A Novel Hybrid Nonlinear Forecasting Model for Interval-Valued Gas Prices

IF 3.4 3区 经济学 Q1 ECONOMICS
Haowen Bao, Yongmiao Hong, Yuying Sun, Shouyang Wang
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引用次数: 0

Abstract

This paper proposes a novel hybrid nonlinear interval decomposition ensemble (NIDE) framework to improve forecasting accuracy of interval-valued gas prices. The framework first decomposes the price series using bivariate empirical mode decomposition and interval multiscale permutation entropy to capture dynamics driven by long-term trends, events, and short-term fluctuations. Tailored models are then employed for each component, including a threshold autoregressive interval model, interval event study methodology, and interval random forest. Finally, an ensemble prediction integrates the component forecasts. Empirical results show that the NIDE approach significantly outperforms benchmarks in out-of-sample forecasting of interval-valued natural gas prices. For instance, the RMSE improvements range from 10.3% to 38.8% compared to benchmark models. Additionally, the NIDE approach not only enhances accuracy but also provides economic interpretation by identifying drivers like speculative trading and public interest proxied by online trends.

区间值天然气价格的混合非线性预测模型
为了提高区间值天然气价格的预测精度,提出了一种新的混合非线性区间分解集成框架。该框架首先使用二元经验模式分解和区间多尺度排列熵对价格序列进行分解,以捕获由长期趋势、事件和短期波动驱动的动态。然后对每个组成部分采用定制模型,包括阈值自回归区间模型、区间事件研究方法和区间随机森林。最后,集成预测将组件预测集成在一起。实证结果表明,NIDE方法在区间价值天然气价格的样本外预测方面明显优于基准。例如,与基准模型相比,RMSE改进范围从10.3%到38.8%。此外,NIDE的方法不仅提高了准确性,而且通过识别投机交易和网络趋势所代表的公共利益等驱动因素,提供了经济解释。
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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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