Analytical Study for Hybrid Method based Stock Recommendation

Abstract

Forecasting investment call on numerous offered stocks within the market could be a very difficult task. Economics and applied math models, yet as ML techniques and data pre-processing techniques, have planned hands-on type heuristic primarily related results with controlled long-range accomplishment. In follow, financial consultants potentiality and intellectuality are required to create and manage their portfolio of stocks. Non- professional investors are highly interested to follow an experts investment call because subjective judgment on offered stock associate degreed is not a cup of for them. It is crucial to search out associate degree knowledgeable with similar investment preferences for this purpose. In this proposed work stock recommendation model is proposed to gain profit from the facility of e-Social network analytical study. In foremost phase the social network of economic consultants will be build a social network of economic consultants supported there in public offered portfolios. This social network will be used for additional associate degree analysis to advocate an acceptable managed portfolio for non-professional investors supported their activity correspondence to the knowledgeable investors. This approach is conceptualized from real portfolios based case studies.