Computational intelligence applications to option pricing, volatility forecasting and value at risk
Mostafa, Fahed,
Computational intelligence applications to option pricing, volatility forecasting and value at risk Fahed Mostafa, Tharam Dillon, Elizabeth Chang. - 1 recurso en línea (x, 171 páginas) ilustraciones - Studies in computational intelligence volume 697 1860-949X .
SpringerLink
Incluye referencias bibliográficas
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.
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.
3319516663 331951668X 9783319516660 9783319516684
Inteligencia artificial
Q342 / .M678 2017 EB
Computational intelligence applications to option pricing, volatility forecasting and value at risk Fahed Mostafa, Tharam Dillon, Elizabeth Chang. - 1 recurso en línea (x, 171 páginas) ilustraciones - Studies in computational intelligence volume 697 1860-949X .
SpringerLink
Incluye referencias bibliográficas
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.
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.
3319516663 331951668X 9783319516660 9783319516684
Inteligencia artificial
Q342 / .M678 2017 EB