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Transkrypt:

DYNAMICZNE MODELE EKONOMETRYCZNE 9,,, 2JyOQRSROVNLH 6HPLQDULXP DXNRZH ZU]HQLD Z 7RUXQLX.DWHGUD (NRQRPHWULL L 6WDW\VW\NL 8QLZHUV\WHW 0LNRãDMD.RSHUQLND Z 7RUXQLX Henryk Gurgul AGH Unversy of Scnce and Technology n Crakow 3DZHáMajdosz Hgh School of Economcs and Compuer Scence n Crakow Roland Mesel Unversy of Graz, Ausra GARCH Modelng of Ausran Sock Marke Reacons on Dvdend Announcemen Inroducon Ths paper examnes he mplcaons of announced changes n dvdends on sock prces usng daa from he Ausran sock marke. We assess he marke mpacs of hese announcemens by measurng abnormal reurns and he varably of reurns. Thereby we nfer he nformaon conen of a company s dvdend polcy. To esablsh he mpac of dvdend announcemens on sock prces, we conduc an even sudy analyss based on seleced non-lnear sochasc meseres models. Ths s dfferen from mos relaed sudes ha use smple lnear regressons (based on he Marke Model) o forecas sock reurns. Sgnfcan effecs surroundng corporae announcemens of changng dvdend payous are confrmed by several sudes, manly for he US marke. One of he frs s ha of Aharony and Swary []. For a sample of 384 evens, he auhors repor average sgnfcan excess reurns on he day of announced dvdend changes of +0.36% n case of dvdend ncreases, and.3% for dvdend decreases. The auhors hank Chrsan Gulederer (Reuers Ausra) and Peer Ladreer (Capal Bank) for supplyng daa, and Peer Sener for helpful commens. All remanng errors are our own responsbly.

80 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel Asquh and Mullns [3] conduc a somewha more rgorous sudy by lmng her nvesgaon o frms ha eher nae dvdends afer a long haul or pay dvdends for he frs me. From he naure of hs sample, he auhors assume announcemens o be oally unexpeced. To capure he enre mpac of he announcemen a wo-day wndow s consdered. For a sample of 60 frms hey repor an average wo-day excess reurn of +3.7%. Dyl and Wegand [2] add ha dvdend naons no only lead o an ncrease n sock prces, bu are also accompaned by an mmedae downward shf n boh oal and sysemac company rsk. Furhermore hey repor a declne n earnngs' volaly n he frs years followng he dvdend naon. The auhors conclude ha a managemen decson o nae regular dvdend paymens brngs new nformaon o nvesors regardng he rsk of a frm. Dhllon and Johnson [] no only fnd sock prces bu also bond prces o change sgnfcanly n reacon o he announcemen of changng dvdends. Takng no consderaon only large dvdend changes hs sudy suppors he wealh redsrbuon hypohess as bond prces move n he oppose drecon o sock prces. Lone e al. [6] compue announcemen effecs for he UK sock marke. They fnd sascally sgnfcan abnormal reurns of +2.03% for a wo-day wndow n case of dvdend ncreases and 2.5% n case of dvdend decreases. Ineresngly, n conras wh mos oher sudes, hs sudy also repors a posve excess reurn of abou +.45% on he mmedae day before he announcemen of no change n dvdends. For 200 companes lsed on he German sock marke Amhud and Murga [2] nvesgae he effecs of changng dvdends on shareholders' value durng he perod 988 o 992. In lne wh he sudes menoned above, hey fnd a sascally sgnfcan cumulave abnormal reurn for he announcemen day and he prevous day of +0.96% for dvdend ncreases and.73% for dvdend decreases. The auhors emphasze ha due o less nformave accounng rules n Germany (compared o he US), dvdends convey valuable nformaon o he marke especally on curren earnngs. Conssen wh mos heorecal models on corporae dvdend polcy hese emprcal resuls sugges ha (grosso modo) hgher dvdends are good news o nvesors, whereas an announcemen of decreases n dvdend payous s bad news o he marke 2. For he Ausran marke our sudy s he frs o quanfy he reacon of sock prces on changng dvdends. The Ausran sock marke s very small compared o oher Wesern European markes and s ofen samped o be an nsder marke. Is aggregaed urnover volume amouned o abou 5 bllon EUR n he ATX Marke segmen n 200. Ths segmen comprses he mos lqud socks n Ausra (blue chps) and s he Ausran equvalen o he DAX 2 A comprehensve overvew of dvdend polcy heores can be found n Frankfurer and Wood Jr. BG (2002).

