Handbook of High-Frequency Trading and Modeling in Finance

455 Pages·2016·45.941 MB·English

by  Ionut Florescu, Maria C. Mariani, H. Eugene Stanley, Frederi G. Viens (eds.)

HANDBOOK OF
HIGH-FREQUENCY
TRADING AND
MODELING IN
FINANCE
Ionut Florescu
Maria C. Mariani
EDITED BY
H. Eugene Stanley
Frederi G. Viens

Handbook of
High-Frequency Trading
and Modeling in Finance
WileyHandbooksin
FINANCIAL ENGINEERING AND ECONOMETRICS
AdvisoryEditor
Ruey S. Tsay
TheUniversityofChicagoBoothSchoolofBusiness,USA
Acompletelistofthetitlesinthisseriesappearsattheendofthisvolume.
Handbook of
High-Frequency Trading
and Modeling in Finance
Edited by
IONUT FLORESCU
MARIA C. MARIANI
H. EUGENE STANLEY
FREDERI G. VIENS
Copyright©2016byJohnWiley&Sons,Inc.Allrightsreserved
PublishedbyJohnWiley&Sons,Inc.,Hoboken,NewJersey
PublishedsimultaneouslyinCanada
Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedinanyform
orbyanymeans,electronic,mechanical,photocopying,recording,scanning,orotherwise,exceptas
permittedunderSection107or108ofthe1976UnitedStatesCopyrightAct,withouteithertheprior
writtenpermissionofthePublisher,orauthorizationthroughpaymentoftheappropriateper-copyfee
totheCopyrightClearanceCenter,Inc.,222RosewoodDrive,Danvers,MA01923,[phone],
fax[phone],oronthewebatwww.copyright.com.RequeststothePublisherforpermission
shouldbeaddressedtothePermissionsDepartment,JohnWiley&Sons,Inc.,111RiverStreet,
Hoboken,NJ07030,[phone],fax[phone],oronlineat
http://www.wiley.com/go/permission.
LimitofLiability/DisclaimerofWarranty:Whilethepublisherandauthorhaveusedtheirbestefforts
inpreparingthisbook,theymakenorepresentationsorwarrantieswithrespecttotheaccuracyor
completenessofthecontentsofthisbookandspecificallydisclaimanyimpliedwarrantiesof
merchantabilityorfitnessforaparticularpurpose.Nowarrantymaybecreatedorextendedbysales
representativesorwrittensalesmaterials.Theadviceandstrategiescontainedhereinmaynotbe
suitableforyoursituation.Youshouldconsultwithaprofessionalwhereappropriate.Neitherthe
publishernorauthorshallbeliableforanylossofprofitoranyothercommercialdamages,including
butnotlimitedtospecial,incidental,consequential,orotherdamages.
Forgeneralinformationonourotherproductsandservicesorfortechnicalsupport,pleasecontactour
CustomerCareDepartmentwithintheUnitedStatesat(800)762-2974,outsidetheUnitedStatesat
[phone]orfax(317)572-4002.
Wileyalsopublishesitsbooksinavarietyofelectronicformats.Somecontentthatappearsinprint
maynotbeavailableinelectronicformats.FormoreinformationaboutWileyproducts,visitourweb
siteatwww.wiley.com.
LibraryofCongressCataloging-in-PublicationData:
Names:Florescu,Ionut,1973-editor.
Title:Handbookofhigh-frequencytradingandmodelinginfinance/editedbyIonutFlorescu,
MariaC.Mariani,H.EugeneStanley,FrederiG.Viens.
Description:Hoboken,NJ:JohnWiley&Sons,Inc.,[2016]|Includesindex.
Identifiers:LCCN2015043237(print)|LCCN2016000501(ebook)|ISBN9781118443989(cloth)|
ISBN9781118593400(pdf)|ISBN9781118593325(epub)
Subjects:LCSH:Investmentanalysis–Mathematicalmodels.|Investments–Mathematicalmodels.|
Finance–Mathematicalmodels.
Classification:LCCHG4529.H358632016(print)|LCCHG4529(ebook)|
DDC332.64/20285–dc23
LCrecordavailableathttp://lccn.loc.gov/2015043237
PrintedintheUnitedStatesofAmerica
10 9 8 7 6 5 4 3 2 1
Contents
NotesonContributors xiii
Preface xv
1 TrendsandTrades 1
MichaelCarlisle,OlympiaHadjiliadis,andIoannisStamos
1.1 Introduction 1
1.2 Atrend-basedtradingstrategy 3
1.2.1 Signalingandtrends 3
1.2.2 Gainoverasubperiod 5
1.3 CUSUMtiming 7
1.3.1 Cusumprocessandstoppingtime 7
1.3.2 ACUSUMtimingscheme 10
1.3.3 UStreasurynotes,CUSUMtiming 11
1.4 Example:Randomwalkonticks 12
1.4.1 Randomwalkexpectedgainoverasubperiod 15
1.4.2 Simplerandomwalk,CUSUMtiming 18
1.4.3 Lazysimplerandomwalk,cusumtiming 21
1.5 CUSUMstrategyMonteCarlo 24
1.6 Theeffectofthethresholdparameter 27
1.7 Conclusionsandfuturework 39
