Forecasting stock prices of fintech companies of India using random forest with high-frequency data

dc.contributor.author	Singh, Manohar
dc.contributor.author	Meher, Bharat Kumar
dc.contributor.author	Birau, Ramona
dc.contributor.author	Anand, Abhishek
dc.date.accessioned	2024-08-12T09:05:29Z
dc.date.available	2024-08-12T09:05:29Z
dc.date.issued	2024
dc.identifier.issn	2199-8531
dc.identifier.uri	https://thuvienso.hoasen.edu.vn/handle/123456789/15581
dc.description.tableofcontents	Journal of Open Innovation: Technology, Market, and Complexity, Vol.10, 2024; P. 1-10 https://doi.org/10.1016/j.joitmc.2023.100180	vi
dc.language.iso	en	vi
dc.publisher	Elsevier	vi
dc.subject	Forecasting	vi
dc.subject	Random Forest	vi
dc.subject	High-frequency data	vi
dc.subject	Python	vi
dc.title	Forecasting stock prices of fintech companies of India using random forest with high-frequency data	vi
dc.type	Article	vi