Fahed Mostafa, Tharam Dillon, Elizabeth Chang

Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk

• Broschiertes Buch

Produktbeschreibung

This book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.

Produktdetails

• Studies in Computational Intelligence 697
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-84713-9
• Softcover reprint of the original 1st ed. 2017
• Seitenzahl: 184
• Erscheinungstermin: 4. Mai 2018
• Englisch
• Abmessung: 235mm x 155mm x 11mm
• Gewicht: 290g
• ISBN-13: 9783319847139
• ISBN-10: 3319847139
• Artikelnr.: 53572354

Inhaltsangabe

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.

Rezensionen

"The book describes how to deal with the different sorts of financial market risk. ... The book can be used by advanced undergraduate students and graduate students in its entirety. It is also interesting for the specialists in financial market risk and is of considerable importance to practitioners in the field." (Yuliya S. Mishura, zbMath 1410.91004, 2019)