P anan a, Billy; Alexiou, Cons an inos
A icle
Exchange a es, bond yields and he s ock ma ke :
Nonlinea e idence o Indonesia du ing he COVID-19
pe iod
Asian Jou nal o Economics and Banking (AJEB)
P o ided in Coope a ion wi h:
Ho Chi Minh Uni e si y o Banking (HUB), Ho Chi Minh Ci y
Sugges ed Ci a ion: P anan a, Billy; Alexiou, Cons an inos (2024) : Exchange a es, bond yields and
he s ock ma ke : Nonlinea e idence o Indonesia du ing he COVID-19 pe iod, Asian Jou nal o
Economics and Banking (AJEB), ISSN 2633-7991, Eme ald, Leeds, Vol. 8, Iss. 1, pp. 83-99,
h ps://doi.o g/10.1108/AJEB-12-2022-0157
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Exchange a es, bond yields
and he s ock ma ke : nonlinea
e idence o Indonesia du ing
he COVID-19 pe iod
Billy P anan a
Bank Indonesia, Jaka a, Indonesia, and
Cons an inos Alexiou
School o Managemen , C an ield Uni e si y, Bed o d, UK
Abs ac
Pu pose –The au ho s explo e he ela ionship be ween he exchange a e, bond yield and he s ock ma ke as
well as he e ec o capi al ma ke dynamics on he exchange a e be o e and du ing he COVID-19 pandemic.
Design/me hodology/app oach –The au ho s employ a non-linea au o eg essi e dis ibu ed lag (NARDL)
me hodology using daily da a o he Indonesian economy o e he pe iod 2012–2021.
Findings –Whils , o e he ull sample pe iod, he au ho s ind no coin eg a ion be ween he exchange a e,
he 10-yea bond yield and s ock ma ke , o he COVID-19 pe iod, e idence o coin eg a ion is p esen .
Fu he mo e, he esul s sugges ha asymme ic e ec s a e e iden bo h in he sho as well as he long un.
O iginali y/ alue –To he bes o he au ho s’knowledge, his is he i s ime ha he ela ionship be ween
he exchange a e, bond yield and he s ock ma ke as well as he e ec o capi al ma ke dynamics on he
exchange a e be o e and du ing he COVID-19 pandemic has been explo ed in he case o he Indonesian
economy.
Keywo ds Capi al ma ke dynamics, Exchange a e, Asymme ic e ec , Bond ma ke , S ock ma ke
Pape ype Resea ch pape
1. In oduc ion
The inc easingly in eg a ed global economy has accele a ed he g ow h o o eign cu ency
ansac ions, no ably in in e na ional ansac ion paymen s. These ansac ions a e mos ly
non-physical in na u e and a e ela ed o in e na ional ade paymen s and in es men o
o eign capi al in he capi al ma ke s ha a e iden i ied as capi al lows.
The ole o he capi al ma ke is c ucial in helping he economy, pa icula ly o
de eloping coun ies, which gene ally expe ience a de ici and seek unds o inance
economic ac i i ies om in es o s, especially h ough he s ocks and bonds ma ke . A e he
Asian Cu ency C isis in 1997, many de eloping coun ies educed ulne abili ies a ising
om ex e nal deb by issuing bonds in local cu encies (Ho mann e al., 2021). Due o limi ed
unds om domes ic in es o s, de eloping coun ies egula ly issue local cu ency bonds as
means o a ac ing unds om o eign in es o s. Howe e , such e o s ha e no been able o
The e ec o
capi al ma ke
dynamics
83
JEL Classi ica ion —C32, F31, G11
© Billy P anan a and Cons an inos Alexiou. Published in Asian Jou nal o Economics and Banking.
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h ps://www.eme ald.com/insigh /2615-9821.h m
Recei ed 3 Decembe 2022
Re ised 4 Feb ua y 2023
13 Ma ch 2023
Accep ed 17 Ma ch 2023
Asian Jou nal o Economics and
Banking
Vol. 8 No. 1, 2024
pp. 83-99
Eme ald Publishing Limi ed
e-ISSN: 2633-7991
p-ISSN: 2615-9821
DOI 10.1108/AJEB-12-2022-0157
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elimina e cu ency isk issues as o eign in es o s ha e always he op ion o con e ing hei
asse s o hei p e e ed cu ency.
