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

• Κύριοι συγγραφείς: Mostafa, Fahed (Συγγραφέας), Dillon, Tharam (Συγγραφέας), Chang, Elizabeth (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Studies in Computational Intelligence, 697
• Θέματα: Engineering.; Operations research.; Decision making.; Artificial intelligence.; Computational intelligence.; Macroeconomics.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).; Macroeconomics/Monetary Economics//Financial Economics.; Operation Research/Decision Theory.
• Φυσική περιγραφή: X, 171 p. 23 illus. online resource.
• ISBN: 9783319516684
• ISSN: 1860-949X ;

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. .