2017•Indian Journal of Research in Capital MarketsRequires access

Autoregressive Integrated Moving Average Model for Gold Price Forecasting : Evidence from the Indian Market

Khujan Singh, A.Ashok Kumar

Abstract

The present study was conducted to forecast the gold prices in India by employing ARIMA (1, 1, 2) model on time series data for short term. The stationarity of time series data was tested by using the ADF unit root test. To overcome the problem of autocorrelation, Breusch - Godfrey serial correlation was conducted. The study forecasted gold prices within sample and post sample forecast. Actual values of gold prices and the forecasted values of gold prices moved in the same direction very closely. The post sample forecasted values of gold prices revealed an increasing trend. The predicted six months values of gold prices probably indicated reasonable returns for investors who held gold in their financial portfolios. Hence, the ARIMA (1, 1, 2) model was found to be the best fit to forecast short term gold prices on time series data.

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Key concepts: Autoregressive integrated moving average, Autocorrelation, Econometrics, Gold as an investment, Autoregressive model, Unit root, Economics, Sample (material)