Optimisation-Enabled Transfer Learning Framework for Stock Market Prediction
Pankaj Rambhau Patil,
Deepa Parasar,
Shrikant Charhate
Abstract:Stock market prediction is a vital task with high attention for gaining attractive profits with proper decisions to invest. Predicting the stock market is becoming a major challenge nowadays due to chaotic data, non-stationary data, and blaring data. Hence, it’s challenging for investors to invest money to make profits. Many techniques are developed to predict stock market trends, but each differs based on time and year. In this paper, hybridised optimisation algorithm, namely the proposed Gannet Ladybug Beetl… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.