Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach.real options, power plants, stochastic revenues and cost, CO2 allowances, LNG

Valuing Flexibility: The case of an Integrated Gasification Combined Cycle Power Plant

In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant. First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained. Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type. Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively. Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.real options, power plants, flexibility, stochastic costs

Income risk of EU coal-fired power plants after Kyoto

Coal-fired power plants may enjoy a significant advantage relative to gas plants in terms of cheaper fuel cost. Still, this advantage may erode or even turn into disadvantage depending on CO2 emission allowance price. This price will presumably rise in both the Kyoto Protocol commitment period (2008-2012) and the first post-Kyoto years. Thus, in a carbon-constrained environment, coal plants face financial risks arising in their profit margins, which in turn hinge on their so-called "clean dark spread". These risks are further reinforced when the price of the output electricity is determined by natural gas-fired plants' marginal costs, which differ from coal plants' costs. We aim to assess the risks in coal plants' margins. We adopt parameter values estimated from empirical data. These in turn are derived from natural gas and electricity markets alongside the EU ETS market where emission allowances are traded. Monte Carlo simulation allows to compute the expected value and risk profile of coal-based electricity generation. We focus on the clean dark spread in both time periods under different future scenarios in the allowance market. Specifically, bottom 5% and 10% percentiles are derived. According to our results, certain future paths of the allowance price may impose significant risks on the clean dark spread obtained by coal plants.clean spark spread, clean dark spread, EU Emissions Trading Scheme, Monte Carlo

Valoración de la garantía de los planes de pensiones en España

Este trabajo ha sido presentado en la Universidad del País Vasco y en el VII Encuentro de Economía Aplicada.planes de pensiones, aportación definida, España, garantías

Privatización de pensiones y provisión de garantías: una exploración del caso español

Los sistemas de pensiones públicas de reparto con prestación definida a lo largo del mundo se están convirtiendo a planes de aportación definida capitalizados, donde los agentes eligen sus carteras de acciones y bonos. A fin de hacer más atractivas al público estas reformas, los gobiernos típicamente han proporcionado garantías que reducen la exposición de los individuos a los riesgos de inversión, por ejemplo, una garantía de prestación mínima. En este trabajo se analiza una conversión hipotética del actual sistema español de reparto a un modelo de estas características. El valor de la garantía de prestación mínima se aproxima utilizando datos representativos de la situación española. Con objeto de controlar el coste de esta garantía, se exploran algunas técnicas de gestión de riesgos. La práctica más común, a saber, la sobrecapitalización, es bastante ineficaz. Precisamente por ello, después se presentan dos alternativas: (a) una garantía sobre una cartera estandarizada, y (b) un impuesto contingente (dependiente del estado de la naturaleza) sobre los rendimientos. Los cálculos indican que los compromisos no capitalizados pueden reducirse significativamente, e incluso por completo, bajo ambos enfoques, con tasas de aportación relativamente modestas.prestación definida, sistema de reparto, prestación mínima, garantías, pensiones, España

Valuation of wind energy projects: A real options approach

27 p.This paper addresses the valuation of an operating wind farm and the …nite-lived option to invest in such a farm under di¤erent reward and/or support schemes. They range from a feed-in tari¤ to a premium on top of electricity market price, to a transitory subsidy to capital expenditure. The availability of futures contracts on electricity with ever longer matu- rities allows to undertake valuations based on market data. The model considers two sources of uncertainty, namely the future electricity price (which shows seasonality) and the level of wind generation (which is in- termittent in addition to seasonal). Lacking analytical solutions we resort to a trinomial lattice (which supports mean reversion in prices) combined with Monte Carlo simulation at each of the nodes in the lattice. Our data set refers to the UK. The numerical results show the impact of a number of factors involved in the decision to invest: the subsidy per unit of elec- tricity generated, the initial lump-sum subsidy, the investment option’s maturity, and price volatility

Evaluation of a cross-border electricity interconnection: The case of Spain-France

[EN]This paper focuses on the economics of a cross-border transmission interconnector. The domestic spot electricity price is modelled as a stochastic process with mean reversion and jumps; it also includes a deterministic part that accounts for hourly and daily sasonalities along with non-working days. The two domestic spot prices are assumed to be correlated. As an illustration of the approach, we consider the particular case of the interconnector between Spain (an 'electric island') and France. Domestic prices are first calibrated and then used for simulating the stochastic behavior of the price gap between the two countries. In addition, the actual import/export behavior as a function of the price gap is captured by a Tobit model fitted from observed data. This model is then combined with the simulated price gaps to compute a multiple series of hourly prices and exports/imports of electricity through the interconnector. Drawing on these simulations we derive the probability distributions of revenues and expenses from exports and imports, and also some risk measures. According to our results, the economics of this interconector depends on different domestic seasonalities (hourly and daily), the growing trend of the price gap and some stochastic idiosyncrasies.This research is supported by the Basque Government through the BERC 2018-2021 programme and by the Spanish Ministry of Economy and Competitiveness (MINECO) through BC3 Maria de Maeztu excellence accreditation MDM20170714. Further support is provided by the project MINECO RTI 2018093352BI00

Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach

Income risk of EU coal-fired power plants after Kyoto

Coal-fired power plants may enjoy a significant advantage relative to gas plants in terms of cheaper fuel cost. Still, this advantage may erode or even turn into disadvantage depending on CO2 emission allowance price. This price will presumably rise in both the Kyoto Protocol commitment period (2008-2012) and the first post-Kyoto years. Thus, in a carbon-constrained environment, coal plants face financial risks arising in their profit margins, which in turn hinge on their so-called "clean dark spread". These risks are further reinforced when the price of the output electricity is determined by natural gas-fired plants' marginal costs, which differ from coal plants' costs. We aim to assess the risks in coal plants' margins. We adopt parameter values estimated from empirical data. These in turn are derived from natural gas and electricity markets alongside the EU ETS market where emission allowances are traded. Monte Carlo simulation allows to compute the expected value and risk profile of coal-based electricity generation. We focus on the clean dark spread in both time periods under different future scenarios in the allowance market. Specifically, bottom 5% and 10% percentiles are derived. According to our results, certain future paths of the allowance price may impose significant risks on the clean dark spread obtained by coal plants

Customizing Fuzzy Partitions for Visual Texture Representation

Visual textures in images are usually described by humans using linguistic terms related to their perceptual properties, like "very coarse", "low directional", or "high contrasted". Thus, computational models with the ability of providing a perceptual texture characterization on the basis of these terms play a fundamental role in tasks where some interaction with subjects is needed. In this sense, fuzzy partitions defined on the domain of computational measures of the corresponding property have been proposed in the literature. However, the main drawback of these proposals is that they do not take into account the subjectivity associated to the human perception. For example, the perception of a texture property may change depending on the user, and in addition, the image context may influence the global perception of the properties. In this paper, we propose to solve these problems by means of a methodology that automatically adapts any generic fuzzy partition modeling a texture property to the particular perception of a user or to the image context. In this method, the membership functions associated to the fuzzy sets are automatically adapted by means of a functional transformation on the basis of the new perception. For this purpose, the information given by the user or extracted from the textures present in the image are employed.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund - ERDF (Fondo Europeo de Desarrollo Regional - FEDER) under project TIN2014-58227-P Descripción lingüística de información visual mediante técnicas de minería de datos y computación flexible