Modelado de sistemas de inversión mediante lógica borrosa como soporte a la toma de decisiones en mercados bursátiles
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2018
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07/07/2017
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Universidad Complutense de Madrid
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Abstract
Saber cuándo y cómo invertir en los mercados de valores es una decisión difícil de tomar para los inversores. Los mercados bursátiles requieren conocimientos específicos, un análisis exhaustivo de los mercados y una gran experiencia. Hoy en día hay multitud de mercados, diferentes variables, indicadores, patrones, etc., que deben ser analizados antes de tomar una decisión financiera en un corto intervalo de tiempo. Por ese motivo los inversores recurren a técnicas computacionales, algunas de ellas provenientes de inteligencia artificial, para paliar esta gran carga de trabajo que supone el análisis de dichos mercados.Dentro de esta línea, la presente tesis incide en el soporte que ofrecen las técnicas de soft computing, en concreto la lógica borrosa, a la toma de decisión. Debido a las características propias de este escenario de aplicación, se presenta como idónea y ofrece una gran mejora respecto a los sistemas clásicos de trading. Este trabajo de investigación se ha focalizado en el análisis técnico, el cual se basa exclusivamente en la observación de los precios y volúmenes de transacción de las operaciones bursátiles, permitiendo a los inversores anticipar los movimientos del mercado...
Knowing when and how to invest in stock markets is a difficult decision to make by investors. Stock markets require knowledge, a thorough analysis of the markets and a great deal of experience. Today, there are a multitude of markets, different variables, indicators, patterns, etc. that need to be analyzed before making a financial decision in a short time interval. Because of this, investors use artificial intelligence techniques to alleviate this heavy workload that involves the analysis of these markets.In this area, the present thesis focuses on the field of decision systems implemented by soft computing techniques, namely fuzzy logic. Due to the characteristics of the application scenario, it is presented as suitable and promises a great improvement over the classical trading systems. In particular, the technical analysis has been chosen, which is based exclusively on observing market prices and transaction volumes, allowing investors to anticipate market movements...
Knowing when and how to invest in stock markets is a difficult decision to make by investors. Stock markets require knowledge, a thorough analysis of the markets and a great deal of experience. Today, there are a multitude of markets, different variables, indicators, patterns, etc. that need to be analyzed before making a financial decision in a short time interval. Because of this, investors use artificial intelligence techniques to alleviate this heavy workload that involves the analysis of these markets.In this area, the present thesis focuses on the field of decision systems implemented by soft computing techniques, namely fuzzy logic. Due to the characteristics of the application scenario, it is presented as suitable and promises a great improvement over the classical trading systems. In particular, the technical analysis has been chosen, which is based exclusively on observing market prices and transaction volumes, allowing investors to anticipate market movements...
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Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 07-07-2017