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Computational intelligence applications to option pricing, volatility forecasting and value at risk / Fahed Mostafa, Tharam Dillon, Elizabeth Chang.

By: Mostafa, Fahed,, autor
Contributor(s): Chang, Elizabeth,, autor | Dillon, Tharam S., (1943-), autor
Material type: materialTypeLabelE-bookSeries: (Studies in computational intelligence, 1860-949X ; volume 697).Publisher: Cham, Switzerland : Springer, 2017Description: 1 recurso en línea (x, 171 páginas) : ilustraciones.ISBN: 3319516663; 331951668X; 9783319516660; 9783319516684.Subject: Inteligencia artificialOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
CHAPTER 1 Introduction -- CHAPTER 2 Time Series Modelling -- CHAPTER 3 Options and Options Pricing Models -- CHAPTER 4 Neural Networks and Financial Forecasting -- CHAPTER 5 Important Problems in Financial Forecasting -- CHAPTER 6 Volatility Forecasting -- CHAPTER 7 Option Pricing -- CHAPTER 8 Value-at-Risk -- CHAPTER 9 Conclusion and Discussion.
Abstract: The results in this book demonstrate the power of neural networks in learning complex behavior from the underlying financial time series data . The results in this book also demonstrate how neural networks can successfully be applied to volatility modeling, option pricings, and value at risk modeling. These features allow them to be applied to market risk problems to overcome classical issues associated with statistical models.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q342 .M678 2017 EB (Browse shelf(Opens below)) Acceso electrónico eBook.20023136
Total holds: 0

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CHAPTER 1 Introduction -- CHAPTER 2 Time Series Modelling -- CHAPTER 3 Options and Options Pricing Models -- CHAPTER 4 Neural Networks and Financial Forecasting -- CHAPTER 5 Important Problems in Financial Forecasting -- CHAPTER 6 Volatility Forecasting -- CHAPTER 7 Option Pricing -- CHAPTER 8 Value-at-Risk -- CHAPTER 9 Conclusion and Discussion.

The results in this book demonstrate the power of neural networks in learning complex behavior from the underlying financial time series data . The results in this book also demonstrate how neural networks can successfully be applied to volatility modeling, option pricings, and value at risk modeling. These features allow them to be applied to market risk problems to overcome classical issues associated with statistical models.

Online resource; title from PDF title page (SpringerLink, viewed March 9, 2017).

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