Political elections, abnormal returns and stock price volatility: the case of Greece

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1 Poliical elecions, abnormal reurns and sock price volailiy: he case of Greece AUTHORS ARTICLE INFO DOI JOURNAL FOUNDER Ahanasios Koulakiois Harry Papapanagos Nicholas Papasyriopoulos Ahanasios Koulakiois, Harry Papapanagos and Nicholas Papasyriopoulos (16). Poliical elecions, abnormal reurns and sock price volailiy: he case of Greece. Invesmen Managemen and Financial Innovaions, 13(1-1), doi:1.1511/imfi.13(1-1).16.3 hp://dx.doi.org/1.1511/imfi.13(1-1).16.3 "Invesmen Managemen and Financial Innovaions" LLC Consuling Publishing Company Business Perspecives NUMBER OF REFERENCES NUMBER OF FIGURES NUMBER OF TABLES The auhor(s) 18. This publicaion is an open access aricle. businessperspecives.org

2 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 Ahanasios Koulakiois (Greece), Harry Papapanagos (Greece), Nicholas Papasyriopoulos (Greece) Poliical elecions, abnormal reurns and sock price volailiy: he case of Greece Absrac The impac of he Greek poliical elecions on he reurn and volailiy of he Ahens Sock Exchange (ASE) is invesigaed using boh he sandard even sudy mehodology and various univariae GARCH models. The empirical resuls reveal posiive pre- and pos-elecion abnormal reurns, bu negaive on he day of he elecion. Srong evidence is also found ha suggess ha he elecion oucome significanly affecs he ASE reurn; however, he evidence is raher limied for he ASE volailiy. The empirical findings raise doubs abou he efficiency of he Greek sock marke and migh have imporan implicaions for invesors wih respec o decisions regarding enering and/or exiing he marke or invesmen sraegies around ime periods where poliical elecions are going o ake place. Keywords: poliical elecions, sock price volailiy, Ahens Sock Exchange, GARCH models. JEL Classificaion: C, G14, G15. Inroducion Greece is known as he birhplace of democracy and has a long hisory of poliical elecions. In recen years, afer he collapse of he miliary juna in 1974 and he resoraion of he parliamenary democracy, he poliical environmen in Greece is sable wih wo poliical paries dominaing he poliical life: he conservaive pary known as New Democracy (ND) and he socialis pary known as he Pan-Hellenic Socialis Movemen (PASOK). These wo poliical paries have succeeded each oher in he cabine for he las 3 years wih he socialis pary saying considerably longer in power han he conservaive pary; hough he laer is in power since March of 4 up o he wriing of his sudy. Alhough for mos of is hisory he Ahens Sock Exchange (ASE) was regarded as a developing sock marke, from he middle of 198s he ASE sared o develop noably. The driving forces behind his developmen were he Invesmen Services Direcive (EC, 1993) aiming a liberalizing he ASE and harmonizing i wih he oher European sock markes, he convergence of he Greek economy o he European requiremens, he sable poliical environmen and improvemens in he echnical infrasrucure. As a resul, capial inflows from boh domesic and foreign invesors increased and he ASE developed considerably in erms of marke capializaion, urnover and number of lised companies. During he examined period (1985-8), Greece experienced a raher large number of poliical elecions (i.e., 7 elecion bales) and herefore, i would be ineresing o examine Ahanasios Koulakiois, Harry Papapanagos, Nicholas Papasyriopoulos, 16. Ahanasios Koulakiois, Deparmen of Balkan, Slavic and Orienal Sudies, Universiy of Macedonia, Greece. Harry Papapanagos, Deparmen of Balkan, Slavic and Orienal Sudies, Universiy of Macedonia, Greece. Nicholas Papasyriopoulos, Deparmen of Balkan, Slavic and Orienal Sudies, Universiy of Macedonia, Greece. wheher hese poliical changes had a significan effec on he ASE reurn and volailiy. Our paper invesigaes he sock price index response around he elecion daes and he effecs of change in he ruling poliical pary in Greece on he reurn and risk in he ASE. In paricular, he radiional and very popular even sudy mehodology, described well by Dodd and Warner (1983) and Brown and Warner (1985), is adoped o examine he behavior of he ASE composie index daily reurn around he elecion daes during he period from January 1985 o February 8, while he AR(1)-GARCH, AR(1)- EGARCH and AR(1)-GJR-GARCH models are employed, as proposed by Lin and Wang (5), o examine he impac of he governmen change on he sock reurn and volailiy of he ASE. Our primary objecive is o observe wheher he risk underaken by invesors around he elecion daes is compensaed by higher reurns. Besides adding o he raher limied lieraure, he resuls of his sudy can also be of paricular imporance o invesors concerned wih decisions regarding he enry o and/or exi from he marke as well as changes of invesmen sraegies. The remainder of he paper is se ou as follows. Secion 1 briefly reviews he lieraure on he impac of poliical elecions on he sock marke, Secion describes he recen developmen in he ASE, Secion 3 oulines he daa and he mehodology and Secion 4 analyzes he empirical resuls. Final secion summarizes and concludes he paper. 