Exchange Rate Shocks and Sectoral Stock Returns in Nigeria: Do Asymmetry and Structural Breaks Matter?

Fasanya, Ismail Olaleke; Akinwale, Oluwa unmilayo A. A icle Exchange Ra e Shocks and Sec o al S ock Re u ns in Nige ia: Do Asymme y and S uc u al B eaks Ma e ? Cogen Economics & Finance P o ided in Coope a ion wi h: Taylo & F ancis G oup Sugges ed Ci a ion: Fasanya, Ismail Olaleke; Akinwale, Oluwa unmilayo A. (2022) : Exchange Ra e Shocks and Sec o al S ock Re u ns in Nige ia: Do Asymme y and S uc u al B eaks Ma e ?, Cogen Economics & Finance, ISSN 2332-2039, Taylo & F ancis, Abingdon, Vol. 10, Iss. 1, pp. 1-26, h ps://doi.o g/10.1080/23322039.2022.2045719 This Ve sion is a ailable a : h ps://hdl.handle.ne /10419/303601 S anda d-Nu zungsbedingungen: Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen Zwecken und zum P i a geb auch gespeiche und kopie we den. Sie dü en die Dokumen e nich ü ö en liche ode komme zielle Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich machen, e eiben ode ande wei ig nu zen. 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Akinwale To ci e his a icle: Ismail O. Fasanya & Oluwa unmilayo A. Akinwale (2022) Exchange Ra e Shocks and Sec o al S ock Re u ns in Nige ia: Do Asymme y and S uc u al B eaks Ma e ?, Cogen Economics & Finance, 10:1, 2045719, DOI: 10.1080/23322039.2022.2045719 To link o his a icle: h ps://doi.o g/10.1080/23322039.2022.2045719 © 2022 The Au ho (s). This open access a icle is dis ibu ed unde a C ea i e Commons A ibu ion (CC-BY) 4.0 license. Published online: 04 Ma 2022. Submi you a icle o his jou nal A icle iews: 2089 View ela ed a icles View C ossma k da a Ci ing a icles: 8 View ci ing a icles Full Te ms & Condi ions o access and use can be ound a h ps://www. and online.com/ac ion/jou nalIn o ma ion?jou nalCode=oae 20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Exchange Ra e Shocks and Sec o al S ock Re u ns in Nige ia: Do Asymme y and S uc u al B eaks Ma e ? Ismail O. Fasanya 1 * and Oluwa unmilayo A. Akinwale 2 Abs ac : This s udy examines he e ec o exchange a e shocks on en (10) sec o al s ock e u ns in Nige ia om Janua y 2007 o Decembe 2018. The au o- eg essi e dis ibu ed lag and nonlinea au o eg essi e dis ibu ed lag a e employed o examine symme ic and asymme ic ela ionship be ween exchange a e and sec o al s ock e u ns. The esul shows ha only inancial se ice sec o mo es in an asymme ic ashion in he sho and long pe iod wi hou aking accoun o s uc u al b eaks and wi h s uc u al b eaks, none o he sec o al s ock e u ns we e asymme ic. The esul shows ha exchange a e mo emen a ec s he sec o s di e en ly. The e o e, his s udy concludes ha a single model canno i all he sec o al s ock e u ns because all sec o s espond di e en ly o exchange a e mo emen s and he in o ma ion abou a pa icula sec o canno be used o o e- cas o he sec o s. These esul s o e impo an insigh s o in es o s, egula o s and policymake s. Subjec s: Economics; Economics; Finance Keywo ds: Exchange a e; s ock e u ns; Asymme y; s uc u al b eaks ABOUT THE AUTHORS Ismail O. Fasanya is a Senio Lec u e o Economics a he School o Economics and Finance, Uni e si y o he Wi wa e s and, Johannesbu g, Sou h A ica. His esea ch in e - es s lie a he in e sec ion o mac oeconomics and inance, wi h special in e es in ene gy eco- nomics, inancial spillo e s and in e connec ed- ness, public sec o economics, and mac o inance. Oluwa unmilayo A. Akinwale is a young esea che in he Depa men o Economics, Augus ine Uni e si y, Epe, Lagos. He esea ch has ocused on ime se ies modelling, exchange a e managemen , inancial ma ke de elop- men , and public inance. PUBLIC INTEREST STATEMENT This esea ch o e s insigh o in es o s, policy analys s and ele an s akeholde s in he inancial and commodi ies ma ke s. Wi h he ecen de elopmen s in asse p ice mo emen s, we a e p esen ed wi h a new oppo uni y o in es iga e co-mo emen s be ween exchange a e and sec- o al s ocks in he Nige ia conside ing hei inhe - en cha ac e is ics. To his end, i is impo an o ind app oaches o examine he isks exchange a e may pose, bu mo e consequen ially, o cha ac e ize he asymme y beha iou o exchange a e on sec o al s ocks which will in o m po en ial in es o s on di e si ica ion s a- egies in building hei po olios. In his s udy, we conside ed echniques ha can help in es o s achie e his by add essing he beha iou o hese asse s and o he ele an mac oeconomic un- damen als ha align wi h he na u e o in es o p e e ences. We ind ha exchange a e mo e- men a ec s he sec o s di e en ly, hence, a single model canno i all he sec o al s ock e u ns, and in o ma ion abou a pa icula sec o canno be used o o ecas o he sec o s. Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 1 o 26 Recei ed: 28 Oc obe 2021 Accep ed: 12 Feb ua y 2022 *Co esponding au ho : Ismail O. Fasanya, School o Economics and Finance, Uni e si y o he Wi wa e s and, Johannesbu g, Sou h A ica E-mail: [email p o ec ed] Re iewing edi o : Yudh i See ha am, School o Economics and Finance, Uni e si y o he Wi wa e s and, Sou h A ica Addi ional in o ma ion is a ailable a he end o he a icle © 2022 The Au ho (s). This open access a icle is dis ibu ed unde a C ea i e Commons A ibu ion (CC-BY) 4.0 license. 1. In oduc ion Fluc ua ions gene a e o e all sense o unce ain y abou u u e consump ion and i ms’ e enue o ma ke pa icipan s, which a e because o asse demand in he o eign exchange ma ke ha has he end o des abilizing he ac i i ies o he eal economy (Obs eld & Rogo , 1998). A shock is an un o eseen and unp edic able e en ha a ec s an economy posi i ely o nega i ely. I is an unexpec ed change ha occu s in ex e nal ac o s ha a e no explained by economics, which may in luence in e nal economic a iables like economic g ow h, unemploymen and in la ion. Exchange a e shock is a e m ha depic s he luc ua ion o a alue o a cu ency ela i e o ano he in an ex emely sho pe iod. Since mos economies opened up o ex e nal s akeholde s a e he 1980s, inancial c isis has become a global occu ence. Meanwhile, wo inancial c ises ha e occu ed in he wo ld economy in he las decade: he 2008 global inancial c isis and he Eu ozone so e eign deb c isis. I is no iced ha exchange a e and s ock p ices ac as indica o s o he inancial sec o as hey a e e y delica e o shi ing ma ke condi ions (Akdogu & Bi kan, 2016). Fu he mo e, exchange