GARCH Modelng n Ausran Sock Marke 8 segmen n Germany. The connuous radng of hese socks s conduced va he XETRA Elecronc Tradng Sysem of Deusche Börse AG snce 999. Dvdends are pad on a yearly bass n Ausra. Our resuls on he Ausran sock marke are very smlar o hose of oher markes n he sense ha conrary o he marke s repuaon here s no ndcaon of leakage of nformaon pror o he announcemen day. In addon, our fndngs provde evdence ha he Ausran sock marke dgess news on dvdends very fas, a leas whn one day, herefore havng a hgh degree of semsrong marke effcency. The well-known defnon of Fama [4] saes ha under he sem-srong form of he effcen capal marke hypohess sock prces, a any me, reflec all publcly avalable nformaon relevan o he valuaon of he frm. Therefore, f an announced change n dvdends s new nformaon o he marke (.e. here s no nsder radng), he speed of prce reacon supples nformaon on he degree of marke effcency. The faser prces adjus o he news he more effcen he capal marke. We also fnd ha he prce reacons on he announcemen days are mosly unbased snce here are no subsequen abnormal prce changes afer ha day. The valdy of our resuls s suppored by non-paramerc rank es sascs. The remander of he paper s organzed as follows: Secon 2 descrbes our daa and mehodology o denfy sgnfcan (excess) prce effecs surroundng announcemen daes. Our emprcal resuls are presened n Secon 3. In Secon 4 we apply varous ess o check he robusness of he assumpons underlyng our emprcal model. Secon 5 conans a dscusson and concludes.. Reserch desgn.. Sample selecon Our sample conans 22 companes lsed on he Ausran sock marke. The companes have been quoed n he Ausran Traded Index (ATX) beween January 992 and Aprl 2002, alhough no all frms have been lsed on he sock marke for he whole perod. The ATX comprses he mos lqud socks n Ausra. Daly closng prces for he sample frms are derved from Bloomberg and he Venna Sock Exchange [7]. For he relevan perod we flered 75 dvdend announcemens from several housands ncluded n he Dow Jones and Reuers Facva daabase. We defne he announcemen (even) dae as he occason of he very frs offcal saemen on dvdends of he execuve board of he analyzed frm ha can be denfed n he Facva daabase. Ths dffers from mos oher sudes ha defne he announcemen dae as he day he upcomng dvdend s fxed [9]. In many cases he announcemens under consderaon are made several

82 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel monhs before he end of he relevan fscal year for whch he dvdend wll be pad, and do no conan exac nformaon on he level of dvdends bu only on he expeced drecon of dvdend changes (ncrease; consan; decrease). Neher he ex-dvdend day nor he day he dvdend s pad s consdered o be an announcemen day. If he drecon of dvdend change s revsed we consder hs day of revson as an addonal even dae conveyng new nformaon o he marke. One major dffculy n assessng he nformaon conen of dvdend announcemens sems from he fac ha mos saemens on dvdends are combned wh ha of earnngs. Ths makes mpossble o exacly solae he mpac of he dvdend nformaon on sock prces. Therefore even f we observe sgnfcan abnormal reurns whn he dvdend announcemen perod we canno be ceran ha hs abnormaly s solely caused by announced dvdend changes. Alhough our daa sample conans oo lle nformaon for sascal ess we fnd suppor (n several cases of announcemen) for he hypohess ha he marke pus more emphass on saemens abou dvdends han on earnngs, snce when dvdend forecass move n he oppose drecon as forecass on earnngs, sock prce movemens end o be algned wh he former..2. Abnormal reurns mehodology We sar our analyss by defnng he dvdend process o be a marngale, ha s, agens expec fuure dvdends o be unchanged. E[ D,y ] E[D,y ] D,y = 0, () where E[ D,y ] denoes he expeced change n dvdend of frm for year y, E[D,y ] sands for he expeced dvdend of frm for year y and D,y s frm s las year s dvdend. A dvdend announcemen s consdered a posve even f D, > E[D,y ], neural f D, = E[D,y ] and a negave even f D, < E[D,y ], a y a y a where D, y denoes he announced dvdend of company for year y. Ths dvdend expecaon model has s background n he relucance-o-change dvdends hypohess, whch assumes ha managers are averse o change dvdends unless hey perceve subsanal changes n he fuure economc suaon of her frm. Ths saemen s especally rue n case of our sudy, snce we consder announcemens ha ofen precede he acual dvdend change by a subsanal amoun of me. Therefore managers wll be cauous n her projecons, especally n case of possble downward adjusmens. In a nex sep, we calculae log-reurns R, for company on dae. From daly sock prces a close we ge R, = ln P P,,, (2) a y

