THE EFFECTS OF INTERNATIONAL ACCOUNTING STANDARDS ON STOCK MARKET VOLATILITY: THE CASE OF GREECE

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 61 THE EFFECTS OF INTERNATIONAL ACCOUNTING STANDARDS ON STOCK MARKET VOLATILITY: THE CASE OF GREECE Chrisos Floros * Absrac The adopion of Inernaional Accouning Sandards (IAS) by he European Union (which sared in 005) is one of he bigges evens in he hisory of financial accouning. This paper invesigaes he effecs of adoping IAS on Greek sock marke volailiy. We consider daily daa (covering he period 003-005) from four major indices of he Ahens Sock Exchange (ASE): he General ASE index, FTSE/ASE-0, FTSE/ASE Mid 40 and FTSE/ASE Small Cap 80. We find ha he inroducion of IAS has a negaive bu no significan effec on Greek sock marke volailiy. This is confirmed by esimaion of hree differen ypes of GARCH specificaions. In addiion, he uncondiional variance indicaes lower marke volailiy afer he inroducion of IAS in Greece for all indices. These findings are helpful o financial managers dealing wih Greek sock indices. Key words: IAS, ASE, GARCH, Volailiy. JEL Classificaion: G14, M40. I. Inroducion From 005 all companies, ha are lised on a European regulaed Sock Exchange, mus prepare heir consolidaed financial saemens based upon Inernaional Financial Reporing Sandards (IFRS). They will no longer be able o produce accouns based upon naional GAAP. The main reason for his is ha EU wans o develop a single capial marke. So, one elemen of his is o have a common language (i.e. accouning sandards) for he financial informaion provided o ha single marke; wha is called inernaional accouning sandards (IAS) 1. The main requiremen o adop IAS/IFRS applies only o hose companies ha are acive direc paricipans in he capial marke. In simple words, hose ha have securiies ha are publicly raded on recognised European sock markes. Therefore, any lised company in he EU ha mees he above definiion mus prepare consolidaed financial saemens using IAS/IFRS for accouning periods commencing on afer 1 January 005. The Inernaional Accouning Sandards Board (IASB) has proposed 41 sandards in order o converge he accouning pracices among he counries wihin he EU. The main purpose of he sandards is o upgrade he qualiy of financial saemens and, of course, increase he degree of comparabiliy. Some of he poenial benefis o a company are: Beer informaion for sraegic decision-making and enhanced risk managemen analysis Sreamlined reporing sysems and quicker publicaion of resuls a he period end Redesigned processes o capure exernal and inernal daa as well as regulaory requiremens Greaer confidence in reporing daa on fuure prospecs and an improved repuaion wih invesors and analyss This paper examines he effecs of IAS on Greek sock marke volailiy. Volailiy is one of he mos imporan conceps in finance. I can be measured as sandard deviaion or variance of series, and is ofen used as a crude measure of he oal risk of financial asses. * Universiy of Porsmouh, UK. 1 The disincion beween IFRS and IAS is ha all exising sandards are called IAS, while all fuure (new) sandards will be called IFRS. Chrisos Floros, 007.