a e has been excessi ely ola ile in A ican coun ies such as Nige ia, Sou h A ica, Kenya and so on, since i s adop ion o he loa ing exchange a e egime (a egime whe e alue o cu ency is allowed o luc ua e in esponse o o eign exchange ma ke dynamics— demand and supply) wi h nega i e e ec s on in es men , ade and g ow h (Emenike, 2017). An A ican coun y like Nige ia adop ed he loa ing exchange a e egime in 1986 by he exchange a e libe a ion policy unde he S uc u al Adjus men P og amme F amewo k. Policies we e made o ensu e Exchange a e s abiliza ion such as i s and Second ie o eign exchange a e ma ke , single o eign exchange ma ke s in July 1987, au onomous o eign exchange ma ke in 1988, in e - bank o eign exchange ma ke in Janua y 1989, he Bu eau de change in 1989, Re ail Du ch Auc ion sys em in Decembe ,1990, au onomous Fo eign Exchange Ma ke ein oduced in 1995, The e was also he ein oduc ion o e ail Du ch Auc ion Sys em in 2002 by Cen al Bank o Nige ia (CBN) which was eplaced by Wholesale Du ch Auc ion Sys em in Feb ua y, 2006 (Cen al Bank o Nige ia, 2016). A e he global inancial c isis in 2008 ha caused a d as ic all in he exchange a e, Cen al Bank o Nige ia ein oduced he e ail Du ch Auc ion Sys em wi h he aim o easing demand p essu e. Wholesale Du ch Auc ion Sys em was la e ein oduced in July 2009 due o he pe sis- en demand p essu e and he con inuous all o exchange a e in all ma ke segmen s. Finally, Re ail Du ch Auc ion Sys em was b ough back in Oc obe 2013 ha was la e aken back in 17 Feb ua y 2015 due o e o ms in ma ke . E en wi h he policies o sus ain exchange a e, Nai a con inues o be uns able agains US Dolla (Cen al Bank o Nige ia, 2016). Howe e , he e a e 12 Sec o s lis ed on he Nige ia S ock Exchange, hey include: Ag icul u e, Cons uc ion/Real Es a e, Consume Goods, Financial Se ices, Heal hca e, Indus ial Goods, In o ma ion and Communica ions Technology, Na u al Resou ces, Oil and Gas, Se ices, U ili ies and Conglome a es. The Nige ian S ock ma ke g ew and gained inancial s eng h as he e was boom and in es o s, egula o s, ma ke analys s and o he economic agen s we e ce ain and pleased wi h he ma ke be ween 1999 o 2008 (Cen al Bank o Nige ia, 2016). I is essen ial, he e o e, o in es o s o be con e san wi h how changes in he a iance o exchange a es ela es o changes in he a iance o s ock p ices and ice e sa when selec ing an op imal in es men po olio and managing isk e ec i ely. Asse s om ma ke s whe e ola ili y in one inancial ma ke spillo e o ano he canno be in ol ed in he same po olio when di e si y- ing isk (Mun, 2007). I is he e o e o impo ance o s udy he nexus be ween exchange a e and sec o al s ock e u ns in Nige ia. Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 2 o 26 This po en ial linkage be ween exchange a e and s ock e u ns has s imula ed esea che s o sea ch o mo e unde s anding o he dynamic ela ionships be ween o eign exchange and s ock ma ke s, hence, he li e a u e is p oli e a ed wi h s udies on exchange a e-s ock e u ns nexus om di e en coun ies. The e a e wo s ands o heo e ical a gumen s ega ding he di ec ion o he linkage be ween hese wo ma ke s by Do nbusch and Fishe (1980) and B anson and Hende son (1985). In he case o Nige ia, i is pa he ically obse ed ha Nai a exchange a e has no been s able. Al hough immedia e pe iods ollowing he adop ion o he S uc u al Adjus men P og amme a e he b eakdown o he B e on Wood sys em o exchange a e, he e was ela i e s abili y in he dynamics o exchange a e om 1970 o 1985 wi h he highes exchange a e alue o 0.8938 nai a o 1 US dolla (Obinwa a e al., 2016). In he ecen decades howe e , Nai a has been ola ile ela i e o US Dolla and he s ock ma ke was no s able as well. In Janua y 1999, Nai a was ₦ 86.00 and All Sha e Index (ASI) on he Nige ian S ock Exchange was 5,494.8. In Decembe 2000, Nai a dep ecia ed u he o ₦106.71 while ASI app ecia ed o 8,111.0. Fu he dep ecia ion (app ecia ion) led Nai a (ASI) o be ₦132.79 (42,092.7) in Decembe 2004. In Decembe 2007 howe e , bo h Nai a and ASI app ecia ed o ₦118.20 and 57,990.2 espec i ely. Following he pe iod o global inancial c isis (GFC) in 2008 and 2009, Nai a and ASI co espondingly dep ecia ed o ₦149.69 and 20,827.2 in Decembe , 2009. A e he c isis howe e , he dep ecia ion a e in Nai a pe sis ed making a e age exchange a e o Nai a o ho e a ound ₦305.22 in Decembe , 2016, while ASI pe sis en ly inc eased and oscilla ed a ound 6874.6 in he same pe iod (Cen al Bank o Nige ia, 2016). F om he beha io o Nai a and ASI, i is obse ed ha in he p e-GFC as Nai a dep ecia es, ASI app ecia es which con i ms he goods ma ke heo y by Do nbusch and Fishe (1980). Howe e , in he GFC and pos -GFC, de alua ion in Nai a was symme ical o dep ecia ion in ASI, which indica es he claim o po olio balance app oach by B anson and Hende son (1985). This phenomenon is also obse ed om 2010 o 2016: exchange a e dep ecia ed and ASI declined oo. In his ega d, inancial ma ke s canno be disen angled om he mo emen s in exchange a e. The e a e ple ho a o e idence in he li e a u e ha show c edence o likely spillo e s be ween exchange a es and he equi y ma ke s (see in e alia, Salisu & Ndako, 2018; Bahmani-Oskooee & Saha, 2018; Raheem e al., 2021). Apa om he issue su ounding he lack o consensus, ano he in e es ing puzzle a ose among he s udies ha conclude signi ican e ec , and ha is whe he he esponse o s ock p ices o exchange a e shocks is symme ic o asymme ic. The need o de e mine his spu s om how la ge o small he isks o gains o asymme ic endencies in he esponse o s ock p ices o cu ency shocks may be o in es o s. Mo i a ed by he abo e discussion, we examine he e ec o exchange a e shocks on sec o al s ocks in Nige ia, and whe he hese e ec s, i any, a e asymme ic. Mo e explici ly, we empi i- cally add ess he ollowing issues: How does exchange a es a ec sec o al s ock e u ns? Is his e ec , i any, asymme ic? And wha ole do s uc u al b eaks/e en s play on he link be ween exchange a e and sec o al s ocks? Agains his backg ound, his pape con ibu es o he sca ce li e a u e on he e ec s o exchange a e shocks on sec o al s ocks in he ollowing ways. Examining his nexus o Nige ia is pa icula ly o u mos impo ance o ce ain easons. The Nige ian S ock Exchange (NSE) has eco ded a phenomenal g ow h la ely, as high economic pe o mance is d i en by he ise