Abstract
Earlier discarded as an irritant by-product of crude oil exploration, Natural gas is considered as world’s most important fuel due to environmental considerations. It plays an important role in meeting global energy demand and has significant share in the international energy market. Natural Gas is emerging as an alternative to crude oil and coal as the main energy source and the global energy consumption pattern has transformed from preeminence of crude oil and gas to escalating share of gas. Accordingly, there is a spur in demand of natural gas and business entities across the world are interested to comprehend natural gas price forecast. The forecast is likely to meet different objectives of producers, suppliers, traders and bankers engaged in natural gas exploration, production, transportation and trading as well as end users. For the supplier the objective is to meet the demand with profit and for the trader it is for doing business. Of late researchers have exercised different approaches to forecast price by developing numerical models in terms of specific parameters which have relationship with Natural Gas price. This chapter examines application of contemporary forecasting techniques—Time Series Analysis as well as Nonparametric Regression invoking Alternating Conditional Expectations (ACE) to forecast Natural Gas price. Noticeable predictor variables that may explicate statistically important amount of inconsistencies in the response variable (i.e. Natural Gas price) have been recognized and the correlation between variables has been distinguished to model Natural Gas price.
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Mishra, P. (2013). Natural Gas Price Forecasting: A Novel Approach. In: Yang, GC., Ao, Sl., Gelman, L. (eds) IAENG Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, vol 229. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6190-2_48
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DOI: https://doi.org/10.1007/978-94-007-6190-2_48
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