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ANALYSIS OF STOCK PRICE PREDICTION USING DATA MINING APPROACH

Mukhariz bin Muhamad, Mukhariz (2012) ANALYSIS OF STOCK PRICE PREDICTION USING DATA MINING APPROACH. Universiti Teknologi PETRONAS. (Unpublished)

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Abstract

Financial forecasting is one of the most interesting subjects within the area of machine learning studies. Forecasting stock prices is challenging due to the nature of stock prices that are usually non-linear, complex and noisy. This paper would be discussing the most prominent forecasting method which is the time-series forecasting and its machine learning tools used to create the prediction. The aim of this project is to study the data mining approach on predicting stock price that offers accuracy and sustains its reliability in the system. Using Data Mining approach in training the algorithms that will produce the best results based on Public Listed Companies‟ stock price data that dates back until 1998. This system utilizes Artificial Neural Network and Support Vector Machine as its main inference engine with numerous methods to measure the accuracy of both. It is anticipated that this analysis would become a platform for producing a prediction application that is reliable for usage in the future.

Item Type: Final Year Project
Subject: T Technology > T Technology (General)
Divisions: Sciences and Information Technology
Depositing User: Users 1278 not found.
Date Deposited: 03 Oct 2012 11:19
Last Modified: 25 Jan 2017 09:40
URI: http://utpedia.utp.edu.my/id/eprint/3898

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