A monthly crude oil spot price forecasting model using relative inventories
By Michael M. Ye, J. Zyren, J. Shore. 2005
155 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/7c4f504deff3cc2e6e58b838071988ce1f8f2fda
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In Economics and Econometrics
- Jeffrey A. Frankel
- Lean Yu
- Kaijian He
- Tak Kuen Siu
- Kin Keung Lai
- Andrew K. Rose
- Robert J. R. Elliott
- Edmundo de Souza e Silva
In Renewable Energy, Sustainability and the Environment
- Robert J. R. Elliott
- Kin Keung Lai
- Kaijian He
- Jeffrey A. Frankel
- Luiz Fernando Loureiro Legey
- Lean Yu
Citations in the corpus
- Effects of speculation and interest rates in a “carry trade” model of commodity prices (2013, unknown): “We assume linearity in our estimation for simplicity, but allowing for non-linearity is a desirable extension 13 Ye et al (2002, 2005, 2006), for example, emphasise the role of inventories in forecasting oil prices.”
- Hidden Markov models with threshold effects and their applications to oil price forecasting (2016, methodology): “In [30, 31], a regression model was proposed to forecast West Texas Intermediate (WTI) price by considering the petroleum inventory level maintained by the Organization for Economic Cooperation and Development (OECD) countries.”
- Crude oil price analysis and forecasting using wavelet decomposed ensemble model (2012, background): “[4] and Ye et al.”
- Determinants of Agricultural and Mineral Commodity Prices (2010, background): “Higher economic activity should have a positive 17 Ye et al (2002, 2005, 2006) emphasise the role of inventories in forecasting oil prices: Notice that, once we condition on the real interest rate (and convenience yield), inventories have…”
- Forecasting oil price trends using wavelets and hidden Markov models (2010, background): “In (Ye et al., 2002, 2005, 2006), for example, the authors suggest that the petroleum inventory levels maintained by OECD countries may be used to predict future crude oil prices.”