Scholars Journal of Economics, Business and Managemen e-issn 2348-5302 Pınar Torun e al.; Sch J Econ Bus Manag, 204; (7):29-297 p-issn 2348-8875 SAS Publishers (Scholars Academic and Scienific Publishers) (An Inernaional Publisher for Academic and Scienific Resources) The Economeric Analysis of Volailiy Dynamics beween Developed Marke Economies and Emerging Marke Economies Aziz Kular, Pınar Torun 2* Professor, Fakuly of Adminisraive and Economics, Deparmen of Economics, Sakarya Universiy, Pin Code: 54050, Turkey 2 Research Assisan, Fakuly of Adminisraive and Economics, Deparmen of Economics, Gümüşhane Universiy, Pin Code: 29000, Turkey *Corresponding Auhor: Pınar TORUN; Email: Absrac: In his sudy volailiy dynamics beween he sock markes of developed marke economies and emerging marke economies were analyzed. Wihin his conex, in his sudy covering he period of 05.0.2000-3.0.204, daily closing values of he sock marke index of 0 counries were used, and volailiy dynamics beween counries were examined by using he analyses of BEKK GARCH and CCC GARCH. Composie (USA), FTSE 00 (UK), (Germany), (France), (Japan), (Brazil), Composie (China), (Hong Kong), (Russia), 00 (Isanbul) are he sock index included in he analysis. According o he findings, while here is a srong volailiy spillover among developed counry markes here is a weak volailiy spillover, when i comes o from developed counries owards developing counries. However, domesic shocks in he previous period and he volailiy of he previous period affec curren period of volailiy. Keywords: Volailiy Spillover, Mulivariable GARCH Model INTRODUCTION The financial liberalizaion process ha began in he 980s and informaion and echnology revoluion in he 990s have led o he acceleraion of global informaion flow and have increased he volailiy spillover beween counries by speeding up he process of financial inegraion. Failure of he U.S. Sock Exchange in November 987 and of he European currency mechanism in 992 caused a number of empirical sudies o be made explaining shocks spillover mechanism; Souheas Asian crisis, which occured in he 990s increased aciviies relaed o he financial conagion []. While he financial conagion was perceived as a specific problem of he developing counries unil 2008 Global Financial Crisis, afer he 2008 Global Crisis srong findings have been reached poining ou he fac ha he financial conagion is no only limied o developing counries and i is also a maer concerning he financial sysem in a global basis [2]. I has been once again proven ha shorcomings in he financial archiecure and in he financial innovaion in which legal and insiuional processes creaing he financial sysem spread o every field has a srucure ha increases he fragiliy raher han ensuring he effeciveness of he marke. Volailiy spillover process affecs he flows of financial asses beween counries and has led o significan changes in he reurns of he sock marke in he counry, in he volume of ransacions and in he marke value. In 2007, he local companies being a member of WFE have a oal of 6 rillion dollar marke value and a volume of 99 rillion dollar sock, while a he end of 2008 depending on he global crisis, he marke value has decreased o 33 rillion dollars and rading volume increased a 3% over he previous year and rose o 2 rillion $ [3-4]. In 2009 he fac ha Fed explained sress ess used by financial insiuions o assess capial adequacy come ou posiive creaed an air of opimism in he markes and i increased he saemen of confidence in he marke. Due o he increasing confidence in he markes, oal marke value in 2009 increased o 47 rillion dollars, bu rading volume decreased by 28% compared o he previous year and decreased o 80 rillion dollars. In 200, he marke value rose o $ 55 rillion, and he ransacion volume decreased by 22% o 63 rillion dollars [5-6].A he end of he 20 because he financial crisis deepened and was ransformed ino a deb crisis, he oal marke value declined by 4% and here has been no change in he oal volume of ransacions while reurning o he level of 2009 again. Under he influence of he expansionary moneary and fiscal policies, sock markes enered ino a recovery endency and in 202, he oal marke value of local companies being a member of WFE reached o approximaely 55 rillion dollars while he rading volume reached o 49 million dollars [7]. Available Online: hp://saspjournals.com/sjebm 29
