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Autor(en): 
  • Christoph Schwab
  • Christoph Winter
  • Oleg Reichmann
  • Norbert Hilber
  • Computational Methods for Quantitative Finance: Finite Element Methods for Derivative Pricing 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Februar 2013  
    Genre:  Schulbücher 
     
    Applications of Mathematics / B / Economics, Mathematical / Mathematics and Statistics / Numerical analysis / Probabilities / Probability & statistics / Probability Theory
    ISBN:  9783642354007 
    EAN-Code: 
    9783642354007 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Springer Finance  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  5974 gr 
    Seiten:  299 
    Illustration:  XIII, 299 p. 56 illus., 47 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Many mathematical assumptions on which classical derivative pricing methods are based have come under scrutiny in recent years. The present volume offers an introduction to deterministic algorithms for the fast and accurate pricing of derivative contracts in modern finance. This unified, non-Monte-Carlo computational pricing methodology is capable of handling rather general classes of stochastic market models with jumps, including, in particular, all currently used Lévy and stochastic volatility models. It allows us e.g. to quantify model risk in computed prices on plain vanilla, as well as on various types of exotic contracts. The algorithms are developed in classical Black-Scholes markets, and then extended to market models based on multiscale stochastic volatility, to Lévy, additive and certain classes of Feller processes. 

    This book is intended for graduate students and researchers, as well as for practitioners in the fields of quantitative finance and applied and computational mathematics with a solid background in mathematics, statistics or economics.

      



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