in ini ial public o e ing (Fowowe, 2015). Wi h his he ou s anding economic ac i i ies, she has main ained a gian s and in he A ican con inen . The e o e, we ex end he exis ing knowledge by making make ce ain addi ions. Fi s ly, majo i y o he s udies ca ied ou o Nige ia conside ed he agg ega e s ock ma ke h ough he use o he All Sha e Index as p oxy o s ock p ices (see o example, Bala & Hassan, 2018; Fowowe, 2015). To he bes we know, he comp ehensi eness o his s udy anks i highes among he ew no able s udies in Nige ia ha conside sec o al analyses, as i is he i s o cap u e as high as en indi idual sec o al s ock p ices in a single s udy. This does no only enable clea -cu policy by in es o s ha ing unde s ood he he e o- geneous na u e o each sec o , bu also leads o op imiza ion o c oss-sec o in es men decisions and possible gains. Secondly, we ake a depa u e om he common me hodology engaged by mos s udies. Ra he han he GARCH- ype and SVAR models o en adop ed (Bala & Hassan, 2018; Emenike, 2017; Fowowe, 2015; Maku & A anda, 2010; Obinwa a e al., 2016), we conside he non-linea Au o eg essi e Dis ibu ed Lag Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 3 o 26 (NARDL) p oposed by Shin e al. (2014) which p o es i s supe io i y by accoun ing o bo h sho - and long- un asymme ies in each sec o al analysis. In achie ing his, we allow o s uc u al b eaks using he Bai—Pe on uni oo es , which endogenously de e mines up o i e possible b eaks. Dis ega ding hese b eaks when hey exis may bias eg ession esul s (see, in e alia, Salisu & Mobolaji, 2013; Fasanya e al., 2018a,Fasanya e al., 2018b; 2021a,Fasanya e al., 2021b). We la e decompose he da a o accoun o possible cu ency asymme ic esponses o he s ock ma ke . The NARDL app oach has some in insic wo h as i allows modelling he coin eg a ion ela ion ha could exis be ween he endogenous and exogenous a iables and mo e especially es ing bo h he linea and nonlinea coin eg a ion. These a o emen ioned me i s o he NARDL app oach may also be alid o nonlinea h eshold Vec o E o Co ec ion Models (VECM) o smoo h ansi ion models; howe e , hese models may su e om he con e gence p oblem due o he p oli e a ion o he numbe o pa ame e s ha is unlike he NARDL model. In all, unlike o he e o co ec ion models whe e he o de o in eg a ion o he conside ed ime se ies should be he same, he NARDL model elaxes his es ic ion and pe mi s combining da a se ies ha ing di e en in eg a ion o de s (see in e alia, Shin e al., 2014). Meanwhile, he sho - and long- un symme ic models will also be es ima ed in o de o es i asymme y ma e s. This also appea s o be he i s no able s udy o conside his app oach o exchange a e shocks-sec o al s ock nexus in Nige ia. The emainde o he pape is as ollows— he nex sec ion e iews exis ing li e a u e. Sec ion 3 desc ibes he da a and me hodology. Sec ion 4 de ails empi ical esul s, and sec ion 5 concludes he pape wi h policy implica ions. 2. Re iew o ele an li e a u e The e is li le o no s udy on exchange a e shock and sec o al s ock e u ns in Nige ia. Howe e , he e a e se e al s udies ha ha e been ca ied ou wi h esul s o unidi ec ional causali y, bi di ec ional causali y and no causali y be ween exchange a e and he ac i i ies o he s ock ma ke . S udies like Kpughu e al. (2017), Okpa a and Odionye (2012), Chowdhu y e al. (2014), Alley (2018), Sui and Sun (2016), Bala and Hassan (2018), Blau (2018), Jayasinghe and Tsui (2008), and Ka agedikli e al. (2015), and Fape u e al. (2017) obse e a uni di ec ional causali y be ween exchange a e and s ock p ices. While s udies like Yinusa (2008), Sikhosana and Aye (2018), A. A. Salisu and Mobolaji (2013), Lim and Sek (2014), Wong (2017), A shan e al. (2017), Sha ma (2017), Umo u and Asekome (2013), and Tu soy (2017) deduce ha he e is he p esence o bi di ec ional ela ionship be ween exchange a e and s ock p ices. Mo eo e , Ho and Huang (2015), Zubai (2013), Rahman and Uddin (2009), and Zia and Rahman (2011) obse e ha he e is no ela ionship be ween exchange a e and s ock p ice. Sikhosana and Aye (2018) used mon hly da a om 1996 o 2016 and employed EGARCH, GJR- GARCH and APARCH as he es ima ion echniques and deduced ha he e is a bi di ec ional ela ion- ship be ween exchange a e and s ock p ices. Kpughu e al. (2017) employed Mul i a ia e Vec o Au o eg essi e Mo ing A e age—Asymme ic Gene alized Au o eg essi e Condi ional He e oscedas ici y model (VARMA-AGARCH) as he es ima ion echnique and deduced ha he e is a uni di ec ional ela ionship ollowing om s ock ma ke o he o eign exchange ma ke . Howe e , Sui and Sun (2016) employed Vec o Au o eg essi e (VAR) and Vec o E o Co ec ion model (VECM) as es ima ion echniques and ound ha he e is a unidi ec ional ela ionship be ween exchange a e and s ock p ices occu ing om exchange a e shocks o s ock e u ns. Ka agedikli e al. (2015) applied ac o - augmen ed ec o au o eg ession (FAVAR) o es ima ion echniques and deduced ha an unexpec ed exchange a e shock has signi ican e ec on almos ansac ional sec o s o he New Zealand economy. The esul s om pas s udies a e insigh ul, howe e , majo i y o he s udies done in Nige ia ha e no empi ically examined he e ec o (i) exchange a e shock and sec o al s ock e u ns wi h s uc u al b eaks, (ii) ole o asymme y on exchange a e- sec o al s ock e u ns ela ionship, which is a majo o ce o his s udy. The e o e, his s udy is an unasse i e a emp in his ega d o ill he gap. Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 4 o 26 3. Da a and me hodology 3.1. Da a desc ip ion This s udy employs exchange a e (EXR), Index o Indus ial p oduc ion (IPI), Consume p ice index (CPI), Measu e o nominal money supply (M2) and e u ns o 10 sec o al s ock p ices. These sec o s consis o Ag icul u e (AGR); Consume goods (CGD); Conglome a e (CGL); Cons uc ion (CON); Financial Se ices (FIN); Heal h (HLH); Indus ial goods (IND); Na u al esou ces (NTR); Oil and Gas (OGS); Se ice (SVS). All a iables a e measu ed in loga i hms. The pe iod o s udy is om Janua y 2007 o Decembe 2018. Da a on he mon hly sec o al s ock p ices is sou ced om (h p:// www.cashc a .com/plis o de .php while da a on Index o Indus ial p oduc ion (IPI), Consume p ice index (CPI), Measu e o nominal money supply (M2), and Exchange a e (EXR) is ob ained om Cen al Bank o Nige ia s a is ical bulle in. 3.2. Me hodology This s udy es s on he po olio balance heo y ha desc ibes a nega i e co ela ion be ween s ock p ices and exchange a es exp essed in a di ec quo a ion o m whe e a ia ions in he o me in luence he la e ’s mo emen s ia po olio ebalancing (see, Cenedese e al., 2015 o de ails o he heo y). To analyze he sho un and long un asymme ical e ec s o exchange a e shocks on sec o al s ock e u ns in Nige ia and o obse e he link among he a iables in he model, he nonlinea au o eg essi e dis ibu ed lag o Shin e al. (2014) is employed in his s udy. Indeed, he NARDL model is employed o disen angle he hidden coin eg a ion. In addi ion, he NARDL model has he ad an age o es ing coin eg a ion be ween da a se ies wi h di e en o de s o in eg a ion, in ha i allows combining I(0) and I(1) da a. Fu he mo e, i p o ides a nice amewo k o es o he long- and sho - un ansmission o exchange a e o s ock e u ns. Howe e , since he NARDL model imposes an exogenous ze o h eshold, he Quan ile nonlinea au o eg essi e dis ibu ed lag (QNARDL) may come handy o cha ac e ize he dis ibu ional asymme y, bo h in he long and sho un acco ding he posi ion o he dependen a iable wi hin i s own dis ibu ion. Howe e , in his p esen s udy, we depa comple ely om he dis ibu ional asymme y o he a iables since asymme ies obse ed in he ela ionships be ween da a se ies a e no caused by he complex sys ems and sudden e en s ha may likely a ise, ha e been cap u ed by he s uc u al dummies in he models. The e o e, an econome ic model is pu o wa d as: Lnsi ¼αþβLnEXR þφLnIPI þθLnCPI þϕLnM2 þε (1) Whe e: si = he sec o al s ock e u ns (whe e i ep esen each o he sec o s); EXR = he e ec i e exchange a e; IPI = an index o indus ial p oduc ion used as a measu e o domes ic economic ac i i y; CPI = Consume P ice Index as a measu e o p ice le el; M2 = nominal money supply; ε = Whi e noise e o e m Mo eo e , he e eme ge o be signs o some signi ican shi s in he ime se ies; hence, his s udy adjus s he Shin e al. (2014) model o ake in o accoun s uc u al b eaks. To show i posi i e shock and nega i e shock a ec he sec o al s ock e u ns di e en ly o simila ly, ou models a e b ough o wa d. The s udy conside s bo h linea and nonlinea au o eg essi e dis ibu ed lag wi h o wi hou s uc u al b eaks. 3.2.1. MODEL I: Linea au o eg essi e dis ibu ed lag wi hou s uc u al b eaks This can be speci ied as: Δsi ¼#0þ∑m τ¼1ατΔLns i τþ∑p τ¼0βτΔLnEXR τþ∑q τ¼0φτΔLnIPI τþ∑s τ¼0θτΔLnCPIiτþ∑u τ¼0ϕτΔLnM2iτ þ#1Lns i 1þ#2LnEXR 1þ#3LnIPI 1þ#4LnCPIi1þ#5LnM2I1þε (2) Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 5 o 26 Whe e si deno es he o sec o al s ock e u ns; EXR deno es he eal exchange a e; IPI deno es an index o indus ial p oduc ion used as a measu e o domes ic economic ac i i y; CPI deno es Consume P ice Index as a measu e o p ice le el and M2 is a measu e o nominal money supply, ε is whi e noise e o e m; #0 #1;#2 #1;#3 #1;#4 #1;and #5 #1 a e he long un coe icien s o he in e cep and he slope, espec i ely; and αi;βi;φi;θi;and ϕi a e he sho un coe icien s. m, p, q, s, and u a e he op imal lags on he i s di e enced a iables. The linea me hod be ween exchange a e and sec o al s ock e u ns o he long un is cen e ed on he Wald es (F s a is ics), by ha ing limi a ions on he long un es ima ed coe icien s o one pe iod lagged le el o exchange a e, sec o al s ock e u ns, index o indus ial p oduc ion, consume p ice index and nominal money supply o be an amoun o ze o. The e o co ec ion e m λ is pu ac oss in model (2) in o de o he a e o al e a ion o be a ained. Δsi ¼#0þ∑m τ¼1ατΔLns i τþ∑p τ¼0βτΔLnEXR τþ∑q τ¼0φτΔLnIPI τþ∑s τ¼0θτΔLnCPIiτþ∑u τ¼0ϕτΔLnM2iτ þλecm 1þυ (3) 3.2.2. MODEL II: Linea ARDL wi h s uc u al b eaks We b oaden he model in equa ions (1) and equa ions (2) o ake accoun o endogenous s uc u al b eaks. The model is s a ed below: Δsi ¼#0þ∑m τ¼1ατΔLns i τþ∑p τ¼0βτΔLnEXR τþ∑q τ¼0φτΔLnIPI τþ∑s τ¼0θτΔLnCPIiτþ∑u τ¼0ϕτΔLnM2iτ þ#1Lns i 1þ#2LnEXR 1þ#3LnIPI 1þ#4LnCPIi1þ#5LnM2I1þ∑s ¼1X D þε (4) The addi ion o ∑s ¼1X D po ays he s uc u al b eaks, whe e D ep esen s a dummy a iable o each o he s uc u al b eaks deno ed as D = 1 o iTD, i no D = 0. ep esen s he ime; s uc u al b eaks da e a e TD whe e = 1,2,3,4, . . .,κand X is he cons an o b eak dummy. Fu he mo e, he esul s go en a e pu side by side wi h hose om equa ion (1) o a ain i aking accoun o s uc u al b eaks in he eg ession is i al. The Wald es is used o es o mu ual impo ance o s uc u al b eaks in equa ion (3) o be exac , we es ∑s ¼1X ¼0 coun e o ∑s ¼1X �0 . No accep ing null hypo hesis shows ha s uc u al b eaks a e essen ial and should be added in he model he e o e p oposing he accep ance o equa ion (4). 3.2.3. MODEL III: NARDL wi hou s uc u al b eaks The co in eg a ing NARDL is o g ea in e es because we seek o s udy he ole o asymme ies in he model. This model employs he b eakdown o he independen a iable EXR in o i s posi i e exchange a e changes and nega i e exchange a e changes. This is due o he ac ha economic agen s eac di e en ly o posi i e and nega i e changes in exchange a e. The b oken-down exchange a e pa ial sums o inc eases and dec eases o example, EXR þ¼∑ j¼1ΔEXRjþ¼∑ j¼1maxðΔEXRj;0Þ(5a) EXR ¼∑ j¼1ΔEXRj¼∑ j¼1minðΔEXRj;0Þ(5b) Shin e al. (2014) pu on iew ha linea au o eg essi e dis ibu ed lag model (1) can be adjus ed o accoun o asymme ies o gene a e he ollowing nonlinea au o eg essi e dis ibu ed lag model: Δs i ¼#0þ∑m τ¼1ατΔs i τþ∑p τ¼0ðβτþΔLnEXRþ τþβτΔLnEXR  τÞ þ ∑q τ¼0φΔLnIPI τþ∑s τ¼0θΔLnCPI τ þ∑u τ¼0ϕΔLnM2 τþ#1Δs i 1þ#2þLnEXRþ 1þ#2LnEXR 1þ#3LnIPI 1þ#4LnCPI 1þ#5LnM2 1þε (5) Equa ion can be modi ied o add in he e o co ec ion e m as: Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 6 o 26 Δs i ¼#0þ∑m τ¼1ατΔs i τþ∑p τ¼0ðβτþΔLnEXRþ τþβτΔLnEXR  τÞ þ ∑q τ¼0φΔLnIPI τþ∑s τ¼0θΔLnCPI τ þ∑u τ¼0ϕΔLnM2 τþψecm 1þμ (6) Whe e ecm 1¼s i 1ωþLnEXR þ 1ωLnEXR  1 is he non-linea e o co ec ion e m; he pa ame e δ is he speed o adjus men , hough he basic long- un pa ame e s a e explained as ωþ¼  #2þ #1and ω¼#2 #1 and ela ed sho - un adjus men s o posi i e and nega i e shocks in exchange a e a e desc ibed by βτþand βτ espec i ely. The non-linea au o eg essi e dis ibu ed lag also includes bounds es ha is F dis ibu ion. Howe e , in his case, null hypo hesis o no coin eg a ion pu ac oss as H0:#1¼#2þ¼#2¼0 is es ed agains he al e na i e hypo hesis o coin eg a ion ep esen ed as H1:#1¼#2þ¼#2¼0. Mo eo e , we es o he long- un and sho - un symme y employing Wald es . The ele an null hypo hesis o no asymme ies is de ined as H0:#2þ¼#2¼0 es ed agains he al e na i e (p esence o asymme ies) H1:#2þ�#2�0 o long- un symme- y. The sho - un addi i e symme y can also be es ed wi h he null hypo hesis (no asymme ies) H0:∑q τ¼0βτþ¼∑q τβτ¼0 which is es ed agains he al e na i e p esence o asymme- ies H1:∑q τ¼0βτþ�∑q τβτ�0. 