Acco ding o Juh o e al., (2022), o eign capi al lows make eme ging ma ke coun ies
ulne able o ex e nal shocks. In pa icula , in lows o o eign capi al, o a g ea ex en , a e
de e mined by he p e ailing economic condi ions and he le el o yield o e ed. As such,
nega i e in es men pe cep ion en ails an ou low o capi al which in u n causes a dis up ion
in he domes ic economy and mo e ulne able o ex e nal shocks. Engel and Wu (2018)
p o ide e idence ha liquidi y yield on so e eign bonds has signi ican explana o y powe o
in luence he exchange a e mo emen s in G10 cu encies. They also ound ha in e es a es
and lagged adjus men e ms o he eal exchange a e a e impo an de e minan s o
exchange a e mo emen s. Fu he mo e, Boda and Reding (1999) show ha hei s udy
explains ha he le el o exchange a e a iabili y in luences in e na ional bonds and s ock
co ela ions in Eu opean coun ies.
Fundamen ally, in lows o capi al cons i u e a signi ican sou ce o inance o de eloping
coun ies as a means o spu ing economic g ow h, enhancing inancial sec o
compe i i eness, enabling g ea e in es men ac i i ies and smoo hing ou consump ion
(Juh o e al., 2022;In e na ional Mone a y Fund, 2012). The s a e o he undamen als and he
deg ee economic openness, he cu ency a e egime and he mac oeconomic policies adop ed
a e all signi ican ac o s ha a ec o eign capi al lows. In his con ex , s onge economies
can o e highe yields, hence a ac ing mo e o eign capi al in low. Global economic shocks,
howe e , can dis up a coun y’s economy h ough a e e sal o o eign capi al lows.
Coun ies ha ope a e unde a ixed exchange a e sys em o a simila sys em as happened in
he 1990s in La in Ame ica and Sou heas Asia a e p one o p onounced cu ency c isis
s emming om exchange a e specula ion. As such in op imizing he ad an ages o o eign
capi al in es men whils mi iga ing he isk o cu ency c ises in he u u e, i is impe a i e
ha we examine he ela ionship be ween capi al lows and exchange a e mo emen s.
In his pape , we in es iga e he ela ionship be ween exchange a e mo emen s and capi al
ma ke ansac ions in he bond and s ock ma ke s and explo e he possibili y o nonlinea i ies
in he unde lying ela ionships. Mo e speci ically, we ocus on he mo emen o bond p ice, he
s ock index –in e ms o daily p ice e u ns –and he exchange a e o e he pe iod 2012–2021.
In addi ion, hiss udy also in es iga es he capi al ma ke dynamicsdu ing heCOVID-19 c isis.
To his objec i e, we in es iga e he asymme ic coin eg a ion among a iables using he
nonlinea au o eg essi e dis ibu ed lag (NARDL) app oach de eloped by Shin e al. (2014).
Using he NARDL model will allow us o simul aneously ind and analyse bo h nega i e and
posi i e asymme ic coin eg a ion among a iables in he sho and long un, simul aneously.
Se e al empi ical s udies ha e p e iously been conduc ed o in es iga e he ela ionship
be ween he s ock ma ke and he exchange a e using di e en me hodologies. Howe e ,
he e a e s ill limi ed s udies ha use he NARDL me hod o in es iga e he ela ionship
be ween a iables, especially hose ela ed o exchange a es, go e nmen bonds and s ock
ma ke s. To he bes o ou knowledge, his is he i s s udy ha employs he NARDL
me hodology in he con ex o he Indonesian economy and hence o e s signi ican policy
implica ions o be conside ed by policymake s, in es o s and po olio manage s when
an icipa ing po en ial ola ili y in exchange a es, go e nmen bonds and s ock ma ke s.
The es o he pape is o ganized as ollows: sec ion 2 ouches on he ele an li e a u e in
he a ea whils sec ion 3 ocuses on he empi ical in es iga ion u ilized in his s udy. Sec ion 4
p esen s and discusses he esul s, and inally, sec ion 5 p o ides some concluding ema ks.