1. Lieraure review One of he firs researchers who analyze he relaionship beween economics and poliics was Nordhaus (1975) who showed ha elecions induced significanly economic cycle in he US. I has long been argued ha major poliical evens such as elecions can have a significan impac on he sock marke. For example, Panzalis e al. () found 161

3 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 ha sock marke prices end o respond o new informaion regarding poliical decisions ha may affec a naion s fiscal and moneary policy. Oher sudies invesigaed he effecs of economic evens on presidenial voing and he impac of differen poliical srucures o various economic variables (see, for example, Aesoglou and Congleon, 198; and Burdekin, 1988). Brasiois (), for example, examined he inflaionary consequences of eleced poliical paries in Greece before and afer is commimen o he Single European Ac (SEA) 1 in 1986 and found ha inflaion plays a significan role in he poliical parisan cycle in Greece afer he inroducion of SEA. Anoher se of sudies examined he sock marke efficiency around poliical elecion daes. Gemmill (199), for example, found an exremely close relaionship beween polls and he FTSE 1 index. However, here was evidence of gross inefficiency in opions prices in he UK during he las week of he elecions period, implying a low probabiliy of a conservaive pary win, while he opinion polls showed he opposie. A number of sudies have also sudied he impac of poliical elecions on sock marke reurns (see, for example, Huang, 1985; and Foerser and Schmiz, 1997). In general, he resuls of hese sudies suppored he so-called presidenial elecion cycle hypohesis according o which he US sock marke offers higher reurn in years 3 and 4 han in years 1 and of a presidenial erm. In addiion, Panzalis e al. () invesigaed he sock marke performance around poliical elecions using daa from 33 developed and developing counries around he world. They found a posiive sock marke reacion in he wo week-period preceding elecion daes. This posiive abnormal reurn was sronger for elecions wih higher degree of uncerainy 3. Kim and Mei (1) found ha poliical developmens in Hong Kong had a significan impac on volailiy and reurn while Chan and Wei (1996) and Bilingmayer (1998) found evidence ha posiive poliical news posiively affec currency and equiy markes. More recenly, Siokis and Kapopoulos (7) examined wheher movemens in he ASE sock prices could be parially explained by he dynamics of he poliical environmen. Using an EGARCH-M 1 The Single European Ac can be considered as he firs formal aemp owards he economic and poliical convergence and inegraion of EU counry members. This is mainly because he firs and second year of he presidenial erm are considered o be more appropriae o inroduce unpopular changes such as ax increases. As business profis suffer he negaive effecs of hese policies, earnings shorfalls lead o negaive or low sock marke reurns. 3 Similar findings were repored in he lieraure for he case of he UK sock marke by Peel and Pope (1983). model and daily daa for he ASE composie index from January 1987 o June 4, hey found ha poliical changes have a significan impac on he condiional variance in he ASE and hey also presened evidence ha he behavior of he reurn is asymmerically affeced by pas innovaions. They also repored ha volailiy increases more in he pre-elecion period and when he righ-wing pary is in power. Bialkowski e al. (8) invesigaed a sample of 7 OECD counries o es wheher naional elecions bring abou higher sock marke volailiy. Greece s elecion bale of March 4 was also among he presidenial and parliamenary elecions ha were invesigaed in heir sudy. The auhors provided evidence ha sock marke volailiy was subsanially higher (abou double) han normal around elecion daes, a finding ha was inerpreed as an elemen of surprise on he par of invesors. According o Bialkowski e al. (8), several facors, such as a narrow margin of vicory, lack of compulsory voing laws, change in he poliical orienaion of he governmen, or he failure o form a governmen wih parliamenary majoriy significanly conribued o he magniude of he elecion shock. Finally, i was found ha sock markes wih shor rading hisory had sronger marke reacion around elecion daes.. The Ahens Sock Exchange Unil he lae 198s he ASE has araced lile aenion from boh local and inernaional invesors mainly