Abstract:
The demand of the metal gold makes a significant role in the world
economy. In the real world, different types of social and economic factors
are directly affected on the gold demands; especially the volatility of the
share market conditions are significant. The main objective of this current
study is to develop high accuracy model for forecasting gold price demands
to fulfill investors’ expectations. Different Autoregressive integrated
moving average (ARIMA) models were considered. The model selection
results of Akaike information criterion (17.549), Schwarz criterion (17.575)
and Hannan-Quinn criterion (17.559) suggested that, ARIMA (2, 1, 2) is
the best model for forecasting daily gold prices under the volatility during
the period from June 2014 to June 2017. In addition to that, the Vector
Autoregression model (VAR) is used to test the effectiveness with respect
to the external factors such as GDP, Real Effective Exchange rate and
Broad Money. The empirical findings of Vector Autoregressive Modeling
Approach suggested that, GDP and Real Effective Exchange rate highly
affect for the gold price demands in Sri Lanka.
