Portfolio Management under Stress: A Bayesian-Net Approach to Coherent Asset Allocation

518 Pages·2014·6.99 MB·English

by  Riccardo Rebonato

Portfolio Management Under Stress
Portfolio Management Under Stress offers a novel way to apply
the well-established Bayesian-net methodology to the important
problemofassetallocationunderconditionsofmarketdistressor,
moregenerally,whenaninvestorbelievesthataparticularscenario
(suchasthebreak-upoftheEuro)mayoccur.Employingacoher-
entandthoroughapproach,itprovidespracticalguidanceonhow
best to choose an optimal and stable asset allocation in the pres-
enceofuser-specifiedscenariosor‘stressconditions’.Theauthors
placecausalexplanations,ratherthanassociation-basedmeasures
such as correlations, at the core of their argument, and insights
from the theory of choice under ambiguity aversion are invoked
toobtainstableallocationsresults.Step-by-stepdesignguidelines
are included to allow readers to grasp the full implementation of
theapproach,andcasestudiesprovideclarification.Thisinsightful
bookisakeyresourceforpractitionersandresearchacademicsin
thepost-financial-crisisworld.
riccardo rebonato is Global Head of Rates and FX Ana-
lytics atPIMCO, and a visitinglecturer inMathematical Finance
atOxfordUniversity(OCIAM).Hehaspreviouslyheldpositions
asHeadofRiskManagementandHeadofDerivativesTradingat
severalmajorinternationalfinancialinstitutions.DrRebonatohas
been on the Board of ISDA (2002–2011), and still serves on the
BoardofGARP(2001topresent).Heistheauthorofseveralbooks
on finance and an editor for several journals (International Jour-
nal of Theoretical and Applied Finance, Journal of Risk, Applied
MathematicalFinance,JournalofRiskforFinancialInstitutions).
alexander denev isaseniorteamleaderintheRiskModels
department at the Royal Bank of Scotland. He is specialized in
CreditRisk,Regulations,AssetAllocationandStressTesting,and
has previously worked in management roles at European Invest-
mentBank,Socie´te´ Ge´ne´raleandNationalBankofGreece.
‘Standard portfolio theory has been shown by recent events to have two major short-
comings: it does not deal well with extreme events and it is often based on mechanical
statistical procedures rather than modelling of fundamental causal mechanisms. In this
book, Rebonato and Denev put forward an interesting approach for dealing with both
of these problems. Their method is flexible enough to accommodate individual views of
underlying causal mechanisms, but disciplined enough to ensure that decisions do not
ignore the data. Anyone with a serious interest in making good portfolio decisions or
measuringriskwillbenefitfromreadingthisbook.’
IanCooper,ProfessorofFinance,LondonBusinessSchool
‘This book is self-contained in that it covers a lot of familiar but diverse material from
a fresh perspective. Its purpose is to take an ambitious new approach to combining this
material into a coherent whole. The result is a new methodology for practical portfolio
managementbasedonBayesiannets,whichsatisfactorilytakesintosimultaneousaccount
bothnormalandextrememarketconditions.Whilereadersmaythemselvesbeunderstress
inabsorbingthedetailsofthenewapproach,seriousfundmanagersandfinanceacademics
willignoreitattheirperil.’
M.A.H.Dempster,EmeritusProfessor,DepartmentofMathematics,
UniversityofCambridge;CambridgeSystemsAssociatesLimited
‘RebonatoandDenevhavedemolishedthestatusquowiththeirradicalextensionofbest-
practice portfolio management. The key is to integrate realistic “extreme” scenarios into
risk assessment, and they show how to use Bayesian networks to characterize precisely
thosescenarios.Thebookisrigorousyetcompletelypractical,andreadingitisapleasure,
withthe“Rebonatotouch”evidentthroughout.’
FrancisX.Diebold,PaulF.andWarrenS.MillerProfessorof
Economics,ProfessorofFinanceandStatistics,andCo-Director,Wharton
FinancialInstitutionsCenter,UniversityofPennsylvania
‘Here is a book that combines the soundest of theoretical foundations with the clearest
practical mindset. This is a rare achievement, delivered by two renowned masters of the
craft,truepractitionerswithanacademicmind.Bayesiannetsprovideaflexibleframework
totackledecisionmakingunderuncertaintyinapost-crisisworld.Modelingobservations
according to causation links, as opposed to mere association, introduces a structure that
allows the user to understand risk, as opposed to just measuring it. The ability to define
scenarios,incorporatesubjectiveviews,modelexceptionalevents,etc.,inarigorousmanner
isextremelysatisfactory.Iparticularlylikedtheuseofconcentrationconstraints,because
history shows that high concentration with low risk can be more devastating than low
concentration with high risk. I expect fellow readers to enjoy this work immensely, and
monetizeontheknowledgeitcontains.’
MarcosLopezdePrado,ResearchFellow,HarvardUniversity;
HeadofQuantitativeTrading,HessEnergyTradingCompany
‘InarecentbookofmyownIbemoanrampant“confusion”amongacademicsaswellas
practitionersofmodernfinancialtheoryandpractice.Iamdelightedtosaythattheauthors
ofPortfolioManagementUnderStressarenot confused.Itisheart-warmingtofindsuch
clarityofthoughtamongthosewithpositionsofgreatinfluenceandresponsibility.’
HarryM.Markowitz,NobelLaureate,Economics1990
‘RebonatoandDenevhaveploughedforallofusthevastfieldofapplicationsofBayesian
netstoquantitativeriskandportfoliomanagement,leavingabsolutelynostoneunturned.’
AttilioMeucci,ChiefRiskOfficerandDirectorof
PortfolioConstructionatKeposCapitalLP

