Financial time series prediction using hybrid Support Vector Machine and Adaptive Neuro Fuzzy Inference System (SVM-ANFIS)

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Financial time series prediction using hybrid Support Vector Machine and Adaptive Neuro Fuzzy Inference System (SVM-ANFIS)

TA, Muhammad Rheza Satria - Personal Name; Widiputra, Harya Damar - Personal Name;

In this study, an evolutionary novel hybrid approach of Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference System (ANFIS) based on trust factor is proposed. The aim is to predict the direction of movement for N-step-ahead prediction task. SVM's output will be in directional movement via multiclass directions rather than via binary direction. The multiclass directions are constructed from frequency distribution. Similarly, ANFIS's output will be in multiclass directions but, constructed from predicted price. Some technical analysis features from previous studies are employed to measure the performance. The result showed that SVM- ANFIS-TYPE-III with proper weighting allocation for each classifier can outperform single classification technique.

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B01179 (wh) Available

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Series Title: -
Call Number: 1179
Publisher: : Swiss German University., 2012
Collation: -
Language: English
ISBN/ISSN: -
Classification: NONE
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Subject(s): IT
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