Gerard A. Moerman 1,# Financial Management Department, Erasmus University Rotterdam, Rotterdam School of Management. Working paper, 26 November 2002

Transcription

1 DIVERSIFICATION IN EUROPEAN STOCK MARKETS: COUNTRY VS. INDUSTRY Gerard A. Moerman 1,# Financial Managemen Deparmen, Erasmus Universiy Roerdam, Roerdam School of Managemen Working paper, 26 November 2002 Absrac The European Union and he inroducion of he Euro make he connecion beween European counries much sronger. Because of hese insiuional changes one migh expec ha counry effecs diminish over ime and ha diversificaion sraegies concenrae more on he indusrial composiion of he porfolio. So far empirical evidence has yielded raher mixed resuls. Hence, we would like o shed ligh on his discussion wih anoher specificaion. Using recen daa we find ha more efficien porfolios can be found by diversifying over indusries compared o diversificaion over counries. Keywords: EMU, European sock markes, inegraion, porfolio diversificaion JEL Classificaion: G11, G15 1 Corresponding auhor: Gerard A. Moerman Erasmus Universiy Roerdam Financial Managemen Deparmen, Room F4-31 P.O. Box DR Roerdam The Neherlands Phone: fax: gmoerman@fbk.eur.nl # I like o hank Kees Koedijk, Ronald Mahieu, Philip Hans Franses, Mahijs van Dijk and seminar paricipans of he Erasmus Universiy Roerdam for heir valuable commens.

2 1. Inroducion The exen o which financial markes and counries have become more inegraed has been he opic of exensive debae. Especially in he European Moneary Union (EMU) he number of insiuional changes has been large. These changes and especially he inroducion of he euro are par of he inegraion process of several European counries ino he European Moneary Union 1. Theory suggess ha counry effecs wihin Europe should diminish over ime and hus ha he level of inegraion beween hese counries should rise. Prior empirical research mainly found ha counry effecs were more imporan han indusry effecs (e.g. Roll, 1992; Heson & Rouwenhors, 1994; Griffin & Karolyi, 1998; Rouwenhors, 1999). These papers concluded ha invesing according o a pure counry sraegy ouperformed a sraegy based on informaion from indusries only. More recen research, however, shows ha he dominaion of counry effecs may have diminished (e.g. Carrieri, Errunza & Sarkissian, 2000; Cavaglia, Brighman & Aked, 2000; Isakov & Sonney, 2002; Adjaoue & Danhine, 2001). Indusry effecs play a significan role in explaining he cross-secion of sock reurns and may overake he counry effecs in he near fuure. I looks like indusry effecs are slowly geing more imporan, while counry effecs are losing field. This conclusion is confirmed by he exension of he Rouwenhors (1999) mehodology. In his original paper he concludes ha counry effecs are more imporan han indusry effecs wih a sample ha lass ill On his websie 2 he presens he resuls when he sample is lenghened unil July A plo depics ha indusry effecs have risen sharply since 1998 and Rouwenhors concludes ha indusry effecs are nowadays a leas as imporan as counry effecs. In his sudy we wan o conribue o his discussion by inroducing a differen research design. Firs of all, we sudy he correlaion coefficien beween European counries and European indusries. Wih a parsimonious mulivariae GARCH model we are able o consruc he condiional covariance marix, which we will use o sudy he ime behaviour of he average correlaion coefficien. Mos oher research in his area does no sudy ime 1 see Hardouvelis, Malliaropulos & Priesley (2001) for a more deailed discussion abou European inegraion - 2 -

