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Forecasting Natural Gas Price - Time Series and Nonparametric Approach

Globally there is a spur in demand of natural gas and business entities are interested to realize natural gas price forecast. The forecast is likely to suffice to different objectives to producers, suppliers, traders and bankers engaged in natural gas exploration, production, transportation and trading as well as end users engaged in utilization of natural gas. For the supplier the objective is to meet the demand with profit and for the trader it is for doing business. Researchers have invoked different methodologies to forecast natural gas price. It was intended to develop a model to forecast natural gas price in terms of specific parameters which may have relationship with natural gas price by applying Time Series as well as nonparametric regression invoking Alternating Conditional Estimation (ACE). Discernible predictor variables that may elucidate statistically important amount of the inconsistencies in the response variable have been recognized and the correlation between variables has been established. Statistical tests and techniques viz. unit root and ADF tests, and ARIMA have been applied. Present work is an attempt to demonstrate these models pertaining to natural gas pricing.