2. Rele an li e a u e
The li e a u e on exchange a e de e mina ion is inunda ed wi h s udies ha employ
mac oeconomic indica o s, capi al ma ke indices and mic os uc u al app oaches o
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in es iga e he impac o he bond and s ock ma ke on cu ency a e mo emen s. Fo
ins ance, in an eme ging ma ke con ex , Jongwanich and Kohpaiboon (2013) explo ed he
impac o capi al lows on he exchange a e in Asian coun ies and a i med ha he
s uc u e o capi al lows plays a c ucial ole in de e mining how hey a ec exchange a es.
The s udy showed ha capi al ma ke in es men and loan om banks ha e a bigge
in luence on cu ency app ecia ion han di ec in es men om o e seas. They a gued ha
he ela i ely s able and concen a ed na u e o o eign di ec in es men lows, especially in
he adable and expo -o ien ed sec o s, caused he slow pace o adjus men in he exchange
a e. The e o e, by closely obse ing he de elopmen o in es men po olios, i will p o ide
us wi h a be e unde s anding o he mo emen o exchange a es.
In he con ex o de eloped coun ies, he e a e s udies om Lace e al. (2015) and Engel
and Wu (2018) who s udied he e ec o go e nmen bond yields and o he mac oeconomic
indica o s on he exchange a e. Lace e al. (2015) ound ha Uni ed S a es (US) and Ge man
go e nmen deb yields can be u ilized o de e mine he EUR/US$ exchange a e mo emen s.
Simila esul s we e also ound by Engel and Wu (2018) who obse ed a s ong causal
ela ionship be ween go e nmen bond liquidi y and exchange a es.
In con as o p e ious s udies, acco ding o Rosnawin ang e al. (2021), by using mon hly
da a om 2006 o 2018, hey ound no long- un associa ion among he US$/IDR cu ency a e
and he yield on 10-yea Indonesian so e eign bonds. Those ac o s, howe e , ha e a wo-
way causal associa ion in he sho un. In he same spi i , Soni e al. (2018) looked a he
impac o a ious mac oeconomic ac o s on he US$/INR exchange a es om 2000 o 2017
and ound ha go e nmen bonds a e a signi ican p edic o ha a ec s he US$/INR
exchange a e. Fu he mo e, using qua e ly da a om 1983 o 2014, Hsing (2016) es ablished
a posi i e impac be ween he Sou h A ican go e nmen bond yield, US eal g oss domes ic
p oduc (GDP), US s ock p ice, Sou h A ican in la ion and exchange a e ola ili y.
In so a as po olio in es men a ec s exchange a e mo emen s, a numbe o s udies ha e
explo ed he impac o changes in equi y ma ke and cu ency ola ili y (see o ins ance,
Ande sen e al., 2007;Eh mann e al., 2011;Kal e al., 2015;Raza and Wu, 2018). Bahmani-
Oskooee and Soh abian (1992) by using G ange causali y and coin eg a ion me hodologies
es ablished a wo-way associa ion among he equi y ma ke and cu ency a e in he sho un,
bu no long- un associa ion among he equi y ma ke and he domes ic cu ency a e was ound.
Fu he mo e, using daily da a om 1986 o 1998, G ange e al. (2000) examined he
ela ionship be ween exchange a es and s ock ma ke s in Asian coun ies. The eme ging
e idence sugges ed a mixed pic u e as o Japan and Indonesia, no link was es ablished, whils in
he case o Ko ea, he exchange a e was ound o a ec he s ock p ice. Fo he es o he
coun ies in he sample, he s ock p ice o a ce ain ex en was ound o a ec he exchange a e.
In ano he s udy, Nieh and Lee (2001) when in es iga ed he in e ac ion be ween s ock p ices
and exchange a es in he G-7 economies ailed o es ablish a long- un ela ionship.
When s udied he ela ionship be ween he s ock ma ke and cu ency a e in he con ex
o 17 O ganisa ion o Economic Co-ope a ion and De elopmen economies, Hau and Rey
(2006) ound ha be e e u ns in he domes ic equi ies ma ke ela i e o he o eign equi y
ma ke a e linked o a dep ecia ion o he domes ic cu ency. This inding howe e
con adic s he iew ha inc easing s ock ma ke s a e ollowed by ising exchange a es.
