Academic Journal

Forecasting Natural Gas Prices in Real Time

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Forecasting Natural Gas Prices in Real Time
Συγγραφείς: Baumeister, C., Huber, F., Lee, T.K., Ravazzolo, F.
Πηγή: Journal of Applied Econometrics. 41:139-155
Στοιχεία εκδότη: Wiley, 2024.
Έτος έκδοσης: 2024
Θεματικοί όροι: temperature anomalies, casting, out-of-sample fore, expert forecasts, natural gas futures, real-time data vintages, model confidence set
Περιγραφή: This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in complexity and economic content. We find that considerable reductions in mean‐squared prediction error relative to a no‐change benchmark can be achieved in real time for horizons of up to 2 years. A particularly promising model is a vector autoregressive (VAR) model that includes the fundamental determinants of supply and demand for natural gas. To capture real‐time data constraints of these and other predictors, we assemble a rich database of historical vintages from multiple sources. We also compare our model‐based forecasts to model‐free forecasts provided by experts and futures markets. Given that no single forecasting method dominates, we show that combining forecasts from individual models selected in real time using the model confidence set as a novel criterion for dynamic model selection delivers the most accurate forecasts.
Τύπος εγγράφου: Article
Γλώσσα: English
ISSN: 1099-1255
0883-7252
DOI: 10.1002/jae.70018
DOI: 10.2139/ssrn.5024248
Σύνδεσμος πρόσβασης: https://pure.iiasa.ac.at/id/eprint/20981/
Rights: CC BY NC
Αριθμός Καταχώρησης: edsair.doi.dedup.....d77325d60341c7b00792ff95c7aa92db
Βάση Δεδομένων: OpenAIRE
Περιγραφή
ISSN:10991255
08837252
DOI:10.1002/jae.70018