Relationship Between Public Expectations and Financial Market Dynamics in South- East Europe Capital Markets

Transcription

1 Economc Alernaves, 07, Issue, pp Relaonshp Beween Publc Expecaons and Fnancal Marke Dynamcs n Souh- Eas Europe Capal Markes An Sosova-Soykova * Summary We examne he marke effcency, nformaon asymmery and he lnkages beween fnancal marke dynamcs and publc expecaons of he sock markes of Souh Eas Europe (SEE). Therefore, hs sudy ams o answer he queson of wheher here s a dfference beween he sock marke performance of he developed and emergng SEE sock exchanges. Ths paper employs GARCH models and uses he daly and monhly reurns of eleven sock marke ndces of Souh Eas Europe (SEE) - Bulgara, Banja Luka, Sarajevo, Croaa, Greece, Serba, Slovena, Turkey, Romana, Monenegro and Macedona over he perod from January 005 o November 05. The resuls reveal ha SEE capal markes excep Monenegro are no effcen n he conex of he effcen marke hypohess (EMH). Moreover, he consumer senmen nformaon and nflaon expecaons affec he fnancal marke dynamcs of SEE sock ndces. The analyss shows ha here s no lnkage beween ndusral expecaons and he dynamcs of he SEE capal markes. Tes resuls poenally presen ha he consumer and nflaon expecaons have predcve power for he performance of SEE capal markes. Key words: Effcen Marke Hypohess, marke effcency and nformaon asymmery, publc expecaons, capal markes, GARCH models. JEL Classfcaon: C3, E7, G4, G5. Inroducon Effcen marke hypohess and he random walk hypohess have been major ssues n fnance for he pas 50 years. The erm effcency s used o characerze a marke n whch relevan nformaon s mpounded no he prce of fnancal asses. In pracce, hs means ha he sock markes ndces are unpredcable. Accordng o he effcen markes hypohess (EMH) marke prces fully reflec all avalable nformaon. On he oher hand, behavor economss ry o prove ha economc agens don always ac raonally due o emoonal and personal facors and senmens. Wha s more, we can assume ha he publc expecaon nformaon can predc oal producon, whch on he oher hand affecs he sock marke ndces. We wll aemp o answer he followng quesons: How effcen are capal markes acually? Can he publc expecaons be used o forecas he * Asssan professor, Faculy of Economcs, Deparmen of Fnance and accounng, Souh-Wes Unversy Neof Rlsk, Bulgara; Conac address: 8 Aon Sr., fl., apar. 9, Blagoevgrad 700, Bulgara; Emal address: an_qankova_s@abv.bg; Phone number:

2 dynamcs and movemens of sock ndces? Consequenly, hs sudy focuses on he marke effcency, nformaon asymmery and he lnkages beween fnancal marke dynamcs and publc expecaons of eleven capal markes of Souh Eas Europe (SEE). We can dvde he sock exchanges of SEE no wo groups n he conex of her developmen, usng he sock marke capalzaon as a creron. The frs group conans he emergng markes Bulgara, Romana, Serba, Monenegro, Macedona, Slovena, Banja Luka and Sarajevo (Bosna and Herzegovna) and he second one developed markes Croaa, Turkey and Greece (Table 3 and Table 4). The daa range s s January 005 o 4 h November 05. The ndces under examnaon are eleven ndces represen all capal markes of Souh Eas Europe: he Bulgaran SOFIX, he Banja Luka BIRS, he Sarajevo BIFX, he Greek Ahex Compose Share Prce Index, he Macedonan MBI0, he Romanan BET, he Serban BELEX5, he Croaan CROBEX, he Slovenan SBI TOP, he Turksh BIST00 and he Monenegrn MONEX. We use daly reurns o examne he marke effcency and monhly reurns, respecvely for analyzng he mpac of he publc expecaons on he sock exchange performance, applyng an approprae GARCH models. The paper s organzed n he followng way. The frs secon naes wh he nroducon. Secon summarzes he leraure revew. Secon 3 dscusses he daa and he research