NATIONAL BANK OF POLAND WORKING PAPER No. 119

NATIONAL BANK OF POLAND WORKING PAPER No. 9 Liquidiy needs, privae informaion, feedback rading: verifying moives o rade Barosz Gębka, Dobromił Serwa Warsaw 0

Verifying moives o rade Barosz Gębka Newcasle Universiy Business School, 5 Barrack Road, Floor 6, Room 6.06, Newcasle upon Tyne, NE 4SE, UK, b..gebka@ncl.ac.uk Barosz Gębka Barosz Gębka Newcasle Universiy Business School, 5 Barrack Road, Floor 6, Room 6.06, Newcasle upon Dobromił Serwa Newcasle Universiy Business Tyne, School, NE 4SE, 5 Barrack UK, b..gebka@ncl.ac.uk Road, Floor 6, Room 6.06, Newcasle upon Naional Bank of Poland, Tyne, Financial NE 4SE, Sysem UK, Deparmen, b..gebka@ncl.ac.uk ul. Święokrzyska /, 00-99 Warszawa, Poland, dobromil.serwa@nbp.pl Warsaw School of Economics, Insiue Dobromił of Economerics, Serwa al. Niepodległości 64, 0-554 Dobromił Serwa Naional Bank of Poland, Financial Warszawa, Sysem Deparmen, Poland ul. Święokrzyska /, 00-99 Naional Bank of Poland, Warszawa, Financial Poland, Sysem dobromil.serwa@nbp.pl Deparmen, ul. Święokrzyska /, 00-99 Warsaw School of Economics, Warszawa, Insiue Poland, of dobromil.serwa@nbp.pl Economerics, al. Niepodległości 64, 0-554 Warsaw School of Economics, Insiue Warszawa, of Economerics, Poland al. Niepodległości 64, 0-554 Warszawa, Poland We would like o hank Janusz Brzeszczyński and Fabrizio Casallin for helpful suggesions, and Pior Szpunar, Mara Gołajewska and colleagues from he Financial Sysem Deparmen of he Naional Bank of Poland for advice and suppor. We would like o hank Janusz Brzeszczyński and Fabrizio Casallin for helpful suggesions, We and would Pior Szpunar, like o hank Mara Janusz Gołajewska Brzeszczyński and colleagues and Fabrizio from he Casallin Financial for helpful Sysem suggesions, Deparmen and of he Pior Naional Szpunar, Bank Mara of Poland Gołajewska for advice and and colleagues suppor. from he Financial Sysem Deparmen of he Naional Bank of Poland for advice and suppor. Design: Oliwka s.c. 5 Layou and prin: NBP Prinshop 5 5 Published by: Naional Bank of Poland Educaion and Publishing Deparmen 00-99 Warszawa, / Święokrzyska Sree phone: +48 653 3 35, fax +48 653 3 Copyrigh by he Naional Bank of Poland, 0 ISSN 084 64X hp://www.nbp.pl

Conens Conens. Inroducion...3 3. A simple heoreical model of heerogeneous invesors...5 5 3. Economeric specificaion...0 4. Empirical resuls... 5. Conclusions...7 8 References...8 9 Tables and figures... WORKING PAPER No. 9

Absrac Absrac We analyse invesors moives for rading on inernaional sock markes and invesigae wheher evidence for hese moives is robus when ime-varying marke volailiy, changes beween calm and urbulen periods, and exisence of inernaional financial spillovers are conrolled for. Applying he Markov-swiching GARCH specificaion of he sandard model commonly used in he lieraure, we find ha rades conduced due o liquidiy needs or driven by privae informaion canno be idenified unequivocally in any marke, and posiive feedback rading becomes predominan when reurn spillovers from he US marke are aken ino accoun. Keywords: Informed rading, liquidiy rading, feedback rading, reurn auocorrelaion, rading volume, financial spillovers, conagion. JEL classificaion: C3, G, G5 N a i o n a l B a n k o f P o l a n d

Inroducion. Inroducion A series of heerogeneous agen models have been proposed o explain how price changes in financial markes are driven by arrivals of privae informaion and by changes in liquidiy needs or risk aversion of invesors. Predominan moives underlying rading decisions have ofen been sudied by analyzing he ineracion beween reurn auocorrelaion and rading volume. Several auhors (e.g. Campbell e al., 993, Wang, 994, and Llorene e al., 00) demonsrae ha following periods of inensive rading, sock reurns end o rever (coninue) if he majoriy of rades were conduced due o liquidiy needs or changes in risk aversion (due o privae informaion). In addiion, posiive (negaive) reurn auocorrelaion poins o he presence of negaive (posiive) feedback rading (e.g. Senana and Wadhwani, 99). The quesion invesigaed in his paper is wheher he predominan rading moives on large inernaional sock exchanges, found using sandard linear regression models, are sill presen afer aking ino accoun inernaional informaion spillovers, ime-varying reurn volailiy, and changes beween calm and urbulen regimes in hese financial markes. This quesion is based on hree presumpions. Firs, informaion from inernaional markes is an imporan deerminan of sock reurns on local markes and may affec he observed links beween consecuive reurns and rading volume (see, e.g., Gagnon and Karolyi, 006, for a review). Second, exising empirical sudies on rading moives yield inconclusive resuls, as some auhors find evidence of a lack of informaiveness of rades (Campbell e al., 993, Conrad e al., 994, Gebka, 005), whereas ohers argue in favour of ransacions mainly driven by privae informaion (Cooper, 999, Llorene e al., 00, Ciner and Karagozoglu, 008, Bajo, 00). Finally, a subsanial body of research shows ha invesors risk preferences, invesmen sraegies, inclinaion o panic, herding behaviour, conagion effecs and heerogenous inerpreaion of informaion all change during crisis periods (Shalen, 993, Kaminsky e al., 004, Couder and Gex, 008). We anicipae ha some moives for rading may change or become insignifican when ime-varying reurn volailiy or changes beween calm and urbulen periods are conrolled for. Addiionally, financial spillovers from he US marke have been shown o affec reurns on oher inernaional sock exchanges (e.g. Gagnon and Karolyi, 006, Ibrahim and Brzeszczyński, 009, Ashgarian and Nossman, 0), bu are usually unaccouned for in he sudies of feedback rading, poenially leading o biased conclusions abou he naure of his phenomenon. We es for he validiy of hese premises by consrucing a wo-regime Markov swiching regression model (wih one calm and 3 one urbulen regime) where he parameers idenifying he rading moives and financial spillovers are allowed o change depending on he curren sae of he marke. The GARCH specificaion in each regime is responsible for accurae modelling of residual volailiy (e.g., Haas e al., 004). Resuls from some recen WORKING PAPER No. 9 sudies confirm he soundness of our approach. For example, Baele and Ingelbrechs (00) find regime swiching effecs of regional and global facors on local sock reurns in 3