In his sudy volailiy dynamics beween he sock marke of developed counries economies and emerging marke economies were analyzed. Wihin his conex, in his sudy covering he period of 05.0.2000-3.0.204, daily closing values of he sock marke index of 0 counries were used and volailiy dynamics beween counries were examined by using he analyses of BEKK GARCH and CCC GARCH. Composie (USA), FTSE 00 (UK), (Germany), (France), (Japan), (Brazil), Composie (China), index (Hong Kong), (Russia), 00 (Isanbul) are he sock index included in he analysis. Composie Table : Descripive Saisics of Reurn Series Composie RESEARCH METHODOLOGY Financial ime series have is own unique characerisics in common. Firsly financial ime series are lepokuric series. Secondly he series are saionary in is own cluser and series ha followed he same rend in he saionary period series show exreme volailiy in periods of crisis and hey reurn o is former course afer he crisis period. In his case, he error erm ges smaller in he saionary periods, and ges larger values in he periods of flucuaions hus leading o differen variance cases. Therefore primarily descripive saisics values belonging o index series will be examined. FTSE 00 00 Mean 0.00039 0.0009 0.000347 0.000-7.84E5 0.0003.04E-05-4.78E-0 0.000643 0.000434 Median 0.000462 0.000734 0.000442 0.00000 0.0002 0.00000 0.00002 0.00000 0.000950 0.000837 Maksimum 0.348930 0.0685 0.25982 0.094008 0.0966 0.34068 0.286400 0.269046 0.27637 0.470279 Minimum -0.3396-0.09575-0.2226-0.09256-0.0947-0.3582-0.2695-0.27559-0.299-0.20332 SD 0.06334 0.0639 0.09470 0.06523 0.0574 0.06354 0.05278 0.09455 0.02395 0.026294 Skewness -0.09774-0.08472-0.0539 0.044092-0.0327-0.04750 0.4285-0.0369-0.040.54853 Kurosis 32.9656 6.930973 7.488280 7.42075 7.3948.22727 78.699 52.9450 6.32845 40.220 Jarque Bera 4258 2066.04 2689.882 2609.602 2287.425 9034.724 762340 33293.7 23709.45 8592.4 Analyzing he Table i is observed ha series of counry reurns did no have a normal disribuion. While he UK sock marke has he highes average reurn, France sock has he lowes average reurns. However, Turkey is a counry wih he highes volailiy of he sock marke. Turkey is followed by he Russian sock marke. Fig- shows he volailiy clusering in he counry sock marke. Analysing he able i is seen ha volailiy movemens usually follow each oher; ha is o say, high flucaions follow high volailiy, while low volailiy racks a low volailiy. Fig-: Volailiy Clusering In he case of a heeroscedasiciy problem in he radiional ime series analysis, The Leas Squares esimaor proec he characeriscs of unbiasedness and consisency, whereas i loses he predicive efficacy and parameers become saisically insignifican. Therefore, in he sudies carried ou wih financial ime series he nonlinear models of he condiional variance are necessary o be used raher han models of linear ime series. Models in which he long-erm variance is consan, bu he value of variance changes during periods of flucuaions are referred o as condiional differen variance models. The differen variance model (Auoregressive Condiional Heeroskedasic, ARCH) developed for he firs ime by Engle [8] is a model allowing he esimaion of series variance and also allowing condiional variance o change over ime, bu accep he uncondiional variance as consan. However in he ARCH (p) model he problem of over- Available Online: hp://saspjournals.com/sjebm 292
parameerizaion is faced wih. To solve his problem, Bollerslev [9] creaed he GARCH (p, q) model by represening he condiional variance ARMA (Auoregressive Moving Average) process. Models developed by Engle [82] and Bollerslev are univariae models [9]. The generalized form of differen variance models for series of n is he VECH GARCH model developed by Bollerslev Engle and Wooldridge [0]. Due o he fac ha number of parameers o be esimaed is quie high in he he GARCH model and he posiive cerainy of he condiional variance is no guaraneed, BEKK GARCH model were developed by Engle and Kroner []. In his model cerainy of posiive variance is ensured. However Bollerslev [2] has developed a new model called he CCC GARCH which models volailiy spillover process by using correlaion coefficien in he condiional variancecovariance equaion. In his sudy, o analyze he spillover of volailiy beween counries he models