@inproceedings{0931dd891262472db010729541a73f87,
title = "Trend Detection in Stock Prices using Ensemble Methods",
abstract = "Stock market index prediction and forecasting is a tedious task; this is pure since stock data series start behaving as a similar to arbitrary-walk. The businesses have to hire investment specialists who would take excessively high profits in order to advise on investment choices. Such investment professionals offer an easy approach, which can be used by anyone with an internet connection and a computer. Market data analysis has always been of interest to various studies and research. Many factors affect the outcome of a particular stock. Hence correct and efficient understanding of the different indicators involved is essential for this domain. Estimating whether a particular stock would go high, or low is an intricate task and requires a lot of research. The proposed research aims to achieve better detection methods that can be applied to any market.",
author = "E. Naresh and \{Ananda Babu\}, J. and Tejonidhi, \{M. R.\} and Keerthi, \{K. S.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Data Science and Information System, ICDSIS 2022 ; Conference date: 29-07-2022 Through 30-07-2022",
year = "2022",
doi = "10.1109/ICDSIS55133.2022.9915848",
language = "English",
series = "IEEE International Conference on Data Science and Information System, ICDSIS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IEEE International Conference on Data Science and Information System, ICDSIS 2022",
address = "United States",
}