Appendix:Tables 40
References 47
2 GaussianInequalitiesandTrancheSensitivities 51
ClaasBeckerandAmbarN.Sengupta
2.1 Introduction 51
2.2 Thetranchelossfunction 52
2.3 Asensitivityidentity 54
2.4 Correlationsensitivities 55
Acknowledgment 58
References 58
v
vi Contents
3 ANonlinearLeadLagDependenceAnalysisofEnergy
Futures:Oil,Coal,andNaturalGas 61
Germa´nG.CreamerandBernardoCreamer
3.1 Introduction 61
3.1.1 Causalityanalysis 62
3.2 Data 64
3.3 Estimationtechniques 64
3.4 Results 65
3.5 Discussion 67
3.6 Conclusions 69
Acknowledgments 69
References 70
4 PortfolioOptimization:ApplicationsinQuantum
Computing 73
MichaelMarzec
4.1 Introduction 73
4.2 Background 75
4.2.1 Portfoliosandoptimization 76
4.2.2 Algorithmiccomplexity 77
4.2.3 Performance 78
4.2.4 Isingmodel 79
4.2.5 Adiabaticquantumcomputing 79
4.3 Themodels 80
4.3.1 Financialmodel 81
4.3.2 Graph-theoreticcombinatorialoptimization
models 82
4.3.3 IsingandQubomodels 83
4.3.4 Mixedmodels 84
4.4 Methods 84
4.4.1 Modelimplementation 85
4.4.2 Inputdata 85
4.4.3 Mean-variancecalculations 85
4.4.4 Implementingtheriskmeasure 86
4.4.5 Implementationmapping 86
4.5 Results 88
4.5.1 Thesimplecorrelationmodel 88
4.5.2 Therestrictedminimum-riskmodel 91
4.5.3 TheWMISminimum-risk,maxreturnmodel 94
Contents vii
4.6 Discussion 95
4.6.1 Hardwarelimitations 97
4.6.2 Modellimitations 97
4.6.3 Implementationlimitations 98
4.6.4 Futureresearch 98
4.7 Conclusion 100
Acknowledgments 100
Appendix4.A:WMISMatlabCode 100
References 103
5 EstimationProcedureforRegimeSwitchingStochastic
VolatilityModelandItsApplications 107
IonutFlorescuandForrestLevin
5.1 Introduction 107
5.1.1 Theoriginalmotivation 108
5.1.2 Themodelandtheproblem 108
5.1.3 Abriefhistoricalnote 109
5.2 Themethodology 110
5.2.1 Obtainingfilteredempiricaldistributionsat
t ,…,t 110
1 T
5.2.2 ObtainingtheparametersoftheMarkovchain 112
5.3 Resultsobtainedapplyingthemodeltorealdata 113
5.3.1 Parti:financialapplications 113
5.3.2 Partii:physicaldataapplication.temperature
data 119
5.3.3 Partiii:analysisofseismometerreadings
duringanearthquake 121
5.3.4 Analysisoftheearthquakesignal:beginning 123
5.3.5 Analysis:duringtheearthquake 125
5.3.6 Analysis:endoftheearthquakesignal,
aftershocks 127
5.4 Conclusion 127
5.A Theoreticalresultsandempiricaltesting 128
5.A.1 Howdoestheparticlefilterwork? 128
5.A.2 Theoreticalresultsaboutconvergenceand
parameterestimates 129
5.A.3 Markovchainparameterestimates 131
5.A.4 Empiricaltesting 132
5.A.5 Alistofsupplementarydocuments 133
References 133
viii Contents
6 DetectingJumpsinHigh-FrequencyPricesUnder
StochasticVolatility:AReviewandaData-Driven
Approach 137
Ping-ChenTsaiandMarkB.Shackleton
6.1 Introduction 137
6.2 Reviewontheintradayjumptests 140
6.2.1 RealizedvolatilitymeasureandtheBNStests 140
6.2.2 TheABDandLMtests 142
6.3 Adata-driventestingprocedure 146
6.3.1 Spydataandmicrostructurenoise 146
6.3.2 Ageneralizedtestingprocedure 149
6.4 Simulationstudy 153
6.4.1 Modelspecification 153
6.4.2 Simulationresults 158
6.5 Empiricalresults 161
6.5.1 Resultsonthebackward-lookingtest 162
6.5.2 Resultsontheinterpolatedtest 165
6.6 Conclusion 165
Acknowledgments 166
Appendix6.A:Least-squareestimationofHAR-MA(2)
modelforlog(BP)ofSPY 167
Appendix6.B:EstimationofARMA(2,1)modelfor
log(BP)ofSPY 168
Appendix6.C:Minimizedlossfunctionloss(𝜌 ,𝜌 )for
1 2
SV2FJ_2𝜌model,SPY 169
Appendix6.D.1:Calibrationof𝜉 underSV2FJ_2𝜌modelat
2-minfrequency,E[N]=0.08 170
t
Appendix6.D.2:Calibrationof𝜉 underSV2FJ_2𝜌modelat
2-minfrequency,E[N]=0.40 171
t
Appendix6.D.3:Calibrationof𝜉 underSV2FJ_2𝜌modelat
5-minfrequency,E[N]=0.08 172
t
Appendix6.D.4:Calibrationof𝜉 underSV2FJ_2𝜌Modelat
5-minfrequency,E[N]=0.40 173
t
Appendix6.D.5:Calibrationof𝜉 underSV2FJ_2𝜌modelat
10-minfrequency,E[N]=0.08 174
t
Appendix6.D.6:Calibrationof𝜉 underSV2FJ_2𝜌modelat
10-minfrequency,E[N]=0.40 175
t
References 175