GARCH Modelng n Ausran Sock Marke 83 where P, sands for he sock prce of company on dae, P, denoes he sock prce of company on dae, and ln denoes he naural logarhm. For each even (dvdend announcemen) n he sample we defne an evenwndow and a pre-even wndow. The even wndow comprses 5 radng days, he announcemen dae ( = 0) plus he wo days before ( = 2, = ) and he wo days afer he announcemen ( = +, = +2). In conras o many oher sudes examnng he mpac of corporae announcemens on sock prces we choose a farly shor even wndow. Ths s jusfed by wo facs: Frs, as s shown by Brown and Warner [6], he longer he even wndow he lower he power of he es sasc. Ths can lead o false nferences abou he sgnfcance of an even. Second, by usng a shor even wndow we can beer conrol for confoundng effecs (oher news relevan for he sock prce of he company). Snce he announcemen day can be deeced exacly n he Facva daabase and elecronc radng makes possble mmedae reacons on new nformaon (buy or sell orders), hs shor even wndow seems o be jusfed. The pre-even wndow covers he 50 radng days pror o he even wndow. For each day of he even wndow we compue he abnormal reurn AR as he dfference beween he acual ex-pos reurn and he secury s normal reurn ha s predced n he absence of he even. Formally, for each announcemen of he analyzed companes we compue AR, = R, E[R, X ], (3) where R, sands for he acual reurn of frm on dae n he even wndow and E[R, X ] denoes he predced reurn condonal on he nformaon se X, where X = (R, 52,,R, 3 ). To model rsk-adjused expeced reurns E[R, X ] we use GARCH meseres models. GARCH mehodology (frs nroduced by Engle n [3] and refned and exended by Bollerslev n [4] and [5]) has proved o be an exremely popular class of non-lnear sochasc processes for fnancal mes seres. To llusrae he model denfcaon we consder general GARCH(p, q) model for a me seres z : z = µ + ε σ 2 = h = a 0 + p = a σ q 2 + = b ε 2 ( 0 ) ε ~ N, (4) h where s he consan, 0 s he error erm, a 0 s he consan erm, a are he parameers for he lagged condonal varance a lag, b are he parameers for he lagged squared error a lag. If sum of parameers a and b s less han one, he uncondonal varance s consan (.e., homoskedasc) and gven by he formula 2 = a0 σ. p q a b = = (5)