Inroducion We es for he validiy of hese premises by consrucing a wo-regime Markov swiching regression model (wih one calm and one urbulen regime) where he parameers idenifying he rading moives and financial spillovers are allowed o change depending on he curren sae of he marke. The GARCH specificaion in each regime is responsible for accurae modelling of residual volailiy (e.g., Haas e al., 004). Resuls from some recen sudies confirm he soundness of our approach. For example, Baele and Ingelbrechs (00) find regime swiching effecs of regional and global facors on local sock reurns in inernaional sock markes. In he sudy of Amira, Taamoui and Tsafack (0) volailiy of sock reurns has a sronger impac on iner-marke reurn correlaion during down-urn periods han in oher imes. The conribuions of his paper are as follows. On heoreical grounds, we show how differen moives o rade (liquidiy needs, privae informaion, feedback sraegy) can be unified wihin one framework explaining auocorrelaion of reurns. On mehodological grounds, we argue in favour of applying muliple regime models o idenify periods of high and low volailiy, as boh heoreical consideraions and our empirical resuls indicae heir superioriy vis-à-vis single regime counerpars. Furher, our resuls demonsrae poenial deficiencies of he empirical framework inroduced by Campbell e al. (993) o idenify prevailing moives o rade. Lasly, empirical evidence repored in his paper highlighs he imporance of posiive feedback rading and inernaional spillovers as major deerminans of sock reurn behaviour. In he nex secion we presen a simple heoreical model explaining he reurns on he sock marke wih heerogeneous ypes of invesors. Secion 3 describes economeric mehodology and model specificaions used in our invesigaion. Secion 4 conains empirical resuls and he final secion concludes. 4 4 N a i o n a l B a n k o f P o l a n d

A simple heoreical model of heerogeneous invesors. A simple heoreical model of heerogeneous invesors In his secion, we presen a series of exensions o he Senana and Wadhwani (99) model (SW for shor) of feedback rading. By including liquidiy and informed rading as well as financial spillovers from abroad, we show analyically how auocorrelaion in sock reurns depends on he exisence of calm and volaile regimes, pas rading volume, and evens on he global marke.. The Senana and Wadhwani (99) model of feedback rading In he model proposed by Senana and Wadhwani (99) wo ypes of raders are assumed o ac on he marke, i.e., fundamenal raders (smar money) and non-informed raders, also called feedback raders. Fundamenal raders demand is proporional o expeced excess reurn and inversely proporional o he risk premium: Q 0 E ( R ) R, () ( ) where Q is he fracion of shares held by fundamenal raders, E ( R ) is he reurn a ime expeced a ime, R is he risk-free ineres rae, and ( ) denoes he risk 0 premium, he laer being a funcion of volailiy risk,. The demand of feedback raders is a funcion of pas reurns: Y R. () Y is he fracion of shares held by feedback raders. For 0 ( 0), he raders will be involved in he posiive (negaive) feedback rading sraegy, implying buying a ime afer an observed price increase (decline) a. The marke equilibrium requires ha he aggregae demand equals aggregae supply of, i.e., Q Y. Afer subsiuion of eq. () and () and rearrangemen, his yields: 0 E ( R ) R ( ) [ ( )] R. (3) Auocorrelaion in reurns is a funcion of feedback rading: posiive (negaive) feedback rading resuls in negaive (posiive) auocorrelaion as 0 ( 0).Wih no feedback rading presen ( 0 ), he formula reduces o he CAPM equaion, i.e., he expeced excess 0 reurn on an asse is solely a funcion of risk: E ( R ) R ( ) (e.g. Meron, 980).. Inroducing liquidiy- and privae informaion-moivaed rades ino he SW model Several auhors have presened models 5 where liquidiy or informed rading affec asse prices and rading volume (e.g. Campbell, Grossman, and Wang, 993, Wang, 994, Llorene, Saar, Michaely, and Wang, 00). They show ha in equilibrium, if liquidiy rading prevails, periods wih inense rading are characerized by large price movemens, as WORKING PAPER No. 9 5 he marke is rying o absorb he buying/selling pressure of liquidiy rades. However, on subsequen days, prices will end o reurn o heir fundamenal values, hereby exhibiing a

A simple heoreical model of heerogeneous invesors. Inroducing liquidiy- and privae informaion-moivaed rades ino he SW model Several auhors have presened models where liquidiy or informed rading affec asse prices and rading volume (e.g. Campbell, Grossman, and Wang, 993, Wang, 994, Llorene, Saar, Michaely, and Wang, 00). They show ha in equilibrium, if liquidiy rading prevails, periods wih inense rading are characerized by large price movemens, as he marke is rying o absorb he buying/selling pressure of liquidiy rades. However, on subsequen days, prices will end o reurn o heir fundamenal values, hereby exhibiing a paern of reversals and generaing negaive auocorrelaion in sock reurns. Should mos rades be driven by privae informaion, however, price movemens induced by agens capializing on heir informaion and accompanied by high rading volume will end o coninue on subsequen days, as he informaion becomes more widely available and generaes furher rades by broader masses of raders. These price coninuaions following high volume days will induce posiive correlaion in reurns. Our firs exension o he SW model is o incorporae rading by liquidiy- and informaion-moivaed agens. We do no aim o consruc an original heoreical model, bu raher o reflec he main characerisics of he classical models of Campbell e al. (993), Wang (994), and Llorene e al. (00), namely how curren reurns and volume predic fuure reurns. Therefore, insead of analysing how invesors wih heerogeneous risk aversion, wealh, or access o privae informaion rebalance heir porfolios afer informaion or liquidiy shocks, we add a group of invesors who use a simple rading rule o accoun for hese shocks. We assume ha here exiss a group of invesors whose demand for socks depends on pas reurns and volume of rades: L V R, (4) where L is he fracion of asses held by his group of invesors and V denoes rading volume a ime. Wheher rading of he group analysed here is driven primarily by liquidiy moives or by privae informaion of marke paricipans is refleced in he sign of he parameer. We inerpre his parameer in he following paragraphs. Formula (4), afer simple mahemaical rearrangemens presened below, fis well he economeric regressions explaining fuure reurns wih curren volume and reurns, derived by Campbell e al. (993, Theorem, p.98) and Llorene e a. (00; see equaions 9 and, and he discussion on p. 0). I also incorporaes he argumens concerning he effecs of liquidiy and informaion driven rades on fuure reurns. In he model of Campbell e al. (993) a group of invesors characerized as marke makers accommodaes buying or selling pressure from noninformaional raders. In line 6 wih his convenion, we call he group of raders following he rule represened in formula (4) marke makers. 6 Prevalence of non-informaional rading The demand of he marke makers group parially depends on liquidiy-driven rading by oher invesor groups. Specifically, if buy orders are generaed for liquidiy reasons a ime, rading volume V is high, and prices rise, i.e., R is high. The buying pressure will N a i o n a l B a n k o f P o l a n d cause a emporary increase of prices and he marke maker will increase supply of asses off