6 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 We consider daily daa from four major indices of he Ahens Sock Exchange (ASE). The main objecive of his research paper is o idenify any (posiive/negaive) effec of IAS using General Auoregressive Condiional Heeroskedasic (GARCH) volailiy models. Our findings are very imporan since no previous work has examined he effec of IAS on he Greek sock indices of he ASE. The remainder of he paper is as follows: In secion he lieraure review is presened. In secion 3 he mehodology and daa employed are presened. Also, in secion 4, he resuls from he empirical invesigaion are repored. In he final secion (secion 5) summary and conclusions are drawn. II. Lieraure Review Marke observers, researchers and regulaors argue ha financial saemens prepared under he shareholder or invesor model, such as IAS, provide beer informaion han financial saemens prepared under he sakeholder model (naional GAAP). According o Schipper (005), he EU adopion of IFRS in 005 offers some elemens of research designs. The EU offers considerable differences in financial reporing incenives. Firsly, Taylor (1987) examines he raionale behind he Inernaional Accouning Sandards Commiee (IASC). The paper represens an aemp o explain why we do have an organizaion such as he IASC. He repors ha ha raionale is likely o have significanly greaer explanaory power in respec of he oupu produced by he IASC han hose radiionally presened. Flower (1998) analyses he implicaions of he EUs proposal o permi large mulinaional corporaions o presen heir consolidaed accouns in accordance wih he IAS of he IASC. He concludes ha i is improbable ha he American SEC will accep he IAS for lising purposes on Wall Sree. El-Gazzar e al. (1999) examine he underlying moivaions and characerisics of firms complying wih IAS. Their resuls indicae ha he magniude of a firm s foreign operaions, is financing policy, membership of cerain geographical and rade blocks in he EU, and muliple lising of foreign sock exchanges are significanly associaed wih mulinaionals compliance wih IAS. Eccher and Healy (000) invesigae he usefulness of IAS in a ransiional economy, he People s Republic of China (PRC). They conclude ha informaion produced using IAS is no more useful han ha prepared using Chinese sandards. For socks ha can only be owned by inernaional invesors, IAS and PRC earnings and accruals have a similar associaion wih annual sock reurns, while for socks ha can be owned only by domesic invesors, PRC earnings have a higher relaion wih annual sock reurns han IAS earnings. Hung and Subramanyam (004) explain he effecs of adoping IAS on financial saemens and heir value relevance for a sample of German firms during 1998-00. They compare accouning numbers repored under German rules (HGB) wih hose under IAS. They find ha oal asses and book value of equiy, as well as variabiliy of book value and ne income, are significanly higher under IAS han HGB. Also, book value (ne income) plays a greaer (lesser) valuaion role under IAS han under HGB. III. Mehodology and Daa Empirical sudies (Harris, 1989; Lockwood and Lin, 1990) analyse wheher here is a posiive/negaive effec on sock marke volailiy (condiional variance) using he sandard GARCH (1,1) model or he GJR model (developed by Glosen, Jagannahan and Runkle in 1993) which ess for he presence of asymmeries. Harris (1989) repors ha he volailiy of S&P 500 socks increased, relaive o he volailiy of socks. Lockwood and Linn (1990) find ha sock marke volailiy has increased afer he sock index fuures rading. Engle and Ng (1993) define he news impac curve which measures how new informaion is incorporaed ino volailiy esimaes. New diagnosic ess are presened which emphasize he asymmery of he volailiy response o news. Their resuls sugges ha he GJR model is he bes parameric model, while Exponenial GARCH (EGARCH) can capure mos of he asymmery. Here, o analyse he effec of IAS on sock marke volailiy of he ASE, a varian of he GARCH models is employed.