84 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel The model denfcaon refers o he mehodology n denfyng he requred sample sze (we choose n = 50 o be approprae), proper orders p and q and order of negraon when he orgnal me seres s nonsaonary. As a frs sep, we conduc un roo ess on he reurn seres over he preeven wndow. To defne he approprae models he followng equaon s esmaed usng ordnary leas squares mehod (OLS): R k, = + δ R, + a, j R, j + ε, j= µ. (6) R, denoes he frs dfferences of reurns of frm on day, and, / and a,j are he parameers of frm s model. We formulae he null hypohess of he me seres R, o be negraed of order,.e. R,.~.I(). Ths means ha he varance of R, goes o nfny as goes o nfny, he random erm ε, n he model has a permanen effec on he value of R, because R, s he sum of all prevous random erms, he expeced me beween crossngs of R, = 0 s nfne, he auocorrelaons end o as goes o nfny. To es he null hypohess we apply he Dckey-Fuller (DF) es sasc whch s defned as δˆ DF =. (7) ˆ σ δ The numeraor n equaon (7) reflecs he esmaor of parameer δ of frm s model, and he denomnaor shows sandard error of parameer δ of frm s model. The number of me lags k s esablshed by means of he mehod proposed by Cambell and Wasley [7], Cambell e al [8], Mlls [8] and Phllps and Perron [9]. In hs mehod a large nal value k s chosen (k = 8), and han hs value wll be gradually reduced by unl es sasc becomes sgnfcan (for k,i WKH WHVW VWDWLVWLF RI WKH DXJPHQWHG DF s sascally sgnfcan, we should accep he alernave hypohess ha he me seres R, s negraed of order zero,.e. R,.~.I(0), so ha he varance of R, s fne and does no depend on, he random erm has only a emporary effec on he value R,, he vaules R, flucuae around her mean of zero, he auocorrelaons decrease seadly n magnude for large enough me lags, so ha her sum s fne. The resuls of he augmened Dckey-Fuller (ADF) ess show ha our sample reurns are eher negraed of order zero (n 70 cases) or order one (only n 5 cases). In he nex sage, we denfy he orders p and q, based on he Akake nformaon creron, and esmae sx dfferen models for he reurn seres n he pre-even wndow: ARCH() (n 32 cases), ARCH(2), ARCH(3), ARCH(4),

GARCH Modelng n Ausran Sock Marke 85 GARCH(,) and GARCH(2,). We hen use he approprae me seres models o predc even-wndow reurns and calculae abnormal reurns (he forecas errors). We hen dvde our me seres of sock reurns no hree clusers, one comprsng announced dvdend ncreases, one for dvdend decreases and one for consan dvdends. Ths dsncon s based on equaon (). For each cluser, we compue average abnormal reurns across sample members for day as follows: AR = N AR, N =, (8) where N sands for he number of evens n a cluser. The sample sandard devaon of AR (= ˆ [ AR ]) for he pre-even perod s calculaed from he me-seres of mean abnormal reurns for each cluser as 3 ˆ [ AR ] = ( * ) 2 49 AR AR. (9) = 52 Noe ha he sasc defned n (9) can be nerpreed as a cross seconal me seres sandard devaon. AR * n equaon (9) defnes he mean abnormal reurn (cross-seconal and me seres) n he pre-even perod: 3 = 52 * AR = AR 50. (0) Fnally, we wsh o es he null hypohess ha he mean abnormal or excess reurn on day of he even wndow s equal o zero. Our es sasc s he rao of mean cross-seconal abnormal reurns and he sandard devaon gven by (9). sa = AR ˆ [ AR ]. () Assumng ha he AR are ndependen and dencally dsrbued and normal, sa has a Suden- dsrbuon under he null hypohess wh (N ) degrees of freedom (see Brown and Warner [6]). A necessary condon for hs assumpon s ha he abnormal reurns are no auocorrelaed. Alhough daly excess reurns are n general non-normal, by a sandard cenral lm heorem (CLT), he cross seconal mean excess reurn converges o normaly as he number of sample secures ncreases. / 2

86 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel 2. Emprcal resuls 2.. Abnormal reurns Our resuls for abnormal reurns over he even wndow for each cluser are summarzed n able. In order o prove sgnfcance by -Suden es we check he hypoheses ha he me seres of mean abnormal reurns n he clusers consdered are normally dsrbued. Usng he Ch-square goodness-of-f sasc, he Shapro-Wlks W sasc and ess based on skewness and kuross, we canno rejec he menoned hypoheses (p-value for all ess s greaer han 0.05). Furhermore auocorrelaons are no sgnfcan a he 5% level. Table. Average daly abnormal reurns for he even wndow n hree clusers Dvdend ncreases Sample sze: 74 Consan dvdends Sample sze: 74 Dvdend decreases Sample sze: 27 Even perod day AR (%) sa AR (%) sa AR (%) sa 2 + 0.456* + 2.026 0.89 0.938 0.077 0.60 + 0.262 +.65 0.79 0.886 0.25 0.523 0 + 0.652** + 2.900 0.007 0.035.287** 2.678 + + 0.059 + 0.263 0.002 0.02 + 0.045 + 0.093 +2 + 0.596* + 2.652 0.244.22 + 0.073 + 0.52 * sgnfcan a he 5% level ** sgnfcan a he % level For he 74 announced dvdend ncreases he average abnormal reurn on he announcemen day s +0.65% (sgnfcan a he % level) and +0.46% (+0.60%) on day = 2 ( = +2) (sgnfcan a he 5% level). We also fnd ha all average abnormal reurns n he even wndow are posve for hs cluser (alhough no all are sgnfcanly dfferen from zero). Ths resul corroboraes he fndngs of oher sudes ha examne wheher dvdend ncreases are nerpreed as posve sgnals by nvesors. In case of consan dvdends (sample sze: 74), he average abnormal reurns are no sascally dfferen from zero on any day of he even wndow. Ths suppors he hypohess ha companes ha leave her dvdends unchanged communcae no sgnfcan new nformaon o he marke. In he cluser of announced dvdend decreases we fnd a sascally sgnfcan average abnormal daly reurn of.29% on day = 0. Ths resul s