3 varying correlaion coefficiens. A mos, a srucural break is insered and he correlaions before and afer ha break are compared (e.g. Adjaoue & Danhine, 2001). Secondly, we invesigae he implicaions for porfolio diversificaion of a represenaive invesor wih a mean-variance objecive funcion. This provides a benchmark o sudy he diversificaion opporuniies. Using very recen daa he sample ends in Ocober 2002 we find ha diversificaion over indusries gives more efficien porfolios. Our resuls show ha he insiuional changes in Europe decrease he use of pure counry allocaion schemes wihin Europe. This paper is organised as follows. In he following secion we describe our mehodology. In Secion 3 we discuss he daa series ha we use. The resuls are presened in Secion 4 and Secion 5 concludes. 2. Mehodology / Economeric Specificaion We use a mulivariae model in order o sudy he changing correlaions beween he differen European counries over ime. The mulivariae model for asse reurns can be wrien as: R ε z = E( R F 1 F = z H ~ N(0, I) 1 ) + ε 1/ 2 ( 1) where R represens a vecor reurns on ime, F -1 is all informaion up o ime -1, ε and z are boh vecors and follow a mulivariae normal disribuion. H is he ime-varying covariance marix. The expecaion of he asse reurn (E(R F -1 )) can be represened by a consan or by a ime series conaining all informaion up o ime -1. In he res of his paper we assume a consan mean for all indices, bu in fuure research his can be exended wih he informaion variables, like he dividend yield, he erm srucure spread, he shor-erm ineres rae and he defaul spread. The marix H is he covariance marix of he error erm ε. An imporan par of his model is he specificaion of H, because he number of parameers can be very high as soon as he number of variables is higher han wo or hree. In our case (using 10 indusry and 11 counry 2 hp://maye.som.yale.edu/geer - 3 -

4 indices) i is necessary o find alernaive ways o esimae he condiional covariance marix. Differen sudies proposed mehods o sudy he changing correlaions beween asses, e.g. Longin & Solnik (1995) and Engle (2000). We will use he orhogonal-garch mehod as proposed by Alexander (2000). This mehod uses a specific ransformaion of he covariance marix, which reduces he number of parameers dramaically. This secion covers he mehodology in more deail. 3 Firs of all, he uncondiional covariance marix Σ is esimaed from he model R = µ + ε ε ~ N(0, Σ) ( 2) wih µ equal o he uncondiional mean of he asse reurns. Then, he uncondiional covariance marix is diagonalized using he eigenvalues and eigenvecors of he marix. This can be done such ha all eigenvecors are orhogonal o each oher. Σ = 1 V ΛV ( 3) V is he marix conaining he eigenvecors and Λ is a diagonal marix conaining he eigenvalues. V is assumed o be ime invarian. Since he marix V is consruced such ha all eigenvecors are orhogonal, we can consruc orhogonal error series by ransforming he residuals ε, which were found by he regression in equaion 2. η = ε ~ N(0, Λ) ( 4) V By consrucion, he series η i, (i=1,.,n) are all independen (because he eigenvecors are chosen orhogonally). We propose o apply GARCH(1,1) o all separae orhogonal error series η i,, such ha we can sudy he behaviour of he variances over ime. Combining he univariae resuls gives a ime varying (diagonal) covariance marix Λ. This marix can now be ransformed back o a covariance marix for he original series, R i, (i=1,.,n), using he following relaion: 1 H = VΛV ( 5) The resuling H can hus be inerpreed as a condiional covariance marix. 3 In some recen work Van der Weide(2002) proposes a generalized version of he Orhogonal GARCH, also called GO-GARCH

5 As soon as his condiional covariance marix is known we conduc an analysis on he behaviour of he variances and correlaions over ime. We will sudy he average correlaion coefficien over all Euro paricipaing counries by regressing he average correlaion coefficien on a ime rend. We expec his figure o rise over ime, because of a higher rae of inegraion of hese counries. Furhermore, we will presen he implicaions for a meanvariance invesor. 3. Daa We use boh indusry and counry indices in his research from Morgan Sanley Capial Invesmen (MSCI). The counry indices are all EMU-paricipaing counries excep for Luxembourg (following MSCI). The indusrial indices are he MSCI secor indices for he EMU-area. These en indices are consruced from he same capial markes as he eleven counry indices. The sample consiss of monhly reurns from January 1995 unil Ocober Since he euro was only inroduces on January 1 s 1999, he firs par of our sample sill conains exchange rae risk. Therefore, we ake he view of a German invesor and ranslaed all reurns ino German Marks. Tables 1 and 2 presen he saisics for he counry and he indusry indices. 4. Resuls 4.1 The ime -variaion in correlaion coefficiens In his secion, we discuss he main resuls we have obained by applying he mehodology inroduced in secion 2 o our sample of monhly MSCI index reurns. Using his orhogonal- GARCH procedure we are able o esimae he ime-varying covariance marix for all series a he same ime, allowing us o sudy he ime behaviour of he correlaion coefficiens. The average correlaion coefficien, ha we use in his paper, can be seen as a measure for he amoun of diversifiable risk. Hence, lower correlaions mean higher diversificaion opporuniies. The mehodology is applied o boh counry and indusry indices separaely