because of is domesic characer, he inefficien and incomplee regulaion as well as he lack of echnical infrasrucure. However, a series of changes and innovaions, sared o ake place in he lae 198s, led o considerable growh in erms of number of lised companies, marke capializaion and shares urnover. In paricular, in 1985 he capial and profi requiremens as well as he duies and obligaions for companies lised in he ASE were inroduced, while in 1986 all resricions regarding he liquidaion of invesmens and repariaion of profis from non-greek residens were abolished. In 1991, he Capial Marke Commission was esablished as a supervisory auhoriy and he legal framework regarding he regulaion and operaion of invesmen companies and muual funds were inroduced. In 199, elecronic rading was inroduced and he legal framework regarding inside rading was esablished. Alongside hese changes, he commimen of Greece o mee he convergence economic crieria in order o join he European Moneary Union creaed a posiive senimen o invesors and in he lae of 199s he ASE sared o rally. The ASE composie index rose from 868 in 1994 o 5,535 in 1999 while 16

4 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 he annual reurn offered o invesors was 85% in 1998 and 1% in The influx of inernaional funds during ha period was so remarkable ha conribued o he rise of he ASE composie index in record levels reaching 6,355 on Ocober 17, The shares urnover also increased significanly from 3,73 millions in 1994 o 173, millions in Equiy issues also rose from 77 millions in 1994 o 1, millions in 1999 and new lisings wen up from 1 in 1997 o 37 in 1999 and 53 in. The flow of inernaional funds 43 in he Greek capial marke was phenomenal giving a sense of euphoria o local invesors. However, he rally came o an end when he inernaional insiuional invesors found he marke overvalued and decided ha i was ime o sar realizing profis. The evens of Sepember 11 h 1 creaed a negaive senimen in he global markes and ha had a significan effec on he ASE. The ASE composie index plummeed from 3,388 in o 1,748 in wih he annual reurn offered o be -38% in, -3% in 1 and -3% in. Shares urnover decreased from 11, millions in o 5, millions in. Equiy issues also decreased from 9,87 millions in o 1,934 millions in. By he end of March of 3, he majoriy of Greek socks had los more han half of heir values and in some cases, more han 9% of heir values. However, by he end of March of 3 and unil he mid of 7, he ASE composie index experienced a gradual up rend following ha of major developed capial markes such as he UK and he US markes. The subprime morgage loans crisis in he US in he mid of 7 was he firs sign ha global capial markes could no susain heir posiive momenum and he ASE could no be he excepion. In an effor o proec invesors ineres, in November of 7 he Capial Marke Commission adoped he Markes in Financial Insrumens Direcive (MiFID) which provides a harmonised regulaory regime for invesmen services across he 3 member saes of he European Economic Area (he 7 counry members of he European Union plus Iceland, Norway and Liechensein) and aims o increase compeiion and consumer proecion in invesmen services. More recenly, he ASE creaed anoher marke which is called alernaive marke ha is adressed for small companies in erms of marke capializaion and profis. Finally, exchange raded funds (ETF) were also recenly inroduced in he ASE. 3. Daa and mehodology 3.1. Daa descripion. Daily reurns of he ASE composie index were colleced from he 4 According o daily financial press, he flow of inernaional funds exceeded 1 billion Euros during he examined period. Disseminaion Informaion Deparmen of he ASE from January 1985 o February 8. During his period, 8 poliical elecions ook place in Greece; 18/6/89, 5/11/89, 8/4/9, 1/1/93, /9/96, 9/4/, 7/3/4 and 16/9/7. However, he wo elecion daes 5/11/89 and 8/4/9 were excluded from he sample as hey were runner up elecions of ha of 18/6/89 where he winning poliical pary could no form a majoriy governmen. In addiion, since elecions in Greece ake place on Sundays, we define he Elecion Day (day ) as he firs rading day afer he elecion. I should be poined ou ha Greece has mandaory voing laws regarding parliamenary elecions and voers paricipaion exceeds 7%. Table 1 repors descripive saisics of he daily reurns of he ASE composie index. The daily mean reurn was.8% and he daily sandard deviaion was 1.74%. An examinaion of Table 1 also reveals ha he hypohesis ha daily reurns follow a normal disribuion can be rejeced due o he large value of kurosis (14.15); also confirmed by he Kolmogorov-Smirnov es saisic. In addiion, he Ljung-Box (LB) es saisic rejecs he hypohesis ha all auocorrelaions up o 1 lags are zero for boh he reurns and squared reurns which