Predicting single stock value movement by using clustering based on linear regression and polynomial equation

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Predicting single stock value movement by using clustering based on linear regression and polynomial equation

Lukas - Personal Name; Kho, Henry - Personal Name;

Time-series prediction has been an active research topic in recent studies. Some popular approaches to this problem are the traditional statistical method (e.g. multiple linear regression and moving average), and neural network with the Multi Layer Perceptron which has shown its supremacy in time-series prediction. In this thesis, a new approach based on linear and polynomial regression clustering for predicting a single stock value exchange is proposed. Every stock movement has shown repeating patterns of movement from the past. To illustrate chaotic time-series data, five stocks exchange and one benchmark data are used to test the strength of the algorithm.

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B00530 (wh) Available but not for loan - Missing

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Series Title: -
Call Number: 530
Publisher: : Swiss German University., 2009
Collation: -
Language: English
ISBN/ISSN: -
Classification: NONE
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Subject(s): IT
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