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 63 Financial research shows much evidence ha reurns characerized by lepokurosis (i.e. if he kurosis exceeds 3, he disribuion is peaked or lepokuric relaive o he normal), skewness (i.e. a measure of asymmery of he disribuion of he series around is mean) and volailiy clusering (i.e. large changes in prices end o be followed by large changes, of eiher sign, and small changes end o be followed by small changes). A usual way o capure he above sylised facs is o model he condiional variance as a (G)ARCH process. Firs, Engle (198) proposes an ARCH model in order o capure for modelling he ime-variance. He inroduces he ARCH (p) ime series models for modelling he ime-varying volailiy clusering phenomenon. Then, Bollerslev (1986) exends ARCH model including pas variances as well as pas forecas errors. This model is referred o as GARCH (p,q) model. The GARCH (p,q) model capures he endency in financial daa for volailiy clusering, and also, i incorporaes heeroskedasiciy ino he esimaion procedure. In his model, posiive and negaive pas values have a symmeric effec on he condiional variance. The mos parsimonious represenaion is GARCH (1,1) model. We examine if he exisence of IAS has any effec on volailiy by using an auoregressive of order one as a mean equaion, while we also use a condiional variance equaion wih a dummy variable (aking he value zero for pre-ias period and one for pos-ias period). The AR(1)-GARCH (1,1) model, for reurns R and prices P, can be expressed as follows: R c R a, where R 1 b 1 ln( P ) ln( P cd e, where c is a consan erm in he mean equaion, R is defined as R ln( P ) ln( P 1), is he consan erm in he condiional variance equaion, a is he ARCH coefficien and b is he GARCH coefficien. The dummy variable D i akes he value zero for he pre-ias period (1/1/003-31/1/004) and one for he pos-ias period (1/1/005-0/1/005). The dummy allows us o deermine wheher he adopion of IAS could be relaed o any change in he sock marke volailiy. When he coefficien of he dummy variable is posiive (negaive) hen here is a posiive (negaive) effec of IAS on volailiy. In addiion, assuming ha markes are efficien, hen (he ARCH parameer) can be viewed as a news/announcemen coefficien, while b (he GARCH parameer) can be viewed as old news/announcemen and persisence coefficien. Furher, an increase (decrease) in a suggess ha news is impounded ino prices more rapidly (slowly). A reducion in b suggess ha old news has a less persisen effec on prices changes. In addiion, an increase in b suggess greaer persisence. Also, when he sum a +b approaches uniy hen he volailiy shocks are persisen. Oher specificaions of he GARCH (p,q) include he exponenial GARCH (EGARCH) and hreshold GARCH (TGARCH). Boh models capure volailiy asymmery. EGARCH (1,1) model The condiional variance equaion of he Exponenial GARCH (1,1) model (Nelson, 1991) is given by: i ) (1) log ( ) blog( ) a cd i. () The main difference wih he GARCH model proposed by Bollerslev (1986) is ha he leverage effec now is exponenial and also ha he variances are posiive. The presence of leverage effecs can be esed by he hypohesis ha < 0. The impac is asymmeric if 0. TGARCH (1,1) model The model is inroduced by Zakoian (1990) and Glosen, Jagannahan and Runkle (1993). TGARCH usually accouns for he fac ha raders reac differenly o posiive and negaive incremens of a facor. The condiional variance equaion of TGARCH (1,1) is given by:

