Structural Breaks in Commodity Futures Markets: Evidence from India

Abstract

One of the major assumptions of predictive statistics is that it assumes the parameters to be consistent and constant over time. However, in actual scenario the financial time series data is highly volatile and inconsistent. Any shift or change in the time series under study can challenges the consistency and constancy of the parameter which can weaken the efficiency of parameter. This unexpected shift in time series is referred to as structural break in the data. In forecasting time series, ignoring structural breaks, which often occur in the time series, significantly reduces the accuracy of the forecast (Pesaran and Timmermann, 2003). The present study is an attempt to highlight the structural breaks in the Indian Commodity Markets and will provide a justification to the shift in parameters of data. The results have important implications on the previous research done on the Indian commodity markets which have ignored the structural breaks in the data. Ignoring the breaks can result in incorrect assessment and can paint a fake picture about Indian commodity markets.

Keywords: structural breaks, commodity markets, bai-perron test, India

JEL Classification: C10, C22