3.2.4. MODEL IV: NARDL wi h s uc u al b eaks In oducing s uc u al b eaks in o he NARDL s uc u e, we ex end equa ion o add in he ele an b eak dummies: Δs i ¼#0þ∑m τ¼1ατΔs i τþ∑p τ¼0ðβτþΔLnEXRþ τþβτΔLnEXR  τÞ þ ∑q τ¼0φΔLnIPI τþ∑s τ¼0θΔLnCPI τ þ∑u τ¼0ϕΔLnM2 τþ#1Δs i 1þ#2þLnEXRþ 1þ#2LnEXR 1þ#3LnIPI 1þ#4LnCPI 1þ#5LnM2 1 þ∑n γ¼1δγD þε (7) The meaning o he pa ame e s s ill adap s he o de o p e ious models. S uc u al b eak es is ca ied ou o de e mine he impo ance o aking accoun o b eaks in he nonlinea au o eg es- si e dis ibu ed lag model. To a i m he exis ence o long un ela ionship, F-dis ibu ed Bound es is inco po a ed and o con i m he ole o asymme y in he exis ence o s uc u al b eaks. 4. Empi ical analysis 4.1. P elimina y esul s A s a is ical analysis o he e u ns and o he a iables is done in an a emp o e eal he s a is ical p ope ies o he e u ns and o he a iables. The Table 1 shows some s a is ical p ope - ies o he employed a iables o his s udy o e he pe iod o 2007M01 o 2018M012. The a iables include he e u ns o he selec ed sec o s in Nige ia, E ec i e Exchange Ra e, Consume P ice Index, Indus ial P oduc ion Index and Nominal Money Supply. The desc ip i e s a is ics include mean, minimum and maximum alues o he obse a ions along wi h he measu e o dispe sion and dis ibu ion o he se ies. The desc ip ion s a is ics om he able makes known ha all he sec o s employed obse e nega i e s ock e u ns in hei a e age excep na u al esou ces and oil and gas. This is a sign ha na u al esou ces, oil and gas, seem o b ing o h compa ed o o he s. Losses in he emaining sec o s loa be ween 0.13% and 6.88%. Fu he mo e, he a e age pe cen age o e ec i e exchange a e, consume p ice index, indus ial p oduc ion index and nominal money supply is app oxima ely 4.67%, 4.93%, 4.81% and 15.63%. On he o he hand, he e exis a high di e ence be ween he minimum and maximum alues o all sec o al s ock e u ns, EEXR, CPI, IPI, and MS. The insinua ion is ha he sec o al s ock ma ke s a e expose o high le el o al e a ions wi hou ce ain y o s abili y o e ime. The s anda d de ia ion alues show he deg ee a which he obse a ions a e dispe sed a ound he co esponding means. Taking in o accoun he skewness s a is ics whose h eshold alue o symme y (o no mal dis ibu ion) is ze o, i can be in e ed ha while MS, R_AGR, R_CON, R_FIN, R_HLH, and R_IND a e nega i ely skewed because hei skewness is less han ze o bu EEXR, CPI, IPI, R_CGL, R_ CGD, Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 7 o 26 sec o s a e signi ican a 1% and indus ial sec o a 5%. Howe e , he mos signi ican e lec s ha a pe cen age change in indus ial p oduc ion index will lead o a 95.69% dec ease in cons uc ion sec o . In ui i ely, his con adic s he heo e ical expec a ion o a posi i e e ec and is a e se o he indings in he li e a u e (see o ins ance, Bahmani-Oskooee & Saha, 2018). Money supply has a posi i e ela ionship wi h all he sec o al e u ns. The pas in luence e u ns end o be nega i e in he case o cons uc ion, indus ial and oil and gas sec o s. In e es ingly, i is signi ican a 1% in he se ice sec o e lec ing ha a pe cen age change in money supply will lead o 16.71% inc ease in se ice sec o . The nega i e and signi ican es ima e o he e o co ec ion model in R_ AGR, R_ CGD, R_ CGL, R_ FIN and R_ HLH e lec s ha he e is he p esence o a sho un ela ionship. The E o Co ec ion Coe icien signi ies he speed o adjus men om sho un dynamics o long un equilib ium. The nega i e sign indica es ha he e will be a con e gence o disequilib ium owa ds long un equilib ium. The long un esul s s a ed in Table 5, he s udy deduces a posi i e exchange a e in luence in all sec o al esul s excep ag icul u al, indus ial and oil and gas sec o s. Howe e , conglome a e sec o is signi ican a 1% showing ha a pe cen age change in exchange a e will lead o a 14.71% inc ease in conglome a e sec o . Consume p ice index has a nega i e e ec on con- sume goods, conglome a e and heal h sec o s. Mo eo e , i is consume goods and conglome a e sec o s a e signi ican a 1% showing ha a pe cen age change in consume p ice index will lead o 20.09% dec ease in conglome a e sec o . The e is he exis ence o a nega i e ela ionship be ween Indus ial p oduc ion index and indus ial sand oil and gas sec o s. Howe e , consume goods and heal h sec o s a e signi ican a 10% and conglome a e a 1% e lec ing ha a pe cen age change in indus ial p oduc ion index will lead o a 22.83% inc ease in conglome a e sec o . While o money supply, he e exis a nega i e ela ion be ween money supply and inancial, indus ial and oil and gas sec o s. In e es ingly, ou o all he sec o s, he inancial sec o eac s o changes in exchange a e shocks. Hence, his s udy inds ou ha exchange a e asymme y only coun s o he e u ns on inancial se ice sec o . This also co obo a es he indings in he li e a u e (see, Fowowe, 2015; Salisu & Ndako, 2018; Bahmani-Oskooee & Saha, 2018, Ahmed, 2020). I consis s bo h long un and sho un. To be p ecise, posi i e and nega i e shocks o exchange a e a e seen o be p esen in he sho un and long un o he inancial se ice sec o and his can be as a esul o he e en s o global inancial c isis ha nega i ely a ec ed he inancial se ice sec o o Nige ia by c ea ing sca ci y o unds o he inancial se ice sec o and also c ashing he capi al ma ke . No o ge ing, he ecession pe iod o 2016, had a nega i e impac on he inancial se ice sec o . Pa o he s udy and ocal poin is o es o asymme y using he Wald es . In doing his, wo scena ios a e conduc ed which a e he ole o s uc u al b eaks and he ole wi hou s uc u al b eaks. Wi hou s uc u al b eaks, only inancial se ice sec o eac s o di e ences in news ei he posi i e o nega i e news. The esul sugges s ha we only conside he nonlinea ARDL o inancial se ice sec o while symme ic ARDL o he o he nine sec o s. In e es ingly, h ee ou o hese en sec o s show no long un ela ionship. Hence, we only conside hei sho un es ima e wi hou he adjus men pa ame e , which is he ECM pa ame e . To implemen he asymme ic ARDL model, he same p ocedu es employed in he linea ARDL model a e ollowed. The ini ial p ocedu e is o es o he exis ence o he nonlinea long un ela ionship (coin eg a ion) be ween he a iables. The esul s p esen ed in Tables 4, 5 and 6 shows ha only he inancial se ice sec o is asymme ic because i esponds o di e ences in news be i posi i e o nega i e news. Hence, he nonlinea ARDL is employed o inancial se ice Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 14 o 26 Table 5. Long- un es ima ion wi hou b eak VARIABLES R_AGR R_CGD R_CGL R_FIN R_HLH R_IND R_OGS Symme y Symme y Symme y Symme y Symme y Symme y Symme y CONSTANT −117.046 (0.473) −145.929 (0.118) −216.259 (0.047)** −5.951 (0.966) −69.787 (0.533) 1646.538 (0.331) 564.896 (0.440) LEEXR −2.066 (0.850) 6.799 (0.270) 14.711** (0.036) 3.380 (0.650) −31.372 (0.647) −63.415 (0.265) DLEEXR_NV - - - 3.103 (0.743) - - - DLEEXR_PV - - - 4.039 (0.666) - - - LCPI 13.819 (0.392) −12.622 (0.091)* −20.092 (0.016)* 5.071 (0.658) −10.661 (0.233) 152.947 (0.342) 5.233 (0.925) LIPI 13.819 (0.392) 16.279 (0.091)* 22.829 (0.045)*** 12.234 (0.371) 19.735* (0.089) −115.785 (0.441) −51.675 (0.463) LMS 6.699 (0.519) 6.257 (0.275) 8.670 (0.182) −6.141 (0.486) 0.605 (0.930) −107.830 (0.344) −3.290 (0.941) No e: ***, ** and * imply signi icance a 1%,5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 15 o 26 sec o . Posi i e and nega i e news o exchange a e a ec he inancial sec o posi i ely bo h in he sho and long pe iods wi hou b eaks. The e alua ion o he signi icance o s uc u al b eaks in he exchange a e, consume p ice index, indus ial p oduc ion index and money supply and sec o al s ock e u ns ela ionship. The s udy ini ial de ines he b eak endogenously using Bai—Pe on es hen employs he b eak dummies as ixed ep esso s in bo h he symme ic and asymme ic ARDL models and las ly inco po a ing Wald es o join ly he s a is ical signi icance o he b eaks. The Bai- Pe on esul s a e s a ed in Table 7 and a leas a b eak is eco ded o each o he sec o al e u ns analyzed. The da es ecognized coincide wi h he 2008 and 2009 se ies o global inancial c isis, 2011 A ab sp ings and he eme gence om ecession in Nige ia in 2017. An ad an age o employing Bai—Pe on es is ha i p oduces eg ession esul s o each o he b eak anges no able including he sign, size and s a is ical signi icance o he ele an a iables. The esul in Tables 8 and 9 shows ha posi i e ela ionship be ween all sec o al e u ns excep ag icul- u al and heal h sec o s and exchange a e. Howe e , he ela ionship is posi i e and signi ican a 1% on consume goods and conglome a e sec o s. Hence, a pe cen age change in exchange a e will lead o a 13.10% inc ease in consume goods sec o . The e is also he exis ence o a nega i e ela ionship be ween consume p ice index and all sec o al e u ns excep na u al esou ces sec o . The e is a posi i e and signi ican ela ionship be ween consume p ice index and consume goods and conglome a e sec o s a 1% and cons uc ion a 10%. Howe e , a pe cen age change in consume p ice index will lead o 33.14% dec ease in consume goods sec o . Indus ial p oduc ion index nega i ely in luences all sec o al e u ns in all sec o al e u ns excep ag icul u al, oil and gas and na u al esou ces sec o s. Howe e , he ela ionship is posi i e and sig- ni ican a 1% on cons uc ion, heal h and se ice sec o . Howe e , a pe cen age change in indus ial p oduc ion index will lead o 109.95% dec ease in cons uc ion, money supply is posi i e in all sec o al e u ns excep oil and gas sec o and conglome a e is signi ican a 1% e lec ing ha a pe cen age change in money supply will lead o 9.45% inc ease in conglome a e. Cons uc ion sec o lagged in yea one, yea wo and yea h ee has a nega i e e ec on he cu en yea o cons uc ion sec o and is signi ican a 1%. Heal h sec o lagged in yea one has a nega i e e ec on he cu en yea o heal h sec o , indus ial sec o lagged in yea one and yea wo has a nega i e impac on he cu en yea o indus ial sec o and is signi ican a 1%, na u al esou ces lagged in yea one has a nega i e signi icance on he cu en yea o R_ na u al esou ces and i s signi ican a 1% and oil and gas sec o lagged in yea one has a nega i e e ec on he cu en yea o oil and gas sec o and i s signi ican a 1%. The b eak poin s a e posi i e o R_ AGR, R_ CDG and signi ican a 1%, R_ CONS, R_HLH, R_ OGS and signi ican a 1%, R_ SVS and signi ican a 1%, i s b eak poin o R_IND and second b eak poin o R_CGL. While he b eak poin s a e nega i e o he second b eak poin o R_IND, i s b eakpoin o R_CGL and i s nega i e and signi ican a 1% o R_NTR. The F s a is ics (Bound es ) e eals ha he e is a long un ela ionship in all sec o al s ock e u ns excep cons uc ion, indus ial and oil and gas sec o s. Fo he long un, he esul shows ha posi i e ela ionship be ween all sec o al e u ns excep ag icul u al sec o . Though he e is a posi i e ela- ionship be ween exchange a e and signi ican a 1% on consume goods sec o and conglome a e sec o . Howe e , a pe cen age change in exchange a e will lead o 20.42% inc ease in consume goods. The e is also he exis ence o a posi i e ela ionship be ween consume p ice index and all sec o al e u ns excep na u al esou ce sec o . The e is a posi i e and signi ican ela ionship be ween consume p ice index and consume goods, conglome a e and se ice sec o s a 1%. Howe e , an inc ease in consume p ice index will esul o 39.82 dec eases in consume goods sec o . Indus ial p oduc ion index posi i ely in luences all sec o al e u ns in all sec o al e u ns excep consume goods and se ice sec o s. Howe e , he ela ionship is nega i e and signi ican a 1% on se ice sec o and a pe cen age change in indus ial p oduc ion index will lead o 29.87% dec ease in se ice sec o . Money supply is posi i e in all sec o al e u ns excep se ice sec o , i is Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 16 o 26 nega i e and signi ican a 5%, and conglome a e sec o is posi i e and signi ican a 10% e lec ing ha a pe cen age change in money sec o will lead o 12.68% inc ease in conglome a e. Howe e , he b eakpoin s a e posi i e R_ AGR and signi ican a 5%, R_ CDG and signi ican a 1% R_HLH and R_SVS and signi ican a 1% and he second b eakpoin o R_ CGL and i s nega i e o he i s b eakpoin o R_ CGL, R_ NTR and signi ican a 1%. This s udy also de e mines he beha iou o asymme ies in he exis ence o b eaks o all selec ed sec o al s ock e u ns. Table 10 shows ha , wi h he inclusion o b eaks, asymme y modelling o pass h ough e ec o exchange a e, consume p ice index, indus ial p oduc ion index and money supply a e no alid o all sec o al s ock e u ns because he e is no p esence o asymme y in sho un and long un wi h b eaks. No iceably, i is only he inancial sec o ha esponds o exchange a e shock in an asymme y manne . Hence, asymme y is ele an o asce ain he ela ionship be ween inancial sec o and exchange a e shock. 