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020 _a331951668X
_q(electronic bk.)
020 _a9783319516660
020 _a9783319516684
_q(electronic bk.)
020 _z9783319516660
_q(print)
040 _aGW5XE
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050 4 _aQ342
_b.M678 2017 EB
100 1 _aMostafa, Fahed,
_eautor
245 1 0 _aComputational intelligence applications to option pricing, volatility forecasting and value at risk
_cFahed Mostafa, Tharam Dillon, Elizabeth Chang.
264 1 _aCham, Switzerland
_bSpringer
_c2017.
300 _a1 recurso en línea (x, 171 páginas)
_bilustraciones
336 _aTexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 0 _aStudies in computational intelligence
_x1860-949X
_vvolume 697
500 _aSpringerLink
504 _aIncluye referencias bibliográficas
505 0 _aCHAPTER 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 3 _aThe 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.
588 0 _aOnline resource; title from PDF title page (SpringerLink, viewed March 9, 2017).
988 _aEBOOK, EBSPRINGER_2017C
650 7 _2embne
_aInteligencia artificial
_9413115
700 1 _aChang, Elizabeth,
_eautor
700 1 _aDillon, Tharam S.,
_d1943-
_eautor
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-319-51668-4
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b02/2018
_dz
_e-
_zSI