In he Indonesian con ex , Anggi awa i and Ekapu a (2020) in es iga ed he ela ionship
be ween he o al amoun o ne o eign in es men s, go e nmen secu i ies, equi y ma ke s
and mo emen s in domes ic cu ency. Applying G ange causali y and Vec o
Au o eg ession (VAR) me hodologies on daily da a om 2011–2016, hey ound a
bidi ec ional causali y be ween o eign in es men in Indonesia’s inancial secu i ies and
he US$/IDR cu ency a e. I was also shown ha o al in e na ional capi al und lows o he
domes ic inancial ma ke had an impac on he US$/IDR cu ency a e’s app ecia ion, while
o eign capi al ou lows caused a dep ecia ion o he US$/IDR.
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On a di e en no e, and by using a mic os uc u e app oach, Rahman (2021) e idence
sugges s ha he US$/IDR is signi ican ly in luenced by he ime lags o o eign ansac ions,
Non-Deli e able Fo wa d (NDF) a e (US$/IDR), he US$/IDR spo p ice and he Bloombe g
JPMo gan Asia Dolla index (ADXY index). In he long un, domes ic indi idual ansac ions,
non-deli e able o wa d ansac ions and he ADXY index we e ound o be impo an
p edic o s o US$/IDR whils ma ke dominance and asymme ic in o ma ion among
Indonesian FOREX ma ke pa icipan s was e ealed.
In iew o he e idence se ou p e iously, i can be disce ned ha se e al mac oeconomic
and inancial a iables ha e been iden i ied as de e minan s o he exchange a e. Acco ding
o Ja e~
no e al. (2019), s udies using classic app oaches such as coin eg a ion, linea eg ession
o G ange causali y migh indeed enable us o gain in aluable insigh s in o he sho and
long- un ela ionships bu do no cap u e po en ial asymme ies in asse p ice dynamics.
In hei s udy, Baek and Choi (2021) a gue ha he assump ion o a symme ical e ec on
asse p ices may no necessa ily hold in he capi al ma ke , since ma ke playe s in he
o eign cu ency ma ke may espond di e en ly o changes in asse p ices. As an in ui i e
explana ion, asse p ice dynamics can a ec exchange a e mo emen s di e en ly depending
on hei holdings, whe he hey a e asse s o domes ic o o eign in es o s.
I is he e o e impe a i e ha in he empi ical pa ha will ollow we add ess he gap in
he ex an li e a u e by explo ing any possible asymme ies in he in e ac ion be ween capi al
ma ke asse p ice and exchange a e mo emen s bo h in he sho and he long- un. In his
di ec ion, we will employ a nonlinea au o eg essi e dis ibu ed lag (NARDL) model
sugges ed by Shin e al. (2014) which is an asymme ic ex ension o he al eady well-
es ablished linea au o eg essi e dis ibu ed lag (ARDL) bounds es ing p ocedu e
de eloped by Pesa an e al. (2001).
3. Empi ical in es iga ion
3.1 The de elopmen o capi al lows in Indonesia
Be o e we se ou o empi ically explo e he ela ionship be ween he capi al ma ke and he
exchange a e, i would be app op ia e o ake a cu so y glance a he de elopmen o capi al
in lows in Indonesia.
Along wi h he g ow h o economic ac i i y, he de elopmen o he capi al ma ke in
Indonesia has expe ienced signi ican g ow h. This de elopmen is d i en by he in es men
g ade s a us ha Indonesia ecei ed in 2011, which encou ages o eign in es o s o in es in
Indonesia’s economy, pa icula ly in he capi al ma ke . In addi ion, capi al ma ke ’s g ow h
is inex icably linked o he g owing demand o unding, which will be used o inance he
go e nmen ’s de ici as well as o p i a e sec o ac i i ies.
In he bond ma ke , he Indonesian’s go e nmen is he p ima y issue o bonds,
accoun ing o 91% o all issuance as o Decembe 2021. The emaining po ion is held by
co po a e bonds, Islamic bonds and asse -backed secu i ies (O o i as Jasa Keuangan, 2022).
The Indonesian go e nmen has issued an inc easing numbe o so e eign bonds in line wi h
he expansiona y s ance o i s iscal policy. Go e nmen bonds ha e inc eased on a e age by
21% annually o e he pas en yea s. In 2021, go e nmen bonds ou s anding ha e eached
4.679 n IDR o g ew almos i e imes om he posi ion a he end o 2012 which was
eco ded a 820 n IDR.
