Short-Term Generation Asset Valuation

We present a method for valuing a power plant over a short term period using Monte Carlo simulation. The power plant valuation problem is formulated as a multi stage stochastic problem. We assume there are hourly markets for both electricity and the fuel used by the generator, and their prices follow some Ito processes. At each hour, the power plant operator must decide to run or not to run the unit so as to maximize expected profit. A certain lead time for commitment decision is necessary to start up a unit. The commitment decision, once made, is subject to physical constraints such as minimum uptime and downtime constraints. The generator\u27\u27s startup cost, is also taken into account in our model. The Monte Carlo method is employed not only in forward moving simulation, but also backward moving recursion of dynamic programming. We demonstrate through numerical tests how the physical constraints affect a power plant value

Variable Capacity Utilization, Ambient Temperature Shocks and Generation Asset Valuation

This paper discusses generation asset valuation in a framework where capital utilization decisions are endogenous. We use real options approach for valuation of natural gas fuelled turbines. Capital utilization choices that we explore include turning on/off the unit, operating the unit at increased firing temperatures (overfiring), and conducting preventive maintenance. Overfiring provides capacity enhancement which comes at the expense of reduced maintenance interval and increased costs of part replacement. We consider the costs and benefits of overfiring in attempt to maximize the asset value by optimally exercising the overfire option. In addition to stochastic processes governing prices, we incorporate an exogenous productivity shock: ambient temperature. We consider how variation in ambient temperature affects the asset value through its effect on gas turbine’s productivity.Electricity generation asset valuation; overfire option; price uncertainty

Reference Models and Incentive Regulation of Electricity Distribution Networks: An Evaluation of Sweden’s Network Performance Assessment Model (NPAM)

The world-wide electricity sector reforms have led to a search for alternative and innovative approaches to regulation to promote efficiency improvement in the natural monopoly electricity networks. A number of countries have used incentive regulation models based on efficiency benchmarking of the electricity network utilities. While most regulators have opted adopted parametric and non-parametric frontier-based methods of benchmarking some have used engineering designed ‘reference firm’ or ‘norm’ models for the purpose. This paper examines the incentive properties and other related aspects of the norm model NPAM used in regulation of distribution networks in Sweden and compares these with those of frontier-based benchmarking methods. We identify a number of important differences between the two approaches to regulation benchmarking that are not readily apparent and discuss their ramifications for the regulatory objectives and process

An Accurate Solution for Credit Value Adjustment (CVA) and Wrong Way Risk

This paper presents a new framework for credit value adjustment (CVA) that is a relatively new area of financial derivative modeling and trading. In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the prices of risky contracts are normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk.

Distinguishing between observationally equivalent theories of crises

The objective of this paper is to empirically test across alternative, apparently observationally equivalent theories of currency crises. Theories of crises are often difficult to distinguish from each other based on the behavior of commonly used predictors. Using a comprehensive data set on gross external assets and liabilities for 167 countries created bythe World Bank's Latin America and the Caribbean Region and the Development Research Group, this study is able to make a significant move toward redressing this shortcoming. It focuses on identifying potential crisis predictors, as well as testing the validity of the distinct transmission mechanisms implied by various theories of currency crisis. Evidence is presented in support of insurance-based models, suggesting that proxies for contingent liability accumulation are effective crisis predictors.Economic Theory&Research,Fiscal&Monetary Policy,International Terrorism&Counterterrorism,Payment Systems&Infrastructure,Banks&Banking Reform,Economic Theory&Research,Banks&Banking Reform,Environmental Economics&Policies,International Terrorism&Counterterrorism,Financial Crisis Management&Restructuring

VALUING ELECTRICITY ASSETS IN DEREGULATED MARKETS: A REAL OPTIONS MODEL WITH MEAN REVERSION AND JUMPS

Valuation of electricity generating assets is of central importance as utilities are forced to spin-off generators with the introduction of competitive markets. A continuous-time mean reverting price path with stochastic upward jumps is proposed as an appropriate model for long-run competitive electricity prices faced by a generator. A real options model is derived via dynamic programming using infinite series solutions. The derived model produces asset values which are uniformly higher than those produced by existing models, and which accurately predict observed generator sale prices. The model has favorable implications for stranded cost recovery and generator entry in competitive markets.real options, electricity deregulation, mean reversion, jump processes, asset valuation, Marketing,