Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price
Commenced in January 2007
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Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price

Authors: Chien-Hui Yang, Che-Yang Lin, Ya-Chen Hsu

Abstract:

Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

Keywords: Gold price, Gold passbook price, Group Method ofData Handling (GMDH), Regression.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328484

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