Figu es 1 and 2sugges ha he yield mo emen o he 10-yea go e nmen bond yield has
luc ua ed in he las decade as a esul o undamen al condi ions and ex e nal sen imen . The
la ge in low o o eign capi al in 2012 d o e yields o hei lowes le el in Feb ua y 2012 o
5.05%, while he highes yield was eco ded in Sep embe 2015 a 9.69%. Mo eo e , a
signi ican change in so e eign bond owne ship du ing he las decade is obse ed wi h o eign
owne ship o all go e nmen bonds dwindling om 42% in 2018 o 19% a he end o 2021.
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3.2 Indonesia’s equi y ma ke de elopmen
In addi ion o he bond ma ke , he Indonesian s ock ma ke has played an inc easingly
impo an ole in he capi al ma ke o e he pas en yea s, as seen by he ise in he s ock
ma ke capi aliza ion alue (see Figu e 3). Ma ke capi aliza ion inc eased o e he p e ious
en yea s, g owing by 100.04% om IDR 4,127 n (equi alen o US$ 427 bn) in 2012 o IDR
8,256 n (equi alen o US$ 579 bn) in 2021.
Despi e he Eu o c isis in 2015 and COVID-19 in 2020 ha ing a big nega i e impac on he
s ock ma ke , he Jaka a Composi e Index (JCI) index has g ea ly inc eased o e he las
10 yea s (see Figu e 4). JCI index was able o con inue o g ow a an a e age o 6.16% pe yea
o each 6,581 un il he end o 2021 o g ow 52% compa ed o he 2012 posi ion which was
Figu e 1.
Indonesia’s so e eign
bonds and o eign
owne ship du ing
2012–2021
Figu e 2.
10-yea go e nmen
bond yields du ing
2012–2021
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eco ded a 4,317. The weigh o he Indonesian s ock ma ke is domina ed by he inancial,
in as uc u e and echnology sec o s, which each 57%, while he weigh o o he sec o s is
less han 10%.
Based on he composi ion o owne ship, he e has been a subs an ial change in equi y
owne ship composi ion in he Indonesian s ock ma ke (KSEI, 2022). Fo eign in es o s held
45.50% o he o al alue sha es a he end o Decembe 2017, while domes ic in es o s held
54.50%. In 2021, hese igu es changed o 41.24% and 58.76%, espec i ely.
The numbe o domes ic in es o s in he Indonesian capi al ma ke has inc eased as a
esul o he apid g ow h o e ail in es o s in Indonesia. In compa ison o he posi ion in he
p e ious yea (3.88 million in es o s), he numbe o domes ic in es o s in he capi al ma ke
inc eased signi ican ly by 92.99% (o an inc ease o 3.61 million in es o s) o 7.49 million
in es o s in 2021, o which 81.48% we e young in es o s.
4,317 4,274
5,227
4,593
5,297
6,356 6,195 6,300
5,979
6,581
12.94%
͵0.98%
22.29%
͵12.13%
15.32% 19.99%
͵2.54% 1.70% ͵5.09%
10.08%
͵40%
͵20%
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
200%
3,000
3,500
4,000
4,500
5,000
5,500
6,000
6,500
7,000
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Jaka a Composi e Index
2012-2021
JCI Index-lhs JCI Index G ow h- hs
Sou ce(s): Figu e has been c ea ed by he au ho s using publicly a ailable
da a o Indonesia’s Composi e Index (JCI) om 2012 o 2021, sou ced
om Bloombe g Financial Da a Se ices
Figu e 3.
Indonesia’s equi y
ma ke capi aliza ion
2012–2021 and
composi e index sec o
weigh s as o June 2022
Figu e 4.
The dynamics and
g ow h o he
Indonesia composi e
index (JCI) om 2012
o 2021
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3.3 Da a and me hodology
3.3.1 Da a. In line wi h he objec i e o his s udy, which is o in es iga e he ela ionship
be ween he capi al ma ke and he exchange a e, we make use o he ollowing da a: (a) he
closing p ice o US$ o IDR, (b) he closing p ice o Indonesia 10-yea go e nmen bond yield –
being he mos ansac ed and used as a benchma k in bond ades (DJPPR, 2021) and (c) he
closing p ice o Indonesia S ock Index Composi e (IDX) which is a composi e index o all
equi ies lis ed on he Indonesia S ock Exchange a e included in his index (p e iously
e e ed o as he Jaka a S ock Exchange). The cu encies used in his s udy a e de e mined
by hei ansac ion ma ke sha e, which is US$/IDR (see Figu e 5). Wi h a p opo ion o
93.65% in Ap il 2019, US$/IDR ansac ions a e he mos aded cu ency pai s in Indonesia’s
o eign exchange ma ke (Bank o In e na ional Se lemen s, 2019).