In he model of Campbell e al. (993) a group of invesors characerized as marke makers accommodaes buying or selling pressure from noninformaional raders. In line A simple heoreical model of heerogeneous invesors wih his convenion, we call he group of raders following he rule represened in formula (4) marke makers. Prevalence of non-informaional rading The demand of he marke makers group parially depends on liquidiy-driven rading by oher invesor groups. Specifically, if buy orders are generaed for liquidiy reasons a ime, rading volume V is high, and prices rise, i.e., R is high. The buying pressure will cause a emporary increase of prices and he marke maker will increase supply of asses off is invenories o mee he exra demand. In he nex period, he price will end o reverse o is fundamenal value (e.g. Campbell e al., 994, Wang, 994, Llorene e al., 00). The demand of he marke makers will be high a, as hey will ry o resore heir opimal asse invenories and will be able o do so a a lower price a ime (due o price reversal). Hence, high values of V R will resul in marke makers high demand L a ime ( >0). The opposie happens when liquidiy needs dicae sales of asses a ; his will lead o high V and negaive R, and he marke makers will accommodae he selling pressure by buying asses. A ime, when prices sar o reverse o he fundamenal values, he marke maker s demand will be low, as she purchased he asses a for a lower price and migh insead wan o reduce her invenories a, selling for a higher price. Therefore, low values of V R, due o falling prices a ( R <0), will resul in low demand L a ime. In sum, if liquidiy rading prevails, hen >0. Prevalence of informed rading Trades can also be generaed by agens acing on privae informaion. If his ype of rading prevails, he marke maker will ry o ake advanage of i by mimicking he acions of informed invesors. Hence, on a day wih heavy rading (high V ), increasing prices ( R >0) generaed by higher demand from informed raders will be inerpreed by he marke maker as a signal of posiive informaion, and she will increase her demand, oo. A ime, informaion coninues o reach broader groups of invenors who increase heir demand and push he price level even furher up, i.e., price coninuaion will resul. However, he marke maker s demand L a will be low as she would have bough a for a lower price. If anyhing, she migh wan o sell for a high price a. Hence, a high value of V R 7 will resul in low demand L of he marke maker in period ( <0). As for negaive privae informaion, he opposie will occur: selling by informed invesors a will drive he volume up and prices down ( R <0), a behaviour which will be mimicked by he marke maker (i.e., low demand for he asse a -, possible shorselling). As prices a coninue o fall o adjus o he new, lower fundamenal value, he marke maker will be more willing o buy for a low price o resore her iniial invenories as well as o capialize on he price difference beween and. Hence, a low value of V R (due o R <0) will resul in her high demand L a ime ( <0). In sum, if WORKING PAPER No. 9 7 informed rading prevails, <0. Including L (eq. (4)) ino he model of Senana and Wadhwani (99) yields

As for negaive privae informaion, he opposie will occur: selling by informed invesors a will drive he volume up and prices down ( R <0), a behaviour which will A simple heoreical model of heerogeneous invesors be mimicked by he marke maker (i.e., low demand for he asse a -, possible shorselling). As prices a coninue o fall o adjus o he new, lower fundamenal value, he marke maker will be more willing o buy for a low price o resore her iniial invenories as well as o capialize on he price difference beween and. Hence, a low value of R V R (due o informed rading prevails, <0. Including <0) will resul in her high demand L a ime ( <0). In sum, if L (eq. (4)) ino he model of Senana and Wadhwani (99) yields Q Y L in he equilibrium, which leads o he formula: E 0 ( R ) R ( ) [ ( ) ( ) V ] R. (5) If liquidiy rading prevails ( 0 ), negaive reurn auocorrelaion should be observed on days wih heavy rading, ( ) 0. Conrary, prevalence of rading based on privae informaion ( 0) will induce posiive auocorrelaion in reurns: ( ) 0. These resuls correspond o he oucomes presened by Campbell e al. (993), Wang (994), and Llorene e al. (00). If none of he moives, liquidiy or privae informaion, prevails on he marke (or boh are nonexisen), 0 and he model is reduced o ha of SW (99). If no significan feedback rading exiss, 0 and he model is he CAPM..3 Accouning for he impac of he global marke in he SW model In a globalized world, vanishing financial accoun conrols, ransacion coss, and increasing correlaions of business cycles induce local invesors o observe news and sraegies of acors on he foreign markes. For insance, feedback raders look for signals of upcoming upward rends in prices by observing movemens in no only domesic bu also foreign prices. Similarly, agens acing as marke makers, be i as liquidiy providers or in response o informed rading, are no resriced o heir domesic markes and can reac o evens occurring abroad, oo. This is especially rue since here are global commonaliies in liquidiy (Brockman, Chung, and Pérignon, 009) and privae informaion: liquidiy needs experienced abroad migh spill over o he domesic marke and privae informaion raded on abroad migh be relevan for asses raded domesically, 8 oo. The demand funcion of foreign rend wachers will be Y R (Faff, Hilier and McKenzie, 005) and he demand of marke makers for domesic asses will be parially driven by foreign liquidiy and privae informaion, L V R (aserisks denoe variables relaed o foreign markes). Puing hese foreign moives ino he equilibrium condiion yields: Q Y Y L L. Afer subsiuion, we obain: 8 E ( R ) R 0 ( ) [ ( ) ( ) V ] R [ ( ) ( ) V As can be seen, spillovers from a foreign marke can be measured by ( ) ( ) V ] R. I is also possible o differeniae beween spillovers due o (6) N a i o n a l B a n k o f P o l a n d feedback rading (measured by ( ) ) and due o liquidiy/privae informaion consideraions (measured by ) V ). (

A simple heoreical model of heerogeneous invesors WORKING PAPER No. 9 9 9 driven by foreign liquidiy and privae informaion, R V L (aserisks denoe variables relaed o foreign markes). Puing hese foreign moives ino he equilibrium condiion yields: L L Y Y Q. Afer subsiuion, we obain: 0 ] ) ( ) ( [ ] ) ( ) ( [ ) ( ) ( R V R V R R E (6) As can be seen, spillovers from a foreign marke can be measured by ) ( ) ( V. I is also possible o differeniae beween spillovers due o feedback rading (measured by ) ( ) and due o liquidiy/privae informaion consideraions (measured by ) ( V ).