4.3. Conclusion and implica ions o policy This s udy e alua es exchange a e shock and sec o al e u ns in Nige ia, using a mon hly da a sou ce om Cen al Bank o Nige ia S a is ical Bulle in and (h p://www.cashc a .com/plis o de .php) co e ing he pe iods o 2007–2018. The a iables on which he da a we e sou ced include E ec i e exchange a e, Consume P ice Index, Indus ial P oduc ion Index, Money supply and p ices o en sec o s in Nige ia which a e Ag icul u e, Consume goods, Conglome a es, Cons uc ion, Finance, Heal h ca e, Indus ial goods, Na u al esou ces, Oil and Gas and Se ices. This s udy inco po a ed he Augmen ed Dickey- Fulle Tes and Phillip Pe on Tes (PP) as well as uni oo es wi h s uc u al b eaks o de ine he s a iona y condi ions o he a iables used o he s udy. The es shows ha he se ies a e in eg a ed o o de ze o and one. Ten models we e es ima ed using Au o eg essi e Dis ibu ed Lag Model. Mo eo e , gi en he signi icance o s uc u al b eaks in beha iou o hese se ies o e ime in Nige ia, a mul iple s uc u al b eak es o be exac Bai- Pe on (2003) was adop ed. This s udy analysis d aws upon he Table 6. Asymme y Wald es wi hou s uc u al b eaks Sec o al e u ns Wald S a is ic Any P esence o Asymme y? Sho un W SR Long un W LR Sho un Long un R_AGR 0.205 (0.652) 0.204 (0.652) NO NO R_CGD 1.226 (0.270) 1.226 (0.270) NO NO R_CGL 1.175 (0.280) 1.114 (0.293) NO NO R_CONS 0.981 (0.329) 0.001 (0.973) NO NO R_FIN 3.782** (0.054) 3.782** (0.054) YES YES R_HLH 0.364 (0.548) 0.364 (0.548) NO NO R_IND 0.908 (0.342) 0.428 (0.514) NO NO R_NTR 0.077 (0.781) 0.077 (0.782) NO NO R_OGS 0.009 (0.925) 0.009 (0.926) NO NO R_SVS 2.457 (0.119) 2.457 (0.119) NO NO No e: ***, ** and * imply signi icance a 1%,5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 17 o 26 linea and Non Linea Au o eg essi e Dis ibu ed Lag (ARDL and NARDL) app oach o e alua e hese ela ionships, which is ound o be sui able wi h he use o mixed non-s a iona y na u e o he da a. Coin eg a ion analysis was employed and long un equilib ium occu ed among o he sec o al e u ns. Fu he mo e, his s udy checks he signi icance o hese b eaks in he symme ic and asymme ic ela ionship ha may be p esen be ween Exchange a e, Consume P ice Index, Indus ial P oduc ion Index, Money supply and e u ns o he selec ed sec o s. The Wald es esul shows clea e idence o asymme y be ween exchange a e and inancial se ice sec o wi hou b eaks bu wi h b eaks, he e is no asymme y ela ionship be ween he e u ns and exchange a e. Exchange a e has an impac on all he employed sec o al s ock e u ns in Nige ia whe he posi i ely o nega i ely and be i in he long o sho un (wi h o wi hou b eaks). Howe e , inancial se ice sec o e u n is ound o be asymme ic and is posi i ely in luenced by bo h nega i e and posi i e exchange a e shock in he sho un and long un wi hou b eak. The e o e, his s udy concludes ha a single model canno i all he sec o al s ock e u ns because all sec o s espond di e en ly o exchange a e mo emen s and he in o ma ion abou a pa icula sec o canno be used o o ecas o he sec o s. Following he indings o his s udy, he e a e a numbe o implica ions o policy in Nige ia. Fi s , ins abili y in exchange a e o en causes in es o s o lose con idence in in es ing in he s ock ma ke , which in u n educes he le el o in es men . Impo a ion o goods especially consume goods makes Nige ia dependen on o he na ion’s esou ces, economic and poli ical powe . Second, sec o s apa om inancial se ice sec o a e insensi i e o asymme ic ends in exchange a e luc ua ions. This enables in es o s ha a e isk a e se o in es in hose sec o s al hough he consequence in ol ed consis s o lesse e u ns om he sec o s. This can also con ibu e o s ock ma ke expe s in enabling hem o ake accoun o isk inclina ion when p edic ing u u e ac i i ies o s ock e u ns. In addi ion, Table 7. Bai- Pe on (2003) s uc u al b eak da e Models B eaks Range Signs ag ¼ ðleex ;lcpi ;lipi;lmsÞ2009M04 2007M02-2009M03 2009M04-2018M12 -/- -/- cgd ¼ ðleex ;lcpi;lipi;lmsÞ2009M03 2012M07 2007M02-2009M02 2009M03-2012M06 2012M07-2018M12 -/- -/- +/+ cgl ¼ ðleex ;lcpi ;lipi;lmsÞ2008M11 2012M04 2007M02-2008M10 2008M11-2012M03 2012M04-2018M12 -/- +/+ +/+ cons ¼ ðleex ;lcpi ;lipi;lmsÞ2009M04 2017M04 2007M02-2009M03 2009M04-2017M03 2017M04-2018M12 -/- -/- +/+ in ¼ ðleex ;lcpi;lipi;lmsÞNO BREAKPOINTS hlh ¼ ðleex ;lcpi ;lipi;lmsÞ2009M01 2013M07 2007M02-2008M12 2009M01-2013M06 2013M07-2018M12 -/- -/- +/+ ind ¼ ðleex ;lcpi ;lipi;lmsÞ2009M03 2017M04 2007M02-2009M02 2009M03-2017M03 2017M04-2018M12 +/+ -/- +/+ n ¼ ðleex ;lcpi ;lipi;lmsÞ2008M11 2007M02-2008M10 2008M11-2018M12 -/- +/+ ogs ¼ ðleex ;lcpi ;lipi;lmsÞ2009M04 2016M11 2007M02-2009M03 2009M04-2016M10 2016M11-2018M12 -/- +/+ -/- s s ¼ ðleex ;lcpi ;lipi;lmsÞ2009M05 2011M10 2007M02-2009M04 2009M05-2011M09 2011M10-2018M12 -/- +/+ +/+ No e: ***, ** and * imply signi icance a 1%,5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 18 o 26 Table 8. Sho un es ima ion wi h b eaks VARIABLES R_AGR R_CGD R_CGL R_CONS R_HLH R_IND R_NTR R_OGS R_SVS Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y DLEEXR −0.647 (0.946) 13.307 (0.001)*** 15.233 (0.007)*** 2.2736 (0.713) −18.619 (0.012) 4.630 (0.353) 0.719 (0.863) 5.132 (0.433) 5.827 (0.211) DLCPI −10.584 (0.374) −33.146 (0.000)*** −29.270 (0.001)*** −15.440 (0.076)* −12.089 (0.239) −9.670 (0.089) 1.931 (0.705) −1.255 (0.847) −20.244 (0.006) DLIPI 2.748 (0.855) −7.502 (0.144) −50.461 (0.02) −109.959 (0.001)*** −78.431 (0.001)*** −57.521 (0.011) 2.073 (0.741) 6.637 (0.429) −19.932 (0.008)*** DLMS 1.232 (0.896) 4.936 (0.160) 9.459 (0.063)* 4.982 (0.490) 2.992 (0.627) 4.587 (0.329) 2.461 (0.570) −0.185 (0.972) 10.540 (0.259) D1_ARG 8.867 (0.057) -------- D1_CGD - 11.493 (0.000)*** ------- D2_CGD - 20.345 (0.000)*** ------- D1_CGL - - −1.543 (0.531) - - - - - - D2_CGL - - 6.096 (0.147) - - - - - - D1_CONS - - - 8.569 (0.015) ----- D2_CONS - - - 1.082 (0.853) ----- D1-HLH - - - - 3.612 (0.168) - - - - D2_HLH - - - - 4.0334 (0.356) - - - - D1_IND - - - - - 2.958 (0.197) - - - (Con inued) Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 19 o 26 Table8. (Con inued) VARIABLES R_AGR R_CGD R_CGL R_CONS R_HLH R_IND R_NTR R_OGS R_SVS Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y D2_IND - - - - - −2.302 (0.554) - - - D1_NTR - - - - - - −27.159 (0.000)*** - - D1_OGS - - - - - - - 23.540 (0.000)*** - D2_OGS - - - - - - - 5.868 (0.248) - D1_SVS - - - - - - - - 7.346 (0.001)*** D2_SVS - - - - - - - - 18.187 (0.000)*** DR_CONS(−1) - - - −0.462 (0.000)*** ----- DR_CONS(−2) - - - −0.415 (0.000)*** ----- DR_CONS(−3) - - - −0.317 (0.000)*** ----- DR_HLH(−1) - - - - −0.183 (0.030) - - - - DR_IND(−1) - - - - - −0.503 (0.000)*** - - - DR_IND(−2) - - - - - −0.325 (0.000)*** - - - DR_NTR(−1) - - - - - - −27.159 (0.000)*** - - DR_OGS(−1) - - - - - - - −0.357 (0.000)*** - (Con inued) Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 20 o 26 Table8. (Con inued) VARIABLES R_AGR R_CGD R_CGL R_CONS R_HLH R_IND R_NTR R_OGS R_SVS Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y Symme y ECM −0.911 (0.000)*** −0.832 (0.000)*** −0.746 (0.000)*** ———– −0.595 (0.000)*** ———– −0.754 (0.000)*** ———- −0.667 (0.000)*** LM (5) 2.323 (0.102) 0.247 (0.782) 1.076 (0.344) 1.663 (0.194) 0.677 (0.510) 3.692 (0.028) 3.925 (0.022) 3.811 (0.025) 2.050 (0.133) ARCH (5) 3.078 (0.007) 1.071 (0.384) 3.201 (0.00) 1.723 (0.012) 4.774 (0.000) 2.581 (0.000) 11.513 (0.000)*** 1.537 (0.042) 2.879 (0.000)*** F_ STATS (BOUNDS) 19.186 13.073 11.273 2.238 12.136 1.416 10.027 1.689 9.314 R 2 Adjus ed 0.024 0.430 0.342 0.794 0.343 0.870 0.365 0.925 0.418 CUSUM S able S able S able S able S able S able S able S able S able CUSUM SQR S able S able S able S able S able S able S able S able S able No e: ***, ** and * imply signi icance a 1%, 5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 21 o 26 Table 9. Long un es ima ion wi h b eaks VARIABLES R_AGR R_CGD R_CGL R_HLH R_NTR R_SVS Symme y Symme y Symme y Symme y Symme y Symme y CONSTANT 16.982 (0.921) 55.099 (0.392) −142.560 (0.176) −98.058 (0.360) −69.456 (0.443) 354.641 (0.001) LEEXR −0.710 (0.946) 15.987 (0.001)*** 20.420 (0.006)*** 6.652 (0.523) 0.954 (0.863) 8.732 (0.208) LCPI −11.623 (0.373) −39.821 (0.000)*** −39.236 (0.001)*** −20.301 (0.242) 2.561 (0.704) −30.338 (0.004)*** LIPI 3.018 (0.855) −9.013 (0.142) 7.780 (0.463) 16.786 (0.260) 2.750 (0.740) −29.870 (0.006)*** LMS 1.353 (0.896) 5.930 (0.160) 12.680 (0.058)* 5.025 (0.629) 3.265 (0.570) −7.876 (0.218) D1_AGR 9.738 (0.054)** - - - - - D1_CGD - 13.807 (0.000)*** - - - - D2_CGD - 24.442 (0.000)*** - - - - CGL1 - - −2.068 (0.530) - - - CGL2 - - 8.171 (0.142) - - - D1-HLH - - - 6.065 (0.179) - - D2_HLH - - - 6.773 (0.360) - - D1_NTR - - - - −12.434 (0.000)*** - D1_SVS - - - - - 11.009 (0.001)*** D2_SVS - - - - - 27.256 (0.000)*** Sou ce: Au ho s Compu a ion No e: ***, ** and * imply signi icance a 1%,5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 22 o 26 he in es o s mus look in o ele an cu ency hedging s a egies o educe dep ecia ion isks and p o ec in es men s expec ed a e o e u n ha a e domina ed in o eign cu ency since he domes ic cu ency dep ecia ion shows some in e se e ec s on he s ock e u ns. In his ega d, po en ial in es o s a e encou aged o lay hold on s udies as his, which elici he ole o asymme ies on he exchange a e-s ock e u ns nexus. Wi h he exposed asymme ic impac o exchange a e shocks on he s ock ma ke e u ns, as well as he di e ing magni ude o impac s ac oss pe iods and sec o s, he in es o s a e p esen ed wi h he choice o de e mining when and whe e o in es . This is because s ock e u ns’ esponse o cu ency changes a ies in he sho and long un and ac oss di e en sec o s. F om a policymaking pe spec i e, ma ke egula o s could bene i om a be e in e p e a ion o exchange a e-sec o s ocks dynamics. Due o he sizeable suscep ibili y o he sec o s ocks o exchange a e shocks, po olio manage s should be a en i e o he mo emen s o he Nige ian Nai a exchange a es, in sea ch o clues abou he u u e cou se o equi y p ices. Nige ia adop s he mul iple exchange- a e egime o a oid an ou igh de alua ion o he nai a by keeping a s onge pegged a e o o icial ansac ions and weake exchange o non-go e nmen ela ed ansac ions, which has been c i icized by In e na ional Mone a y Fund (IMF). Howe e , he pu posi e decision o managed- loa he Nai a appea s o ha e p oduced some o i s aspi ing goals, which include educing he ac i i ies o he pa allel ma ke , imp o ing ade expo s h ough educ ion in ade de ici s and mo e impo an ly imp o ing he con idence o in es o s. Despi e hese posi i e ou comes, he idea o managed- loa he local cu ency has come wi h i s own side e ec s, as he spi al in la ion wi h a double-digi alue has aken a hea y oll on he Nige ian economy. In essence, o a enua e in la iona y p essu es, he ele an au ho i ies mus implemen app op ia e policy measu es, such as aising in e es a es, s abilizing iscal policies, and clea ing ou excess liquidi y. Holis ically, he mone a y au ho i y could conside implemen ing a lexible in la ion a ge ing mone a y policy, which is in ended o bo h lowe he ac ual in la ion owa d an announced a ge a e and o s abilize economic g ow h. Addi ionally, iscal s abili y can be achie ed by simul aneously b oadening go e n- men e enues and consolida ing public expendi u es. As pa o u u e esea ch, a he han ocusing Table 10. Asymme y Wald es wi h s uc u al b eaks Sec o al e u ns Wald S a is ic Any P esence o Asymme y? Sho un W SR Long un W LR Sho un Long un R_AGR 0.446 (0.506) 0.446 (0.506) NO NO R_CGD 0.033 (0.856) 0.033 (0.856) NO NO R_CGL 0.324 (0.570) 0.324 (0.570) NO NO R_CONS 0.682 (0.410) 0.550 (0.460) NO NO R_FIN NO BREAK POINT R_HLH 0.247 (0.620) 0.247 (0.620) NO NO R_IND 0.876 (0.351) 0.219 (0.641) NO NO R_NTR 0.000 (0.983) 0.000 (0.983) NO NO R_OGS 0.583 (0.447) 0.523 (0.471) NO NO R_SVS 1.065 (0.304) 1.065 (0.304) NO NO Sou ce: Au ho s Compu a ion No e: ***, ** and * imply signi icance a 1%, 5% and 10% espec i ely Fasanya & Akinwale, Cogen Economics & Finance (2022), 10: 2045719 h ps://doi.o g/10.1080/23322039.2022.2045719 Page 23 o 26