64 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 d b cdi. (3) Eiher good news ( 1 >0) or bad news ( <0), all have an impac on and respecively. In oher words, a negaive innovaion (shock) has a greaer impac han a posiive innovaion on volailiy. Also when > 0, bad news increases volailiy, and he leverage effec exiss. When 0 and significan hen he news impac is asymmeric. To esimae he above GARCH-ype models he Marquard algorihm wih he Heeroskedasiciy Consisen Covariance opion under he EViews program is employed. We also filer condiional mean srucure in he daa using he AR (1) model (for all GARCH specificaions and indices). This order is deermined by he AIC. Daa descripion Daily closing prices for he General ASE index, FTSE/ASE-0 index as well as FTSE/ASE Mid 40 and FTSE Small Cap 80 indices are used over he period of 003-005. The FTSE/ASE-0 index is a large capialisaion index which includes he 0 larges companies lised on he ASE. The FTSE/ASE Mid 40 index focuses on companies of middle capialisaion and comprises 40 such companies, ranked by capialisaion. The nex 80 larges companies by capialisaion are included in he FTSE/ASE Small Cap 80 index. All daa were obained from he Daasream and he official web page of he Ahens Sock Exchange (www.ase.gr). Table 1 gives he descripive saisics for daily reurns of Greek sock marke indices. The daily reurns are beween 0.000 and 0.001. The negaive (posiive) value for skewness indicaes ha he series disribuion is skewed o he lef (righ). The values for kurosis are high for all indices. So, we find ha prices show excess kurosis (i.e. lepokuric pdf), implying faer ails han a normal disribuion. The Jarque-Bera es rejecs normaliy a he 5% level for all disribuions. Also, all log-prices are non-saionary I(1), while all reurns are saionary I(0). The daa are ploed in levels (P) and reurns (R) in Figure 1. Figure 1 also shows he flucuaion of he reurns and confirms he volailiy clusering fac. Table 1 Descripive Saisics for he Reurns of he Series FTSE/ASE-0 ASE GENERAL FTSE/ASE-80 FTSE/ASE MID 40 Mean 0.001083 0.000938 0.0008 0.000715 Median 0.00070 0.00041 0.000000 0.000181 Maximum 0.0458 0.041005 0.056501 0.0470 Minimum -0.039615-0.038387-0.06730-0.048991 Sd. Dev. 0.010991 0.009851 0.0135 0.010933 Skewness 0.088936 0.019115 0.0063-0.037117 Kurosis 4.3598 4.363 5.748089 4.570388 Jarque-Bera 57.66469 48.33353 43.6047 79.7100 Probabiliy 0.000000 0.000000 0.000000 0.000000 Sum 0.838190 0.7583 0.17976 0.553577 Sum Sq. Dev. 0.093378 0.075009 0.14138 0.09395 Observaions 774 774 774 774 ADF (Level) -0.368957-0.16555-1.678804-0.385410 ADF (1 s diff.) -5.3341-5.593-13.53714-13.68 Noes: Skewness is a measure of asymmery of he disribuion of he series around is mean. Kurosis measures he peakedness or flaness of he disribuion of he series. Jarque-Bera is a es saisic for esing wheher he series is normally disribued. ADF regressions include inercep bu no rend. We employ ADF es on he logarihms of sock indices.

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 65 4000.06 3500.04 3000 500 000 1500 1000.0.00 -.0 -.04 500 -.06 0 100 00 300 400 500 600 700 -.08 100 00 300 400 500 600 700 P0 P40 P80 PASE R0 R40 R80 RASE Noes: P 0: Closing price of FTSE/ASE 0 index, R 0: Reurn on FTSE/ASE 0 index P 40: Closing price of FTSE/ASE Mid 40 index, R 40: Reurn on FTSE/ASE Mid 40 index P 80: Closing price of FTSE/ASE Small Cap 80 index, R 80: Reurn on FTSE/ASE Small Cap 80 index PASE: Closing price of General ASE index, RASE: Reurn on General ASE index Fig. 1. Plo of Prices (P) in levels and Reurns (R) Nex, we repor he main saisics (mean and sandard deviaions) of he reurns for he sub-periods before and afer he adopion of IAS in Greece. Table conains informaion for all indices. I is clear from he sandard deviaions ha daily sandard deviaions changed lile. For boh periods before and afer he inroducion of IAS he s.d. s fall slighly. Tha means, he adopion of IAS may no