mehod employed. Secon 4 shows he man esmaon resuls. The fnal secon provdes summary and conclusons.. Leraure revew Fsher and Saman (00) examne he relaonshp beween consumer confdence and capal markes dynamcs. Besdes, hey fnd evdence ha he consumer expecaons can predc changes n he Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes sock markes. Wha s more, he auhors esablsh an nverse lnkage beween consumer confdence n one monh and sock reurns n he followng monh for he NASDAQ and small cap socks. Kremer and Wesermann (004) examne he lnkage beween sock marke developmens and consumer confdence n he euro area usng VAR analyss. The resuls reveal he exsence of sgnfcan posve relaonshp beween sock marke performance and consumer confdence n he euro area. Görmüş and Güneş (00) analyze he effec of Consumer Confdence Index (CCI) on real exchange rae and sock marke n Turkey for he perod usng economerc echnques. The resuls from GARCH-M and OLS model show ha CCI affec real exchange rae and sock prces. Oprea and Brad (04) nvesgae he relaonshp beween he consumer confdence ndex and he Romanan sock marke for he perod They argue ha here s a posve correlaon beween changes n consumer confdence and sock marke reurns, dsplayng ha ndvdual nvesor senmen affecs sock prces. In he sudy conduced by Mljkovć and Radovć (006) evdence ha he Serban sock marke does no show effcency even n he weak-form of EMH s presened. They fnd sascally sgnfcan levels of auocorrelaon n reurns wh hgh kuross dsrbuon, consderably dfferen from he normal one. Borges (00) sudes sock markes of France, Germany, UK, Greece, Porugal and Span o check for he presence of random walk for he perod from January 993 o December 007. Usng boh paramerc and nonparamerc ess, he fnds evdence of random walk n all sx counres for monhly reurn. Moreover, he hypohess of random walk was rejeced for Porugal and Greece for he daly reurn. Aga and Kocaman (0) es he weak form of effcency for reurn ndex-0 n 38 Economc Alernaves, Issue, 07

3 Isanbul Sock (ISE) for he perod They lead o he concluson ha here s a weak form of effcency n ISE, whch means ha he marke s weakly effcen f he curren me canno be explaned wh he pas values. Invesgang calendar anomales for fve SEE sock markes (Bulgara, Croaa, Greece, Romana and Turkey) durng he perod , Georganopoulos, Kenourgos and Tsams (0) fnd evdence for he exsence of hree calendar effecs (day of he week, urn of he monh, me of he monh) n boh mean and volaly equaons for Greece and Turkey, whch s conssen o he fndngs of prevous sudes. On he oher hand, he effecs for he hree emergng SEE markes are lmed and exs only n volaly. Samas, Kenourgos and Palalds (0) sudy long-run relaonshps among fve Balkan emergng sock markes (Turkey, Romana, Bulgara, Croaa, and Serba), he US and hree developed European markes (UK, Germany and Greece) durng he perod The resuls ndcae ha boh domesc and exernal facors affec he Balkan sock markes, shapng her longrun equlbrum. Overall, hey show evdence n favor of sgnfcan long-run relaons beween he Balkan emergng markes whn he regon and globally. Armeanu and Coaca (04) es he EMH n he case of Romana for usng four mehods, ncludng GARCH model. They fnd ou ha he Romanan capal marke s no weak-form effcen. Dragoa and Oprea (04) nvesgae he Romanan sock marke s nformaonal effcency and fnd ou ha he predcably of reurns sugges ha he Romanan sock marke has a low level of effcency. Furhermore, he mpac of new nformaon s more nense before and afer s release. Esmang he effec of he World Economc Crss on he Counres of he Balkan Regon Geshkov (04) fnds ha he mos affeced counres are Greece and Bosna and Herzegovna. Sudyng he mpac of 008 fnancal crss on he effcency of he capal markes of