rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Discretization of Processes
  name:
    name part: Jacod, Jean.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Protter, Philip.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 596 p. online resource.
  abstract: 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 wont to say, “In God we trust; all others must bring data.” This book establishes the theory of how to go about estimating not just scalar parameters about a proposed model, but also the underlying structure of the model itself. Classic statistical tools are used: the law of large numbers, and the central limit theorem. Researchers have recently developed creative and original methods to use these tools in sophisticated (but highly technical) ways to reveal new details about the underlying structure. For the first time in book form, the authors present these latest techniques, based on research from the last 10 years. They include new findings. This book will be of special interest to researchers, combining the theory of mathematical finance with its investigation using market data, and it will also prove to be useful in a broad range of applications, such as to mathematical biology, chemical engineering, and physics.
  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.
  note: by Jean Jacod, Philip Protter.
  subject:
    topic: Mathematics
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Econometrics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistics for Business/Economics/Mathematical Finance/Insurance
  subject:
    topic: Econometrics
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Stochastic Modelling and Applied Probability, 67
  identifier: 9783642241277
  identifier: http://dx.doi.org/10.1007/978-3-642-24127-7
  record info:
    record creation date: 111021
    record change date: 20151103131922.0
    record identifier: 978-3-642-24127-7