jusifies he use of ARCH-ype models for he variance. Table 1. Descripive saisics of he ASE composie index daily reurns Mean (%) ().8 Sandard deviaion (%) () 1.74 Skewness (S).31* Kurosis (K) 14.15* Kolmogorov-Smirnov es saisic.95* LB (1) 8.74* LB (1) * Noe: This able conains descripive saisics for he ASE daily reurns over he period from January 1985 o February 8. * denoes saisical significance a he 5% significance level.,, S and are he mean, sandard deviaion, skewness and kurosis, respecively. The Kolmogorov-Smirnov es saisic examines he hypohesis ha he ASE reurns are normally disribued (he criical value a he 5% level is 1.36/ n, where n is he sample size). LB (1) and LB (1) are he 1 lags Ljung-Box saisics calculaed for he reurns and he squared reurns, respecively. The LB saisic is disribued as wih n degrees of freedom; where n is he number of lags being esed. However, even hough he LB saisic provides evidence for second-momen ime dependencies, i canno be used o es he asymmeric reurn volailiy of bad and good news because i is a saisical es which accouns for only he amoun of serial correlaion in he reurn series. Therefore, o invesigae wheher he shocks on he ASE reurns have an asymmeric effec on volailiy, he diagnosics proposed by Engle and Ng (1993) are used. These include (i) he sign bias es, (ii) negaive size bias es, (iii) posiive size bias es, 163

5 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 and (iv) join es. The firs es examines he impac of posiive and negaive innovaions on volailiy no prediced by he Engle and Ng (1993) model. In paricular, he squared residuals of he iniial AR(1) model are regressed agains a consan and a dummy S ha akes he value of one when -1 is negaive and zero oherwise. The impac of large and small negaive innovaions on volailiy is capured by he negaive size bias es. I is based on he regression of he sandardized residuals agains a consan and S -1. The calculaed -saisic for S 1 is used o es for he biases. The posiive sign bias es examines possible biases of he esimaed resuls associaed wih large and small posiive innovaions. The sandardized filered residuals are regressed agains a consan and (1 S ) 1. Again, he -saisic for (1 S ) 1 is used o es for he possible biases. Finally, he join es uses he F-es based on a regression ha included all hree variables, i.e. S, S -1 and (1 S ) 1. The calculaed -saisics as well as he F-saisic of hese regressions are repored in Table. Table. Volailiy specificaion ess for filered reurns Sign bias (-es) -.57 Negaive size bias (-es) -.61* Posiive size bias (-es).61* Join es F (3,576) 16.53* ARCH (4) 5.11* ADF (1) * PP(4) * Noe: This able repors he ess proposed by Engle and Ng (1993). These ess invesigae wheher he reurn shocks on ASE have an asymmeric effec on volailiy and are specified as follows: Sign bias: z bs e Negaive sign bias: z bs 1 e Posiive sign bias: z b( 1 S ) 1 e Join es: z b S b S b ( 1 S ) e, 1 1 where S is a dummy variable ha akes he value of one if -1 is negaive and zero oherwise. All -saisics refer o he coefficien b in he firs hree regressions, while he join es F (3, 517) refers o he fourh regression. The normalized residuals z = i / i are based on an AR (1) model applied o he daily reurns. ARCH denoes he Lagrange muliplier es of Engle (198) and he criical value is 7.8 a he 5% significance level. ADF denoes he Augmened Dickey Fuller es saisic, PP denoed he Phillips-Perron es saisic and he lag inerval is deermined by minimizing he Akaike (AIC) and Schwarz Bayesian (SBC) crieria values. The funcions of he AIC and SBC crieria are: AIC (k) = T ln + k and SBC(k) = T ln + k*lnt, where k denoes he lagged period, T denoes he number of sample, and 3 1 denoes he lagged k periods of T.. i1 The criical value for he ADF es is equal o * Denoes saisical significance a he 5% significance level. Boh he ADF and PP ess rejec he null hypohesis ha he ASE reurns have a uni roo a any convenional significance level. The resuls indicaed saisically significan negaive size bias, saisically significan posiive size bias and a significan join F-es, suggesing he presence of asymmeries in he condiional variance. In addiion, volailiy was found o exhibi condiional heeroskedasiciy. Boh he Augmened Dickey Fuller (ADF) and Phillips-Perron (PP) ess rejec he null hypohesis ha here is a uni roo in he ASE reurns 54 a any convenional significance level (see Table ). The uncondiional kurosis of he ASE daily reurns repored in Table 3 was In addiion, he residuals had zero mean and uniy variance. The esimaed LB saisics for 5 and 1 lags rejecs he hypohesis of nonlinear dependence in he normalized residuals and squared normalized residuals. This means ha an ARCH ype model could be used o describe he behavior of he normalized residuals and he behavior of he squared normalized residuals since he auocorrelaions of 5 and 1 lags for he normalized and he squared normalized residuals were saisically significan. Overall, he evidence suppors he inclusion of condiional heeroskedasic and asymmeric componens in he volailiy equaion specificaion in order o model adequaely he ASE volailiy. Table 3. Diagnosic ess for he residuals Kurosis (K) 13.34* E(z) - -8 E(z ).91 LB(5) 13.36* LB(1) 35.13* LB (5) * LB (1) 1843.