Mathematical and Statistical Methods for Actuarial Sciences and Finance

312 Pages·2014·3.19 MB·English

by  Marco Corazza

Marco Corazza
Claudio Pizzi Editors
Mathematical and
Statistical Methods
for Actuarial
Sciences and Finance
MAF
2012
123
Springer
Mathematical and Statistical Methods
for Actuarial Sciences and Finance
·
Marco Corazza Claudio Pizzi
Editors
Mathematical and
Statistical Methods
for Actuarial Sciences
and Finance
Springer
Editors
MarcoCorazza ClaudioPizzi
Ca’FoscariUniversityofVenice Ca’FoscariUniversityofVenice
DepartmentofEconomics DepartmentofEconomics
Venice,Italy Venice,Italy
ISBN978-3-319-02498-1 ISBN978-3-319-02499-8(eBook)
DOI10.1007/978-3-319-02499-8
SpringerChamHeidelbergNewYorkDordrechtLondon
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Preface
Thisvolumeisacollectionofreferredpapersselectedfromthemorethanonehun-
dredandtwentypresentedattheInternationalMAFConference2012–Mathemat-
icalandStatisticalMethodsforActuarialSciencesandFinance.
The conference was held in Venice (Italy), from April 10 to 12, 2012, at the
prestigious Cavalli Franchetti palace of the Istituto Veneto di Scienze, Lettere ed
Arti, on the Grand Canal, very near to the Rialto bridge. It was organized by the
DepartmentofEconomicsoftheUniversityCa’FoscariofVenice(Italy),withthe
collaboration of the Department of Economics and Statistics of the University of
Salerno(Italy).
This conference was the fifth in an international biennial series, which began
in 2004. It was born out of a brilliant idea by colleagues – and friends – of the
DepartmentofEconomicsandStatisticsoftheUniversityofSalerno:theideawas
that a cooperation between mathematicians and statisticians working in actuarial
sciences,ininsuranceandinfinancecouldimprovetheresearchonthesetopics.
Theproofofthemeritsofthisideaisthewideparticipationinalltheconferences.
Inparticular,withreferencetothe2012event,therewere:
• about 180 attendants, including academics, professionals, researchers and stu-
dents;
• morethan120acceptedcommunications,organizedin40parallelsessions;
• attendantsandauthorsfrommorethan20countries:Australia,Austria,Belgium,
Canada,Denmark,Egypt,France,Germany,GreatBritain,Greece,Israel,Italy,
Japan,Mexico,NewZealand,Portugal,RepublicofDjibouti,SierraLeone,Spain,
SwitzerlandandtheUSA;
• 4prestigiousplenarykeynotelecturesdeliveredby:
– ProfessorGiuseppeCavaliereoftheUniversityofBologna(Italy):“Unitroots
inboundedfinancialtimeseries”;
– ProfessorPaulEmbrechtsoftheETHZurich(Switzerland):“Extreme-quantile
trackingforfinancialtimeseries”;
– Professor Dominique Guégan of the University Paris1, Panthéon, Sorbonne
(France): “A quantitative finance and actuarial framework for risk manage-
ment”;
– ProfessorWolfgangRunggaldieroftheUniversityofPadua(Italy):“Onsto-
chasticfilteringapplicationsinfinance”;
vi Preface
• aninstructiveplenarylesson,mainlyaddressedtoPh.D.studentsandyoungre-
searchers, delivered by Professor Chris Adcock of the University of Shefield
(GreatBritain):“Doingresearchandgettingitpublished”.
Generally,thepaperspublishedinthisvolumepresenttheoreticalandmethodolog-
icalcontributionsandtheirapplicationsinrealcontexts.
With respect to the theoretical and methodological contributions, some of the
considered areas of investigation include: actuarial models; alternative testing ap-
proaches; behavioral finance; clustering techniques; coherent andno-coherent risk
measures;credit-scoringapproaches;dataenvelopmentanalysis;dynamicstochas-
tic programming; financial contagion models; financial ratios; intelligent financial
tradingsystems;mixturenormalityapproaches;MonteCarlo-basedmethodologies;
multi-criteriamethods;nonlinearparameterestimationtechniques;nonlinearthresh-
oldmodels;particleswarmoptimization;performancemeasures;portfoliooptimiza-
tion; pricing methods for structured and non-structured derivatives; risk manage-
ment;skeweddistributionanalysis;solvencyanalysis;stochasticactuarialvaluation
methods;variableselectionmodels;timeseriesanalysistools.