Cenral and Easern European (CEE) counres, Tsenkov (05) fnds dfferences n marke reacon of wo of suded markes n he comparson wh he res CEE markes. The Bulgaran and he Romanan ndces show dsposon for faser and more sensve reacon o negave marke mpulses, ypcal for he Crss Perod, n conras o a moderae ncorporaon of he posve marke mpulses specfc o he Pre-crss Perod. Incorporaon of he marke nformaon by Bulgaran SOFIX durng Crss Perod s so acceleraed ha when becomes publcly avalable much of he conen s already ncluded n he values of SOFIX under he form of srongly followed marke rend. Ths ype of reacon s oppose o he behavor from oher CEE ndces whch follows more susanable marke rends durng he pre-crss perod and gves much lower sgnfcance of he new marke nformaon. Ths marke behavor changes durng he Crss Perod, showng an enhanced response only o he shor-erm marke flucuaons. Durng he Pos-crss Perod he Bulgaran and he Romanan ndces are showng predsposon o he shor-erm marke rends. Ths s oppose o he oher CEE ndces whch end o form and pursue longer-erm marke rends. 3. Mehodology and daa In hs paper, we analyze he marke effcency, nformaon asymmery and he lnkages beween fnancal marke dynamcs and publc expecaons of eleven capal markes of Souh Eas Europe (SEE) - Bulgara, Croaa, Greece, Serba, Slovena, Turkey, Romana, Monenegro, Macedona, Banja Luka and Sarajevo (Bosna and Herzegovna). We can dvde he sock exchanges of SEE no wo groups n he conex of her developmen, usng he sock marke 39

4 Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes capalzaon as a creron. The frs group conans he emergng markes Bulgara, Romana,, Banja Luka and Sarajevo (Bosna and Herzegovna), Serba, Monenegro, Macedona, Slovena and he second one developed markes Croaa, Turkey and Greece (Table 3 and Table 4). Daly closng prces of eleven SEE marke ndces were avalable on he Sock s webses of he nvesgaed counres. The daa range s s January 005 o 4 h November 05. We should dvde he analyss no wo separaed pars n he frs one we wll examne f he capal markes are characerzed wh marke Table. Analyzed sock exchanges, ndces and a number of observaons effcency n he conex of he effcen marke hypohess (EMH) and n he second one f he publc expecaons are relaed o he fnancal capals dynamcs, respecvely. The frs par of he analyss wll be made by he daly reurns ( r ) formulaed below by usng daly closng prces of he sock markes of he counres: P r = log( ) P () where P and P - are he closng value of he marke ndex a he curren day and prevous day, respecvely. (Table ). Counry Sock exchange Index Number of observaons Bulgara Bulgaran Sock 693 SOFIX Bosna and Banja Luka sock 660 BIRS Herzegovna exchange Bosna and Sarajevo sock 708 BIFX Herzegovna exchange Greece Ahens Sock Ahex Compose 704 Share Prce Macedona Macedonan Sock 640 MBI0 Romana Buchares Sock 77 BET Serba Belgrade Sock 54 BELEX5 Croaa Zagreb Sock 704 CROBEX Slovena Ljubljana Sock 395 SBI TOP Turkey Borsa Isanbul BIST00 77 Monenegro Monenegro Sock 675 MONEX Noes for Table.: Souheas Europe ncludes 0 counres: Bulgara, Bosna and Herzegovna, Greece, Macedona, Romana, Serba, Croaa, Slovena, Turkey and Monenegro. Source: Auhor s calculaons. 40 Economc Alernaves, Issue, 07

