Application of soft computing technique in the modelling and prediction of gold and silver rates

M. Dhiyanji and K. Sundaravadivu
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M. Dhiyanji: Department of Commerce, Madras University, Chennai, Tamilnadu, India
K. Sundaravadivu: Department of Electronics and Instrumentation Engineering, Anna University, Chennai, India

Journal of Advances in Technology and Engineering Research, 2016, vol. 2, issue 4, 118-124

Abstract: Over the past few years the modelling approach is widely used to discover the complex and dynamic relationship between various profitable variables. This paper focuses on the modeling of gold and silver rates with respect to a certain period of time and also on the prediction of the gold and silver rates. In this paper, with the assistance of Particle Swarm Optimization (PSO) algorithm, the BOX JENKINS and the Auto Regressive Integrated Moving Average(ARIMA) models are developed for the considered economic variables. A comparative study is also presented to assure the model accuracy. Following that, the PSO based KALMAN FILTER DESIGN approach is implemented on the gold and silver rates in order to forecast the market prices. In today's unpredictable world, investors believe that gold can act as a hedge against unexpected disasters, both natural and economical. Therefore forecasting the price of gold has been of highest interest. The major advantage of the proposed PSO based modeling and prediction approach is that, it is a fully automated method which results in higher flexibility and greater accuracy. This study also confirms that the PSO based ARIMA model yields a better result than the PSO based BOX JENKINS model. The proposed PSO based KALMAN FILTER approach also provides better prediction.

Keywords: Gold rate; Silver Rate; Box Jenkins Model; ARIMA Model; Kalman Filter PSO (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:apb:jaterr:2016:p:118-124

DOI: 10.20474/jater-2.4.3

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