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Stock Trend Prediction from Mobile Device through Web Services

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dc.contributor.author Aung, Kay Thi
dc.date.accessioned 2019-07-18T16:01:36Z
dc.date.available 2019-07-18T16:01:36Z
dc.date.issued 2017-12-27
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/977
dc.description.abstract This paper presents a study of regression analysis for use in stock price prediction. The system shows the stock market trend of the specified bank using the previous stock prices. Data were obtained from the daily official list of the prices of all shares traded on the stock exchange. Android devices invoke stock price prediction process via restful web service. In the server side, the data mining process uncovers patterns and relationships and also extracts values of variables from the database to predict the future values of other variables through the use of time series data that employed moving average method. The data mining process predicts the trend of the future stock market price. The predicted result is sent as JSON response to android device. Android client shows the result with graph lines to support investors for decision making in stock market. For reducing the risk in stock investment, the investors can see the predicted trends of the companies comparing in one graph diagram and make decisions. en_US
dc.language.iso en en_US
dc.publisher Eighth Local Conference on Parallel and Soft Computing en_US
dc.title Stock Trend Prediction from Mobile Device through Web Services en_US
dc.type Article en_US

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