of Diagonal BEKK and CCC GARCH were used. BEKK GARCH MODEL The firs mulivariae GARCH model is he VECH GARCH model developed by Bollerslev and ohers [0]. In his model he condiional variance and covariance, lagged condiional variance and covariance values are considered in his case as a funcion of he lagged error erm of he squared values and he lagged error erm of he squares of he cross produc and his leads over-parameerizaion problems in he model o be encounered. Therefore he BEKK GARCH model was developed by Engle and Kroner []. In he BEKK GARCH model proposed by Engle and Kroner he process begins by obaining reurns equaions. Reurn series are defined as; r r I N(0,H ) As i can be seen from he Equaion he reurn series is he sum of he error erm wih is delay value. Random variable of conneced o prior knowledge ( I ) is zero and i variance is H. Selecing H parameer as a funcion of prior knowledge allows all pars of H o be modelled depending on he lagged values (q) of square and he cross and H s own lagged values (p) and weakly on he exernal variables on jx vecor. Therefore he elemens of he covariance marix is a vecor defined by ARMAX process comprising of and he cross produc of residues and he squares. For he firs ime wih he concep of ARCH i was used by Engle, Granger, Kraf [3] and wih he concep of he diagonal presenaion GARCH connecing each elemen of covariance marix wih jk, h x, is own pas values and j, k, pas values was used for he firs ime by Bollerslev, Engle and Woodridge [0]. Tha is o say he variance depends on only covariance of he squares of he residual values of is pas hisory and covariance depends on he pas values of he cross produc. Because of he informaion ha he variance is usually explained by he residual of he square ha appears inuiively reasonable and if covariance changes slowly, fuure variance can be esimaed by using delayed residual frames. A similar argumen can be made for covariance. In he VECH GARCH model a diagonal presenaion can be obained assuming ha marix of A and G are diagonal. In he model, he i i condiional variance and covariance equaions are defined as follows. 2 h, c0 a 0 0, g 0 0 h, h h 2, c 02 0 a22 0, 2, 0 g22 0 h2, c 0 0 a 2 h 22, 03 33 0 0 g 2, 33 h 22, Or h c a g h 2, 0,, h c a g h 2, 02 22, 2, 22 2, h c a g h 2 3, 03 33 2, 33 2, Available Online: hp://saspjournals.com/sjebm 293
There are hree independen parameers of in each marix of A and G in he model wih wo variables and in he model wih he variable of n diagonical marix, each marix has (n (n +) / 2) unis independen parameers.in he model BEKK GARCH, he fac ha coefficiens are significan shows he exisence of volailiy beween counries, while i does no show he degree of volailiy spilover. I is also possible o achieve he degree of correlaion beween counries wih he CCC GARCH model. CCC GARCH MODEL In he CCC GARCH model as in he BEKK GARCH model, modeling process begins by obaining he average yield equaion. r E(r ) () Var( ) H The variance of which depends on pas knowledge is H. H is sricly posiive definie for all values. The formulaion se forh in he following equaion allows modeling of boh condiional and uncondiional variance. All elemens of he marix H is h shown wih ij,.in his case he condiional covariance values can be shown as follows; h ij h h ij, ii, jj, The values in he CCC GARCH model developed by Bollerslev [2] gives he correlaion coefficien beween sock marke indices. When he model n is generalized for n variable i can be wrien as follows; PRELIMINARY ANALYSIS Mulivariae GARCH models are models based on VAR model. Sabiliy of he series is imporan in his ype of models. Therefore, before saring o analyze, he ADF uni roo ess were conduced o es he sabiliy of he index reurn series and as well as of he series. Table 2: Uni Roo Tes Resuls Indice Reurn Composie -.9498 (0.6278) -47.882 -.6522 (0.7720) -57.9222 -.9286 (0.639) -56.0483 Composie -.5702 (0.8046) -56.5667 FTSE 00 -.8335 (0.6883) -58.8253-2.772 (0.2078) -58.5548-2.435 (0.360) -49.059 -.835 (0.6875) -37.983 00 -.6469 (0.7742) -52.6764-3.069 (0.39) -56.662 Table 2 presens he resuls of uni roo es predicions belonging o he index and reurn series. Analyzing Table 2 i is observed ha indice series are non-saionary and reurn series are saionary. Mulivariae GARCH models are obained on he basis of he average reurn ha