6 Due o he insiuional changes in Europe (wih an emphasis on he end of he exchange rae risk) one would expec ha counry indices become more alike and hus ha he correlaion beween hese counries would rise. However, counries will never be perfecly correlaed because of differen indusrial composiion and oher differences (e.g. differen inflaion raes). Heson & Rouwenhors (1994) and Griffin & Karolyi (1998), however, showed ha he indusrial composiion of a counry does explain only lile of he ime-variaion of he crosssecion of reurns. Our expecaions for he indusry indices are ambivalen. On one hand, he argumen of inegraion ha makes he correlaion of counries rise can also be applied on individual socks and hus (afer aggregaion) on indusry indices. Furhermore i is very hard o esimae he effec of he inroducion of he Euro on he average indusry correlaion, since hese indices are already counry-diversified porfolios. Figure 1 shows he 6-monh moving average of he average correlaion coefficien ha we found by applying he orhogonal GARCH procedure on boh he counry and he indusry indices. The firs, mos sriking, observaion is ha here is a big ime-variaion in he correlaion coefficiens and his paern is almos he same for he counry and he indusry correlaions. Apparenly, all sock indices are sensiive for he same kind of shocks, which make all correlaions go up or down. Individual correlaions (beween wo counries or wo indusries) also show his ype of behaviour. Some furher research will be needed o undersand his ime-behaviour, however, we will leave his quesion since i is no direcly relaed o our research quesion. We are mosly ineresed in answering he quesion wheher he average correlaion coefficien of counry indices has risen over ime. Clearly, figure 1 can no give us he answer, since he correlaion coefficiens are very volaile and dependen on some business cycle like paern. I looks like boh invesmen ypes share a common facor. We can, however, compare he series wih each oher. Figure 2 is a plo of he difference beween he average correlaion coefficien of he counries minus he average correlaion coefficien of he indusries. Alhough his picure also shows similar paerns, he beginning of 1998 can be seen as a urning poin. Before ha ime he indusry indices were more correlaed wih each oher han - 6 -

7 he counry indices were. From 1998 onwards his is he oher way around, excep for he end of sample, where he correlaions are very close o each oher. We aribue his change o he insiuional changes in he EMU-area. A firs sigh, he beginning of 1998 migh no seem a logical urning poin, since he inroducion of he Euro was only one year laer. However, he fac ha he common currency would be inroduced was known earlier, which explains ha his effec can be found even before January Hardouvelis, Malliaropulos & Priesley (2001) find similar resuls. They sudy European marke inegraion wih a model similar o he inegraion model of Bekaer & Harvey (1995). Their resuls sugges ha mos counries are fully inegraed wih he European marke a he end of heir sample (June 1998). Our resul, ha he average counry correlaion is higher han he average indusry correlaion, is in line wih ha. Concluding, he average correlaion coefficien of boh he counry and he indusry indices is very volaile. Hence, i is hard o draw conclusions from he absolue value of his coefficien. Therefore, our resuls need o be inerpreed wih care, because of he aggregaion of coefficiens afer a complex esimaion procedure. In he following secion we will sudy he resuls for porfolio diversificaion opporuniies using mean-variance analysis. 4.2 Mean-variance analysis The previous secion discussed he correlaions beween counries and beween indusries. The correlaion coefficien can be seen as an indicaion for he diversificaion opporuniies, bu naurally his informaion has o be combined wih he expeced reurns and he variances in order o ge a view of possible diversificaion opporuniies. Mean-variance analysis is a meaningful ool for his purpose. Figure 3 depics he capial marke lines for he oal sample for hree ypes of invesmens: counry indices only, indusry indices only and boh ypes of indices. Comparing counries and indusries wih each oher we can clearly see ha (over he whole sample) invesing in indusry indices gave much more diversificaion opporuniies han a pure counry invesmen sraegy. From a more saisical poin of view, we can say ha boh spanning ess are rejeced (see able 3). This means ha neiher he counry indices nor he indusry indices - 7 -