* Noe: * Denoes saisical significance a he 5% significance level. z is he model normalized residual. LB(.) and LB (.) are he Ljung-Box es saisics for he z and z, using 5 and 1 lags, respecively. The residuals came from an AR(1) model. 3.. Mehodology The mean-adjused reurn model. The classical even sudy mehodology described by Dodd and Warner (1983) and Brown and Warner (1985) was employed o esimae he ASE index reurn reacion around he day of an elecion. We define as day zero ( = ) he firs rading day following he elecion dae. Using he mean-adjused reurn model, abnormal reurns 6 (AR ) 1 of he ASE composie index around he firs 5 Siokis and Kapopoulos (7) found ha a uni roo exiss in he level of he ASE index. However, hey used sock prices insead of log reurns. This means ha if here is no a uni roo in he reurn series of he ASE we do no need o ake ino accoun second logarihmic differeniaion of he series. 6 The ASE logarihmic reurns were calculaed according o he formula R lnp P 1, where P is he index price on day and P -1 is he index price on day

6 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 pos-elecion day are calculaed as he difference beween he ex-pos reurn R and he normal reurn R : AR R R, (1) where he normal reurn for he ASE composie index ( R ) is he mean hisorical reurn over a 5- days period prior o he even period, ha is, from day -6 o day -11. The even period is a 1-day window around he firs pos-elecion day ( =); ha is, from = -11 o = +11. The saisical significance of he mean abnormal reurn was esed using he -saisic, while he saisical significance of he median abnormal reurn was esed using he Wilcoxon signed rank es ARCH-ype modeling approach. A number of sudies have used he so-called GARCH, E-GARCH models of Nelson (1991) and he GJR-GARCH model of Glosen, Jagannahan, and Runkle (1993) (see, for example, Bollerslev, 1986; Friedman and Sanddorf-Kohle, ; and Siokis and Kapopoulos, 7). The firs model (GARCH) is symmeric which means ha posiive and negaive innovaions on he condiional volailiy have he same impac wih regards o he arrival of news; however, his does no hold for he case of he wo asymmeric models. Having assessed he abiliy of all hree models o describe he daily ASE reurns volailiy, he effecs of ransiion of he ruling pary on he sock marke behavior is also examined. Dummies are also included in he hree afore-menioned models o deec he effec of ransiion of he ruling pary on sock price reurns and volailiy as follows: R 1D1D 3R 1, () where 1 ~ T (, h ). D 1 denoes he dummy variable ha akes he value of 1 for he ransiion of ruling pary and oherwise. The second dummy variable D conrols for he sock marke crash of Ocober 1987 where here was a large increase in volailiy 8. 7 Therefore, he sample period is broken ino he pre-1987 and pos-1987 period. In paricular, dummy D equals 1 for he pos-1987 period and for he pre-1987 period. The symmeric response o shocks is aken from Bollerslev s (1986) GARCH model: 7 The Wilcoxon signed rank es, also known as he Wilcoxon mached pairs es, is a non-parameric es used o es he median difference in paired daa. This es is he non-parameric equivalen of he paired - es. The Wilcoxon signed rank procedure assumes ha he sample is randomly aken from a populaion which has a symmeric probabiliy disribuion. The symmeric assumpion does no assume normaliy; i simply assumes ha here is roughly he same number of values above and below he median. 8 We conrol for he impac of Ocober 1987 crash because i is known ha i increases volailiy (Aggarwal, Inclan and Leal, 1999; and Nich, ). h, 1D1 D 1h 1 1 (3) he parameer resricions, >, 1, and 1 + < 1, ensure ha he sochasic process ( ) is well-defined (i.e., h > ) and he covariance is saionary wih, E( ) =, Var() = h and cov(, s ) =. To allow for asymmeric volailiy effecs he E- GARCH and he GJR-GARCH models are also considered. The E-GARCH asymmeric volailiy model is given by: ln h D D lnh [ u E u u ], (4) where u / h. The news -j impac on condiional volailiy ln(h ). The model capures an asymmeric response because: ln h/ ( 1), when, and 1-1 ln h/ ( 1), when, 1-1 volailiy is minimized in he absence of news, -1 =. The GJR-GARCH asymmeric volailiy model is described by: h D D h S (5) , 1 where S 1 1 if if e1 1 and he process is well-defined when