relaes he curren reurn wih he previous period's reurn. Table 3 presens he resuls of esimaion parameers belonging o he average reurn for each counry. Table 3: Esimaed Coefficien From Mean Equaion (Diagonal BEKK GARCH) Composie 0.00048 (0.0002) 0.00043 (0.0005) 0.00090 (0.0003) 0.0008 (0.4984) 0.0009 (0.090) 0.00044 (0.0530) FTSE 00-0.00006 (0.043) 00-0.000 (0.6066) 00 0.000 (0.0009) 0.0007 (0.0056) Analyzing Table 3 he parameers of sock exchanges for all counries excep China and Japan sock exchanges are seen o be significan. Tha is o say he average reurn in he curren period is deermined depending on he yield of he previous period. Available Online: hp://saspjournals.com/sjebm 294
Table 4: Volailiy Spillover Esimaion (Diagonal BEKK GARCH) Composi CAC40 FTSE 00 00 Comp 0.002 0.00084 0.0064 0.00076 0.0004 0.0050 0.0028 0.00095 0.00070-0.003 0.00007 (0.0303) 0.00006 (0.955) -0.000-0.000-0.0090-0.004-0.00077-0.0006 0.0009 (0.0383) -0.00089 0.0003 0.00003 (0.6035) 0.00046-0.00026 (0.308) (0.099)** 0.00023 (0.0599)*** 0.00074 0.00044 0.0002 (0.0603) 0.00049 0.007 0.00066 (0.0088) -0.000 0.0004 (0.0367) -0.00033 0.0035 0.00 (0.074)** 0.00092 0.00025 (0.0033) 0.00093-0.00002 (0.8350) 0.00020 (0.0774)*** FTSE 00-0.00030 0.00300-0.0037-0.0006 ** Is significan a he 5% significance level. *** Is significan a he 0% significance level. 0.008 0.00037 (0.0008) 0.00044 0.00057-0.0009 00 0.00070 0.00 Analyzing Table 4 here is no volailiy spillover from Germany o China, from Brazil o Hong Kong and from Hong Kong o Russia. The volailiy spillover is concerned beween he counries remaining ouside he specified counries. Table 5: Effec of Domesic Shock and Pas Volailiy Spillover Esimaion A B Composie 0.2686 0.9659 0.252 0.9739 0.457 0.9865 0.04 0.996 FTSE 00 0.2346 0.9720 0.55 0.9858 0.3393 0.9349 0.2076 0.9365 0.888 0.9768 00 0.880 0.9808 The parameer of A locaed in he condiional variance equaion shows he impac of he counries pas period shocks on he curren period of volailiy, while he parameer B shows he effec of he pas volailiy on he volailiy of he curren period. Analyzing he resuls all parameers are seen o be significan. Pas period shocks in he counry (from he previous period), and he volailiy of pas period (he previous period) is effecive on he curren period of volailiy. Table 6: Esimaed Coefficien From Mean Equaion (CCC GARCH) Composie 8.07046 0.005 0.006 2.7965 (0.277) 9.0445 7.3825 (0.0006) FTSE 00 5.248 (0.0022) 5.2853 (0.0793) 0.0020 00 0.006 Analyzing Table 6 parameers for he sock marke of all counries excep China are seen o be significan. Namely he average reurn in he curren period is deermined depending on he earning of he previous period. Available Online: hp://saspjournals.com/sjebm 295
Table 7: Volailiy Spillover Esimaion (CCC GARCH Model) Composie FTSE 00 Composie 0.60463 0.60835 0.07959 0.58737 0.2599 0.49940 0.585 0.3236 0.45694 0.080 0.8854 0.27045 0.69686 0.2356 0.44590 0.3342 0.4486 0.2634 0.37760 0.4599 0.340 0.09472 0.05793 0.07794 0.953 0.2733 0.27958 0.73042 0.2320 0.46288 0.23658 0.8642 0. FTSE 00 0.29555 0.4350 0.2594 00 00 0.25584 0.35990 0.28262 0.08859 0.36475 0.8786 0.33482 0.4776 0.37604 Parameers of he CCC GARCH model gives he correlaion coefficien beween he sock marke. Analyzing he resuls of forecass, he sock marke of counries having he highes correlaion wih he U.S. are seen o be respecively Brazil, Germany, France and Briain. I is observed ha excep Brazil here is a weak correlaion beween he U. S. and oher developing counries sock marke. There is a srong correlaion beween Germany and France. France is followed by Briain, Brazil and Russia. There is weak correlaion beween Germany and oher developing counries sock marke. There is a very low correlaion beween Chinese sock exchange and ha of oher counries. The second counry which has a high correlaion wih he French sock marke is he UK sock marke. Beween France and he Russian sock marke here is a moderae correlaion, and i is observed ha here is a low correlaion beween France and he devoloping counries excluding he Russian sock marke. Alhough Hong Hong is higher compared o China, i has a weak correlaion wih he sock marke of Japan and Turkey and oher counries sock markes. Russia has he highes correlaion wih he sock marke of Turkey. The parameer of A locaed in he condiional variance equaion shows