Economeric specificaion 3. Economeric specificaion We obain an empirical version of he model (6) by assuming raional expecaions: R c ( R, (7) V ) R ( V ) where R E ( R ) and unexpeced reurns ~ iid (0, ). The parameers: 0 c ( ), ( ), ( ), ( ), ( ) all R 3 depend on he measure of risk, i.e., reurn volailiy. Model (7) embeds several approaches proposed in he lieraure. If we assume parameers c, α, α, β and β o be ime-invarian, i reduces o he approach used in Gagnon and Karolyi (003, 009). If α =β =0, he model collapses o he one proposed in Faff e al. (005) o analyse feedback rading and iner-marke spillovers, and for β =β =0, i mimics he approach o analyse informaional moives o rade inroduced by Campbell e al. (993) and Llorene e al. (00). Lasly, for α =β =β =0, i would resul in he Senana and Wadhwani (99) model of feedback rading. Model (7) can be esimaed for any marke, wih parameers capuring reurn auocorelaion in low and high-volume insances, and parameers measuring he inensiy of cross-border spillovers from he global marke, again differeniaed beween hose riggered by high volume ( ) and hose following periods of normal level of rading aciviy ( ). In his way, we are able o invesigae wheher cross marke linkages affec resuls on he posulaed rading moives (e.g., Gagnon and Karolyi, 009). We propose o model he dependency of parameers c, and on volailiy by esimaing he equaion (7) in he Markov-swiching framework, which allows regression parameers o differ beween low and high volailiy regimes and does no impose any specific funcional form on he relaionship beween risk and auocorrelaion, unlike previous approaches (Senana and Wadhwani, 99). The parameers c, and are allowed o change heir values beween wo regimes, one wih low (calm periods) and one wih high (urbulen periods) volailiy, o capure he ime-varying naure of moives o rade. This is done empirically by esimaing equaion (7) using a Markov swiching regression wih GARCH (,) effecs, using he novel approach of Hass e al., (004). Therefore, our model becomes: R c ( R, (8a) s s,, s, s V ) R (, s, s V ), (8b) 0 where ~ iin(0, ) probabiliy marix: s is a Markov chain wih finie sae space,, 0 S and a ransiion p p P. (8c) p p The condiional residual variance in regime s follows he GARCH(,) equaion: s, 0, s, s, s s, N a i o n a l B a n k o f P o l a n d. (8d)

Economeric specificaion where ~ iin(0, ) probabiliy marix: s is a Markov chain wih finie sae space,, S and a ransiion p p P. (8c) p p The condiional residual variance in regime s follows he GARCH(,) equaion:. (8d) s, 0, s, s, s s, Boh mean and variance equaions have parameers ha swich heir values depending on he regime of he model (approximaing calm or urbulen sae of he marke). Thus, mean reurn and is variance also change in calm and urbulen regimes. The Markov swiching effec no only allows for idenifying periods of increased reurn volailiy, i also capures persisence of high and low volailiy regimes a feaure observed on he markes, bu is difficul o describe using oher regime swiching models, e.g., hreshold regressions or srucural change models. The regimes are ypically inerpreed as calm and urbulen (or even crisis) periods on financial markes. Our approach also accouns for heeroscedasiciy of sock reurns, as sandard GARCH models do. We compare he general model specificaion (8) wih more resricive specificaions ofen used in empirical invesigaions, formulaed by assuming: only one volailiy regime on he sock marke, no impac from he foreign markes, no GARCH effecs (no condiional persisence of residual reurn volailiy). In our empirical invesigaion we show ha assuming one or more of hese consrains can lead o he resuls ha are significanly differen from hose obained using he mos general model. We also demonsrae ha he resriced versions of he model are rejeced using saisical ess. 3 WORKING PAPER No. 9