GARCH Modelng n Ausran Sock Marke 87 nuve and suppors emprcal fndngs for oher markes ha a cu n dvdend paymens conveys negave nformaon o he publc. In comparson o he abnormal reurns nduced by ncreasng dvdends he repored negave reurn due o an announced conracon n dvdends s much hgher n absolue erms. Ths confrms he general observaon on fnancal markes ha bad news has a greaer mpac on sock reurns han good news. Ths can be seen as an ndcaon ha analyss revse her forecass for fuure earnngs of companes much more srongly n case of dvdend decreases han ncreases. A graphcal llusraon of our resuls s gven n fgure, whch shows average abnormal reurns wh 99% confdence ses for he hree clusers from = 52 o = +2 relave o he announcemen dae. Fgure. Cross-seconal abnormal reurns wh 99% confdence regons for hree clusers over he preeven and even perod 'LYLGHQG LQFUHDVHV &RQVWDQW GLYLGHQG 'LYLGHQG GHFUHDVHV The effec of dvdend announcemens on sock prces s less pronounced when we consder cumulave abnormal reurns (CAR) for he even wndow. For consan dvdends and dvdend decreases he CAR are 0.62% and.05%, respecvely, and no sgnfcan. For dvdend ncreases he CAR s 2.03% and sgnfcanly dfferen from zero a he 5% level. In order o check he relevance of usng GARCH me seres models o replcae he reurn generang process of socks n our sample we es he model

88 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel assumpons. To analyze wheher he resduals (abnormal reurns) n he preeven wndow are whe nose, we frs es he mean values of abnormal reurns for sgnfcance n each pre-even wndow by -Suden es. In all cases he mean value of resduals s no sgnfcanly dfferen from 0 a he 5%. In a nex sep we es homogeney of resduals by usng Engle s ARCH es. Only n four cases (ou of 75) he GARCH effecs (.e. heeroscedascy) s sascally sgnfcan a he 5% level. Fnally we compue he sample ACF (auocorrelaon funcon) and sample PACF (paral auocorrelaon funcon) of resduals for each pre-even wndow o see wheher hey do no form any paern and are sascally nsgnfcan. In addon, we es he auocorrelaon of resduals by usng pormaneau lack of f es. Ths es uses all he resdual sample ACFs as a un o check he jon null hypohess ha he frs k auocorrelaons are no sgnfcan (we chose k = 5). We apply Q es sasc (pormaneau sasc) whch approxmaely follows he ch-square (k m) dsrbuon where m s he number of parameers esmaed n he model. Our fndng s ha n weny wo cases Q slghly exhbs he crcal value a he 5% sgnfcance level (.e. n weny wo cases resduals are sgnfcanly auocorrelaed). Tesng resuls of mean resduals, homoscedascy of varance and auocorrelaon of resduals does no delver sgnfcan evdence agans he null hypohess of resduals o be whe nose. 2.2. Volaly Besdes he level of abnormal reurns, we are also neresed n her second momens, snce varance s an ndcaor of he level of uncerany, as well as he relave mporance of new nformaon o he marke, and affecs he accuracy of our sascal nferences on he levels. We sar by analyzng he me seres of cross-seconal varances of abnormal reurns over he enre me-horzon (pre-even and even wndow) o es wheher he varances from he pre-even perod dffer from hose of he even perod. An llusraon s gven n fgure 2 whch shows cross-seconal varances of abnormal reurns for he hree clusers from = 52 o = +2 relave o he announcemen dae. Fgure 2 shows a sgnfcan ncrease n varances n he even wndow for he consan dvdend and dvdend decrease cluser. The fac ha varances end o ncrease n he even wndow jusfes he resrcon of he model fng o he pre-even wndow. From fgure 2 one can also see ha pre-even varances n he dvdend decrease cluser are n mos cases on a subsanally hgher level han n he oher clusers. Ths can be seen as an ndcaor of rumors abou upcomng negave nformaon ha ncrease uncerany and hence he varance of excess reurns. A consequence of he larger varance n he pre-even wndow s

