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

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
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:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Mostafa, Fahed.  |e author. 
245 1 0 |a Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk  |h [electronic resource] /  |c by Fahed Mostafa, Tharam Dillon, Elizabeth Chang. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a X, 171 p. 23 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 697 
505 0 |a 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. 
520 |a 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. . 
650 0 |a Engineering. 
650 0 |a Operations research. 
650 0 |a Decision making. 
650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
650 0 |a Macroeconomics. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Macroeconomics/Monetary Economics//Financial Economics. 
650 2 4 |a Operation Research/Decision Theory. 
700 1 |a Dillon, Tharam.  |e author. 
700 1 |a Chang, Elizabeth.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319516660 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 697 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-51668-4  |z Full Text via HEAL-Link 
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950 |a Engineering (Springer-11647)