Developing a Forecast Model for Transactions Value in Iran Mercantile Exchange (IME)

Abstract

Commodity exchanges in the world are known as the organized and self-regulated markets for discovery of efficient, transparent and fair price. Despite the high impact of the commodity exchanges on national economies and the UNCTAD’s forecast about the growing of commodity exchanges in developing countries, so far, no model has been developed to predict the Iran Mercantile Exchange trading value.  Therefore, developing a model for suppliers and applicants seems essential. In this paper, forecasting model of trading value of IME, has developed by discovering the macroeconomic indicators which are effective on the trading value in IME. Totally, indicators like inflation, unemployment, construction budget, exports, imports, taxes, USD exchange rate, economic growth, world GDP, world oil prices and oil revenues of the government during the analysis period of 2008 to 2015, are counted and considered in the paper.In the current research, for the quantitative analysis of data, Pearson correlation coefficient and R^2 for identification of economic variables which are effective on IME trading value and correlation test with significant level of 99% and 5 degrees of freedom are used. Then, by using least squares method of regression equation, the macroeconomic indicators effects on IME traded value are estimated.In order to investigate and compare the forecasting power of the model Root Mean Square Error(RMSE) and The Mean Squared Error (MSE) are used. The results show that, the IME trade value is affected from indicators like USD exchange rate, trade balance, world GDP, world economic growth rate, world inflation rate and supplier price index in Iran's economy.  In the middle, USD exchange rate has the most positive effect (1.21) and supplier price index (-4.24) has the most negative reverse effect on the IME trade value. Research findings shows that, based on the fitted model for forecasting of IME trade value of IME, RMSE equals to 0.063, MSE is equal to 0.047 and based on the fitted model, has a high power to be used.

Keywords: Commodity exchange, IME, Iran's Macroeconomic indexes, World's economy trends, Forecast of transactions value.