Regime-dependent commodity price dynamics: A predictive analysis

IF 3.4 3区 经济学 Q1 ECONOMICS Journal of Forecasting Pub Date : 2024-05-20 DOI:10.1002/for.3152
Jesus Crespo Cuaresma, Ines Fortin, Jaroslava Hlouskova, Michael Obersteiner
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Abstract

We develop an econometric modelling framework to forecast commodity prices taking into account potentially different dynamics and linkages existing at different states of the world and using different performance measures to validate the predictions. We assess the extent to which the quality of the forecasts can be improved by entertaining different regime-dependent threshold models considering different threshold variables. We evaluate prediction quality using both loss minimization and profit maximization measures based on directional accuracy, directional value, the ability to predict turning points, and the returns implied by a simple trading strategy. Our analysis provides overwhelming evidence that allowing for regime-dependent dynamics leads to improvements in predictive ability for the Goldman Sachs Commodity Index, as well as for its five sub-indices (energy, industrial metals, precious metals, agriculture, and livestock). Our results suggest the existence of a trade-off between predictive ability based on loss and profit measures, which implies that the particular aim of the prediction exercise carried out plays a very important role in terms of defining which set of models is the best to use.

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与时间相关的商品价格动态:预测分析
我们开发了一个计量经济学建模框架来预测商品价格,其中考虑到了世界不同状态下可能存在的不同动态和联系,并使用不同的绩效衡量标准来验证预测结果。考虑到不同的阈值变量,我们评估了通过采用不同的制度相关阈值模型可以在多大程度上提高预测质量。我们根据方向准确性、方向价值、预测转折点的能力以及简单交易策略隐含的收益,使用损失最小化和利润最大化两种衡量标准来评估预测质量。我们的分析提供了压倒性的证据,表明考虑到制度依赖性动态会提高高盛商品指数及其五个子指数(能源、工业金属、贵金属、农业和畜牧业)的预测能力。我们的研究结果表明,基于损失和利润指标的预测能力之间存在权衡,这意味着所进行预测工作的特定目的在确定使用哪套模型最好方面起着非常重要的作用。
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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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