Forecasting Methods for Assets Prices

Abstract

The movements in Asset prices are very complex and therefore, seem to be unpredictable. However, one of the main challenges of the econometric models is to forecast such a seemingly unpredictable economical series. This paper investigates forecasting methods for assets prices and determines the best model for each asset price; gold and crude oil are used as case study. The forecasting method used is: ARCH family models, such as GARCH and EGARCH and. Analysis of the two ARCH family models are conducted, the two testing parameters used are Akaike Information Criterion (AIC) and Schwartz Information Criterion (SIC). The guidelines are, the lower the values of AIC and SIC better the model of the asset. Eventually, the study shows that each asset s price has its peculiar model for forecasting. Hence, GARCH model is best for forecasting crude oil price while EGARCH is best for forecasting gold price. Moreover, gold has strong market value and ability to withstand stress during economic recession; therefore, it can serve as hedge and safe haven.