A Short-Run Crude Oil Price Forecast Model with Ratchet Effect

Abstract

Crude oil prices, Crude oil inventory, Crude oil excess production capacity, Duesenberry ratchet effect, Q00 Agriculture and Natural Resources,

Economic Sustainability of Products and Processes

“…Frequently, the identified model is rather simple and comprises either ADL(0,1) or ADL(1,1) formulations. The keep-it-simple approach to modeling, coupled to avoiding overparameterization risks, reduces the Ye et al, 2009 complexity of the model. The evaluation of a,b,c parameters in Eqn (25.3) is carried out by a linear regression procedure (e.g., multidimensional unconstrained optimization) that minimizes the sum of squared errors between real quotations and model values.…”

Daqing Crude Oil Price Forecast Based on the ARIMA Model

“…To explain and predict changes in crude oil prices firstly need to understand the behavior of crude oil prices itself (Michael (2009) [5]; Kendix (2010) [6]; Leder (2008) [7]). Jose (2002) [8] analysis results on the price of crude oil using Hurst multidimensional showed that the crude oil market is a highly complex process of interaction at different time scale, long-term memory mechanism to influence the evolution of oil prices.…”

“…(Chaudhuri K (2001) [14]; Smith, Grimm (2003) [15]; Michael Ye, John Zyren, Carol Joyce Blumberg, Joanne Shore (2009) [16]; Watkins, G.C. and Plourde (1994) [17]).…”

A New Theory to Forecast the Price of Nonrenewable Energy Resources with Mass and Energy-Capital Conservation Equations

“…Cuaresma et al [88], using a simple unobserved components model, showed that explicitly modelling asymmetric cycles on crude oil prices improves the forecast ability of univariate time series models of the oil price. Ye et al [89] predicted crude oil prices from 1992 through early 2004 by using OECD's relative inventories and OPEC's excess production capacity improving forecasts for the post-Gulf War I time period over models without the ratchet mechanism. Cheong [90] investigated the timevarying volatility of two major crude oil markets, the West Texas Intermediate (WTI) and the Europe Brent, with a flexible autoregressive conditional heteroskedasticity (ARCH) model to take into account the stylized volatility facts such as clustering volatility, asymmetric news impact, and long memory volatility.…”