Portfolio Management
Under Stress
A Bayesian-Net Approach to
Coherent Asset Allocation
Riccardo Rebonato
and
Alexander Denev
UniversityPrintingHouse,CambridgeCB28BS,UnitedKingdom
CambridgeUniversityPressisapartoftheUniversityofCambridge.
ItfurtherstheUniversity’smissionbydisseminatingknowledgeinthepursuitof
education,learningandresearchatthehighestinternationallevelsofexcellence.
www.cambridge.org
Informationonthistitle:www.cambridge.org/9781107048119
©RiccardoRebonatoandAlexanderDenev2013
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithoutthewritten
permissionofCambridgeUniversityPress.
Firstpublished2013
PrintedintheUnitedKingdombyCPIGroupLtd,CroydonCR04YY
AcataloguerecordforthispublicationisavailablefromtheBritishLibrary
LibraryofCongressCataloguinginPublicationdata
Rebonato,Riccardo.
Portfoliomanagementunderstress:aBayesian-netapproachtocoherentasset
allocation/RiccardoRebonatoandAlexanderDenev.
pages cm
Includesbibliographicalreferencesandindex.
ISBN978-1-107-04811-9(hardback)
1.Portfoliomanagement–Mathematicalmodels. 2.Investments–Mathematical
models. 3.Financialrisk–Mathematicalmodels. I.Denev,Alexander. II.Title.
HG4529.5.R43 2013
332.601(cid:2)519542–dc23 2013037705
ISBN978-1-107-04811-9Hardback
CambridgeUniversityPresshasnoresponsibilityforthepersistenceoraccuracyof
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Contents
Listoffigures pagexviii
Listoftables xxiii
Acknowledgements xxvi
PartI Ourapproachinitscontext 1
1 Howthisbookcameabout 5
1.1 Anoutlineofourapproach 6
1.2 Portfoliomanagementasaprocess 9
1.3 Planofthebook 10
2 Correlationandcausation 13
2.1 Statisticalversuscausalexplanations 13
2.2 Aconcreteexample 19
2.3 Implicationsforhedginganddiversification 22
3 Definitionsandnotation 23
3.1 Definitionsusedforanalysisofreturns 23
3.2 Definitionsandnotationformarketriskfactors 25
PartII Dealingwithextremeevents 27
4 Predictabilityandcausality 31
4.1 Thepurposeofthischapter 31
4.2 Isthistimedifferent? 32
4.3 Structuralbreaksandnon-linearities 34
4.4 Thebridgewithourapproach 37
5 Econophysics 40
5.1 Econophysics,tailsandexceptionalevents 40
ix