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007			cr nn nnnaamaa
008			191113s2019 gw a o |||| 0|eng d
020			_a9783030302634
024	7		_a10.1007/978-3-030-30263-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aHG4529.5 _b2019 EB
100	1		_aXing, Frank _eautor _9672547
245	1	0	_aIntelligent Asset Management _cby Frank Xing, Erik Cambria, Roy Welsch
250			_aFirst edition
264		1	_aCham, Switzerland _bSpringer International Publishing _c2019
300			_a1 recurso en línea (XXII, 149 páginas) _b43 ilustraciones, 34 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aSocio-Affective Computing _x2509-5706 _v9
490	0		_aBiomedical and Life Sciences (Springer-11642)
505	0		_aChapter 1. Introduction -- Chapter 2 -- Revisiting the Literature -- Chapter 3. Theoretical Underpinnings on Text Mining -- Chapter 4. Computational Semantics for Asset Correlations -- Chapter 5. Sentiment Analysis for View Modeling -- Chapter 6. Storage and Update of Domain Knowledge -- Chapter 7. Dialog Systems and Robo-advisory -- Chapter 8. Concluding Remarks -- Appendix -- Index.
520	3		_aThis book presents a systematic application of recent advances in artificial intelligence (AI) to the problem of asset management. While natural language processing and text mining techniques, such as semantic representation, sentiment analysis, entity extraction, commonsense reasoning, and fact checking have been evolving for decades, finance theories have not yet fully considered and adapted to these ideas. In this unique, readable volume, the authors discuss integrating textual knowledge and market sentiment step-by-step, offering readers new insights into the most popular portfolio optimization theories: the Markowitz model and the Black-Litterman model. The authors also provide valuable visions of how AI technology-based infrastructures could cut the cost of and automate wealth management procedures. This inspiring book is a must-read for researchers and bankers interested in cutting-edge AI applications in finance.
988			_aPrimersemestre_2020_BiomedLife
650		7	_9151190 _aGestión de cartera
700	1		_aCambria, Erik _eautor _993992
700	1		_aWelsch, Roy E. _eautor _9672548
710	2		_aSpringerLink (Online service) _9106996
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030302627
776	0	8	_iPrinted edition: _z9783030302641
776	0	8	_iPrinted edition: _z9783030302658
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-30263-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2020 _da _eh _zSI