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Stock prediction and mutual fund portfolio management using curve fitting techniques
Investment in the share market helps generate more profit than the other financial instruments but has the threat of market risk that might lead to a high loss. This risk factor refrains many potential investors from investing in the share market directly. Instead, they invest in different mutual fu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7776288/ https://www.ncbi.nlm.nih.gov/pubmed/33425048 http://dx.doi.org/10.1007/s12652-020-02693-6 |
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author | Maji, Giridhar Mondal, Debomita Dey, Nilanjan Debnath, Narayan C. Sen, Soumya |
author_facet | Maji, Giridhar Mondal, Debomita Dey, Nilanjan Debnath, Narayan C. Sen, Soumya |
author_sort | Maji, Giridhar |
collection | PubMed |
description | Investment in the share market helps generate more profit than the other financial instruments but has the threat of market risk that might lead to a high loss. This risk factor refrains many potential investors from investing in the share market directly. Instead, they invest in different mutual funds that are being managed by experienced portfolio managers. To avoid the risk factors and increase the gain, they put the accumulated capital in multiple stocks. They need to perform many calculations and predictions to overcome the uncertainties and unpredictability and need to ensure higher gains to the investors of that mutual fund. In this research work initially, a data mining based approach employs a curve fitting/regression technique to forecast the individual stock price. Based on the above analysis, we propose a framework to diversify the investment of the capital fund. This method employs buy and hold strategy using both statistical features and basic domain knowledge of the share market. The proposed framework distributes the capital first, by distributing sector-wise, and then for each sector, investing company-wise, as a diversified approach among different stocks for higher return but maintaining lower risks. Experimental results show that the proposed framework performs well and generates a good yield compared to some benchmark and ranked mutual funds in the Indian stock market. |
format | Online Article Text |
id | pubmed-7776288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-77762882021-01-04 Stock prediction and mutual fund portfolio management using curve fitting techniques Maji, Giridhar Mondal, Debomita Dey, Nilanjan Debnath, Narayan C. Sen, Soumya J Ambient Intell Humaniz Comput Original Research Investment in the share market helps generate more profit than the other financial instruments but has the threat of market risk that might lead to a high loss. This risk factor refrains many potential investors from investing in the share market directly. Instead, they invest in different mutual funds that are being managed by experienced portfolio managers. To avoid the risk factors and increase the gain, they put the accumulated capital in multiple stocks. They need to perform many calculations and predictions to overcome the uncertainties and unpredictability and need to ensure higher gains to the investors of that mutual fund. In this research work initially, a data mining based approach employs a curve fitting/regression technique to forecast the individual stock price. Based on the above analysis, we propose a framework to diversify the investment of the capital fund. This method employs buy and hold strategy using both statistical features and basic domain knowledge of the share market. The proposed framework distributes the capital first, by distributing sector-wise, and then for each sector, investing company-wise, as a diversified approach among different stocks for higher return but maintaining lower risks. Experimental results show that the proposed framework performs well and generates a good yield compared to some benchmark and ranked mutual funds in the Indian stock market. Springer Berlin Heidelberg 2021-01-02 2021 /pmc/articles/PMC7776288/ /pubmed/33425048 http://dx.doi.org/10.1007/s12652-020-02693-6 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Maji, Giridhar Mondal, Debomita Dey, Nilanjan Debnath, Narayan C. Sen, Soumya Stock prediction and mutual fund portfolio management using curve fitting techniques |
title | Stock prediction and mutual fund portfolio management using curve fitting techniques |
title_full | Stock prediction and mutual fund portfolio management using curve fitting techniques |
title_fullStr | Stock prediction and mutual fund portfolio management using curve fitting techniques |
title_full_unstemmed | Stock prediction and mutual fund portfolio management using curve fitting techniques |
title_short | Stock prediction and mutual fund portfolio management using curve fitting techniques |
title_sort | stock prediction and mutual fund portfolio management using curve fitting techniques |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7776288/ https://www.ncbi.nlm.nih.gov/pubmed/33425048 http://dx.doi.org/10.1007/s12652-020-02693-6 |
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