Discretization of Processes

In applications, and especially in mathematical finance, random time-dependent events are often modeled as stochastic processes. Assumptions are made about the structure of such processes, and serious researchers will want to justify those assumptions through the use of data.  As statisticians are w...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Jacod, Jean (Author), Protter, Philip (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edition:1st ed. 2012.
Series:Stochastic Modelling and Applied Probability, 67
Subjects:
Probabilities.
Statistics .
Econometrics.
Probability Theory.
Statistics in Business, Management, Economics, Finance, Insurance.
Online Access:Texto Completo
Table of Contents:
  • Part I Introduction and Preliminary Material
  • 1.Introduction
  • 2.Some Prerequisites
  • Part II The Basic Results
  • 3.Laws of Large Numbers: the Basic Results
  • 4.Central Limit Theorems: Technical Tools
  • 5.Central Limit Theorems: the Basic Results
  • 6.Integrated Discretization Error
  • Part III More Laws of Large Numbers
  • 7.First Extension: Random Weights
  • 8.Second Extension: Functions of Several Increments
  • 9.Third Extension: Truncated Functionals
  • Part IV Extensions of the Central Limit Theorems
  • 10.The Central Limit Theorem for Random Weights
  • 11.The Central Limit Theorem for Functions of a Finite Number of Increments
  • 12.The Central Limit Theorem for Functions of an Increasing Number of Increments
  • 13.The Central Limit Theorem for Truncated Functionals
  • Part V Various Extensions
  • 14.Irregular Discretization Schemes. 15.Higher Order Limit Theorems
  • 16.Semimartingales Contaminated by Noise
  • Appendix
  • References
  • Assumptions
  • Index of Functionals
  • Index.

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