AgentApplication in the Stock Market

Perminous Kahome, Elisha Opiyo, William Okello-Odongo


The stock market is a key market in any economy and financial forecast
such as stock price prediction is a field receiving much attention both
for research studies and commercial applications. Stock market
forecasters are keen on developing a successful approach to predict
stock prices even more accurately since there is motivation of gaining
massive profits from trading shares by using well defined attractive
strategies. This research project develops a stock price prediction model
built using JADE environment. It is based on multi-agent architecture
in order to harness the power of agents. This provides investors with
predicted trend of share price by incorporating various correlated
factors like economic, political, company outlook to traditional price
over time, demand and supply in order to accurately forecast the stock
price trend and thus, provide a buying or selling signal to traders. The
end is determined by incorporating text processing in agents from
live news sources. The model was tested and has proved to be a key                                                         tool for stockbrokers, novice traders and investment bankers since it
is automated and more robust than traditional methods of price

Keywords: Agents, Stock Market, Prediction, Model, Text processing.

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[ISSN 1821-7567 (Print)  & eISSN 2591-6947 (Online)]