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Autor(en): 
  • Jean Jacod
  • Philip Protter
  • Discretization of Processes 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2011  
    Genre:  Schulbücher 
     
    B / Econometrics / Econometrics & economic statistics / Economics, finance, business & management / Mathematics and Statistics / Probabilities / Probability & statistics / Probability Theory / Probability Theory and Stochastic Processes / Quantitative Economics / Statistics / Stochastics
    ISBN:  9783642241260 
    EAN-Code: 
    9783642241260 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  #67 - Stochastic Modelling and Applied Probability  
    Dimensionen:  H 235 mm / B 155 mm / D 38 mm 
    Gewicht:  1075 gr 
    Seiten:  596 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      
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