Effect of Leaders Voice on Financial Market: An Empirical Deep Learning Expedition on NASDAQ, NSE, and Beyond
CoRR(2024)
摘要
Financial market like the price of stock, share, gold, oil, mutual funds are
affected by the news and posts on social media. In this work deep learning
based models are proposed to predict the trend of financial market based on NLP
analysis of the twitter handles of leaders of different fields. There are many
models available to predict financial market based on only the historical data
of the financial component but combining historical data with news and posts of
the social media like Twitter is the main objective of the present work.
Substantial improvement is shown in the result. The main features of the
present work are- a) proposing completely generalized algorithm which is able
to generate models for any twitter handle and any financial component, b)
predicting the time window for a tweets effect on a stock price c) analyzing
the effect of multiple twitter handles for predicting the trend. A detailed
survey is done to find out the latest work in recent years in the similar
field, find the research gap, and collect the required data for analysis and
prediction. State-of-the-art algorithm is proposed and complete implementation
with environment is given. An insightful trend of the result improvement
considering the NLP analysis of twitter data on financial market components is
shown. The Indian and USA financial markets are explored in the present work
where as other markets can be taken in future. The socio-economic impact of the
present work is discussed in conclusion.
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