8 span he mean-variance fronier for boh ypes of invesmen caegories. In oher words, a mean-variance invesor can always gain by adding he oher ype of indices ino his porfolio. Taking ino accoun he average correlaion coefficiens from he previous secion, he difference beween he capial marke lines migh be a lile counerinuiive, since he correlaion coefficiens are very close o each oher. This difference mus hen be found in he expeced reurns and he sandard deviaion, which are saed in able 1 and 2. In order o make his comparison easier, figure 4 depics a scaer plo ha shows all indices by heir means and sandard deviaions. From his figure i is obvious why an invesor would be beer off by invesing along a pure indusry invesmen sraegy compared o invesing in counry indices only. Especially wo indusries had a very high reurn compared o heir sandard deviaion: Consumer Saples and Healh Care. Their average reurn over he whole sample was over 1 percen per monh, while heir sandard deviaion was around 5 percen per monh. E.g. in he case of he Consumer Saples indusry only wo counries had a higher reurn (Spain and Finland), while none of he counries has a lower variance. I looks like he ime ha counry effecs were more imporan han indusry effecs is over, as far as Europe is concerned. All of his can be considered as a resul of he ongoing process of poliical and economical inegraion wihin he European Moneary Union. This conradics wih lieraure ha discuss counry and indusry effecs during he nineies (mos noably Heson & Rouwenhors, 1994; Griffin & Karolyi, 1998; Rouwenhors, 1999). On he oher hand, we can srenghen he resuls of Cavalia, Brighman & Aked (1999) and Isakov & Sonney (2002). They concluded ha imes are changing and ha indusry effecs are geing more imporan. The following secions will ake a look a he mean-variance properies of some sub samples. 4.3 Mean-variance analysis for subsamples A naural spli in our sample is of course January This approximaely divides he sample in wo equal halves and more imporanly i marks he inroducion of he common currency. Figures 5 and 6 presen he capial marke lines of boh sub samples. In he second sub sample i is clear ha a more efficien porfolio can be creaed using indusry indices only - 8 -

9 compared o using counry indices. In his sample here is no more exchange rae risk, which could be he reason ha invesors are beer off invesing in indusries. The hypohesis of no inersecion is no rejeced (which is no he case for all samples), bu also he hypohesis ha indusry indices span he invesmen fronier of boh ypes of indices can also no be rejeced. In oher words, his saisic says ha he addiion of counry indices is no very valuable given a mean-variance efficien indusry index allocaed porfolio. This is a clear indicaion ha invesmen in indusry indices is more imporan han invesing in counry indices, which srenghens our conclusion ha he resuls of Rouwenhors (1999) and ohers are oudaed. The resuls before 1999 (figure 5) are very similar. The analysis shows ha already in his period indusries are doing beer han counries. The differences are no as big as hey are in he las sub sample wih he mos recen daa. However, we can conclude ha he akeover of he indusries sared before Comparing his wih our resuls discussed in secion 4.1 his is no very srange. Using he orhogonal GARCH mehodology we found ha he average correlaion coefficien of he counries is higher han he indusry correlaion coefficien afer he beginning of For compleeness, le us consider a las sub sample: 1995: :02. February 1998 is he urning poin in he orhogonal GARCH analysis, where he average counry correlaion coefficien becomes larger han he average indusry correlaion. Figure 7 shows ha invesing in counry indices would gain slighly more diversificaion opporuniies han invesmens in indusry indices. However, his difference is neglecable, since he spanning ess (able 3) show ha neiher he counry nor he indusry indices span he fronier of efficien porfolios consising of boh counry and indusry indices. More imporanly, his figure (combined wih he oher figures) shows ha here is a ime rend in Europe. Because of he insiuional changes wihin he European Moneary Union counry indices ge more correlaed wih each oher and hus conain less diversificaion opporuniies. Our conclusion is ha an invesor is beer off by invesing in indusry indices only, alhough he bes sraegy remains o consider all possible invesmens