p, q,, i1,,3,..., p, 1, j 1,,3,..., q. The maximum likelihood (ML) esimaion mehod, as i is very common, is used o esimae he parameers of he mean and he ime-varying condiional variance-covariance equaions The empirical resuls 4.1. The sock marke reacion around six elecion daes. Table 4 repors he abnormal reurns (ARs) for he 6 elecion daes for he even period which sared 1 days before he elecion dae ( = -1) and ended 1 days afer he elecion dae ( = +1). I can be noiced ha he average AR is posiive on day -1 and equal o 1.4% which is saisically significan a he 1% significance level, whereas he median AR is.49% and saisically significan a he 5% significance level. On he firs rading day afer he elecion dae (day ), he ASE reacs negaively having a mean (median) abnormal 9 The BHHH algorihm proposed by Bernd e al. (1974) was used o obain he maximum likelihood esimaes of he parameers. 165

7 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 reurn equal o -1.65% (-.8%). The sign of he abnormal reurn becomes posiive on days 1 and, wihou, however, being saisically significan (a mean equal o.46% and.9% on days +1 and +, respecively). This resul can be aribued o he fac ha he elecion resul is officially announced a he end of he following working day (Monday in our case) and, herefore, he sock marke incorporaes ha informaion one day laer. Moreover, he negaive marke reacion on day can be also aribued o he oucome of he elecions which leads o he formaion of a governmen wih marginal MP majoriy 1,9signaling o he marke ha he winning pary is prone o populis pressures by labor unions and oher social forces. On he oher hand, he posiive reacion of he ASE before he Elecion Day can be aribued o he formaion of invesors expecaions ha he new governmen will fulfill is pre-elecoral promises and a new era of economic prosperiy will begin. These resuls are in line wih hose of Panzalis e al. (), who employed a sample of boh developed and developing counries and found posiive marke reacion prior o he elecion daes and negaive marke reacion on he elecion dae, even hough hey used weekly daa insead of daily ones. As far as he possible occurrence of he day-of-he-week effec 111 in he ASE, i should be noiced ha here is no consensus. Alexakis and Xanhakis (1995) found significan negaive reurns on Tuesdays and posiive reurns on he oher days of he week for he period from January 1985 o February Cous e al. () found significan posiive reurns on Fridays and insignifican reurns on he oher days of he week for he period from Ocober 1986 o Augus Mills e al. () found significan posiive reurns on Fridays and negaive reurns on Wednesdays for he period from Ocober 1986 o April Al-Khazali e al. (8), using sochasic dominance analysis, found evidence of he highes reurns occurring on Fridays and he lowes on Tuesdays for he period from January 1985 o December 4. Finally, Tsangarakis (8) revealed ha he day-of-he-week effec is no a dominan phenomenon of he Greek sock marke. Therefore, we can argue ha our finding of negaive sock reurns on he Elecion Day which is always on Monday canno be aribued o he dayof-he-week effec. 1 Three ou of six elecions resuled in he formaion of a governmen wih marginal majoriy. 11 According o he day-of-he-week effec or Monday effec or weekend effec, on average, sock reurns are higher on Fridays, ha is, he las rading day of he week, and negaive on Mondays which is he firs rading day of he week. Table 4. ASE reurn behavior over a period of 1 days around 6 elecion daes Day Mean % p-value (-es) Median % p-value (Wilcoxon signed rank es) * ** *.6.49** * Noe: The mean abnormal reurns (ARs) of he ASE index is he difference beween he ex-pos reurn R and he normal reurn R which is he mean hisorical reurn over a 5-day period prior o he even period, ha is, from day -6 o day -11. The Wilcoxon signed rank es is a non-parameric es used o es he median difference in paired daa. ** and * indicae saisical significance a he 5% and 1% significance levels, respecively. 4.. The sock marke reurns and volailiy around elecion daes. Tables 5 o 7 repor he coefficiens of ransiion of ruling pary dummies, 1 (-3 - for he AR(1)-GARCH model, - - for he AR(1)-E-GARCH model and for he AR(1)- GJR-GARCH model) and 1 (5-4 for he AR(1)- GARCH model, 1.19 for he AR(1)-E-GARCH model and 51-4 for he AR(1)-GJR-GARCH model). These esimaes are saisically significan a he 5% significan level for all he models when we consider he sock price reurns, bu only for he AR(1)-E-GARCH model when we consider volailiy. Therefore, he ransiion of ruling pary in Greece has an imporan impac on he ASE reurn, according o he hree GARCH models, and an imporan impac on volailiy, according o he AR(1)-E-GARCH model. Therefore, he above finding does no hold for he AR(1)-GARCH, and AR(1)-GJR-GARCH models when we consider volailiy, regardless if he model capures symmeric or asymmeric news. This finding is in agreemen wih Lin and Wang (5) who also found no significan relaionship beween he dummy of ransiion of ruling pary and he sock 166