Empirical resuls 4 4. Empirical resuls Model (8) and is consrained versions were esimaed for daily reurn series of sock 4. marke Empirical indices resuls for each of he following counries: Canada, France, Germany, Ialy, Japan, and he Model UK, for (8) he and period is consrained 3/03-990-3/03/00. versions were esimaed To capure for he daily impac reurn of series inernaional of sock financial marke indices spillovers for each on rading of he moives, following some counries: model specificaions Canada, France, incorporae Germany, lagged Ialy, reurns Japan, and rading he UK, volume for he from period he 3/03-990-3/03/00. US (he foreign marke). To To capure measure he he impac daily rading of inernaional volume, we financial use a spillovers proxy of urnover on rading raio moives, (number some of model socks specificaions raded o socks incorporae ousanding), lagged derended reurns by and aking rading logs volume and from subracing he US (he a one-year foreign marke). backward-moving To measure average he daily from rading daily volume, daa (Campbell we use a proxy e al., of 993, urnover Llorene raio e (number al., 00). of All socks daa raded are from o socks Daasream. ousanding), derended by aking I should logs and be noed subracing ha, alhough a one-year he heoreical backward-moving models describe average he from volume-reurn daily daa (Campbell relaionship e for al., individual 993, Llorene securiies, e al., heir 00). implicaions All daa are have from also Daasream. been exensively esed on porfolio I should daa, boh be noed using ha, he alhough resuling he empirical heoreical model models similar describe o our he equaion volume-reurn (7) on relaionship markewide for daa individual (i.e. index securiies, reurns and heir volume, implicaions e.g., have Campbell also been e al., exensively 993, Gagnon esed and on porfolio Karolyi, 003) daa, as boh well using as reurns he resuling and volume empirical of porfolios model from similar a conrarian o our sraegy equaion (Conrad (7) markewide al., 994, daa Coopers, (i.e. 999, index Parisi reurns and and Acevedo, volume, 00, e.g., Campbell Gebka, 005, e al., Alsubaie 993, Gagnon and Najand, and 009). Karolyi, Similarly, 003) as well he Senana as reurns and and Wadhwani volume of (99) porfolios model from of a conrarian feedback rading sraegy has (Conrad been widely e al., 994, esed Coopers, on index 999, raher Parisi han and individual Acevedo, securiies 00, Gebka, reurns 005, (e.g., Alsubaie Koumos and 997, Najand, Bohl and 009). Siklos, Similarly, 008, he Dean Senana and and Faff, Wadhwani 008). Using (99) he model proposed of feedback empirical rading framework has been on aggregae widely esed daa on allows index o raher conclude han abou individual he average, securiies or reurns dominan, (e.g., moive Koumos for rading 997, Bohl on a and given Siklos, marke 008, (if such Dean a dominan and Faff, moive 008). is Using presen) he raher proposed han empirical providing framework insighs ino on aggregae heerogeneous daa moives allows o underlying conclude rading abou he in individual average, or securiies. dominan, moive for rading on a given 4.. Evidence marke on (if predominan such a dominan moives moive o rade is presen) raher han providing insighs ino heerogeneous The relevan moives esimaion underlying resuls rading of model in individual (8) and securiies. is resriced versions are presened in 4.. Table Evidence. The firs on predominan hree columns moives wih numbers o rade conain parameer esimaes of regressions wihou The financial relevan spillovers esimaion from resuls abroad of ( model (8) and 0 ), is while resriced he laer versions five columns are presened conain esimaes Table. The from firs he hree regressions columns accouning wih numbers for spillovers conain from parameer he US esimaes (as in model of regressions (8)). For each wihou counry financial eigh spillovers model specificaions from abroad ( are considered. 0 ), while Firs, he he laer regressions five columns are esimaed conain using esimaes ordinary from leas he regressions squares and accouning assuming for no GARCH spillovers effecs. from he These US models (as in model are denoed (8)). For as each SRR counry (single-regime eigh model regressions). specificaions The saisical are considered. significance Firs, of he parameers regressions is assessed are esimaed using using sandard The sock ordinary indices -saisics, leas are oal squares bu marke he and ess indices assuming employing calculaed no by a GARCH Daasream block-boosrap effecs. excep for These mehod Canadian models provide S&P/TSX are very denoed Composie similar as Index and German DAX 30 index. Series for some counries are marginally shorer due o unavailabiliy of daa. resuls Spillovers and from he he saisics US marke adjused are lagged wih by one a Newey-Wes period o accoun mehod for he are fac marginally ha he US marke less significan. closes afer he European and Asian markes (e.g., Dungey and Marin 007; Gagnon and Karolyi 009). In our empirical resuls, Second, The sock even he indices his GARCH are oal lagged effecs marke indices informaion are from incorporaed calculaed by he US marke o Daasream regressions excep (possibly no in for reflecing order Canadian o all accoun S&P/TSX possible news for Composie changing from he Index and German DAX 30 index. Series for some counries are marginally shorer due o unavailabiliy of daa. marke, bu surely adding more informaion o he empirical marke model) sill allows us o negae he volailiy of reurns on sock markes (SRR-GARCH). Third, he parameers of he models conjecure Spillovers from he US marke are lagged by one period o accoun for he fac ha he US marke closes afer from some earlier sudies ha negaive feedback raders and non-informaional rades dominae sock he European and Asian markes (e.g., Dungey and Marin 007; Gagnon and Karolyi 009). In our empirical markes. resuls, are presened even his lagged in he informaion wo regimes from he of US he marke Markov (possibly swiching no reflecing regressions all possible which news from capure he marke, bu surely adding more informaion o he changing moives o rade in calm and urbulen empirical marke model) sill allows us o negae he periods. Boh regime-swiching models conjecure from some earlier sudies ha negaive feedback raders and non-informaional rades dominae sock markes. assuming ime-invarian volailiy (MSR) and hose wih GARCH effecs (MSR-GARCH) are considered. Lasly, all models are esimaed wih and wihou inernaional spillovers. Inroducing GARCH(,) effecs ino our Markov swiching models usually reduces N a i o n a l B a n k o f P o l a n d persisence of a leas one regime, i.e., one of he parameers p or p is significanly smaller han (similar o he empirical resuls in Haas e al., 004). Therefore, in he

Empirical resuls SRR (single-regime regressions). The saisical significance of parameers is assessed using sandard -saisics, bu he ess employing a block-boosrap mehod provide very similar resuls and he saisics adjused wih a Newey-Wes mehod are marginally less significan. Second, he GARCH effecs are incorporaed o regressions in order o accoun for changing volailiy of reurns on sock markes (SRR-GARCH). Third, he parameers of he models are presened in he wo regimes of he Markov swiching regressions which capure changing moives o rade in calm and urbulen periods. Boh regime-swiching models assuming ime-invarian volailiy (MSR) and hose wih GARCH effecs (MSR-GARCH) are considered. Lasly, all models are esimaed wih and wihou inernaional spillovers. Inroducing GARCH(,) effecs ino our Markov swiching models usually reduces persisence of a leas one regime, i.e., one of he parameers p or p is significanly smaller han (similar o he empirical resuls in Haas e al., 004). Therefore, in he empirical invesigaion we resric condiional variance in one of he regimes by seing 0 or 0 o ensure ha boh regimes are persisen ( p or p are greaer, s, s, s han 0.95), hence he model capures calm and urbulen saes wih a long duraion raher han possible ouliers in one of he saes. The significance of parameers in he laer hree specificaions is measured using robus -saisics. The classical SRR models wih no inernaional spillovers included poin o he presence of posiive reurn auocorrelaion ( >0) following days wih average levels of rading aciviy in four ou of seven counries. This resul could indicae he predominan presence of negaive feedback raders on hese markes (Senana and Wadhwani, 99) bu could also be driven by non-synchronous rading (Lo and MacKinlay, 990), ime-varying expeced reurns (Conrad and Kaul, 988) or ransacion coss (Mech, 993). The negaive values of parameer for all counries (significan in five markes) sugges ha he majoriy of rades on high-volume days have been conduced due o non-informaional moives, resuling in price reversals. When more precise models are employed o conrol for changing volailiy and saes of he marke (i.e., SRR-GARCH, MSR, and MSR-GARCH), he significan posiive auocorrelaion of reurns remains in Canada, France and Japan. However, he noninformaional moives o rade dominae only in Germany and France. Negaive values of he parameer remain in all specificaions (no in all regimes), bu hey are rarely saisically significan. The inclusion of lagged reurns and volume from he US marke ino he four model specificaions also drasically affecs he inerpreaion 3 of moives o rade, as discussed below. In addiion, for nearly all markes, models and regimes he parameer is significanly larger han zero, showing a srong posiive impac of US reurns on inernaional sock reurns. According o Faff e al. (005), his resul can also be inerpreed as evidence of prevalence of negaive feedback rading on foreign news. One imporan effec of his US impac is he swich of he domesic auocorrelaion WORKING PAPER No. 9 3 parameer from he posiive value observed in SRR specificaions o he significanly negaive value in all specificaions in five ou of six markes. This resul could sugges ha 4

