NON-GAUSSIAN STATISTICS OF OIL PRICING TIME-SERIES: A CASE STUDY

The stochastic nature of oil price fluctuations is investigated over a twelve-year period, borrowing feedback from an existing database (USA Energy Information Administration database, available online). We evaluate the scaling exponents of the fluctuations by employing different statistical analysis methods, namely rescaled range analysis (R/S), scale windowed variance analysis (SWV) and the generalized Hurst exponent (GH) method. Relying on the scaling exponents obtained, we apply a rescaling procedure to investigate the complex characteristics of the probability density functions (PDFs) dominating oil price fluctuations. It is found that PDFs exhibit scale invariance, and in fact collapse onto a single curve when increments are measured over microscales (typically less than 30 days). The time evolution of the distributions is well fitted by a Levy-type stable distribution. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer. Our results also exhibit a degree of multifractality as the PDFs change and converge toward to a Gaussian distribution at the macroscales.

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

Do focus groups contribute anything to the contingent valuation process?

The qualitative aspects of the Contingent Valuation Method (CVM) are largely ignored by (environmental) economists. This paper aims to instigate a discussion on (a) the usefulness of qualitative data to the contingent valuation process in general; and (b) the use and applicability of the focus group method in particular. We consider the range and uses of focus groups within the CVM and highlight problems with their analysis that have, to date, largely been ignored. A potential solution to circumvent the problem of non-independence of group data is suggested. While there are several distinct and worthwhile uses for qualitative data, focus groups should not automatically be taken as the only or best method to produce these insights even though they are the major one considered in this article. (C) 1999 Elsevier Science B.V. All rights reserved.

Combining preference ordering and contingent valuation methods to assess non market benefit of alternative afforestation projects

The application of the contingent valuation method (CVM) in this paper incorporates a prior preference ordering of several alternative future afforestation programmes which could be implemented in Ireland over the next decade. This particular experimental design is thereby shown to reveal the potentially conflicting preferences of different groups within society. These findings are used to devise appropriate CVM scenarios to take account, not only of the efficiency gains of choosing a single policy alternative over others, but also the effects on the distribution of non market benefit between different groups within society, arising from choice between alternatives. (C) 1998 Elsevier Science Ltd. All rights reserved.