Modelling and Forecasting Commodities Prices in Emerging Market: Lessons from the Preceding Super Cycle

Abstract

Futures trading is one of the oldest methods of trading and investing in commodities. History of commodities futures trading in India is interrupted, flabbergasted and disrupted unlike commodities future trading in Chicago Mercantile Exchange (CME), Chicago Board of Trade (CBOT), or London Metal Exchange (LME) where futures trading has been taking place uninterrupted for over a century. Prohibiting of futures trading in India in a large part of the last few decades has ensured research on commodities trading in India is still at an embryonic stage. In this study, we model Commodity prices of select Agriculture (Barley, Jeera, Sugar, and Pepper), Metal (Aluminium, Copper, Lead, and Gold), and Energy commodities (Crude Oil) in Indian Commodity Markets. Data during the Super-cycle period of commodities in India from 2003 to 2013 is used for the study and modeled using the state-space specification. The results of the study suggest that state-space specification and Kalman filter provides preeminent estimates for modeling and forecasting Indian commodity prices during the Super-cycle period. The results of the study provide crucial insights for pension funds, alternate investment funds, hedge funds and sovereign wealth funds worldwide to strategize better in the next expected super-cycle period of commodities post Covid-19 with burgeoning demand from developing economies of Asia and Africa.