4 4 The inclusion of lagged reurns and volume from he US marke ino he four model Empirical resuls specificaions also drasically affecs he inerpreaion of moives o rade, as discussed below. In addiion, for nearly all markes, models and regimes he parameer is significanly larger han zero, showing a srong posiive impac of US reurns on inernaional sock reurns. According o Faff e al. (005), his resul can also be inerpreed as evidence of prevalence of negaive feedback rading on foreign news. One imporan effec of his US impac is he swich of he domesic auocorrelaion parameer from he posiive value observed in SRR specificaions o he significanly negaive value in all specificaions in five ou of six markes. This resul could sugges ha he presence of negaive feedback raders on hese sock exchanges indicaed by purely domesic models was spurious and due o model misspecificaion; when a correc model wih inernaional spillovers is applied, resuls poin o he prevalence of posiive feedback rading. Ineresingly, he excepional marke is Japan, he only marke wih robus impac of boh US variables on local sock reurns. The second effec of using models accouning for inernaional spillovers is a much weaker evidence of non-informaional moives o rade. When single-regime regressions esimaed wih OLS mehod are considered, he negaive values of he parameer are presen in five cases, bu hey are saisically significan only in hree cases. The resuls from SRR-GARCH, MSR and MSR-GARCH specificaions are less likely o show dominance of non-informaional moives as hey are found o be significan in only hree ou of eigheen models. Hence, resuls from simple models seem o be inaccurae, as more general, superior model specificaions repor much weaker evidence of prevalence of liquidiy-moivaed rading. In fac, he esimaes obained do no allow o disinguish beween liquidiy- and informaion-moivaed rading, as is mosly insignifican. As for he rading based on foreign liquidiy and privae informaion, mos esimaes of are insignifican. This resul furher demonsraes ha he approach employed in his paper and originaed by Campbell e al. (993) canno disinguish beween moives o rade, a leas for he counries and daily reurns daa used here. The only excepion is Japan, a counry wih significanly negaive esimaes of. This resul is in line wih Gagnon and Karolyi (003) and suggess ha heavy rading in he US is believed by he marke paricipans in Japan o be driven by liquidiy needs, raher han o convey privae informaion abou US raded companies. To sum up, we observe a subsanial impac of he US variables on all markes invesigaed. Posiive feedback raders dominae 4 on four ou of six markes ( <0) and negaive feedback raders do no dominae anywhere according o he mos general MSR- GARCH models, while he mos consrained SRR models idenify negaive feedback rading in four markes and no posiive feedback rading. This is in line wih he lieraure reporing he dominan role of posiive feedback rading, afer conrolling for ime-varying volailiy of sock reurns (e.g., Koumos 997, Bohl and Siklos, 008, Dean and Faff, 008). Similarly, he finding of almos no evidence of prevailing informed or liquidiy rading moives in MSR-GARCH models conradics he evidence of predominan liquidiy moives on some N a i o n a l B a n k o f P o l a n d markes obained from he single-regime regressions. Ye again, resuls generaed using model specificaions accouning for ime-varying volailiy, regimes and inernaional

negaive feedback raders do no dominae anywhere according o he mos general MSR- GARCH Empirical resulsmodels, while he mos consrained SRR models idenify negaive feedback rading in four markes and no posiive feedback rading. This is in line wih he lieraure reporing he dominan role of posiive feedback rading, afer conrolling for ime-varying volailiy of sock reurns (e.g., Koumos 997, Bohl and Siklos, 008, Dean and Faff, 008). Similarly, he finding of almos no evidence of prevailing informed or liquidiy rading moives in MSR-GARCH models conradics he evidence of predominan liquidiy moives on some markes obained from he single-regime regressions. Ye again, resuls generaed using model specificaions accouning for ime-varying volailiy, regimes and inernaional spillovers conradic hose obained from simple models. In he nex secion, we demonsrae ha he former provide a beer daa fi han he laer, herefore i is jusified o say ha simple models are inferior and can generae incorrec resuls. 4.. Relaive performance of empirical models applied We aim o demonsrae ha he noably differen resuls beween he unresriced models and hose assuming srong resricions on parameers are due o he fac ha he laer are a poor descripion of reurns on he six (plus he US) sock markes in comparison o he unresriced MSR-GARCH models. Our esing sraegy is o sar wih he mos resricive specificaions and verify more general specificaions if needed (i.e., specific o general). Firs, we noe ha GARCH effecs are saisically significan in each specificaion of he single-regime regression (cf. he firs row of Table ). This suggess ha he OLS esimaion echnique may provide no only inefficien bu also biased parameer esimaes even when he single-regime specificaions are correc (Hamilon, 00). Second, we look a he esimaed single-regime specificaions of he model, conrolling for he GARCH effecs in residuals (SRR-GARCH). Using he moving window echnique, we esimae he parameers and find ha heir values change significanly in differen periods (cf. Figure ). This is especially imporan for he parameers and as i affecs economic inerpreaion of predominaing rading sraegies and moives o rade. We find parameers of mos models o vary significanly over ime in he invesigaed ime inerval, as demonsraed in Figure. The changing parameer values may sugges ha he parameers depend on some exernal facors, e.g., marke volailiy as in he models (6) and (8). 5 Moreover, we es he sabiliy of he parameers and he linear specificaion of each model using he Chow es and he RESET es, respecively. Boh ess rejec he linear specificaion wih sable parameer values for he overwhelming majoriy of cases (cf. he second and hird row of Table ). These resuls sugges ha a nonlinear specificaion such as MS may beer explain sock reurns on he analyzed markes. The wo-regime specificaion describing he calm and urbulen regimes on he sock markes seems reasonable and several sudies have already found he Markov swiching models successful in explaining changes in asse prices (e.g. Hamilon, 008 and ciaions herein). Neverheless, i is difficul o formally es he presence of wo regimes in he Markov swiching framework agains he null hypohesis of a single regime due o some parameers being unidenified under he null hypohesis. The ypically applied likelihood raio (LR), F or Lagrange muliplier ess do no have heir sandard disribuions and WORKING PAPER No. 9 5 4

