论文标题
量化利率的作用，油价上的美元和共同
Quantifying the Role of Interest Rates, the Dollar and Covid in Oil Prices
论文作者
论文摘要
这项研究通过不可知论的随机森林模型的镜头分析了石油价格运动，该森林模型基于1,000棵回归树。它表明，相对于使用相同的11个解释因子集的标准线性最小平方模型，这种纪律严明的柔性计算模型将样本均方根误差减少65％。在预测练习中，RMSE的减少范围在51％至68％之间，强调了非线性在石油市场中的相关性。结果强调了将财务因素纳入石油模型的重要性：美国利率，美元和VIX占2010年后样本中RMSE降低的39％，在2020年后样本中上升至48％。如果Covid 19也被认为是危险因素，则这些股份变得更大。
This study analyses oil price movements through the lens of an agnostic random forest model, which is based on 1,000 regression trees. It shows that this highly disciplined, yet flexible computational model reduces in sample root mean square errors by 65% relative to a standard linear least square model that uses the same set of 11 explanatory factors. In forecasting exercises the RMSE reduction ranges between 51% and 68%, highlighting the relevance of non linearities in oil markets. The results underscore the importance of incorporating financial factors into oil models: US interest rates, the dollar and the VIX together account for 39% of the models RMSE reduction in the post 2010 sample, rising to 48% in the post 2020 sample. If Covid 19 is also considered as a risk factor, these shares become even larger.
