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Herausgeber: 
  • Rogemar S. Mamon
  • Robert J Elliott
  • Hidden Markov Models in Finance 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2007  
    Genre:  Ratgeber 
     
    B / Business / Business & management / Business and Management / Business and Management, general / Decision Making / Finance / Finance, general / Management & management techniques / Management decision making / Management science / Mathematical Modeling and Industrial Mathematics / Mathematical modelling / Mathematical models / Maths for engineers / Operational research / Operations Research / Operations Research and Decision Theory / Operations Research, Management Science / Operations Research/Decision Theory / Probabilities / Probability & statistics / Probability Theory / Probability Theory and Stochastic Processes / Stochastics
    ISBN:  9780387710815 
    EAN-Code: 
    9780387710815 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  #104 - International Series in Operations Research & Management Science  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  1040 gr 
    Seiten:  186 
    Illustration:  XX, 186 p. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    A number of methodologies have been employed to provide decision making solutions to a whole assortment of financial problems in today's globalized markets. Hidden Markov Models in Finance by Mamon and Elliott will be the first systematic application of these methods to some special kinds of financial problems; namely, pricing options and variance swaps, valuation of life insurance policies, interest rate theory, credit risk modeling, risk management, analysis of future demand and inventory level, testing foreign exchange rate hypothesis, and early warning systems for currency crises. This book provides researchers and practitioners with analyses that allow them to sort through the random "noise" of financial markets (i.e., turbulence, volatility, emotion, chaotic events, etc.) and analyze the fundamental components of economic markets. Hence, Hidden Markov Models in Finance provides decision makers with a clear, accurate picture of core financial components by filtering out the random noise in financial markets.

     

      



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