4 second and hird row of Table ). These resuls sugges ha a nonlinear specificaion such as MS may beer explain sock reurns on he analyzed markes. Empirical resuls The wo-regime specificaion describing he calm and urbulen regimes on he sock markes seems reasonable and several sudies have already found he Markov swiching models successful in explaining changes in asse prices (e.g. Hamilon, 008 and ciaions herein). Neverheless, i is difficul o formally es he presence of wo regimes in he Markov swiching framework agains he null hypohesis of a single regime due o some parameers depend being unidenified on some exernal under facors, he null e.g., hypohesis. marke volailiy The ypically as in he applied models likelihood (6) and (8). raio (LR), F or Lagrange muliplier ess do no have heir sandard disribuions and simulaion Moreover, echniques we need es he o be sabiliy used o of derive he parameers approximaed and criical he linear values. specificaion of each model using We employ he Chow he es modified and he LR RESET es of es, Hansen respecively. (99), Boh where ess he rejec null hypohesis linear specificaion assumes he wih linear sable single-regime parameer regression, values for while he overwhelming he alernaive majoriy hypohesis of cases allows (cf. one he second regression and parameer hird row and of Table he residual ). These variance resuls o sugges change ha values a nonlinear depending specificaion he regimes such as of MS calm may and beer urbulence. explain As sock our ineres reurns on is in he he analyzed changes markes. of dominan rading moives, we selec he parameer The wo-regime in he regression specificaion o change describing beween he calm regimes. and urbulen Hansen (99) regimes argues on he ha sock he es markes saisic seems may reasonable in heory be and raher several conservaive, sudies have i.e., already i may rejec found he he false Markov null hypohesis swiching models oo rarely. successful However, in in explaining our case changes all ess rejec in asse he prices null hypohesis (e.g. Hamilon, a any 008 sandard and levels ciaions of herein). significance Neverheless, (cf. he fourh i is row difficul of Table o ) formally 3. es he presence of wo regimes in he Markov Having swiching empirically framework esablished agains he ha null he hypohesis Markov-swiching of a single regressions regime due are o a beer some parameers approximaion being of he unidenified sock marke under behaviour he null han hypohesis. he linear The specificaion, ypically applied we can likelihood es if he raio regression (LR), parameers F or Lagrange responsible muliplier for ess inernaional do no spillovers have heir are sandard significan disribuions and change and simulaion echniques need o be used o derive approximaed criical values. beween regimes. The null hypohesis saes ha 0 in each regime of he model We employ he modified LR es of Hansen (99), where he null hypohesis (8). The ypical likelihood raio (LR) saisic has an asympoic sandard disribuion in assumes he linear single-regime regression, while he alernaive hypohesis allows one his case. As presened in he fifh row of Table, here is srong evidence of he US marke regression parameer and he residual variance o change values depending on he regimes of affecing reurns on all local markes. calm and urbulence. As our ineres is in he changes of dominan rading moives, we selec Addiionally, we verify he presence of GARCH effecs in he residuals of Markovswiching regressions by using he LR saisic (cf. he sixh row of Table ). Conrolling for he parameer in he regression o change beween regimes. Hansen (99) argues ha he es saisic may in heory be raher conservaive, i.e., i may rejec he false null hypohesis ime-varying volailiy on financial markes also improves he fi of models o he daa 3 oo We rarely. use he GAUSS However, program in our wrien case by all Bruce ess Hansen rejec o he compue null hese hypohesis es saisics. any sandard levels of significanly. Thus, employing boh he LR ess we find ha he bes models are he MSRsignificance (cf. he fourh row of Table ) 3. 6 GARCH specificaions conrolling for he impac of foreign markes on sock reurns in he Having empirically esablished ha he Markov-swiching regressions are a beer local markes. approximaion of he sock marke behaviour han he linear specificaion, we can es if he regression parameers responsible for inernaional spillovers are significan and change beween regimes. The null hypohesis saes ha 0 in each regime of he model (8). The ypical likelihood raio (LR) saisic has an asympoic sandard disribuion in his case. As presened in he fifh row of Table, here is srong evidence of he US marke affecing reurns on all local markes. Addiionally, we verify he presence of GARCH effecs in he residuals of Markovswiching regressions by using he LR saisic (cf. he sixh row of Table ). Conrolling for 3 We use he GAUSS program wrien by Bruce Hansen o compue hese es saisics. 6 6 N a i o n a l B a n k o f P o l a n d

Conclusions 5. Conclusions In his paper we find ha financial spillovers from he US marke and changes beween calm and urbulen regimes have a significan impac on he analysis of he presence of feedback rading, liquidiy and informed rading on he developed inernaional sock markes. Saisical ess confirm he preference for Markov-swiching models wih GARCH effecs over single-regime regressions. Conrolling for ime varying volailiy and inernaional spillovers no only improves he fi of esimaed models, bu also changes he economic inerpreaion of prevailing moives of rading. Employing he recenly developed echniques o esimae he Markov-swiching regressions wih GARCH effecs, we find evidence of posiive feedback rading driven by pas home-marke informaion on large inernaional sock markes. Posiive reurn spillovers from he US marke are anoher finding robus o model changes. However, he resuls from he mos comprehensive, bes-fiing model specificaions show ha he approach o deerminaion of rading moives widely employed in he lieraure fails o produce unambiguous oucomes. Specifically, accouning for spillovers, changing volailiy and marke regimes weakens he evidence of prevalence of he non-informaional moive for rading on inernaional sock exchanges. These findings sugges ha fuure analyses of he empirical relaionship beween reurn and volume in differen financial markes should incorporae he impac of news and invesor sraegies on local and foreign markes, as well as he curren (calm or urbulen) sae of financial markes. Possible reasons for differences in predominaing rading sraegies beween inernaional sock markes could be he frequency of volaile shocks and he srengh of financial links wih he global markes. These reasons clearly need furher empirical invesigaion. 5 8 WORKING PAPER No. 9 7

