Leili Ulfiati, - and Sugiman, - (2015) Peramalan Data Saham Dengan Transformasi Wavelet Haar. Unnes Journal of Mathematics, 4 (2). pp. 136-146. ISSN 2460-5859

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Abstract

Wavelet is a method without parameters that can be used in complex financial processes and dynamic. Formulation of the problem in this research is how to forecast the stock price with the Haar wavelet DWT method using Matlab R2013a and how value Mean Square Eror (MSE). The purpose of this research is to know how to predict the stock price with the Haar wavelet DWT method using Matlab R2013a and know the value of MSE. The method used is the DWT (Discrete Wavelet Transform) to analyze a time series data. In particular, the Discrete Wavelet Transformation allows to decompose a time series into constituent components multiresolution. Steps to forecast stock prices is to choose the data stocks, plotting the data stock, stock price data split into training data and testing the data, then perform forecasting. Testing the stock price data using the Haar wavelet method with DWT (Discrete Wavelet Transform) using matlab R2013a software.

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