Asregardstheapplications,theyarerelatedtorealproblemsassociated,among
theothers,to:banks;collateralizedfundobligations;creditportfolios;defined-benefit
pension plans; double-indexed pension annuities; efficient-market hypothesis; ex-
changemarkets;financialtimeseries;firms;hedgefunds;non-lifeinsurancecompa-
nies;returnsdistributions;sociallyresponsiblemutualfunds;unit-linkedcontracts.
Ofcourse,successofthisconferencewouldnothavebeenpossiblewithoutthe
valuablehelpofoursponsors(inalphabeticalorder):
• AMASES:AssociazioneperlaMatematicaApplicataalleScienzeEconomiche
eSociali;
• CentroInterdipartimentalesuCulturaeEconomiadellaGlobalizzazione;
• DepartmentofEconomicsoftheUniversityCa’FoscariofVenice;
• DepartmentofEconomicsandStatisticsoftheUniversityofSalerno;
• DIAMANSIMS.p.A.;
• IstitutoVenetodiScienzeLettereeArti;
• NethunS.p.A;
• RegionedelVeneto;
• VENISS.p.A.
Further, we would also like to express our deep gratitude to the members of the
ScientificandOrganizingCommittees,totheCenterofQuantitativeEconomicsof
theCa’FoscariUniversityofVenice,totheWebmaster,andtoallthepeoplewhose
collaborationcontributedtothesuccessoftheconferenceMAF2012.
Finally, we are pleased to inform you that the organizing machine of the next
editionisalreadyworking:theconferenceMAF2014willbeheldinVietrisulMare
(Italy),ontheenchantingAmalfiCoast,fromApril22to24,2014(formoredetails
visitthewebsitehttp://www.maf2014.unisa.it/).
Welookforwardtoseeingyou.
Venice,August2013 MarcoCorazza
ClaudioPizzi
Contents
WeakFormEfficiencyofSelectedEuropeanStockMarkets:Alternative
TestingApproaches.............................................. 1
GiuseppinaAlbano,MicheleLaRoccaandCiraPerna
AnEmpiricalComparisonofVariableSelectionMethodsinCompeting
RisksModel.................................................... 13
AlessandraAmendola,MarialuisaRestainoandLucaSensini
AComparisonBetweenDifferentNumericalSchemesfortheValuation
ofUnit-LinkedContractsEmbeddingaSurrenderOption ............. 27
AnnaRitaBacinello,PietroMillossovichandAlvaroMontealegre
Dynamic Tracking Error with Shortfall Control Using Stochastic
Programming................................................... 41
DianaBarroandElioCanestrelli
Firm’sVolatilityRiskUnderMicrostructureNoise ................... 55
FlaviaBarsottiandSimonaSanfelici
SociallyResponsibleMutualFunds:AnEfficiencyComparisonAmong
theEuropeanCountries .......................................... 69
AntonellaBassoandStefaniaFunari
FittingFinancialReturnsDistributions:AMixtureNormalityApproach. 81
RiccardoBramanteandDiegoZappa
Single-NameConcentrationRiskMeasurementsinCreditPortfolios .... 89
RaffaellaCalabreseandFrancescoPorro
BifactorialPricingModels:LightandShadowsinCorrelationRole ..... 99
RosaCocozzaandAntonioDeSimone
DynamicStrategiesforDefinedBenefitPensionPlansRiskManagement. 111
IlariaColivicchi,GabriellaPiscopoandEmanueleVannucci
viii Contents
Particle Swarm Optimization for Preference Disaggregation in
MulticriteriaCreditScoringProblems.............................. 119
MarcoCorazza,StefaniaFunariandRiccardoGusso
TimeSeriesClusteringonLowerTailDependenceforPortfolioSelection. 131
GiovanniDeLucaandPaolaZuccolotto
SolvencyAnalysisofDefinedBenefitPensionSchemes ................ 141
PierreDevolderandGabriellaPiscopo
StochasticActuarialValuationsinDouble-IndexedPensionAnnuity
Assessment..................................................... 151
EmiliaDiLorenzo,AlbinaOrlandoandMarilenaSibillo
Testing forNormality When theSampledDistribution Is Extended