GARCH Modelng n Ausran Sock Marke 89 ha -sascs for abnormal reurns are generally smaller n hs cluser han for dvdend ncreases (see able ). Table 2 presens he cross seconal varances of excess reurns n he even wndow for each cluser. Whle he varances for dvdend ncreases say relavely consan over me, he varances for consan dvdends and dvdend decreases ncrease by a facor of more han 2 and more han 4, respecvely, on he announcemen day (relave o he day before). Fgure 2. Cross-seconal varances of abnormal reurns for hree clusers over he preeven and even perod 'LYLGHQG LQFUHDVHV &RQVWDQW GLYLGHQG 'LYLGHQG GHFUHDVHV Table 2. Varances of abnormal reurns over he even wndow for hree clusers Dvdend ncreases Sample sze: 74 Consan dvdends Sample sze: 74 Dvdend decreases Sample sze: 27 Even perod day Varance Varance Varance 2 4.989 0-5 5.650 0-5 5.44 0-5 3.590 0-5 3.45 0-5 2.968 0-5

90 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel 0 4.50 0-5 8.386 0-5 2.840 0-5 + 4.85 0-5 3.035 0-5 5.332 0-5 +2 4.542 0-5 4.430 0-5 6.262 0-5 We apply several ess (Cochran s C, Barle s, Harley s and Levene s ess sascs) o check he null hypohess ha cross seconal varances n each cluser are he same for each day n he even wndow agans he alernave hypohess of heeroscedascy along he me dmenson. The resuls of hese ess are presened n able 3 and confrm our earler mpresson from able 2 ha he cross seconal varances are sable n case of dvdend ncreases bu no for consan or decreasng dvdends. Table 3. Varance check of abnormal reurns over he even wndow for hree clusers Dvdend ncreases Sample sze: 74 Consan dvdends Sample sze: 74 Dvdend decreases Sample sze: 27 Tes Sasc p-value Sasc p-value Sasc p-value Cochrane C 0.2325 0.685 0.336 0.000 0.390 0.002 Barle.0059 0.70.0708 0.000.205 0.006 Harley.3897-2.7628-4.3267 - Levene 0.3637 0.835.6085 0.72 0.73 0.572 These observaons allow wo possble conclusons. Frs, hey confrm he usual hypohess ha bad news have a sronger mpac on volaly han good news. In hs sense consan dvdends canno (n mean) be nerpreed as good news. Second, he fac ha for some clusers cross seconal varances flucuae over consecuve days pons owards a clenele effec snce nvesors of dfferen companes reac dfferenly owards smlar nformaon. In lne wh heorecal predcons from behavoral models (see e.g. Frankfurer/Wood [5]) our resuls confrm ha nvesors manly prefer regular and hgher paymens o capal gans. If a company announces hgher dvdends, s clenele does no change as hs mees he preferences of he nvesors. In case of dvdend decreases as well as consan dvdends, hese announcemens mply a change n he cleneles of hese companes, as he dsrbuon of corporae payous does no correspond wh he dsrbuon of nvesors preferences for payous. Therefore varances of abnormal reurns change n hese clusers. The appled ess ndcae ha he varances of abnormal reurns are no homogeneous over he even wndow n he cases of consan and decreasng dvdends. The mos wdely appled es n hs case s Barle s es; p-values of