10 5. Conclusions The ongoing process of inegraion wihin he European Union is ofen he subjec of debae. Due o a number of insiuional changes under which he inroducion of he Euro per January 1 s 1999, European financial markes are geing more correlaed wih each oher. This paper deal wih he consequences of hese changes on he diversificaion opporuniies wihin he Euro-zone. Special aenion was paid o he difference beween counry and indusry effecs. Well-known papers ha cover his subjec (Roll, 1992; Heson & Rouwenhors, 1994; Griffin & Karolyi, 1998; Rouwenhors, 1999) find ha counry effecs are more prevalen han indusry effecs. Recen research (Cavaglia, Brighman & Aked, 1999; Isakov & Sonney, 2002) finds ha counry effecs are losing field. We show ha indusries are more imporan han counries wih respec o diversificaion opporuniies. In he firs par of he paper we use an orhogonal GARCH approach o sudy he ime variaion in correlaion coefficiens. Firs of all, i follows ha correlaions are very volaile and seem o follow a business cycle ype of paern. Secondly, we find ha he difference in he average correlaion coefficien beween counries and indusries has changed. In he firs par of our sample he average indusry correlaion was higher han he average counry correlaion. From he beginning of 1998 his is exacly he oher way around. This implies ha diversificaion opporuniies in indusry indices should increase compared o diversificaion beween counry indices. The second par of our paper provides some evidence for his. We plo he capial marke lines of hree invesmen caegories (counry indices only, indusry indices only and boh ypes of indices) for differen samples. Counry indices performed beer in he period unil Using more recen sub samples we find ha he invesor would have been beer ou by invesing in indusries. This alogeher shows ha counry effecs are slowly vanishing over ime and ha indusries are geing more imporan

11 References Adjaoue,K. and J.P. Danhine, 2001, EMU and Porfolio Diversificaion Opporuniies, Discussion paper series No. 2962, Cenre for Economic Policy Research Alexander, C.O., 2000, Orhogonal Mehods for Generaing Large Posiive Semi-Definie Covariance Marices, Discussion Papers in Finance, ISMA Cenre, Bekaer, G., and C.R. Harvey, 1995, Time-varying world marke inegraion, Journal of Finance, Vol.50, pp Carrieri, F., V. Errunza and S. Sarkissian, 2000, Indusry Risk and Marke Inegraion, Working paper SSRN Cavaglia, S., C. Brighman and M. Aked, 2000, The Increasing Imporance of Indusry Facors, Financial Analys Journal, Sepember/Ocober 2000, pp DeRoon, F.A. & T.E. Nijman, 2001, Tesing for mean-variance spanning: a survey, Journal of Empirical Finance, Vol 8, pp Engle, R.F., 2000, Dynamic Condiional Correlaion A Simple Class of Mulivariae GARCH Models, Discussion paper , Universiy of California, San Diego Griffin, J.M. and G.A. Karolyi, 1998, Anoher look a he role of he indusrial srucure of markes for inernaional diversificaion sraegies, Journal of Financial Economics, Vol. 50, pp Hardouvelis, G.A., D. Malliaropulos and R. Priesley, 2001, EMU and European Sock Marke Inegraion, SSRN working paper Heson, S.L. and K.G. Rouwenhors, 1994, Does indusrial srucure explain he benefis of inernaional diversificaion?, Journal of Financial Economics, Vol. 36, pp Isakov, D. and F. Sonney, 2002, Are praciioners righ? On he relaive imporance of indusrial facors in inernaional sock reurns, SSRN working paper Longin, F. and B. Solnik, 1995, Is he correlaion in inernaional equiy reurns consan: ?, Journal of Inernaional Money and Finance, 1995, Vol. 14 (1) pp.3-26 Roll, R., 1992, Indusrial Srucure and he Comparaive Behavior of Inernaional Sock Marke Indices, The Journal of Finance, Vol 47 (1), pp Rouwenhors, K.G., 1999, European Equiy Markes and he EMU, Financial Analys Journal, Vol 55 (3), pp Van der Weide, R., 2002, GO-GARCH: A Mulivariae Generalized Orhogonal GARCH Model, Journal of Applied Economerics, forhcoming