5 Analyzng he SEE capal markes we use he models of he GARCH- famly models (GARCH(p,q), (p,q), TGARCH(p,q) and PGARCH(p,q)) for esng he marke effcency and nformaon asymmery. The selecon of values p and q for used models s based on esng dfferen combnaons of values by applyng he Akake nformaon crera (AIC) es. The oupu combnaons of parameers p and q are deermned by he maxmum value of for boh parameers and hus esed are he followng combnaons: (,), (,), (,) and (,). The selecon procedure res o fnd a combnaon of he wo parameers ha leads o more successful modelng of he suded daa. The approprae model has Table. The approprae GARCH model of he GARCH-famly models for each ndex, applyng o examne he marke effcency examnaon г г. BIRS TGARCH(,)- BIFX GARCH(,)- SOFIX GARCH(,) - CROBEX GARCH(,)- ACSP PARCH(,)- MBI0 GARCH(,)- MONEX (,)- BET (,)- BELEX5 GARCH(,)- SBI TOP GARCH(,)- BIST00 TARCH(,)- Noes for Table.: The selecon of values p and q for GARCH-famly models s based on esng dfferen combnaons of values by applyng he Akake nformaon crera (AIC) es. The esed combnaons are followng: (,), (,), (,) and (,). The selecon procedure seeks a combnaon of he wo parameers ha leads o more successful modelng of he suded daa. Source: Auhor s calculaons Table 3. Marke capalzaon of SEE capal markes for 0 SEE capal markes Counry Bulgara Croaa Greece Banja Luka (Bosna and Herzegovna) Sarajevo (Bosna and Herzegovna) Monenegro Romana Serba Slovena Turkey Macedona Marke capalzaon (US$) 0 (bllon) 8,53.5 US$, US$ 33, US$,60.39 US$,63.89 US$ 3,509. US$ 4,03.9 US$ 4, US$ 6,35.86 US$ 97, US$ US$ Noes for Table 3.: The oal marke capalzaon of each capal marke s for 0 (approxmaely n he mddle of he examned perod ). Source: The webses of he SEE sock exchanges. been chosen for each ndex (usng he AIC values of each model, Table ). On he oher hand, for he second par of he analyss, we wll use he values of he reurns of he ndces wh a monhly frequency. We calculae he percenage change beween he openng value of he ndex on he frs workng day of monh (V) and he openng value on he frs workng day of nex monh (V+), or: V V R = + () V Agan, n he analyss of he SEE capal markes we use he models of he GARCH- famly models (GARCH(p,q), (p,q), TGARCH(p,q) and 4

6 Table 4. Developng and developed capal markes (accordng o he marke capalzaon) Developng SEE capal markes Bulgara Banja Luka (Bosna and Herzegovna) Sarajevo (Bosna and Herzegovna) Macedona Monenegro Romana Serba Slovena Developed SEE capal markes Greece Croaa Turkey Noes for Table 4.: Medan marke capalzaon s US $ 6,35.86 bllon. Source: Auhor s calculaons. Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes PGARCH(p,q)) for examnng he relaonshp beween publc expecaons and fnancal marke dynamcs, ncludng he addonal varables n he models, such as consumer confdence ndcaor (CCI), ndusral confdence ndcaor (ICI) and nflaon expecaons (InfExp). All daa s avalable n he daabase of he Eurosa Sascal Servce. Consumer and ndusral confdence ndcaors are ndces composed of quesons abou general condons for households and frms, respecvely. Inflaon expecaons daa s a queson askng he general publc f hey expec prces o rse faser, rse a he same rae, rse slower, reman he same, or decrease. Addonally, here s no avalable daa for hese ndcaors for Monenegro, Serba, Bosna and Herzegovna and Banja Luka, alhough n he neares fuure hese SEE counres should sar calculang he publc expecaon ndcaors because of he erms of jonng he European Unon. Hgher order GARCH models, denoed GARCH (q, p) can be esmaed by choosng Table 5. The approprae GARCH model of GARCH-famly models for each ndex, applyng o examne he relaonshp beween publc expecaons and capal marke dynamcs Indces Monhly daa-3 observaons SOFIX PGARCH(,) - CROBEX PGARCH(,)- ACSP (,)- MBI0 (,)- BET (,)- SBI TOP (,)- BIST00 (,)- MONEX * (, )- Noes for Table 5.: The selecon of values p and q for GARCH-famly models s based on esng dfferen combnaons of values by applyng he Akake nformaon crera (AIC) es. The esed combnaons are followng: (,), (,), (,) and (,). The selecon procedure seeks a combnaon of he wo parameers ha leads o more successful modelng of he suded daa. *Only daa for he nflaon expecaons. Source: Auhor s calculaons 4 Economc Alernaves, Issue, 07