To p o ide mo e cla i y abou he ela ionship among a iables, he da a se ies used in
his s udy is based on daily da a, which is di ided in o wo pa s as ollows: ull sample, wi h a
pe iod o 10 yea s, s a ing om he ea ly Janua y 2012 o end o Decembe 2021, which ha e
2,610 obse a ions and a subsample, wi h a pe iod o wo yea s, s a ing om he ea ly
Janua y 2020 o end o Decembe 2021, which ha e 523 obse a ions. The subsample is
in ended o examine he dynamics du ing he COVID-19 pandemic pe iod. See Tables A1 and
A2 in Appendix o summa y s a is ics and co ela ion ma ix.
Gi en ha his s udy employs daily da a as means o acqui ing a be e unde s anding o
he a iables ha d i e he mo emen o he US$/IDR cu ency a e and o examine he
impac o independen a iable ansmission mo e conc e ely we ha e le ou po en ially
o he key mac oeconomic a iables such as in la ion, ade imbalance (expo /impo ), GDP
and unemploymen a e due o he lowe equencies a ailable. The main da a sou ces we e
Bloombe g Financial Da a Se ices, he Bank Indonesia (www.bi.go.id), Di ec o a e Gene al
o Budge Financing and Risk Managemen –Indonesia’s Minis y o Finance (h ps://www.
djpp .kemenkeu.go.id) and Indonesia S ock Exchange (www.idx.co.id).
The ac ha Indonesia has he wo ld’s 16 h la ges economy and he la ges economy in
Sou heas Asia is he main eason why we selec ed Indonesia as he ocal economy in his
s udy coun y. Fu he mo e, Indonesia implemen s a ee- loa ing exchange a e and ee
capi al low egime, and in 2030, acco ding o McKinsey (2021), i is expec ed o become he
se en h la ges economy in he wo ld.
3.3.2 Me hodology. Fo he empi ical in es iga ion, he NARDL app oach de eloped by
Shin e al. (2014) will be used [1]. The NARDL app oach o e s se e al ad an ages: in con as
93.65%
4.55%
0.80%
0.73%
0.15%
0.12%
USD
o he
EUR
JPY
GBP
AUD
Sou ce(s): Figu e has been c ea ed by he au ho s using publicly a ailable
da a o Indonesia’s Fo eign Exchange Tu no e by Cu ency as o Ap il
20191, sou ced om BIS T iennial Su ey 2019
Figu e 5.
Indonesia’s o eign
exchange u no e by
cu ency as o
Ap il 2019
The e ec o
capi al ma ke
dynamics
89
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o he no mal VAR echnique, which can lose in o ma ion con ained in connec ions be ween
se ies le els, he NARDL app oach can show a iances in he eg esso s’ esponses o
posi i e and nega i e shocks om he asymme ic dynamic mul iplie s (Ja e~
no e al., 2019
and Allen and McAlee , 2021); we a e able o es simul aneously he long and sho - un
asymme ic o e he nega i e and posi i e pa ial sum decomposi ions o he eg esso s
(Ja e~
no e al., 2019) because he NARDL app oach lacks esidual associa ion, and his model is
unsuscep ible o he omission o lag bias (A ize e al., 2017).
To ensu e ha he equi emen s o conduc non-linea ARDL me hodologies a e ul illed,
he se ies we e es ed o uni oo s o de e mine he le el o in eg a ion (see Ja e~
no e al., 2020:
Baek and Choi, 2021).
The gene ic o m o he eg ession equa ion o examine he asymme ic link be ween
Indonesian bond yield and equi y ma ke p ice wi h he exchange a e is exp essed as ollows:
EXC ¼β0þβ1BON þβ2JCI þ
ε
(1)
whe e EXC
is he US$/IDR cu ency a e, BON
is he 10-yea Indonesian go e nmen bond
yield, JCI
is he Indonesian S ock Exchange ma ke p ice, β
0
is he cons an e m, is he ime
index ( ading day), β
1
and β
2
a e he slope coe icien s and
ε
is he e o e m. I should also
be s essed ha we ha e aken he na u al loga i hm all a iables used in his s udy and
hence e lec ing ela i e changes.