desabilize he Greek sock marke. However, a more deailed empirical invesigaion needs o be carried ou by using GARCH-family models. Saisics for daily reurns (R) Table A. General ASE index Sample Period N Mean S.d. Pre-IAS 5 0.000893 0.010535 Pos-IAS 5 0.001031 0.00873 B. FTSE/ASE-0 index Sample Period N Mean S.d. Pre-IAS 5 0.001117 0.011757 Pos-IAS 5 0.001013 0.0094 C. FTSE/ASE Mid 40 index Sample Period N Mean S.d. Pre-IAS 5 0.000400 0.011893 Pos-IAS 5 0.001369 0.008596 D. FTSE Small Cap 80 index Sample Period N Mean S.d. Pre-IAS 5.8e-05 0.015410 Pos-IAS 5 0.000818 0.008351

66 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 IV. Empirical Resuls Selecing he GARCH model by using he AIC value, he bes represenaion for all indices is he AR (1)-GARCH (1,1) model and is exensions, AR (1)-EGARCH (1,1) and AR (1)- TGARCH (1,1). In Table 3 all he GARCH family models wih a dummy variable are repored. As can been seen, here is a negaive coefficien on dummies for all cases. The negaive effec is no saisically significan, and herefore, here is no a significan decrease in volailiy associaed wih IAS adopion. Hence, he resuls presened in Table 3 show ha he inroducion of IAS in Greece has no effec on he volailiy of he Greek sock marke. Our nex sep is o examine and compare he values of he volailiy parameers for he pre-ias and he pos-ias periods. The resuls from all GARCH-family models are presened in Table 4 for he pre-ias period and Table 5 for he pos- IAS period. I is very clear ha mos of he ARCH and GARCH parameers are saisically significan a he 5% level in he pre-ias period. The effec of IAS on sock marke volailiy Table 3 A. General ASE index MODEL COEFF. ON DUMMY T RATIO -7.19e-07-0.950089 AR(1)-EGARCH (1,1) -0.0048-1.491670-8.01e-07-0.996438 B. FTSE/ASE-0 index MODEL COEFF. ON DUMMY T RATIO -9.61e-07-0.998458 AR(1)-EGARCH (1,1) -0.014481-1.314646-9.87e-07-1.00954 C. FTSE/ASE Mid 40 MODEL COEFF. ON DUMMY T RATIO -.5e-06-1.36916 AR(1)-EGARCH (1,1) -0.039664-1.53077 -.74e-06-1.438177 D. FTSE Small Cap 80 index MODEL COEFF. ON DUMMY T RATIO -1.7e-06-1.05668 AR(1)-EGARCH (1,1) -0.01880-1.403513 -.08e-06-1.54569 Noes: We repor he resuls from he coefficien on dummy variable only. According o Table 4, all parameers in AR (1)-GARCH (1,1) are non-negaive (and saisically significan) indicaing ha he GARCH (1,1) models are well specified 1. Therefore, here have been significan changes in volailiy srucure of sock marke afer he inroducion of IAS in Greece. In addiion, he evidence from AR (1)-GARCH (1,1) indicaes an increase in ARCH parameer which suggess ha news is impounded ino prices more rapidly. Also, a decrease in he GARCH parameer suggess ha old news have a less persisen effec on price changes. Therefore, old news will have less impac on oday s price changes. The sum of he coefficiens a and b (General ASE index) changes from 0.9774 (pre-ias) o 0.47085 (pos-ias) for he AR (1)- 1 The GARCH (1,1) model has been found o be he mos parsimonious represenaion of condiional variance ha bes fis many financial series (see Bollerslev, 1987).

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 67 GARCH (1,1), and from 0.97681 (pre-ias) o 0.4948 (pos-ias) for he FTSE/ASE-0 index. Hence, he persisence of shocks from he pre-ias period o he pos-ias period is reduced indicaing marke efficiency. This is also confirmed by he reducion of he GARCH parameer (b ). This resul is also applied o he oher wo indices, FTSE/ASE Mid 40 and FTSE/ASE Small Cap 80. Appendix 1 and Appendix show he plos of condiional variance series (resuling from he above models) before and afer he inroducion of IAS, respecively. Furhermore, for he AR (1)-EGARCH (1,1) model, here is a decrease in a parameer (he only excepion is FTSE/ASE Small Cap 80 index). Also, he leverage effec erm is negaive. In