7 eher q or p greaer han where q s he order of he auoregressve GARCH erms and p s he order of he movng average ARCH erms. The represenaon of he GARCH (q, p) varance s: q p + β jσ j + j= = σ = ω β ε (3) The or Exponenal GARCH model was proposed by Nelson (99). The specfcaon for he condonal varance s: q log( σ ) = ω + β j log( σ j ) + j= p r ε ε k + α + γ k k = σ k (4) = σ Noe ha he lef-hand sde s he log of he condonal varance. Ths mples ha he leverage effec s exponenal, raher han quadrac, and ha forecass of he condonal varance are guaraneed o be nonnegave. The presence of leverage effecs can be esed by he hypohess ha γ < 0. The mpac s asymmerc fγ 0. The Threshold GARCH (TGARCH) Model TARCH or Threshold ARCH and Threshold GARCH were nroduced ndependenly by Zakoïan (994) and Glosen, Jaganahan, and Runkle (993). The generalzed specfcaon for he condonal varance s gven by: q p σ = ω + β jσ j + α ε + j= = p r + α ε + γ kε k I k = k = (5) where I = f ε < 0 and 0 oherwse. In hs model, good news, ε > 0, and bad news ε < 0, have dfferenal effecs on he condonal varance; good news has an mpac of α, whle bad news has an mpac of. If γ > 0, bad news ncreases volaly, and we say ha here s a leverage effec for he -h order. If γ 0, he news mpac s asymmerc. The Power GARCH (PGARCH) Model Taylor (986) and Schwer (989) nroduced he sandard devaon GARCH model, where he sandard devaon s modeled raher han he varance. Ths model, along wh several oher models, s generalzed n Dng e al. (993) wh he Power ARCH specfcaon. In he Power ARCH model, he power parameer δ of he sandard devaon can be esmaed raher han mposed, and he oponal γ parameers are added o capure asymmery of up o order r : q p δ δ δ σ = ω + β jσ j + α ( ε γ ε ) (6) j= >, γ = where δ 0 for =,..., r, γ = 0, for all > r, and r p. The symmerc model ses γ = 0 for all. Noe ha f δ = and γ = 0 for all, he PARCH model s smply a sandard GARCH specfcaon. As n he prevous models, he asymmerc effecs are presen fγ Emprcal resuls 4.. Marke effcency and nformaon asymmery Table 6 shows he coeffcen of perssence, leverage effec and power parameer for daly sock reurns of he SEE ndces for he whole analyzed perod Here, we can make a noe ha coeffcens of perssence ake values n he range from (BIST00) o.0489 (ACSP). Also, we can separae he SEE ndces no wo groups accordng o he values of he coeffcen of perssence. The frs group conans ndces MONEX and BIST00 wh coeffcens of perssence lower han Ths leads us o he concluson ha he ndces from he frs group are wh relavely hgh marke effcency. On he oher hand, he second group ncludes BIRS, BIFX, SOFIX, CROBEX, ACSP, MBI0, BELEX5, SBI TOP and BET whch coeffcens of perssence are 43

8 Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes Table. The value of he power parameer, coeffcen of perssence and leverage coeffcen for he sample perod Indces coeffcen of perssence BIRS leverage coeffcen (Prob.) (0.0000) power parameer * (Prob) NA BIFX NA NA SOFIX NA (0.000) CROBEX NA NA ACSP (0.0044) (0.0000) MBI NA NA MONEX (0.009) NA BET (0.06) NA BELEX NA NA SBI TOP NA NA ARCH()** (Prob) (0.0000) (0.00) ARCH()** (Prob) (0.0000) (0.0450) BIST (0.0000) NA Noes for Table 6.: * Only for PGARCH ** Only for TGARCH and PGARCH wh power parameer close o. Source: Auhor s calculaons larger han We should make mporan remark here ha hese ndces above are wh relavely low marke effcency. The absolue values of he leverage coeffcen represened n Table 3 for observed SEE ndces are n he range from (BIRS) o (ACSP). In he TGARCH (, )- model, he good news has an mpac on he volaly of whle he bad news has an mpac of for BIST00, ndcang ha good news generae less volaly han bad news. In comparson, he