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Artificial intelligence in Behavioral Finance
Niyazli, Toghrul ; Ismayilov, Ilgar (vedoucí práce) ; Novák, Jiří (oponent)
Since the dot.com bubble burst in 2001, financial markets have been plagued by extreme volatility caused by investors emotions and irrational behaviors. Since the financial market has become more complex and tech oriented, stock market sentiment has been a key determinant of large market movements. In this context, it is worth to look into the role of emotions such as fear, greed, and excitement in influencing investment decisions. In addition, newly developed artificial intelligence techniques can be utilized to record and collect data from online sources to conclude collective irrational human behaviors. Behavioral finance is a newly developed discipline that examines the impact of psychological elements on decision-making processes when individuals encounter uncertain situations. This thesis aims to analyze the influence of behavioral finance phenomena including Herding, Anchoring, and Overconfidence biases on the investment decision-making practices within the context of the United States stock market. One of the study goals is to investigate whether sentiment of public, can be a rational tool impacting on investors' decision- making process or not. The investigation is prompted by the potential of Artificial Intelligence and Machine Learning to accurately analyze vast amounts of data and make...
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