Examinando por Autor "Trespalacios, Alfredo"
Mostrando 1 - 4 de 4
Resultados por página
Opciones de ordenación
Ítem Modeling electricity price and quantity uncertainty: An application for hedging with forward contracts(Universidad EAFIT, 2020-06-08) Trespalacios, Alfredo; Cortés, Lina; Perote, Javier; lcortesd@eafit.edu.coEnergy purchases/sales in liberalized markets are subject to price and quantity uncertainty, which should be jointly modeled by relaxing the unreliable normality assumption for capturing risk. In this paper, we consider the spot price and energy generation to follow a bivariate semi-nonparametric distribution defined in terms of the Gram-Charlier expansion. This distribution allows to jointly model not only mean, variance, and correlation, but also skewness, kurtosis, and higher-order moments. Based on this model, we propose a static hedging strategy for electricity generators that participate in a competitive market where hedging is carried out through forward contracts that include a risk premium in their valuation. For this purpose, we use Monte Carlo simulation and consider information from the Colombian electricity market as the case study. The results show that the volume of energy to be sold under long-term contracts depends on each electricity generator and the risk assessment made by the market in the Forward Risk Premium. The conditions of skewness, kurtosis, and correlation, as well as the type of risk indicator to be employed, affect the hedging strategy that each electricity generator should implement.Ítem Modeling the electricity spot price with switching regime semi-nonparametric distributions(Universidad EAFIT, 2019-11-22) Trespalacios, Alfredo; Cortés, Lina M.; Perote, Javier; alfredotrespalacios@itm.edu.coSpot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized facts, we propose a stochastic process with a component of mean reversion and switching regime to represent the dynamics of the spot price of electricity and its logarithm. The short-term movements are represented by semi-nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. The application is done for the Colombian electricity market, where El Niño phenomenon represents an additional source of risk that should be considered to guarantee long-term supply, sustainability of investments and efficiency of prices. We show that the switching regime model with SNP distributions for the random components outperforms traditional models leading to accurate estimates and simulations, and thus being a useful tool for risk management and policy making.Ítem Modelización de la demanda de energía eléctrica: más allá de la normalidad(Universidad EAFIT, 2019-06-04) Rendón, Juan F.; Trespalacios, Alfredo; Cortés, Lina M.; Villada, Hernán D.; lcortesd@eafit.edu.coThe main characteristic that differentiates electricity markets from other markets corresponds to the need to produce energy at the same time it is consumed, to such an extent that in real time the systems must maintain a perfect balance: at each moment the demand for electrical energy is equal to its generation. This characteristic prevents, for example, intertemporal arbitrage by those who carry out transactions in this market. In this regard, when modelling demand, it is common to find econometric analyzes that consider the assumption of normality; however, this assumption may ignore, a priori, an eventual presence of bias, kurtosis or higher order moments in this variable. In this paper, the Semi-Nonparametric approach (SNP) is studied to describe the demand for electricity in Colombia and the residuals of an ARIMA process. We propose the selection of probability density functions in terms of a finite Gram-Charlier expansion adjusted by the criterion of maximum likelihood. As a case study, the demand for electrical energy in the Colombian market is considered. As a result, it is found that the SNP type distribution achieves better adjustment than the normal distribution for some transformations of the electrical energy demand where it can be required more than four moments to represent this variable.Ítem Uncertainty in Electricity Markets from a seminonparametric Approach(Universidad EAFIT, 2019-06-04) Trespalacios, Alfredo; Cortés, Lina M.; Perote, Javier; lcortesd@eafit.edu.coThe spot price of electricity is highly skewed and heavy-tailed, as a result of the interaction of different variables that affect that market. Such characteristics impact the design of power plants with different technologies, fuel prices, and energy demand. This paper introduces the semi-nonparametric (SNP) approach to describe the uncertainty of different variables in an electricity market, reducing the limitations that normality and parametric density functions impose. The selection of probability density functions is achieved in terms of a finite Gram– Charlier expansion fitted by the maximum likelihood criterion. The study case is the Colombian electricity market, where the SNP distribution outperforms the normal distribution for spot price, national energy demand, the climate index ONI, and the series of hydrologic inflows of the system and some rivers. The results show that risk analysis in electricity markets requires the measurement of skewness, kurtosis, and high-order moments. The flexible methodology in our study has directly applications for implementing policies on electricity markets that improve the sustainability indicators of different systems. The particular characteristics of the series under analysis should be considered as a starting point for risk analysis and portfolio choice.