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.

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 modelin...

Πίνακας περιεχομένων:

• 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.