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This 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.
Medicine. --- Data mining. --- Artificial intelligence. --- E-business. --- Electronic commerce. --- E-commerce. --- Biomedicine, general. --- Data Mining and Knowledge Discovery. --- Artificial Intelligence. --- e-Business/e-Commerce. --- e-Commerce/e-business. --- Cybercommerce --- E-business --- E-commerce --- E-tailing --- eBusiness --- eCommerce --- Electronic business --- Internet commerce --- Internet retailing --- Online commerce --- Web retailing --- Commerce --- Information superhighway --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Health Workforce --- Asset allocation. --- Allocation of assets --- Investments --- Portfolio management --- Intel·ligència artificial --- Ciència cognitiva --- Mètodes de simulació --- Processament de dades --- Sistemes autoorganitzatius --- Aprenentatge automàtic --- Demostració automàtica de teoremes --- Intel·ligència artificial distribuïda --- Intel·ligència computacional --- Sistemes adaptatius --- Tractament del llenguatge natural (Informàtica) --- Raonament qualitatiu --- Representació del coneixement (Teoria de la informació) --- Sistemes de pregunta i resposta --- Traducció automàtica --- Visió per ordinador --- Xarxes neuronals (Informàtica) --- Xarxes semàntiques (Teoria de la informació) --- Agents intel·ligents (Programes d'ordinador) --- Programació per restriccions --- Vida artificial --- Intel·ligència artificial.
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Mathematical statistics --- Regression analysis --- Analyse de régression --- Regression Analysis --- 519.237 --- 519.235 --- AA / International- internationaal --- 303.0 --- 303.5 --- 303.3 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Multivariate statistical methods --- Statistics of dependent variables. Contingency tables --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek). --- Waarschijnlijkheid. Probabiliteit. Nauwkeurigheid. Residuals: measurement and specification (wiskundige statistiek). --- Regression analysis. --- 519.235 Statistics of dependent variables. Contingency tables --- 519.237 Multivariate statistical methods --- Analyse de régression --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Waarschijnlijkheid. Probabiliteit. Nauwkeurigheid. Residuals: measurement and specification (wiskundige statistiek) --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek)
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This paper attempts to provide the user of linear multiple regression with a battery of diagnostic tools to determine which, if any, data points have high leverage or influence on the estimation process and how these possibly discrepant data points differ from the patterns set by the majority of the data. The point of view taken is that when diagnostics indicate the presence of anomolous data, the choice is open as to whether these data are in fact unusual and helpful, or possibly harmful and thus in need of modifications or deletion. The methodology developed depends on differences, derivatives, and decompositions of basic regression statistics. There is also a discussion of how these techniques can be used with robust and ridge estimators. An example is given showing the use of diagnostic methods in the estimation of a cross-country savings rate model.
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