Skew-Normal................................................... 159
CinziaFranceschiniandNicolaLoperfido
OntheRODEOMethodforVariableSelection....................... 171
FrancescoGiordanoandMariaLuciaParrella
PortfolioAllocationUsingOmegaFunction:AnEmpiricalAnalysis ..... 179
AsmerildaHitaj,FrancescoMartinelliandGiovanniZambruno
Investment Rankings via an Objective Measure of Riskiness:
ACaseStudy ................................................... 195
MariaErminiaMarinaandMarinaResta
A Squared Rank Assessment of the Difference Between US and
EuropeanFirmValuationRatios................................... 205
MarcoMarozzi
ABehaviouralApproachtothePricingofEuropeanOptions........... 219
MartinaNardonandPaoloPianca
ThresholdStructuresinEconomicandFinancialTimeSeries .......... 231
MarcellaNiglioandCosimoDamianoVitale
Intelligent Algorithms for Trading the Euro-Dollar in the Foreign
ExchangeMarket ............................................... 243
DaniloPelusi,MassimoTivegnaandPierluigiIppoliti
Risk Management and Capital Allocation for Non-Life Insurance
Companies ..................................................... 253
MarcoPirra,SalvatoreForteandMatteoIalenti
Modelling Asymmetric Behaviour in Time Series: Identification
ThroughPSO................................................... 265
ClaudioPizziandFrancescaParpinel
Contents ix
ValuationofCollateralizedFundsofHedgeFundObligations:ABasket
OptionPricingApproach......................................... 277
GianLucaTassinariandCorradoCorradi
ValuationofR&DInvestmentOpportunitiesUsingtheLeast-Squares
MonteCarloMethod ............................................ 289
GiovanniVillani
TheDeterminantsofInterbankContagion:DoPatternsMatter? ....... 303
StefanoZedda,GiuseppinaCannasandClaraGalliani
Weak Form Efficiency of Selected European
Stock Markets: Alternative Testing Approaches
GiuseppinaAlbano,MicheleLaRoccaandCiraPerna
Abstract Modelling and forecasting financial data is an important problem which
has received alot ofattention especially forthe intrinsic difficulty in practical ap-
plications.Thepresentpaperinvestigatestheweakformefficiencyofsomeselected
European markets: AEX, CAC40, DAX, FTSE100, FTSEMIB, IBEX35. In order
tokeepintoaccountnonlinear structuresusually foundinreturnstimeseriesdata,
anonparametrictestbasedonneuralnetworkmodelshasbeenemployed.Thetest
procedure has been structured as a multiple testing scheme in order to avoid any
datasnoopingproblemandtokeepundercontrolthefamilywiseerrorrate.Forsake
ofcomparisonwealsodiscusstheresultsobtainedbyapplyingsomeclassicaland
wellknowntestsbasedontheRandomWalkHypotheses.Thedataanalysisresults
clearlyshowthatignoringthemultipletestingstructureoftheselattertestmightlead
tospuriousresults.
1 Introduction
Theefficientmarkethypothesis(EMH),initsweakform,statesthatallavailablein-
formationisfullyandinstantaneouslyreflectedinprice,soitwillbenotpossiblefor
investors, usingpast prices, todiscover undervalued stocks anddevelop strategies
to systematically earn abnormal returns. Clearly, this is a fundamental issue in fi-
G.Albano( )
DepartmentofEconomicsandStatistics,UniversityofSalerno,Salerno,Italy
e-mail:[email protected]
M.LaRocca
DepartmentofEconomicsandStatistics,UniversityofSalerno,Salerno,Italy
e-mail:[email protected]
C.Perna
DepartmentofEconomicsandStatistics,UniversityofSalerno,Salerno,Italy
e-mail:[email protected]
M.Corazza,C.Pizzi(eds.),MathematicalandStatisticalMethodsforActuarialSciencesand
Finance,DOI10.1007/978-3-319-02499-8_1,©SpringerInternationalPublishingSwitzer-
land2014