Ambit Stochastics
Mentés helye:
| Szerző: | |
|---|---|
| Testületi szerző: | |
| Közreműködő(k): | |
| Különgyűjtemény: | e-book |
| Formátum: | könyv |
| Nyelv: | angol |
| Megjelenés: |
Cham : : Springer International Publishing : : Imprint: Springer,,
2018
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| Kiadás: | 1st ed. 2018. |
| Sorozat: | Probability Theory and Stochastic Modelling,, ISSN 2199-3130 ; ; 88 |
| Tárgyszavak: | |
| Online elérés: | https://doi.org/10.1007/978-3-319-94129-5 |
| Címkék: |
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| id |
opac-EUL01-000979048 |
|---|---|
| collection |
e-book |
| institution |
L_200 EUL01 |
| spelling |
Barndorff-Nielsen, Ole szerző aut http://id.loc.gov/vocabulary/relators/aut 1935- EUL10000206475 Y Barndorff-Nielsen, Ole Eiler 1935- EUL10000206475 N Nielsen, Ole Barndorff- 1935- EUL10000206475 N Ambit Stochastics by Ole E. Barndorff-Nielsen, Fred Espen Benth, Almut E. D. Veraart. 1st ed. 2018. Cham : Springer International Publishing : Imprint: Springer, 2018 XXV, 402 p. 39 illus., 25 illus. in color. online forrás szöveg txt rdacontent számítógépes c rdamedia távoli hozzáférés cr rdacarrier szövegfájl PDF rda Probability Theory and Stochastic Modelling, 2199-3130 ; 88 Part 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. Drawing 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. Nyomtatott kiadás: ISBN 9783319941288 Nyomtatott kiadás: ISBN 9783319941301 Nyomtatott kiadás: ISBN 9783030068028 Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők. könyv e-book Distribution (Probability theory. Finance. EUL10000378121 Y Statistics. EUL10000081563 Y Probability Theory and Stochastic Processes. Mathematical Applications in the Physical Sciences. Quantitative Finance. Mathematical Physics. Statistics for Business, Management, Economics, Finance, Insurance. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. elektronikus könyv Benth, Fred Espen. szerző aut http://id.loc.gov/vocabulary/relators/aut Veraart, Almut E. D. szerző aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) közreadó testület Online változat https://doi.org/10.1007/978-3-319-94129-5 EUL01 |
| language |
English |
| format |
Book |
| author |
Barndorff-Nielsen, Ole, szerző(1935-) |
| spellingShingle |
Barndorff-Nielsen, Ole, szerző(1935-) Ambit Stochastics Probability Theory and Stochastic Modelling,, ISSN 2199-3130 ; ; 88 Distribution (Probability theory. Finance. Statistics. Probability Theory and Stochastic Processes. Mathematical Applications in the Physical Sciences. Quantitative Finance. Mathematical Physics. Statistics for Business, Management, Economics, Finance, Insurance. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. elektronikus könyv |
| author_facet |
Barndorff-Nielsen, Ole, szerző(1935-) Barndorff-Nielsen, Ole Eiler (1935-) Nielsen, Ole Barndorff- (1935-) Benth, Fred Espen., szerző Veraart, Almut E. D., szerző SpringerLink (Online service), közreadó testület |
| author_variant |
Barndorff-Nielsen, Ole Eiler (1935-) Nielsen, Ole Barndorff- (1935-) |
| author2 |
Benth, Fred Espen., szerző Veraart, Almut E. D., szerző |
| author_corporate |
SpringerLink (Online service), közreadó testület |
| author_sort |
Barndorff-Nielsen, Ole 1935- |
| title |
Ambit Stochastics |
| title_short |
Ambit Stochastics |
| title_full |
Ambit Stochastics by Ole E. Barndorff-Nielsen, Fred Espen Benth, Almut E. D. Veraart. |
| title_fullStr |
Ambit Stochastics by Ole E. Barndorff-Nielsen, Fred Espen Benth, Almut E. D. Veraart. |
| title_full_unstemmed |
Ambit Stochastics by Ole E. Barndorff-Nielsen, Fred Espen Benth, Almut E. D. Veraart. |
| title_auth |
Ambit Stochastics |
| title_sort |
ambit stochastics |
| series |
Probability Theory and Stochastic Modelling,, ISSN 2199-3130 ; ; 88 |
| series2 |
Probability Theory and Stochastic Modelling, |
| publishDate |
2018 |
| publishDateSort |
2018 |
| physical |
XXV, 402 p. 39 illus., 25 illus. in color. : online forrás |
| edition |
1st ed. 2018. |
| isbn |
978-3-319-94129-5 |
| issn |
2199-3130 ; |
| callnumber-first |
Q - Science |
| callnumber-subject |
QA - Mathematics |
| callnumber-label |
QA273 |
| callnumber-raw |
979048 |
| callnumber-search |
979048 |
| topic |
Distribution (Probability theory. Finance. Statistics. Probability Theory and Stochastic Processes. Mathematical Applications in the Physical Sciences. Quantitative Finance. Mathematical Physics. Statistics for Business, Management, Economics, Finance, Insurance. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. elektronikus könyv |
| topic_facet |
Distribution (Probability theory. Finance. Statistics. Probability Theory and Stochastic Processes. Mathematical Applications in the Physical Sciences. Quantitative Finance. Mathematical Physics. Statistics for Business, Management, Economics, Finance, Insurance. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. elektronikus könyv Distribution (Probability theory. Finance. Statistics. Probability Theory and Stochastic Processes. Mathematical Applications in the Physical Sciences. Quantitative Finance. Mathematical Physics. Statistics for Business, Management, Economics, Finance, Insurance. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
| url |
https://doi.org/10.1007/978-3-319-94129-5 |
| illustrated |
Not Illustrated |
| dewey-hundreds |
500 - Science |
| dewey-tens |
510 - Mathematics |
| dewey-ones |
519 - Probabilities & applied mathematics |
| dewey-full |
519.2 |
| dewey-sort |
3519.2 |
| dewey-raw |
519.2 |
| dewey-search |
519.2 |
| first_indexed |
2023-12-27T22:04:53Z |
| last_indexed |
2023-12-30T21:17:09Z |
| recordtype |
opac |
| publisher |
Cham : : Springer International Publishing : : Imprint: Springer, |
| _version_ |
1786739351941545985 |
| score |
13,371208 |
| generalnotes |
Drawing 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. |