e-ISSN 2231-8542
ISSN 1511-3701

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Improving Prediction of Gold Prices through inclusion of Macroeconomic Variables

Beh, W. L. and Pooi, A. H.

Pertanika Journal of Tropical Agricultural Science, Volume 24, Issue S, October 2016

Keywords: Multivariate power-normal distribution, macroeconomic variables, prediction interval, parsimonious model

Published on: 09 Dec 2016

This paper uses a method based on multivariate power-normal distribution for predicting future gold prices in Malaysia. First let r(t) be the vector consisting of the month-t values of m selected macroeconomic variables, and gold price. The month-(t+1) gold price is then modelled to be dependent on the present and l-1 on past values r(t), r(t-1), …, r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1] -dimensional power-normal distribution. The mean of the conditional distribution is an estimate of the month- (t+1) gold price. Meanwhile, the 100(a/2)% and 100(1-a/2)% points of the conditional distribution can be used to form an out-of-sample prediction interval for the month-(t+1) gold price. For a given value of l, we select various combinations of m variables from a pool of 17 selected macroeconomic variables in Malaysia, and obtain the combinations of which the corresponding mean absolute percentage errors (MAPE) are relatively smaller while the coverage probabilities and average lengths of the prediction interval are still satisfactory. It is found that the parsimonious model is one of which l = 2, m = 1 and involving the macroeconomic variable derived from the Gross Domestic Product, Kuala Lumpur Composite Index or Import Trade.

ISSN 1511-3701

e-ISSN 2231-8542

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