José Paulo Teixeira

The Carbon Market Incremental Payoff in Renewable Electricity Generation Projects in Brazil: A Real Options Approach

The objective of this work is to present a methodology capable of estimating the incremental payoff of the carbon market for grid-connected renewable power generation projects in Brazil. The proposed methodology consists of using the NEWAVE model to determine the optimal operating policy for the Brazilian Interconnected System over the medium-term, and to establish hydrological dispatch scenarios for the power plants connected to this system. Based on these results, the criteria defined in the methodology ACM0002 were used to estimate the baseline of the projects developed in response to the Clean Development Mechanism of the Kyoto Protocol. Having estimated the baseline for the project, the incremental payoff obtained from the sale of Certified Emission Reductions is estimated using the real options theory. Subsequently, the value of the option is added to the conventional cash flow of the project, determining the impact of the carbon market on its internal rate of return.

Ex-ante economic assessment in incremental R&D projects: technical and development time uncertainties addressed by the real options theory

This paper analyzes changes in the assessment of an incremental R&D project by an industrial firm with the progressive consideration of the endogenous treatment of its main sources of uncertainty: technical performance and development time. We found that the project, which was unfeasible under a deterministic assessment by Net Present Value (NPV) without flexibility, became feasible after the treatment of the technical uncertainty by a real options model (NPV with flexibility). Moreover, the project gained approximately 51 percent more value in flexibility when a treatment of the development time uncertainty was added to the model. In terms of additional flexibility per unit cost of the project, the gain is approximately 44 percent. This result demonstrates the importance of addressing the combination of these sources of uncertainty in R&D projects, especially those that are incremental, which is a difficult category to analyze in terms of quantitative benefits.

Term structure of sovereign spreads: a contingent claim model

Este trabalho propoe um modelo estrutural para estimar a estrutura a termo e a probabilidade implicita de default de paises emergentes que representam, em media, 54 % do indice EMBIG do JPMorgan no periodo de 2000–2005. A taxa de câmbio real, modelada como um processo de difusao simples, e considerada como indicativa de default. O modelo calibrado gera a estrutura a termo dos spreads consistente com dados de mercado, indicando que o mercado sistematicamente sobre-estima os spreads para o Brasil em 100 pontos base na media, enquanto para Mexico, Russia e Turquia reproduz o comportamento do mercado.

DETERMINATION OF THE CARBON MARKET INCREMENTAL PAYOFF CONSIDERING A STOCHASTIC JUMP-DIFFUSION PROCESS

The objective of this paper is to verify the robustness of the Least Square Monte Carlo and Grant, Vora & Weeks methods when used to determine the incremental payoff of the carbon market for renewable electricity generation projects, considering that the behavior of the price of Certified Emission Reductions, otherwise known as Carbon Credits, may be modeled using a jump-diffusion process. In addition, this paper analyses particular characteristics, such as absence of monotonicity, found in trigger curves obtained through use of the Grant, Vora & Weeks method to valuate these types of project.

Modelagem da Incerteza nos Valores de Investimentos de Projetos do Setor Petrolífero

There is often a large gap between the planned value of investment in a project (capital expenditure [CAPEX]) and financial implementation of this. This fact creates a mismatch between the net present value (NPV) of the planned project and the outcome achieved. Depending upon the company’s project portfolio, this could even threaten its solvency. Therefore, a quantitative risk analysis that takes into account different possible scenarios for these investment values is extremely important to statistically measure the real value of a project. The aim of this paper is to present the reasons for mismatch between planned and final investment values. Although the results are valid for projects in the petrochemical and refining sector, also called downstream in the oil industry, the methodology can be applied upstream, or even to other industry branches.