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02747nam a22005415i 4500 |
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978-3-319-51668-4 |
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|a 9783319516684
|9 978-3-319-51668-4
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|a 10.1007/978-3-319-51668-4
|2 doi
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|a 006.3
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|a Mostafa, Fahed.
|e author.
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|a Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
|h [electronic resource] /
|c by Fahed Mostafa, Tharam Dillon, Elizabeth Chang.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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|a X, 171 p. 23 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a text file
|b PDF
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 697
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|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.
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|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. .
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|a Engineering.
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|a Operations research.
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|a Decision making.
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|a Artificial intelligence.
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|a Computational intelligence.
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|a Macroeconomics.
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|a Engineering.
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|a Computational Intelligence.
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|a Artificial Intelligence (incl. Robotics).
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|a Macroeconomics/Monetary Economics//Financial Economics.
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|a Operation Research/Decision Theory.
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|a Dillon, Tharam.
|e author.
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|a Chang, Elizabeth.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319516660
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 697
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|u http://dx.doi.org/10.1007/978-3-319-51668-4
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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|a Engineering (Springer-11647)
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