Hybridization of Machine Learning Techniques to Optimize Portfolio of Stock Market: Review of Literature from the Period 2005 to 2018
K.S. Mahajan1, Ulka Toro2, R.V.Kulkarni3
1Mrs. Keerti. Mahajan, Ph.D at Bharati Vidyapeeth Institute of Management ,Kolhapur.
2Dr. Ulka Toro, Associate Professor in Bharati Vidyapeeth Institute of Management, Kolhapur.
3Dr. R.V Kulkarni, Professor and Head of Computer studies in Chh. Shahu Institute of business education and research Kolhapur.
Manuscript received on December 22, 2020. | Revised Manuscript received on December 30, 2020. | Manuscript published on January 30, 2021. | PP: 33-41 | Volume-9 Issue-5, January 2021. | Retrieval Number: 100.1/ijrte.E5107019521 | DOI: 10.35940/ijrte.E5107.019521
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Abstract: In finance there has always been the problem of how to combine investments to form a portfolio. Progress on this problem we focus on some of the important applications such as Forecasting, Trading, Portfolio Selection and Management of Stock Market is considered as one of the fundamental building block of developed country. If number of investor’s increases then the economy of the country also increases and every investor invests to get good returns. But as stock market is uncertain and complicated the selection of good scripts are considered as one of the challenge in stock market field. So much work has been donein this field, The purpose of the present study is to review research articles from the period 2005 to 2018 and to find research gap for future work.
Keywords: Stock Market, Machine Learning Techniques, Fuzzy, Neural Network, Portfolio, BSE Stock Exchange, NSE Stock Exchange.