Treść książki
Przejdź do opcji czytnikaPrzejdź do nawigacjiPrzejdź do informacjiPrzejdź do stopki
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HenrykGurgul,RobertSyrek
astronglongtermrelationship.However
,thebankingsectorcertainlyhadastrongim-
pactonthereturnsandvolatilityofothersectorsintheshortrun.PatraandPoshak-
walealsofoundthatthevarianceofthereturnsofmostsubindexesistoalargeextent
determinedbytheirowninnovations.Themostinfluentialbankingsectorexplains
approximately25%ofvarianceintheconstructionsectorandtheinsurancesectoris
responsibleforapproximatelyof15%ofthevarianceintheindustrial,investmentand
holdingsectors.PatraandPoshakwale(2008)underlinedthepredominantroleofthe
bankingsector(subindex).Therefore,thebankingsectorissupposedtohavepredictive
powerforatleastshort-termchangesinothersectorindexes.Theresultsmeanthatthe
ASEdidnotfulfilltheassumptionsofweakformefficiency.
Amongauthorsfromthefirstdecadeofthiscenturymanyknownscholarsfocused
onthetransferofinformationbetweenstockmarketsandregions.Thesecontributions
concernmostlydevelopedeconomiesandalsothenewlyliberatedeconomiesofSouth
AsiaandLatinAmerica.
Theglobalcrisesof2008andimbalanceswerereasonsforthegrowingattention
tothemarketsofemergingeconomies,notonlyinthesetworegions.Theinvestors
startedtolookintootheremergingmarketssuchasthemarketsoftheMiddleEast
andNorthAfrica(Lagoarde-SegotandLucey2008).Thesemarketsexhibithighreturns
andvolatility,lowcorrelationwiththelargestworldmarkets,andvolatilityclustering.
Lagoarde-SegotandLuceytriedtodiscoverthelevelofcorrelationandthechannelsof
informationflowacrosssectors.Theimportanttaskwastofindproofoftherelativeim-
portanceofthesesectorsinexplainingvariationsofreturnsinthesesectors.Thestudy
isimportantwithrespecttodetermininginformationtransmissionacrosssectorsinthe
samestockmarket(Wangetal.2005).
TheproblemofinterdependenceofdomesticsectoralsubindexesonCEEcountries
hasnotbeenwidelyconsideredintheliterature(GurgulandSyrek2014).Thereforein
thenewsituationaftertheoutbreakoftheCOVID-19pandemicandconsideringmany
sanitaryrestrictionsonsomesectorstheinterrelationsseemtobeinteresting.More-
overidentificationoftheseinterrelationsmaybeusefulforpolicymakers.Thisespe-
ciallyconcernsPolandwhichhasbeenheavyaffectedbytheCOVID-19pandemic.Tothe
bestofourknowledgetheseissuesarenotreflectedintheavailablerecentliteratureon
interrelationsbetweensectoralsubindexes.
Incontrasttotherefereedcontributionswewillperformouranalysisoflinkages
betweenPolishsectorsubindexesusingamethodologyknownasΔCoVaR.Thismea-
sureofsystemicrisk,introducedinAdrianandBrunnermeier(2011),allowstoidenti-
tyorranksystemicallyimportantfinancialinstitutions.BianchiandSorrentino(2020)
estimatedthismeasureforItalianandmainEuropeanbanks.Forthispurposetheau-
thorsusedthequantileregression,aclosedformformulaandanon-parametricmeth-
od.GirardiandErgün(2013)usedmultivariateGARCHmodeltoestimatethesystemic
riskcontributionsoffourfinancialindustrygroupsconsistingofalargenumberofin-
stitutions.Gurguletal.(2017)appliedGARCH-MIDASandDCC-MIDASmodeltorank
componentsofEUROSTOXXBANKSindex,whereasXuetal.(2018)measuresystemic
