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- W2488490732 abstract "Stock trading, used to predict the direction of future stock prices, is a dynamic business primarily based on human intuition. This involves analyzing some non-linear fundamental and technical stock variables which are recorded periodically. This study presents the development of an ANN-based prediction model for forecasting closing price in the stock markets. The major steps taken are identification of technical variables used for prediction of stock prices, collection and pre-processing of stock data, and formulation of the ANN-based predictive model. Stock data of periods between 2010 and 2014 were collected from the Nigerian Stock Exchange (NSE) and stored in a database. The data collected were classified into training and test data, where the training data was used to learn non-linear patterns that exist in the dataset; and test data was used to validate the prediction accuracy of the model. Evaluation results obtained from WEKA shows that discrepancies between actual and predicted values are insignificant." @default.
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- W2488490732 date "2016-07-01" @default.
- W2488490732 modified "2023-09-27" @default.
- W2488490732 title "Simulation of Stock Prediction System using Artificial Neural Networks" @default.
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- W2488490732 doi "https://doi.org/10.4018/ijban.2016070102" @default.
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