Abstract
AbstractThe Black Litterman (BL) model for portfolio optimization combines investors’ expectations with the Markowitz framework. The BL model is designed for investors with private information or with knowledge of market behavior. In this paper I propose a method where investors’ expectations are based on accounting variables, recommendations of financial analysts, and social network indicators of financial analysts and corporate directors. The results show promise when compared to those of an investor that only uses market price information. I also provide recommendations about trading strategies using the results of my model.KeywordsLink miningsocial networkmachine learningcomputational financeportfolio optimizationboostingBlack Litterman model
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