resuls of TGARCH (, )- for BIRS represens ha he negave nformaon has (0.65) (0.000) an nfluence of ( ) showng ha bad news decreases he volaly durng he whole perod. Addonally, we should analyze he values of power parameer (n he case of esmang PGARCH (, )-). Frs, for he ACSP he value of hs parameer s almos uny ( ) meanng ha he PGARCH becomes TGARCH model. Second, for he ACSP bad news ncreases he volaly (he leverage effec s se a ). Sgnfcanly, he ndces ACSP ( ) and BIRS00 ( ) are wh large n sze and posve leverage coeffcens (above 0.5), ha means ha he new nformaon 44 Economc Alernaves, Issue, 07

9 enerng he marke causes grea changes n he volaly durng he whole perod under examnaon. By conras, he leverage effec for he BIRS, MONEX and BET s wh relavely low absolue value ( , and respecvely). We hypohesze ha news has a less mpac on he volaly. The overall pcure for he whole perod shows ha he regsered nformaon asymmery arbues o separaon of he SEE ndces no wo groups. The frs group conans ndces ACSP and BIST00 whch leverage coeffcens have hgh absolue values ndcang ha marke nformaon has large effec on he volaly. The members of he second group are BIRS, MONEX and BET, whch leverage coeffcens have low value resulng n weak reacon o he new nformaon enerng he marke and he aenuaon of he nformaon asymmery. Moreover, he fndngs above abou he values of he coeffcen of perssence and relaed nformaonal effcency reveal ha he SEE ndces can be dvded no wo groups. The frs group ncludes ndces MONEX and BIST000 characerzed wh hgh marke effcency (he value of coeffcen of perssence s lower han 0.97) and he second group - BIRS, BIFX, SOFIX, CROBEX, ACSP, MBI0, BELEX5, SBI TOP and BET wh marke neffcency (he value of coeffcen of perssence s above 0.97). To sum up, he ndces BIRS, BIFX, SOFIX, CROBEX, ACSP, BELEX5, SBI TOP, MBI0 and BET (Banja Luka, Bosna and Herzegovna, Bulgara, Croaa, Greece, Serba, Macedona and Romana, respecvely) are defned as marke neffcen accordng o he EMH durng he whole perod. Addonally, he ndces ACSP and BIST00 are wh hgh values of her leverage coeffcens ndcang ha marke nformaon has large effec on he volaly. All hngs consdered, seems reasonable o assume ha SEE capal markes aren effcen n he conex of EMH. 4.. The mpac of consumer and ndusral senmen on he capal marke dynamcs Table 7. Esmang resuls of GARCH models for he nfluence of he consumer confdence ndcaor on he capal marke dynamcs Index SOFIX CROBEX ACSP MBI0 BET SBITOP BIST00 The mos approprae GARCH model PGARCH (,) - PGARCH (,)- (,)- (,)- (,)- (,)- (,)- CCI (Prob) (0.03) (0.6703) (0.869) (0.07) (0.0047) (0.0008) (0.93) Noes for Table 7.:The daa of he consumer confdence ndcaor s ncluded n he equaon of (p,q) or PGARCH(p,q) model. Source: Auhor s calculaons. The able 7 shows he values of he consumer confdence ndcaor (CCI) n he equaon of (p,q) or PGARCH(p,q) model. We should noe ha for four of he examned ndces here are sascally sgnfcan values a 5% of CCI. Moreover, he absolue values of CCI are n he range from (MBI0) o (SOFIX). Remarkably, he hghes value of CCI s regsered for SOFIX, ndcang ha hs senmen ndcaor has a relavely 45

10 sgnfcan nfluence on he dynamcs of Bulgaran capal marke. Here, we should specfy ha sascally sgnfcan consumer confdence ndcaors are calculaed only for he emergng SEE capal markes Bulgaran (0.5358), Slovenan ( ), Macedonan ( ) and Romanan ( ). One of he possble explanaon of he regsered nsgnfcan values of CCI for he developed markes (Greece, Turkey and Croaa) s ha he cusomer expecaons are already ncluded n he prcng decsons of he marke agens. The resuls obaned for he numbers of CCI ha reach sascal sgnfcance (for four SEE counres) are really mpressve despe he large amoun of