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Jump SDEs and the study of their den...
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Kohatsu-Higa, Arturo.
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Jump SDEs and the study of their densities = a self-study book /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Jump SDEs and the study of their densities/ by Arturo Kohatsu-Higa, Atsushi Takeuchi.
其他題名:
a self-study book /
作者:
Kohatsu-Higa, Arturo.
其他作者:
Takeuchi, Atsushi.
出版者:
Singapore :Springer Singapore : : 2019.,
面頁冊數:
xix, 355 p. :ill., digital ;24 cm.
內容註:
Review of some basic concepts of probability theory -- Simple Poisson process and its corresponding SDEs -- Compound Poisson process and its associated stochastic calculus -- Construction of Levy processes and their corresponding SDEs: The finite variation case -- Construction of Levy processes and their corresponding SDEs: The infinite variation case -- Multi-dimensional Levy processes and their densities -- Flows associated with stochastic differential equations with jumps -- Overview -- Techniques to study the density -- Basic ideas for integration by parts formulas -- Sensitivity formulas -- Integration by parts: Norris method -- A non-linear example: The Boltzmann equation -- Further hints for the exercises.
Contained By:
Springer Nature eBook
標題:
Stochastic differential equations. -
電子資源:
https://doi.org/10.1007/978-981-32-9741-8
ISBN:
9789813297418
Jump SDEs and the study of their densities = a self-study book /
Kohatsu-Higa, Arturo.
Jump SDEs and the study of their densities
a self-study book /[electronic resource] :by Arturo Kohatsu-Higa, Atsushi Takeuchi. - Singapore :Springer Singapore :2019. - xix, 355 p. :ill., digital ;24 cm. - Universitext,0172-5939. - Universitext..
Review of some basic concepts of probability theory -- Simple Poisson process and its corresponding SDEs -- Compound Poisson process and its associated stochastic calculus -- Construction of Levy processes and their corresponding SDEs: The finite variation case -- Construction of Levy processes and their corresponding SDEs: The infinite variation case -- Multi-dimensional Levy processes and their densities -- Flows associated with stochastic differential equations with jumps -- Overview -- Techniques to study the density -- Basic ideas for integration by parts formulas -- Sensitivity formulas -- Integration by parts: Norris method -- A non-linear example: The Boltzmann equation -- Further hints for the exercises.
The present book deals with a streamlined presentation of Levy processes and their densities. It is directed at advanced undergraduates who have already completed a basic probability course. Poisson random variables, exponential random variables, and the introduction of Poisson processes are presented first, followed by the introduction of Poisson random measures in a simple case. With these tools the reader proceeds gradually to compound Poisson processes, finite variation Levy processes and finally one-dimensional stable cases. This step-by-step progression guides the reader into the construction and study of the properties of general Levy processes with no Brownian component. In particular, in each case the corresponding Poisson random measure, the corresponding stochastic integral, and the corresponding stochastic differential equations (SDEs) are provided. The second part of the book introduces the tools of the integration by parts formula for jump processes in basic settings and first gradually provides the integration by parts formula in finite-dimensional spaces and gives a formula in infinite dimensions. These are then applied to stochastic differential equations in order to determine the existence and some properties of their densities. As examples, instances of the calculations of the Greeks in financial models with jumps are shown. The final chapter is devoted to the Boltzmann equation.
ISBN: 9789813297418
Standard No.: 10.1007/978-981-32-9741-8doiSubjects--Topical Terms:
621860
Stochastic differential equations.
LC Class. No.: QA274.23 / .K64 2019
Dewey Class. No.: 519.22
Jump SDEs and the study of their densities = a self-study book /
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Review of some basic concepts of probability theory -- Simple Poisson process and its corresponding SDEs -- Compound Poisson process and its associated stochastic calculus -- Construction of Levy processes and their corresponding SDEs: The finite variation case -- Construction of Levy processes and their corresponding SDEs: The infinite variation case -- Multi-dimensional Levy processes and their densities -- Flows associated with stochastic differential equations with jumps -- Overview -- Techniques to study the density -- Basic ideas for integration by parts formulas -- Sensitivity formulas -- Integration by parts: Norris method -- A non-linear example: The Boltzmann equation -- Further hints for the exercises.
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The present book deals with a streamlined presentation of Levy processes and their densities. It is directed at advanced undergraduates who have already completed a basic probability course. Poisson random variables, exponential random variables, and the introduction of Poisson processes are presented first, followed by the introduction of Poisson random measures in a simple case. With these tools the reader proceeds gradually to compound Poisson processes, finite variation Levy processes and finally one-dimensional stable cases. This step-by-step progression guides the reader into the construction and study of the properties of general Levy processes with no Brownian component. In particular, in each case the corresponding Poisson random measure, the corresponding stochastic integral, and the corresponding stochastic differential equations (SDEs) are provided. The second part of the book introduces the tools of the integration by parts formula for jump processes in basic settings and first gradually provides the integration by parts formula in finite-dimensional spaces and gives a formula in infinite dimensions. These are then applied to stochastic differential equations in order to determine the existence and some properties of their densities. As examples, instances of the calculations of the Greeks in financial models with jumps are shown. The final chapter is devoted to the Boltzmann equation.
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