12 Tables 1 and 2 Table 1 (above) shows he average reurn and sandard deviaion for all he MSCI indices of he counries ha form he Euro -zone (Luxembourg excluded). The saisics are presened for boh he whole sample and wo differen sub samples. Table 2 (below) presens he saisics for he MSCI indusry indices. Counry (MSCI index) Toal sample 95:01 02:10 Subsample I 95:01 98:12 Subsample II 99:01 02:10 Reurn S.dev Reurn S.dev Reurn S.dev Germany Belgium Spain Finland France Greece Ireland Ialy Neherlands Ausria Porugal Indusry (MSCI EMU index) Toal sample 95:01 02:10 Subsample I 95:01 98:12 Subsample II 99:01 02:10 Reurn S.dev Reurn S.dev Reurn S.dev Energy Maerials Indusrials Consumer Discreionary Consumer Saples Healh Care Financials Informaion Technology Telecom. Services Uiliies

13 Tables 3 Table 3 presens he resuls of he spanning and inersecion ess, which are aken from DeRoon & Nijman (2001). Regression analysis can be used o es wheher he inclusion of some exra invesmen opporuniies really enlarges he efficien se of porfolios. E.g., when we es wheher he inclusion of indusry indices is imporan, we need o regress he reurns of he indusry indices on he counry indices reurns (compare equaion 20 of DeRoon and Nijman (2001)): R ind, + 1 = + β Rcou, ε + 1 α (A.1) The es for inersecion and spanning can now be defined as a Wald-es on he esimaed parameers. The resricions imposed by he hypohesis of inersecion are: ( ι β ι ) = 0 α η (A.2) ind cou The inersecion es ess wheher here is one specific value of η such ha mean-variance invesors canno improve heir mean-variance efficien se by including he oher se of indices. η can be seen as he ineres rae, we used a rae of 4% per annum, hus η= (he monhly rae in gross reurn) The hypohesis of he spanning es can be saed by he following resricions: α 0 and β ι ι = 0 (A.3) = cou ind Table 3 is divided ino wo pars. The firs pars gives he p-values of he differen ess done when he inclusion of indusry indices is considered. In case he inersecion es is rejeced, i means ha he mean-variance froniers of he counry indices and of boh ypes of indices do no inersec for his specific ineres rae. When he hypohesis of spanning is rejeced, we can conclude ha he counry indices do no span he universe of boh ypes of indices. For able 3b i is he oher way around Table 3a : P-values of he ess based on he parameer esimaes of his regression: R ind, + 1 = α + β Rcou, ε + 1 p-values 95:01 02:10 95:01 98:12 99:01 02:10 95:01 98:02 Inersecion es Spanning es Table 3b : P-values of he ess based on he parameer esimaes of his regression: R coud, + 1 = + β Rind, ε+ 1 α. p-values 95:01 02:10 95:01 98:12 99:01 02:10 95:01 98:02 Inersecion es Spanning es

14 Figure 1 This figure presens he average correlaions coefficien beween counries and he average correlaion coefficien beween indusries over ime. The correlaions are found using he orhogonal GARCH approach described in he Mehodology secion COUNTRYMA INDUSTRYMA Figure 2 This plo depics he difference in he average correlaion coefficien of counries minus indusries. The correlaions are calculaed using he orhogonal GARCH approach as described in he mehodology secion DIFF

15 Figure 3: This figure plos he capial marke lines for hree invesmen caegories over he whole sample. The solid red line represens all invesmen possibiliies when only counry indices are considered. The dashed blue line is he capial marke line for he indusry indices. The doed black line considers boh ypes of indices. Figure 4: This scaer plo presens all counries and indusries considered. Each do represens he mean and sandard deviaion of one specific index. All counry indices are given by blue squares and all indusry indices are denoed by pink circles. Risk (measured by he sandard deviaion) Counries Indusries Mean reurn (in percenages per monh

16 Figure 5: This figure plos he capial marke lines for hree invesmen caegories over he firs sub sample (95:01 98:12). The solid red line represens all invesmen possibiliies when only counry indices are considered. The dashed blue line is he capial marke line for he indusry indices. The doed black line considers boh ypes of indices. Figure 6: This figure plos he capial marke lines for hree invesmen caegories over he second sub sample (99:01 02:10). The solid red line represens all invesmen possibiliies when only counry indices are considered. The dashed blue line is he capial marke line for he indusry indices. The doed black line considers boh ypes of indices

17 Figure 7: This figure plos he capial marke lines for hree invesmen caegories over he period 95:01 ill 98:02. The solid red line represens all invesmen possibiliies when only counry indices are considered. The dashed blue line is he capial marke line for he indusry indices. The doed black line considers boh ypes of indices