nose ha characerzes he surveys. Here we can make a concluson ha he consumer senmen nformaon has nfluence on he capal marke dynamcs of Bulgara, Macedona, Slovena, Romana, herefore on he prces of fnancal asses. Logcally, we should make an assumpon ha he consumer expecaons wll have larger effec on he socks of he companes especally dependen on consumpon (e.g. consumer goods companes) han on he oher socks. All hngs consdered, we fnd evdence ha consumer senmen has predcve capably, connecng wh he fnancal marke dynamcs of he emergng SEE capal markes. Ths concluson s smlar o he one proposed by Baumohl (0).e he happness of he consumers s mporan as when consumers feel less confden of he economy hey end no o be wllng o make major purchases such as houses and cars whch may deral he economc acvy. Addonally, fallng confdence s no favorable owards eques as s an ndcaon of declnng busness sales. Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes Table 8. Esmang resuls of GARCH models for he nfluence of he ndusral confdence ndcaor on he sock marke dynamcs Index SOFIX CROBEX ACSP MBI0 BET SBITOP BIST00 The mos approprae GARCH model PGARCH (,) - PGARCH (,)- (,)- (,)- (,)- (,)- (,)- ICI (prob) 6.5E-05 (0.988) (0.809) (0.8455) (0.3) (0.739) -.3E-05 (0.9967) (0.40) Noes for Table 8.:The daa of he ndusral confdence ndcaor s ncluded n he equaon of (p,q) or PGARCH(p,q) model. Source: Auhor s calculaons. When we add he ndusral confdence ndcaor (ICI) n he GARCH model equaon, he resuls are que dfferen none of he egh values of ICI s sascally sgnfcan a 5 %. Thus, here s no lnkage beween ndusral senmen and he marke dynamcs of he SEE capal markes. Acually, hese resuls are no unexpeced, n vew of he assumpon ha busness expecaons do no affec he movemen of he ndces. 46 Economc Alernaves, Issue, 07

11 4.3. Inflaon expecaons Table 9. Esmang resuls of GARCH models for he nfluence of he nflaon expecaons on he sock marke dynamcs Index The mos approprae GARCH model SOFIX PGARCH(,) - CROBEX ACSP MBI0 BET SBITOP BIST00 MONEX PGARCH(,)- (,)- (,)- (,)- (,)- (,)- (, )- InflExp (prob) (0.090) (0.044) (0.575) (0.0000) (0.395) (0.60) (0.005) (0.60) Noes for Table 9.:The daa of he nflaon expecaons s ncluded n he equaon of (p,q) or PGARCH(p,q) model. Source: Auhor s calculaons. The values of nflaon expecaons n he GARCH model equaon are presened n Table 9. In macroeconomc heory he nflaon expecaons (InflExp) have a sgnfcan role n he formulaon of he expecaons-augmened Phlps curve. In economcs, he nflaon expecaons affec he overall producon and hrough ndrecly nfluence fnancal marke dynamcs. Here we can make wo mporan remarks. Frsly, sascally sgnfcan values of InflExp are regsered for SEE ndces SOFIX ( ), CROBEX ( ), MBI0 ( ) and BIST00 ( ). Secondly, he absolue values of InflExp are n he range from (MBI0) o (SOFIX). Consequenly, nflaon expecaons nfluence on he capal marke dynamcs of four SEE ndces. Here we should noe ha he sascally sgnfcan values of nflaon expecaons are calculaed for wo developed fnancal markes Turkey and Croaa and wo developng markes Bulgara and Macedona. I s necessary o compare hese resuls wh he prevous resuls revealng sascally sgnfcance of he CCI for Bulgaran and Macedonan ndces. These conclusons are really remarkable because despe relavely llqud radng on he markes and ncomplee daa surveys, he publc expecaons can be used for predcon purposes. Noably, nflaon expecaons are conegraed wh he real nflaon and acually can be used o forecas n he mos of he examned counres. To sum up, daa for he nflaon expecaons have predcve power for he marke performance of he sock ndces, alhough relavely low values of InflExp (from o ). Here, we can look a he macroeconomc fundamenals n order o