Abstract

Gold has become more popular as well as very useful commodity in terms of investment. Gold has been used as a national reserve for many years, and that makes it very crucial in the economics of any country. Most of the investors running to gold as a safe area from uncertainty and political chaos. Determining of the price movement of gold helps the investors in focus in their investments, government to make correct decision about economy since Gold price is a key element is world economy. For the purpose of predicting the price of gold, this article research uses ARIMA and SVM model in prediction. The study uses the daily data from world Gold Council from 1979 to 2019 in analysis. The data up to 2014 are used for the training of the models and the rest are used validation. The study results show that the SVM is better one compares to ARIMA using the performance measurement tools of RMSE and MAPE by having RMSE of 0.028 and MAPE of 2.5 for the SVM and 36.18 and 2897 for ARIMA respectively. The results suggest SVM to be used in prediction of any commodity price due to his high accuracy.

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