8 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 reurns and volailiy of he Nikkei 5 sock index. This was inerpreed as ha he poliical elecions and environmen when a prime miniser succeeds does no influence he Japanese sock marke behavior. The values of he dummy variable ha conrols for he 1987 sock marke crash (-66-4 for he AR(1)- GARCH model, 51-4 for he AR(1)-E-GARCH model and for he AR(1)-GJR-GARCH model) and (55-6 for he AR(1)-GARCH model, 67 - for he AR(1)-E-GARCH model and 55-6 for he AR(1)- GJR-GARCH model) indicaes ha he ASE reurn is negaive in mos of he cases and saisically significan, while he ASE volailiy is significanly posiive a he 5% significance level. Unsurprisingly, he ASE index reurn volailiy,, is found o be significan a he 1% level and posiively relaed o he 1987 sock marke crash (similar findings were repored in he lieraure by Schwer, 199; Engle and Musafa, 199; and Lin and Wang, 5). The hree models also capure he negaive sign of he dummy variable ha conrols for he 1987 sock marke crash for he ASE reurns; wih he resuls being saisically significan. These resuls are in agreemen wih he findings of Lin and Wang (5) who found a saisically significan impac of he 1987 crash on sock price reurns. This migh be aribued o he big impac of he 1987 sock marke crash. The values of he log-likelihood funcion (45.59, 47.3, and for he AR(1)-GARCH, AR(1)-E-GARCH and AR(1)-GJR-GARCH models, respecively) do no indicae grea difference in he amoun of volailiy and noise examined by he hree models. Indeed, he amouns of pas volailiy are equal o.75,.94 and.76 for he AR(1)- GARCH, AR(1)-E-GARCH and AR(1)-GJR- GARCH models, respecively. In addiion, he amoun of pas noise for he AR(1)-GARCH and for he AR(1)-GJR-GARCH model is.4 and.3, respecively. There is no analogous coefficien for he case of E-GARCH model as his model capures he impac of bad and good news arising from shocks wih differen signs. In paricular, if -1 < (bad news) hen he impac of bad news on volailiy 111 is equal o -.41 [.41 (-.18-1)] and if -1 (good news) hen he impac of good news on volailiy 131 is equal o.4 [.41 (-.18+1)]. The analogous coefficien of he GJR-GARCH model for he case of bad news is equal o.1. This 1 The formula used is ( 1). 13 The formula used is ( + 1). coefficien indicaes ha he impac of bad news on volailiy is smaller in magniude in he GJR- GARCH model compared o he E-GARCH model. The difference is due o he fac ha he value of is large and saisically significan a he 1% significance level in he E-GARCH model. Thus, he impac of noise on volailiy has a bigger shorerm effec wih he E-GARCH model compared o he saisically insignifican impac of bad news on volailiy in he GJR-GARCH model. Table 5. Empirical resuls for he AR(1)-GARCH (1,1) model R D D h D D R h D1 denoes he dummy of he change of ruling pary and D denoes he dummy of 1987 crash Variable Reurn Variable Volailiy 1-3 (5.8)*** 9-6 (7.5)*** (-3.7)*** (1.4) (-.44)*** 55-6 (8.41)*** 3.(4.85)*** Coefficien Esimaion 1.75(16.88)***.4 (5.7)*** Log-likelihood Noes: Numbers in parenheses are -saisics. ***, ** and * indicae saisical significance a he 1%, 5% and 1% significance levels, respecively. This able shows he impac of he change of ruling pary, he 1987 sock marke crash and he previous day s reurn on nex day s reurns. The able also shows he impac of he above wo menioned dummy variables plus he previous day s volailiy and noise on he nex day s volailiy. The wo equaions which comprise an AR(1)-GARCH model have wo dummy variables which explain he impac of he change of ruling pary and he 1987 sock marke crash on volailiy., 1, and 3, denoe he coefficiens for he consan, he dummy for he change of ruling pary, he dummy for he 1987 sock marke crash and he previous day s reurns, respecively., 1,, 1, are he coefficiens for he consan, he dummy for he change of ruling pary, he dummy for he 1987 sock marke crash, he previous day s volailiy and he previous day s noise, respecively. Table 6. Empirical resuls for he AR (1)-E-GARCH (1,1) model R D D 1 1 3R 1 ln h D D ln h [ u E u u ] D1 denoes he dummy of he change of ruling pary and D denoes he dummy of 1987 crash Variable Reurn Variable Volailiy 96-4 (5.78)*** -.47(-15.67)*** (-.17** (.49)** 51-4 (-.4)** 67 - (6.61)*** 3.5(45.)*** Coefficien Esimaion 1.94(38.5)*** 167

