LEADER 04117nam  22006375  450 
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010   $a3-319-94129-1
024 7 $a10.1007/978-3-319-94129-5
035   $a(CKB)4100000007110543
035   $a(MiAaPQ)EBC5592879
035   $a(DE-He213)978-3-319-94129-5
035   $a(PPN)232472335
035   $a(EXLCZ)994100000007110543
100   $a20181101d2018      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cn$2rdamedia
183   $anc$2rdacarrier
200 10$aAmbit Stochastics /$fby Ole E. Barndorff-Nielsen, Fred Espen Benth, Almut E. D. Veraart
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $aXXV, 402 p. $cgráf. ;$d25 cm
225 1 $aProbability Theory and Stochastic Modelling,$x2199-3149 ;$v88
300   $aMSC 60Gxx
320   $aIncluye referencias bibliográficas (p. 385-397) e índice
327   $aPart I The purely temporal case -- 1 Volatility modulated Volterra processes -- 2 Simulation -- 3 Asymptotic theory for power variation of LSS processes -- 4 Integration with respect to volatility modulated Volterra processes -- Part II The spatio-temporal case -- 5 The ambit framework -- 6 Representation and simulation of ambit fields -- 7 Stochastic integration with ambit fields as integrators -- 8 Trawl processes -- Part III Applications -- 9 Turbulence modelling -- 10 Stochastic modelling of energy spot prices by LSS processes -- 11 Forward curve modelling by ambit fields -- Appendix A: Bessel functions -- Appendix B: Generalised hyperbolic distribution -- References -- Index.
330   $aDrawing on advanced probability theory, Ambit Stochastics is used to model stochastic processes which depend on both time and space. This monograph, the first on the subject, provides a reference for this burgeoning field, complete with the applications that have driven its development. Unique to Ambit Stochastics are ambit sets, which allow the delimitation of space-time to a zone of interest, and ambit fields, which are particularly well-adapted to modelling stochastic volatility or intermittency. These attributes lend themselves notably to applications in the statistical theory of turbulence and financial econometrics. In addition to the theory and applications of Ambit Stochastics, the book also contains new theory on the simulation of ambit fields and a comprehensive stochastic integration theory for Volterra processes in a non-semimartingale context. Written by pioneers in the subject, this book will appeal to researchers and graduate students interested in empirical stochastic modelling.
410  0$aProbability Theory and Stochastic Modelling,$x2199-3149 ;$v88
606   $aProbabilities
606   $aMathematical physics
606   $aSocial sciences$xMathematics
606   $aStatistics
606   $aProbability Theory
606   $aMathematical Physics
606   $aMathematics in Business, Economics and Finance
606   $aStatistics in Business, Management, Economics, Finance, Insurance
606   $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
615  0$aProbabilities.
615  0$aMathematical physics.
615  0$aSocial sciences$xMathematics.
615  0$aStatistics.
615 14$aProbability Theory.
615 24$aMathematical Physics.
615 24$aMathematics in Business, Economics and Finance.
615 24$aStatistics in Business, Management, Economics, Finance, Insurance.
615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
676   $a519.2
700   $aBarndorff-Nielsen$b Ole E$4aut$4http://id.loc.gov/vocabulary/relators/aut$0249282
702   $aBenth$b Fred Espen$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aVeraart$b Almut E. D$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910300106803321
996   $aAmbit Stochastics$92065744
997   $aUNINA