Forecasting OPEC oil price: a comparison of parametric stochastic models

Most academic papers on oil price forecasting have frequently focused on the use of WTI and European Brent oil price series with little focus on other equally important international oil price benchmarks such as the OPEC Reference Basket (ORB). The ORB is a weighted average of 11-member countries crude streams weighted according to production and exports to the main markets. This paper compares the forecasting accuracy of four stochastic processes and four univariate random walk models using daily data of OPEC Reference Basket series. The study finds that the random walk univariate model outperforms the other stochastic processes. An element of uncertainty was introduced into the point estimates by deriving probability distribution that describes the possible price paths on a given day and their likelihood of occurrence. This will help decision makers, traders and analysts to have a better understanding of the possible daily prices that could occur. JEL Classification Numbers: E64; C22; Q30 Keywords: Oil Price Forecasting, Probability Distributions, and Forecast Evaluation Statistics, Brownian Motion with Mean Reversion process, GARCH Model

COOPERATION SUPPORT IN A DYADIC SUPPLY CHAIN

To improve the supply chains performance, taking into account the customer demand in the tactical planning process is essential. It is more and more difficult for the customers to insure a certain level of demand over a medium term period. Then it is necessary to develop methods and decision support systems to reconcile the order and book processes. In this context, this paper aims at introducing a collaboration support tool and methodology dedicated to a dyadic supply chain. This approach aims at evaluating in term of risks different demand management strategies within the supply chain using a simulation dedicated tool. The evaluation process is based on an exploitation of decision theory and game theory concepts and methods.supply chain ; simulation ; collaboration ; decision theory ; risk

LOGISTICAL COSTS AND STRATEGIES FOR WHEAT SEGREGATION

Special segregations that provide unique qualities for end use products are being specified by buyers. As users of wheat become more specific about quality, the number of quality segregations that the logistical pipeline must accommodate increases. The additional cost of increased grain segregations will influence the optimal level of wheat variety segregations marketed in a supply chain. The primary objective of this research is to develop a model that captures the logistical costs of increased grain segregations in the marketing system. A simulation model was developed to add logistical uncertainty in demand, receipts, rail deliveries, and transit time. Sensitivities were conducted on certain variables to determine their effects on logistical costs. Logistical costs increase as more segregations are added. In addition, increasing uncertainty into the system raises logistical costs. Pipeline configuration also affects costs as the number of categories/storage bins present at origin may differ from the wheat categories demanded or the number of storage bins present at the export elevator.wheat, segregations, Crop Production/Industries,

An Adaptive Inventory Management System for Hospital Supply Chain

In healthcare, delivering high quality care to the patients typically requires significant investment in supply chain management systems. Inventory management is an important part of any supply chain system. Researchers have indicated great potential for optimizing existing healthcare inventory systems, especially within hospitals. With ever changing needs, product prices and policies, managing inventory of products in hospitals becomes difficult. As time progresses, the inventory policies of products become sub-optimal. In this research, we study multiple echelons of a hospital supply chain considering the distributors, to address the need for an efficient and effective hospital inventory management system. We propose a method consisting of two components: (1) system design and optimization; and (2) system monitoring, evaluation, and forecasting. The system design and optimization methodology includes a sim-heuristic approach where optimization of inventory levels and hospital operations is considered. As time evolves, to monitor the relevant system performance measures over time, control-chart like methods are used. When significant deviations in system performance occur, a re-evaluation of the inventory decision variables and/or system operations is conducted to maintain an efficient inventory system. A hierarchical procedure is used to determine the extent of evaluation of the system. Experimental results are presented to demonstrate the effectiveness of this methodology