The explici model ha conside s long- un asymme ies is exp essed in he
ollowing e ms:
Y ¼βþXþþβ−X−þ
ε
(2)
whe e Y
indica es dependen a iable, βþand β
–
a e he long- un pa ame e s o be
e alua ed, whe eas
ε
is he e o e m and X
þ
and X
a e he pa ial sums o he ec o s o
posi i e and nega i e changes o independen a iables.
Equa ion (2) can be e o mula ed o an asymme ic long- un eg ession equa ion (3) as
ollows:
EXC ¼β0þβ1BONPOS þβ2BON: þβ3JCIPOS þβ4JCI: þ
ε
(3)
whe e EXC
deno es he US$/IDR exchange a e, β
0
,β
1
,β
2,
β
3
and β
4
a e coe icien o long-
un pa ame e s o be es ima ed and
ε
ep esen s he e o e m. Mo eo e , BON_POS
and
BON_NEG
a e he pa ial sum o posi i e and nega i e changes in he bond yield, whe eas
JCI_POS
and JCI_NEG
a e he pa ial sum o posi i e and nega i e changes in he s ock
p ice, and he alues a e o mula ed as ollows:
BONPOS ¼X
j¼1
ΔlnBON
þ¼X
j¼1
max
j(4)
BON: ¼X
j¼1
ΔlnBON
−¼X
j¼1
min
j(5)
JCIPOS ¼X
j¼1
ΔlnJCI
þ¼X
j¼1
max
j(6)
AJEB
8,1
90
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sum decomposi ions o he independen a iable(s). Po en ially, due o p esences o asymme ic
impac , he usual ARDL may no able o cap u e his whils he bounds es may show absence o co-
in eg a ion. As such we ha e op ed o he NARDL app oach o cap u e possible asymme ies in he
in e ac ion be ween capi al ma ke asse p ice and exchange a e mo emen s bo h in he sho and
he long un.
2. The da a se is a ailable upon eques o hose who wish o eplica e he esul s o his s udy.
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AJEB
8,1
98
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Appendix
Co esponding au ho
Cons an inos Alexiou can be con ac ed a : [email p o ec ed]
Fo ins uc ions on how o o de ep in s o his a icle, please isi ou websi e:
www.eme aldg ouppublishing.com/licensing/ ep in s.h m
O con ac us o u he de ails: [email p o ec ed]
EXC BON JCI LN_EXC LN_BON LN_JCI
Full Sample: 1/02/2012 o 12/31/2021
Numbe o obse a ions 2,610 2,610 2,610 2,610 2,610 2,610
Mean 12,900 7.22 5,312 9.45 1.97 8.57
Median 13,384 7.21 5,247 9.50 1.97 8.57
Maximum 16,575 9.83 6,723 9.72 2.29 8.81
Minimum 8,935 5.05 3,655 9.10 1.62 8.20
S d. De 1,735 0.98 769 0.15 0.14 0.15
Sub Sample: 1/01/2020 o 12/31/2021
Numbe o obse a ions 523 523 523 523 523 523
Mean 14,419 6.66 5,731 9.58 1.89 8.65
Median 14,343 6.55 5,986 9.57 1.88 8.70
Maximum 16,575 8.38 6,723 9.72 2.13 8.81
Minimum 13,583 5.89 3,938 9.52 1.77 8.28
S d. De 488 0.54 653 0.03 0.08 0.12
Sou ce(s): Au ho s’calcula ions
Full-sample: 1/02/2012 12/31/2021 Sub-sample: 1/01/2020 12/31/2021
LN_BON LN_EXC LN_JCI LN_BON LN_EXC LN_JCI
LN_BON 1 LN_BON 1
LN_EXC 0.443*** 1 LN_EXC 0.683*** 1
LN_JCI 0.033** 0.690*** 1 LN_JCI 0.846*** 0.682*** 1
No e(s): *** 51% le el o signi icance, ** 55% le el o signi icance, * 510% le el o signi icance
Sou ce(s): Au ho s’calcula ions
Table A1.
Desc ip i e s a is ics
Table A2.
Co ela ion ma ix
The e ec o
capi al ma ke
dynamics
99
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