evaluae he money supply nfluence on he sock marke. Wha s more, money supply can have a negave mpac on asse prces by s relaonshp o unexpeced and fuure nflaon. Keynesan hypohess saes ha when money supply changes wll affec sock prces f alers he expecaons of fuure moneary polcy. For nsance, f he money supply ncrease, marke parcpans wll ancpae a conraconary moneary polcy n he fuure whch wll lead o less nvesmens and herefore ncreased neres raes. Thereby lowerng sock marke prces by a hgher dscoun rae and lower expecaons regardng fuure cash flows due o decreased economc acvy (Selln, 00). 47

12 5. Concluson The emergng capal markes n Banja Luka, Sarajevo (Bosna and Herzegovna), Bulgara, Greece, Serba, Macedona, Romana and he developed Croaan marke can be defned wh neffcency accordng o he EMH durng he sample perod. The ndces ACSP (developed Greek capal marke) and BIST00 (developed Turksh capal marke) are wh hgh values of her leverage coeffcens ndcang ha marke nformaon has large effec on he volaly. Only Monenegrn sock exchange s marke effcen due o he values of he coeffcen of perssence and leverage effec. All hngs consdered, s reasonable o assume ha SEE capal markes aren effcen n he conex of EMH. These resuls are conssen wh he fndngs of Ivanov and e al. (Ivanov, I., Lomev, B., Bogdanova, B., 0). They nvesgae he marke effcency of seven emergng Eas-European sock exchanges (Serba, Romana, Turkey, Croaa, Russa, Ukrane, and Bulgara) n respec of long-range dependence (LRD). The auhors esablsh ha for all of he examned ndces here s clearly an ndcaon for devaon from Random walk hypohess and hus he suded markes manfes neffcency. The consumer senmen nformaon has nfluence on he capal marke dynamcs of Bulgara, Macedona, Slovena, Romana, herefore on he prces of fnancal asses. Addonally, consumer expecaons have predcve capably for he performance of he emergng SEE capal markes. In fac, hese resuls are n agreemen wh resuls obaned by Gerunov (04). Gerunov (04) examnes wheher he sock marke ndces of welve key EU economes are conssen Relaonshp Beween Publc Expecaons аnd Fnancal Marke Dynamcs n Souh-Eas Europe Capal Markes wh he mplcaons of he Effcen Marke Hypohess (EMH) and f some publcly avalable nformaon can be usefully ulzed o forecas marke movemens. He fnds enough evdence ha he publc expecaons dsplay predcve power for fnancal ndex dynamcs n fully 6 (Germany, France,Poland, Bulgara, Hungary and Greece) ou of he sampled counres. On he conrary, here s no lnkage beween ndusral expecaons and he dynamcs of he SEE capal markes. Inflaon expecaons have mpac on he performance of four SEE ndces Turkey, Croaa, Bulgara and Macedona. Wha s more, he nflaon expecaons nformaon has predcve power for he marke dynamcs of he SEE sock exchanges. Our fndngs sugges ha he publc expecaons mpac he fnancal marke dynamcs n Bulgara. Hence, macroeconomc ndcaors are mporan as hey provde a ool for analyzng he curren and fuure sae of he Bulgaran economy. As he Bulgaran sock exchange s a concurren par of our economy, ndcaors are used n order o evaluae sock marke nvesmens. Imporanly, n Bulgaran emergng economy, he daly avalable source of nformaon for households s he developmen of he fnancal marke n Bulgara. Generally, households n developng markes can only follow he economc oulook hrough he wllngness o buy facor due o he fac ha he level of ncome s close o subssence. Consequenly, n he case of Bulgara, consumer confdence should be consdered as an economc ndcaor whch derves mos of s nformaon conen from pas and curren economc oulook. Ths s especally rue durng he fnancal crss of 008 when he fuure s unceran and rsky. 48 Economc Alernaves, Issue, 07

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