GARCH Modelng n Ausran Sock Marke 9 hs es are much lower han % n hese wo clusers. I s common pracce n sascs o rejec he hypohess of homogeney of varances n consecuve days f a leas one es rejecs hs hypohess. 3. Non-paramerc es sasc The valdy of our resuls based on GARCH-modelng of sock reurns and he paramerc es sasc s suppored by applcaon of a nonparamerc rank es developed by Corrado [0]. Ths es s based on he ransformaon of each secury s me seres of excess reurns no her respecve rank,.e. K, = rank(ar, ), = -52,,+2. For each day n he even wndow, we compue he es sasc T () u N k ( K, u 28) = =, N σˆ k ( K ) (2) where N k denoes he number of evens n a cluser, u = -2,,+2, and T(u) s asympocally un normal. The esmaor for he sandard devaon of he ranks σ (K) s gven by 2 2 Nk ˆ( ) σ K = (, 28) 55 K. (3) = 52 N k = The resuls of hs es are summarzed n able 4. Table 4. Tesng average daly abnormal reurns for he even wndow n hree clusers by Corrado rank es / 2 Dvdend ncreases Sample sze: 74 Consan dvdends Sample sze: 74 Dvdend decreases Sample sze: 27 Even perod day AR (%) T(u) AR (%) T(u) AR (%) T(u) 2 + 0.456* +.272 0.89 0.909 0.077 0.992 + 0.262 +.200 0.79 0.696 0.25.030 0 + 0.652** + 2.383 ** 0.007 0.972.287**.689 * + + 0.059 + 0.364 0.002 0.857 + 0.045 + 0.869 +2 + 0.596* + 2.078 ** 0.244 0.42 + 0.073 + 0.804 * sgnfcan a he 0% level ** sgnfcan a he 5% level

92 Henryk *XUJXO 3DZHá Majdosz, Roland Mesel In lne wh he -sascs we fnd abnormal reurns n he even wndow o be hghly sgnfcan on day = 0 and = +2 n he dvdend ncrease cluser. The abnormal reurn on = 0 n he dvdend decrease cluser s also sgnfcan a he 0% level. All oher abnormal reurns are no sascally sgnfcan. The resuls of hs nonparamerc rank es suppor our earler fndngs of marke reacons on dvdend changes and suppor he valdy of usng GARCHmodels o generae normal sock reurns n our sudy. 4. Conclusons The fndngs of hs research show ha dvdend polcy s an mporan source of nformaon for nvesors on he Ausran sock marke. In lne wh mos relaed sudes on oher markes we fnd ha dvdend ncreases nduce a sgnfcan posve reacon n sock prces, whereas announced dvdend decreases lead o a fall n sock prces. Consan dvdends leave sock prces unalered. In case of dvdend decreases he varance of abnormal reurns experences a sharp hke on he announcemen day, whch we nerpre as evdence for he ofen-quoed fac ha bad news has a sronger mpac on fnancal markes han good news. Furhermore we fnd ha pre-even varances n he dvdend decrease cluser are on a subsanally hgher level han n he oher clusers. Ths can be seen as an ndcaor of rumors abou upcomng negave nformaon ha ncrease uncerany and hence he varance of excess reurns. We compue non-paramerc rank es sascs o confrm he robusness of our -sascs and fnd ha hey lead o very smlar conclusons. References [] J. Aharony and I. Swary (980). Quarerly dvdend and earnngs announcemens and sockholders' reurns: An emprcal analyss. Journal of Fnance 35, 2. [2] Y. Amhud and M. Murga (997). Dvdends, axes, and sgnalng: evdence from Germany. Journal of Fnance 52, 397 408. [3] P. Asquh and D.W. Mullns (983). The mpac of nang dvdend paymens on shareholders' wealh. Journal of Busness 56, 77 96. [4] T. Bollerslev (986). Generalsed auoregressve condonal heeroscedascy. Journal of Economercs 3, 307 327. [5] T. Bollerslev (987). A condonally heeroscedasc me seres model for speculave prces and raes of reurn. Revew of Economcs and Sascs 69, 542 546. [6] S.J. Brown and J.B.Warner (985). Usng daly sock reurns he case of even sudes. Journal of Fnancal Economcs 4, 3 3. [7] C.J. Campbell and C.E.Wasley (993). Measurng secury prce performance usng daly NASDAQ reurns. Journal of Fnancal Economcs 33, 73-92.

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