Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory

Marta Matyjaszek, Pedro Riesgo Fernández, Alicja Krzemień, Krzysztof Wodarski and Gregorio Fidalgo Valverde

Resources Policy, 2019, vol. 61, issue C, 283-292

Abstract: Price forecasting is a vital matter for mining investment decisions, as it represents the credibility of any financial outcome claimed by the feasibility studies presented to investors in financial markets. Most of these financial studies use forecasts from well-known providers of price assessments and market data that, ultimately, constitute a black box for the investors. This is why, to achieve credibility, user-friendly forecasting techniques through which the future price instability can be bounded are needed.

Keywords: Coking coal; Price forecasting; Autoregressive integrated moving average (ARIMA); Neural networks; Transgenic time series theory (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:61:y:2019:i:c:p:283-292

DOI: 10.1016/j.resourpol.2019.02.017

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