pre-ias period, he leverage effec erm is saisically differen from zero indicaing he exisence of he leverage effec in sock reurns during he sample period (only for he General ASE and FTSE/ASE-0 indices). In pos-ias period, he leverage effec erm is no significan. In addiion, we find an increase in b parameer for he General ASE and FTSE/ASE-0 indices, and a decrease in b parameer for FTSE/ASE Mid 40 and FTSE/ASE Small Cap 80 indices. Furhermore, he resuls from he AR (1)-TGARCH (1,1) models show a decrease in a parameer and decrease in b parameer. So, new news is impounded ino prices slowly, while old news has a less persisen effec on price changes. Also, he leverage effec is no significan. Table 4 Esimaion Resuls of GARCH Models (Pre-IAS Period) A. General ASE index MODELS B.47e-06 (1.033) AR(1)-EGARCH -7.993399 (-1.639048).68e-06 (1.5145) 0.056777 (.646945)* 0.035733 (0.39370) 0.053374 (.14907)* -0.15835 (-.03115)* 0.013310 (0.395573) 0.90656 (7.460)* 0.17103 (0.37699) 0.915750 (6.9119)* B. FTSE/ASE-0 index MODELS b 3.1e-06 (1.4758) AR(1)-EGARCH -8.445711 (-.33696)* 3.37e-06 (1.8160) 0.063646 (.969439)* 0.10103 (1.09751) 0.059143 (.160065)* -0.188477 (-.656954)* 0.013465 (0.381446) 0.913166 (7.5404)* 0.060894 (0.149413) 0.909987 (6.413)* C. FTSE/ASE Mid 40 index MODELS b 4.1e-06 (1.44097) AR(1)-EGARCH -0.569871 (-.09479)* 4.73e-06 (1.55705) 0.080306 (3.06737)* 0.16539 (.90557)* 0.065814 (.37713)* -0.04069 (-1.0665) 0.04136 (0.770116) 0.89013 (3.76665)* 0.950476 (3.81851)* 0.880658 (4.03646)* D. FTSE Small Cap 80 index MODELS b.1e-06 (1.57369) AR(1)-EGARCH -0.63900 (-.8615)*.81e-06 (1.80445) 0.071586 (.819)* 0.1681 (3.6579)* 0.05748 (.847599)* -0.041964 (-1.118386) 0.055765 (1.0577) Noes: We repor he resuls from he condiional variance equaion only. * Significan a he 5% level. 0.9194 (37.341)* 0.984054 (111.1076)* 0.906416 (36.3539)*

68 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 Esimaion Resuls of GARCH Models (Pos-IAS Period) Table 5 A. General ASE index MODELS b 3.5e-05 (0.61413) AR(1)-EGARCH -.585359 (-1.198330) 3.41e-05 (1.06078) 0.09655 (1.140103) 0.001105 (0.009808) 0.01840 (0.15434) -0.13738 (-1.33973) 0.16336 (1.15481) 0.374598 (0.416165) 0.731697 (3.59318) 0.3888 (0.755779) B. FTSE/ASE-0 index MODELS b 4.15e-05 (0.6801) AR(1)-EGARCH -0.347369 (-0.853354) 3.83e-05 (0.94695) 0.087030 (0.98508) 0.091900 (1.149954) 0.018573 (0.19347) -0.0056 (-0.059486) 0.1144 (0.84155) 0.407798 (0.5699) 0.97087 (4.77413)* 0.455580 (0.855388) C. FTSE/ASE Mid 40 index MODELS b 6.80e-06 (1.356584) AR(1)-EGARCH -5.661617 (-.08157)* 3.49e-05 (56.45414)* 0.108533 (1.90757)* 0.035870 (0.303498) -0.10654 (-1.809446) -0.346554 (-4.5030)* 0.455867 (3.586867)* 0.799533 (7.4900)* 0.414375 (1.496770) 0.403515 (4.680164)* D. FTSE Small Cap 80 index MODELS b 1.76e-05 (1.4598) AR(1)-EGARCH -.973785 (-1.101388) 1.17e-05 (1.78844) 0.11086 (1.510074) 0.175379 (1.45433) 0.03635 (0.577833) -0.049454 (-0.466766) 0.073589 (0.586971) Noes: We repor he resuls from he condiional variance equaion only. * Significan a he 5% level. 0.640039 (.671119)* 0.70401 (.535490)* 0.75951 (4.73065)* The Uncondiional Variance In mos of he AR (1)-GARCH (1,1) models he ARCH and GARCH parameers are nonnegaive. Also since he sum of a and b for he GARCH (1,1) model is less han one, hen he models have finie uncondiional variances. The uncondiional variance ( h ) has he form: h 1 a b Comparing he parameers across he wo sub-periods, we find ha, for all indices, here has been a decrease in boh he ARCH and GARCH parameers. Now, in he case of he AR (1)- GARCH (1,1) model he uncondiional variance for he General ASE index is equal o 1.094e-05 for he pre-ias period and o 6.65e-06 for he pos-ias period. In addiion, for FTSE/ASE-0, (4)