9 Invesmen Managemen and Financial Innovaions, Volume 13, Issue 1, 16 Table 6 (con.). Empirical resuls for he AR (1)-E-GARCH (1,1) model Variable Reurn Variable Volailiy.41(35.15)*** (-.11) Log-likelihood 47.3 Noes: Numbers in parenheses are -saisics. ***, ** and * indicae saisical significance a he 1%, 5% and 1% significance levels, respecively. This able shows he impac of he change of ruling pary, he 1987 sock marke crash and he previous day s reurns on nex day s reurns. The able also shows he impac of he above wo menioned dummy variables plus he previous day s volailiy and posiive or negaive noise on he nex day s volailiy. The wo equaions comprise an E- GARCH model which has wo dummy variables which explain he impac of he change of ruling pary and he 1987 sock marke crash on volailiy., 1, and 3 are he coefficiens for he consan, dummy for he change of ruling pary, dummy for he 1987 sock marke crash and he previous day s reurns of sock, respecively., 1,, 1, and are he coefficiens for he consan, he dummy for he change of ruling pary, he dummy for he 1987 sock marke crash, he coefficien of he previous day s logarihmic volailiy, he coefficien of he impac of large innovaions on condiional volailiy suppose ha =, and he coefficien of posiive and negaive innovaions, respecively. Table 7. Empirical resuls for he AR (1)-GJR GARCH (1,1) model R D D R E( ) R i if where S { if h D D h S D1 denoes he dummy of he change of ruling pary and D denoes he dummy of 1987 crash Variable Reurn Volailiy 99-4 (4.83)*** 9-6 (7.8)*** (-3.3)*** (1.43) (-.48)** 55-6 (8.8)*** 3.(4.67)*** Coefficien Esimaion 1.76(16.43)***.3(1.6)*** (1.3) Log-likelihood Noes: Numbers in parenheses are -saisic. ***, ** and * indicae saisical significance a he 1%, 5% and 1% significance levels, respecively. This able shows he impac of he change of ruling pary, he 1987 sock marke crash and he previous day s reurns on nex day s reurns. The able also shows he impac of he above wo menioned dummy variables References plus he previous day s volailiy and negaive noise on he nex day s volailiy. The wo equaions comprise a GJR-GARCH model which has wo dummy variables which explain he impac of he change of ruling pary and he 1987 sock marke crash on volailiy., 1,, and b 1 are he coefficiens for he consan, dummy for he change of ruling pary, dummy for he 1987 sock marke crash and he previous day s reurns of sock, respecively., 1,, 1, and 3 are he coefficiens for he consan, he dummy for he change of ruling pary, he dummy for he 1987 sock marke crash, he coefficien of he previous day s volailiy, he coefficien of previous day s noise and he coefficien of he previous day s negaive noise, respecively. Summary and conclusion This sudy examines he impac of he Greek poliical elecions over he period from January 1985 o February 8 on he ASE reurns around he elecion daes by employing he sandard even sudy mehodology and ARCH-ype models. The empirical resuls indicae a posiive sock marke reacion on he las working day prior o elecion dae and negaive on he firs pos-elecion day. In addiion, he impac of elecions on he ASE reurn is invesigaed and i is found ha his is significanly affeced by he ransiion of he ruling pary from all he GARCH models while volailiy affeced only from he AR(1)-EGARCH model. The impac of he Ocober 1987 sock markes crash on he ASE reurn (volailiy) is found o be negaive (posiive) and saisically significan a he 5% significance level (saisically significan a he 5% significance level). The resuls of his paper migh have imporan implicaions for invesors wih an ineres in he Greek sock marke. In paricular, hey can affec decisions regarding he enry or exi of he ASE and he change of invesmen sraegies. In spie of he elecions resuls, here is an abnormal posiive reacion before he day of he elecions which is followed by a negaive abnormal reurn on he firs pos-elecion day and a reverse hereafer. This resul raises doubs for he efficiency of he Greek sock marke since i appears ha he ASE needs some ime o incorporae he elecion news. Furhermore, he rising volailiy during he elecion daes and he associaed negaive reurns reveal ha invesors bear elecion-induced risk, however, wihou being compensaed wih a premium. Addiionally, he 1987 sock marke crash is also found o have a significan impac on he ASE sock price reurns and volailiy. This resul implies ha he Greek sock marke is vulnerable o global economic crises as much as he oher developed capial markes. 1. Aggarwal, C., Inclan, C., and Leal, R. (1999). Volailiy in emerging sock markes, Journal of Financial and Quaniaive Analysis, 34, pp Alexakis, P. and Xanhakis, M. (1995). Day of he week effec on he Greek sock marke, Applied Financial Economics, 5, pp Al-Khazali, O., Koumanakos, E. And Pyun, C.S. (8). Calendar anomaly in he Greek sock marke: Sochasic dominance analysis, Inernaional Review of Financial Analysis, 17, pp

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