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Tables and Figures Figure : Moving window esimaes of parameer from he SRR-GARCH models wih inernaional spillovers. Canada France Germany Ialy Japan UK Noe: Esimaes of parameer were obained from single regime GARCH models wih inernaional spillovers. Window size: one year (5 rading days), sep size: one monh ( working days). WORKING PAPER No. 9

Tables and Figures Table : Regression parameer esimaes of he models wih and wihou financial spillovers from he US marke Model wihou financial spillovers Model wih financial spillovers from he US marke 0 0 Canada SRR 0.050 0.047-0.838 0.037-0.0736-0.33 0.54-0.0953 SRR-GARCH 0.0556 0.057-0.07 0.0006 0.0434-0.090 0.075 0.088 MSR regime 0.078 0.0985-0.056 0.0770 0.003-0.050 0.7 0.06 regime -0.768 0.004-0.669-0.85-0.59-0.0833 0.03-0.505 MSR-GARCH regime 0.0 0.57-0.087 0.00 0.090-0.0550 0.090 0.940 regime -0.005 0.0699-0.09-0.040-0.0330-0.0680 0.300-0.0380 France SRR 0.097 0.0463-0.77 0.059-0.658-0.090 0.4007 0.0687 SRR-GARCH 0.0634 0.0397-0.48 0.0005-0.89-0.0750 0.3605 0.0766 MSR regime 0.0664 0.0444-0.0756 0.0640-0.070 0.0083 0.397-0.0706 regime -0.386 0.0479-0.38-0.38-0.457-0.087 0.463 0.0653 MSR-GARCH regime 0.89-0.0077-0.3 0.0870-0.00-0.0 0.3460 0.300 regime 0.099 0.046-0.34 0.090-0.00-0.050 0.3650 0.0390 Germany SRR 0.03 0.078-0.73 0.0048-0.98-0.359 0.3357-0.0884 SRR-GARCH 0.05 0.08-0.0844 0.0004-0.358-0.04 0.406-0.093 MSR regime 0.0690 0.0065-0.007 0.0496-0. 0.0478 0.3767-0.75 regime -0.44 0.055-0.004-0.4-0.36-0.666 0.3030-0.047 MSR-GARCH regime 0.85-0.0080 0.0487 0.00-0.680-0.080 0.4960 0.0340 regime -0.068 0.007-0.6-0.080-0.50-0.0480 0.330-0.0830 Ialy SRR 0.0 0.036-0.0966 0.0049-0.34-0.09 0.978 0.040 SRR-GARCH 0.0547 0.0093-0.046 0.0005-0.0947-0.00 0.4 0.078 MSR regime 0.058 0.085 0.0576 0.043-0.0653 0.063 0.0-0.0506 regime -0.0574 0.037-0.346-0.059-0.543-0.009 0.355 0.050 MSR-GARCH regime 0.35-0.04-0.0964 0.60-0.800-0.0990 0.930 0.080 regime 0.0008 0.044-0.0307-0.040-0.090-0.000 0.60 0.0970 Noe: The symbols,, and denoe ha corresponding parameers are saisically significanly differen from zero a he 0.0, 0.05, and 0.0 levels of significance, respecively. N a i o n a l B a n k o f P o l a n d

Tables and Figures Table coninued Model wihou financial spillovers Model wih financial spillovers from he US marke 0 0 Japan SRR -0.0036 0.0505-0.05-0.077-0.067-0.005 0.479-0.577 SRR-GARCH 0.055 0.075-0.06 0.000 0.060 0.000 0.4337-0.9 MSR regime 0.049 0.0795 0.077 0.073 0.0588 0.048 0.3589-0.864 regime -0.0733 0.0354-0.07-0.08-0.0607 0.00 0.558-0.5 MSR-GARCH regime 0.0549 0.0584 0.036 0.040 0.090 0.0300 0.3730-0.0660 regime -0.0347 0.079-0.0505-0.030 0.040-0.040 0.4550-0.700 UK SRR 0.093-0.0003-0.0630 0.057-0.7 0.0458 0.350 0.698 SRR-GARCH 0.0464 0.095-0.003 0.0004-0.394 0.07 0.3058 0.0734 MSR regime 0.0550 0.066-0.76 0.0444-0.070-0.064 0.88 0.036 regime -0.0705-0.086-0.040-0.0635-0.305 0.5 0.4046 0.685 MSR-GARCH regime 0.0784 0.046-0.388 0.0590-0.0640-0.600 0.600 0.0350 regime 0.0097 0.0078 0.0459 0.000-0.780 0.50 0.3350 0.070 USA SRR 0.063-0.045-0.43 SRR-GARCH 0.0546 0.0-0.06 MSR regime 0.0787 0.030 0.0954 regime -0.084-0.0374-0.7 MSR-GARCH regime 0.078 0.0337 0.034 regime 0.009 0.0006-0.0 3 WORKING PAPER No. 9 3

Tables and Figures Table : Tes saisics used o verify model specificaions Tes Canada France Germany Ialy Japan UK USA. Engle and Ng (993) es of he null hypohesis: no ARCH effecs in 08.8 49.98 43.64 44.48 70.77 34.67 53.75 single-regime linear regressions. Chow es of he null hypohesis: all parameers are consan in he sample 9.84.6 0.86 0.98 4.43 5.73 5.5 3. RESET es of he null hypohesis: linear specificaion of he model is correc.7 3.7.85 0.93.80 7.78 8.34 4. Hansen (99) es of he null hypohesis: no Markov-swiching effecs presen in he model 5.LR es of: no significan impac of he US marke in he MSRGARCH models 6. LR es of: no GARCH effecs in he Markov-swiching regressions 7.6 0.5 0.33 3.9 5.5 5.79 30.84 3.08 403.74 35.4 9.43 68.88 449.3 N/A 347.5 3.09 374.0 6.4 67.57 348.84 45.90 Noe: The symbols,, and denoe ha he null hypohesis is rejeced a he 0.0, 0.05, and 0.0 levels of significance, respecively. For each sock marke he es of Hansen (99) verifies he null hypohesis ha he residual variance and he parameer do no depend on he Markov-swiching regime changes. There are wo (adequae) excepions due o esimaion problems. Namely he ess for he German and Ialian markes, where he null hypohesis assumes ha he residual variance and he parameer do no depend on he Markov-swiching regime changes. 0 4 4 N a i o n a l B a n k o f P o l a n d