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 69 he uncondiional variance is equal o 1.384e-05 for he pre-ias period and o 8.15e-06 for he pos-ias period. In oher words, he uncondiional variance in he pos-ias period is lower han ha of he pre-ias period. This indicaes lower marke volailiy afer he inroducion of IAS in Greece. For he FTSE/ASE Mid 40 index, he uncondiional variance is sill lower in he pos-ias period. More specific, for he AR (1)-GARCH (1,1) he uncondiional variance is equal o 1.393e- 05 for he pre-ias period and o 7.396e-06 for he pos-ias period. Also, for FTSE/ASE Small Cap 80 he uncondiional variance changes from.457e-05 o 7.1e-06. Thus, he uncondiional variance in he pos-ias period is lower han ha of he pre-ias period. In oher words, he volailiy of he Greek sock marke diminished afer he inroducion of IAS. V. Summary and Conclusion From 1/1/005, he financial saemens of limied companies in Greece mus be prepared in accordance wih Inernaional Accouning Sandards (IAS). The inroducion of IAS and, in paricular, he impac of IAS on sock marke volailiy are a new research opic. To our knowledge, his is he firs paper ha examines he adopion of IAS relaed o he Greek sock marke. A significan indicaor of his effec is sock marke volailiy. Volailiy is one of he mos imporan conceps in finance. I can be measured as sandard deviaion or variance of series, and is ofen used as a crude measure of he oal risk of financial asses. We analyse he relaionship beween IAS and sock marke volailiy for he Ahens Sock Exchange using several GARCH models for modelling four indices: he General ASE index, FTSE/ASE-0, FTSE/ASE Mid 40 and FTSE Small Cap 80 indices. The AR (1)-GARCH (1,1) and is exensions, AR (1)-EGARCH (1,1) and AR (1)-TGARCH (1,1) have been found o be he mos parsimonious represenaions of condiional variances for all indices considered. The resuls for he effec of IAS on he Greek sock marke sugges ha here has been a negaive bu no significan effec on sock price volailiy. During he sub periods, we find ha good news has a lesser impac on sock reurn volailiy, and also, ha he persisence of shocks is reduced indicaing he increased marke (pricing) efficiency. This is no surprising since he Greek sock marke is a highly liquid marke. In addiion, he resuls sugges ha old news has eiher a greaer or lesser persisen effec on price changes. In conclusion, he evidence suggess ha here is no effec of IAS on Greek sock marke volailiy. This is confirmed by he esimaion of hree differen ypes of GARCH specificaions and uncondiional variances. Paricularly, he uncondiional variance in pos-ias period found o be lower han ha of he pre-ias period (for all indices). This indicaes lower marke volailiy afer he adopion of IAS in Greece. These findings are helpful o financial managers dealing wih Greek sock indices. Finally, for fuure research in his area, we should es wheher he inroducion of IAS affecs accouning values using daa from European companies lised on several sock exchanges. References 1. Bollerslev, T. Generalised Auoregressive Condiional Heeroscedasicy // Journal of Economerics, 1986. No 33. pp. 307-37.. Bollerslev, T.A Condiional Heeroscedasic Time Series Model for Speculaive Prices and Raes of Reurn // Review of Economics and Saisics, 1987. No 69. pp. 54-547. 3. Eccher, E.A. and Healy, R.M. The Role of Inernaional Accouning Sandards in Transiional Economies: A Sudy of he People s Republic of China // Available a SSRN: hp://papers.ssrn.com. 000. 4. El-Gazzar, S.M., Finn, P.M. and Jacob, R. An empirical invesigaion of mulinaional firms compliance wih Inernaional Accouning Sandards // Inernaional Journal of Accouning, 1999. No 34(). pp. 39-48. 5. Engle, R.F. Auoregressive Condiional Heeroscedasiciy wih Esimaes of he Variance of Unied Kingdom Inflaion // Economerica, 198. No 50. pp. 987-1007.