he impac of he counries pas period shocks on he curren period of volailiy, while he parameer B shows he effec of he pas volailiy on he volailiy of he curren period. A B Composie 0.0898 0.8937 Table 8: Effec of Domesic Shock and Pas Volailiy Spillover Esimaion 0.06858 0.9252 0.0533 0.93456 0.05942 0.92784 FTSE 00 0.07455 0.9040 0.0605 0.93083 0.32 0.83894 0.0202 0.8287 0.0997 0.8864 00 0.07684 0.92556 Analyzing he resuls all parameer esimaes are seen o be significan. Domesic shocks of he counries in he previous period and he previous period volailiy have an effec on he curren period's volailiy. RESULT In his sudy covering he period of 05.0.2000-3.0.204, daily closing values of 0 counries sock marke index were used and volailiy dynamics beween counries were examined by using he analyses of BEKK GARCH and CCC GARCH. Composie (USA), FTSE 00 (UK), (Germany), (France), (Japan), (Brazil), Composie (China), index (Hong Kong), RTS (Russia), 00 (Isanbul) are he sock index included in he analysis. According o he findings derived from he BEKK model while here is no volailiy spillover from Available Online: hp://saspjournals.com/sjebm 296
Germany o China, from Brazil o Hong Kong, from Hong Kong o Russia, here is a volailiy spillover beween sock markes of counries in he absence of hese groups of counries. However, domesic shocks in he previous period and he volailiy of he previous period affec he curren volailiy period. According o he findings obained from he CCC GARCH model, counries having he highes correlaion wih he Unied Saes are respecively Germany, France and Briain. Brazil has he highes correlaion wih he U.S. among developing counries. There is a weak correlaion beween he U.S. and oher developing counries exchanges. The counries ha have been deal wih as having he highes correlaion are Germany and France. Alhough here is no a high degree of correlaion beween developed counries and developing counries, he counry indicaing he mos differenaion among he developing counries is China. The counry which has he highes correlaion wih he sock marke of Turkey is Russia. According o he findings i can be said ha financial conagion o be discussed for he period and addressed for he groups of counries is more common beween developed counries and here is a poor volailiy spread beween developed counries and developing counries. REFERENCES. Karolyi GA; Does Inernaional Financial Conagion Really Exis. Inernaional Finance, 2003; 6: 79-99. 2. Kolb RW; Financial Conagion, The Viral Threa o he Wealh of Naions, Ediör: Rober W. Kolb, John Wiley&Sons USA. 20. 3. WFE (World Federaion of Exchange) (2007). Annual Repor and Ssisics available a online a: hp://www.world-exchanges. org/files/ saisics/pdf/wfe%20annual%20repor%20405 09.pdf 4. WFE (World Federaion of Exchange) (2008). Annual Repor and Ssisics available a online a: hp://www.worldexchanges.org/files/saisics/pdf/wfe%20annual %20Repor%2040509.pdf 5. WFE (World Federaion of Exchange) (200). Annual Repor and Ssisics available a online a: hp://www.world-exchanges.org /files /saisics/pdf/wfe%20annual%20repor%2040 509.pdf 6. WFE (World Federaion of Exchange) (20), Annual Repor and Ssisics available a online a: hp://www.worldexchanges.org/files/saisics/pdf/wfe%20annual %20Repor%2040509.pdf 7. WFE (World Federaion of Exchange) (202). Annual Repor and Ssisics available a online a: hp://www.world-exchanges. org/files/ saisics/pdf/wfe%20annual%20repor%20405 09.pdf 8. Engle RF; Auoregressive condiional heeroscedasiciy wih esimaes of he variance of Unied Kingdom inflaion. Economerica: Journal of he Economeric Sociey, 982; 987-007. 9. Bollerslev T; Generalized Auoregressive Condiional Heeroscedasiciiy. Journal of Economerics, 986; 3:307-327. 0. Bollerslev T, Engle RF, Wooldridge JM; A Capial Asse Pricing Model wih Time-varing Covariances. Journal of Poliical Economy. 988; 96: 6-3.. Engle RF, Kroner K; Mulivariae Simulaneous Generalized Arch. Economeric Theory, 995; ():22-50. 2. Bollerslev T; Modelling o Coherence in Shor Run Nominal Exchange Raes: A Mulivarie Generalized ARCH Model. Review of Economics and Saisics, 990; 72: 498-505. 3. Baba Y, Kraf DF, Engle RF, Kroner KF; Combinig Compeing Forecass of Inflaion Using A Bivariae Arch Model. Journal of Economic Dynamics and Conrol, 984; 8:5-65. Available Online: hp://saspjournals.com/sjebm 297