Enhancing forthcoming trend estimation in trading platform based on multiphase combination of sentiment analysis and LSTM

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Title

Enhancing forthcoming trend estimation in trading platform based on multiphase combination of sentiment analysis and LSTM

Content partner

Unitec

Collection

Research Bank

Description

Since its inception, the stock market has piqued the curiosity of researchers, and several attempts have been made to forecast its future patterns. The market is dynamic, and the value of an organisation’s stock price is influenced by a variety of elements, including previous stock data and public attitudes and opinions. Researchers have shown that the "public sentiment" which split them into two factions, one in favor and the other against is the most prevalent of these characteristics. It g...

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Format

Research paper

Research format

Thesis

Thesis level

Masters

Date created

2024

Creator

Trehan, Mohita

URL

https://hdl.handle.net/10652/6470

Related subjects

New Zealand Stock Exchange (NZX) / New Zealand / stock markets / stock movement prediction / stock price analysis / sentiment analysis (SA) / Long Short-Term Memory (LSTM) / computer modelling / deep-learning algorithms / algorithms / Commerce, management, tourism and services / Banking, finance and investment / Banking, finance and investment not elsewhere classified / Mathematical sciences / Statistics / Computational statistics / Information and computing sciences / Artificial intelligence

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