70 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 6. Engle, R.F., and Ng, V. Measuring and Tesing he Impac of News on Volailiy // Journal of Finance, 1993. No 48. pp. 1749-1778. 7. Flower, J. The fuure shape of harmonizaion: he EU versus he IASC versus he SEC // European Accouning Review, 1998. No 6(). pp. 81-303. 8. Glosen, L.R., Jagannahan, R., and Runkle, D.E. On he Relaion Beween he Expeced Value and he Volailiy of he Nominal Excess Reurn on Socks // The Journal of Finance, 1993. No 48. pp. 1779-1801. 9. Harris, L. S&P 500 cash sock price volailiies // Journal of Finance, 1989. No 44. pp. 1155-1175. 10. Hung, M. and Subramanyam, K.R. Financial Syaemen Effecs of Adoping Inernaional Accouning Sandards: The Case of Germany // Available a SSRN: hp://papers.ssrn.com, 004. 11. Lockwood, L.J., and Linn, S.C. An examinaion of sock marke reurn volailiy during overnigh and inraday periods 1964-1989 // Journal of Finance, 1990. No 45. pp. 591-601. 1. Nelson, D.. Condiional Heeroscedasiciy in Asse Reurns: A New Approach // Economerica, 1991. No 59. pp. 347-370. 13. Schipper, K. The inroducion of Inernaional Accouning Sandards in Europe: Implicaions for inernaional convergence // European Accouning Review, 005. No 14. pp. 101-16. 14. Taylor, S. L. Inernaional Accouning Sandards: An Alernaive Raionale // Abacus, 1987. No 3(). pp. 157-170. 15. Zakoian, J.M. Threshold heeroskedasic models // Manuscrip, CREST, INSEE, Paris, 1990.

Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 71 APPENDIX 1: Plos of Condiional Variance Series Before he Inroducion of IAS.0 1 6 G e n e r a l A S E i n d e x.0 1 4.0 1 0.0 0 6 5 0 1 0 0 1 5 0 0 0 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0 C o n d iio n a l S a n d a rd D e v ia io n.0 1 8 F T S E / A S E - 0 i n d e x.0 1 6.0 1 4.0 1 0.0 0 6 5 0 1 0 0 1 5 0 0 0 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0 C o n d iio n a l S a n d a rd D e v ia io n.0.0 0 F T S E / A S E M ID 4 0 i n d e x.0 1 8.0 1 6.0 1 4.0 1 0.0 0 6 5 0 1 0 0 1 5 0 0 0 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0 C o n d iio n a l S a n d a rd D e via io n.0 3.0 8 F T S E / A S E S m a l l C a p 8 0 i n d e x.0 4.0 0.0 1 6.0 0 4 5 0 1 0 0 1 5 0 0 0 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0 C o n d i i o n a l S a n d a r d D e v i a i o n

7 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 APPENDIX : Plos of Condiional Variance Series Afer he Inroducion of IAS.0 1 5.0 1 4 G e n e r a l A S E i n d e x.0 1 3.0 1 1.0 1 0.0 0 9.0 0 7 5 5 0 7 5 1 0 0 1 5 1 5 0 1 7 5 0 0 5 5 0 C o n d iio n a l S a n d a rd D e v ia io n.0 1 5.0 1 4 F T S E / A S E - 0 i n d e x.0 1 3.0 1 1.0 1 0.0 0 9.0 0 7 5 5 0 7 5 1 0 0 1 5 1 5 0 1 7 5 0 0 5 5 0 C o n d i i o n a l S a n d a r d D e v i a i o n.0 0 F T S E / A S E M ID 4 0 i n d e x.0 1 6.0 0 4.0 0 0 5 5 0 7 5 1 0 0 1 5 1 5 0 1 7 5 0 0 5 5 0 C o n d i i o n a l S a n d a r d D e v i a i o n.0 1 5.0 1 4.0 1 3.0 1 1.0 1 0 F T S E / A S E S m a l l C a p 8 0 i n d e x.0 0 9.0 0 7.0 0 6 5 5 0 7 5 1 0 0 1 5 1 5 0 1 7 5 0 0 5 5 0 C o n d i i o n a l S a n d a r d D e v i a i o n