PREDICTION OF NATURAL GAS PRICES ON THE NEW YORK MERCANTILE EXCHANGE BASED ON A PULSE FUNCTION INTERVENTION ANALYSIS APPROACH
Abstract
Natural gas is a key energy commodity with significant global economic impact, and its pricing is influenced by factors like weather, energy policies, geopolitics, and supply-demand balance. The Russia-Ukraine conflict disrupted Russia’s gas exports, causing price volatility and affecting global markets, including Indonesia. This has heightened the need for accurate price prediction to support policy and investment decisions. Previous studies show ARIMA-GARCH models predict well but need pulse function intervention for sudden shocks. This study aims to apply pulse function intervention analysis, which captures the immediate effects of external events on time-series data, to improve the precision of natural gas price forecasts, aiding government and industry decision-makers. The optimal intervention model for predicting natural gas prices on the New York Mercantile Exchange is the Probabilistic ARIMA (0,2,1) with a pulse function intervention order of b=0, r=2, and s=0. Using this model with the pulse function intervention approach yields consistent fluctuation patterns over time and achieves a MAPE value of 12.2586%, indicating that the model provides good predictive accuracy.
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