consis en wi h hose o Abdul, Hsia Hua Sheng,
and Na alia Diniz-Maganini (2021). These au ho s demons a ed ha exchange a e
ola ili y is asymme ic and ime- a ying by using empi ical esea ch based on he
EGARCH (1, 1) speci ica ion i ed on mon hly Asian cu encies. The indings
indica e ha h ee cu encies ha e indica ions o asymme y in hei condi ional
a iance p io o he Asian c isis. Wi h he excep ion o one, all o hem displayed a
no iceable inc ease in ola ili y and asymme y e ec .
The indings om ou s udy also co obo a e hose epo ed by Goda & P iewe
(2020). In ac , he au ho s e alua ed he p ima y causes o cyclical REER beha io
in eme ging ma ke economies (EME). The esea ch employed a sample size o i een
eme ging ma ke economies om 1996 o 2016, co e ing se e al signi ican
economic shocks such as he Asian c ises o 1997–1998; he Russian c isis o 1998;
Da id UMORU, Beau y IGBINOVIA, Mohammed Fa id ALIYU
70
and he Tu kish c isis o 2001. The 15 na ions a e di ided in o wo ca ego ies by he
s udy: indus ial eme ging ma ke economies and commodi ies de eloping ma ke
economies. The dynamic panel ixed e ec s model was he econome ic me hod
employed o de e mine he ac o s in luencing REER. Based on he indings,
de eloping ma ke economies ha ely on commodi ies ypically ha e highe REER
ola ili y.
5. Conclusion
The s udy e alua ed he beha io o he nominal exchange a e in ASEAN
coun ies, namely, Indonesia, Singapo e, he Philippines, Thailand, Vie nam,
Cambodia, Myanma , and Malaysia. The cu en esea ch aims o analyse he
beha io o exchange a es in ASEAN coun ies using quan ile eg ession sensi i i y
analysis. ARCH, GARCH, and FIGARCH modeling a e also pe o med o
obus ness checks. This s udy made use o daily exchange a e da a co e ing he
pe iod om Janua y 1, 1990, o Decembe 30, 2023, inclusi e o weekends and
holidays. The da a we e handled in wo e as (be o e and a e he inancial c isis). The
esul s a e discussed based on each coun y. The models a e well explained, and he
esul s a e p esen ed in an o ganized manne . The GARCH and FIGARCH-DCC
modeling echniques we e execu ed o u he gauge he impulsi e pe o mance o
exchange a es o he a o emen ioned coun ies. Ou esea ch indings uphold
asymme y and pe sis ence in he beha io o exchange a es o ASEAN cu encies.
In e ms o compa a i e discussions, ou esea ch indings conside ably align wi h he
indings o o he esea che s, namely Yuliadi e al. (2024), Rossan o e al. (2023),
Jona han (2022), Ain (2022), and Na alia e al. (2021).
In Indonesia, he FIGARCH esul s show high pe sis ence in ola ili y, as
indica ed by a signi ican GARCH e m, sugges ing ha shocks o he exchange a e
ha e las ing e ec s. Singapo e’s exchange a e exhibi ed signi ican pe sis ence o
shocks, indica ing ha he e ec s o shocks on he exchange a e a e endu ing.
Philippines’s FIGARCH model illus a es a high le el o ola ili y pe sis ence. Fo
Thailand, he ola ili y is cha ac e ized by long-memo y and a conside able ola ili y
Exchange a e beha iou in ASEAN coun ies – a sensi i i y analysis
71
shock, which e lec s he sensi i i y o he exchange a e o ma ke dynamics. In
Vie nam, exchange a e ola ili y does no die o quickly, and his has he endency
o s imula e specula i e chances. Cambodia exhibi s weigh y pe sis ence in exchange
a e ola ili y. Myanma ’s FIGARCH analysis shows pe manen exchange a e
shocks. Las ly, in Malaysia, ola ili y pe sis ence in he nominal exchange a e is
obus . I su ices o ad ise ha all ASEAN go e nmen s should enhance egula o y
amewo ks ha moni o and possibly con ol exchange a e ansac ions o p e en
excessi e specula i e ac i i ies ha could des abilize na ional cu encies.
Acco dingly, we ecommend he need o ASEAN coun ies’ cen al banks o pu in o
e ec he p e en a i e measu es necessa y o p ese e economic s abili y and con ol
he ola ili y dynamics o he o eign exchange ma ke .
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