Spot price modeling and the valuation of electricity forward contracts : the role of demand and capacity.

We propose a model where wholesale electricity prices are explained by two state variables: demand and capacity. We derive analytical expressions to price forward contracts and to calculate the forward premium. We apply our model to the PJM, England and Wales, and Nord Pool markets. Our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive, both of which exert an upward (seasonal) pressure on the price of forward contracts. We assume that both volatility of capacity and the market price of capacity risk are constant and find that, depending on the market and period under study, it could either exert an upward or downward pressure on forward prices. In all markets we find that the forward premium exhibits a seasonal pattern. During the months of high volatility of demand, forward contracts trade at a premium. During months of low volatility of demand, forwards can either trade at a relatively small premium or, even in some cases, at a discount, i.e. they exhibit a negative forward premiumPower prices; Demand; Capacity; Forward premium; Forward bias; Market price of capacity risk; Market price of demand risk; PJM; England and Wales; Nord Pool;

Spot price modeling and the valuation of electricity forward contracts : the role of demand and capacity.

We propose a model where wholesale electricity prices are explained by two state variables: demand and capacity. We derive analytical expressions to price forward contracts and to calculate the forward premium. We apply our model to the PJM, England and Wales, and Nord Pool markets. Our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive, both of which exert an upward (seasonal) pressure on the price of forward contracts. We assume that both volatility of capacity and the market price of capacity risk are constant and find that, depending on the market and period under study, it could either exert an upward or downward pressure on forward prices. In all markets we find that the forward premium exhibits a seasonal pattern. During the months of high volatility of demand, forward contracts trade at a premium. During months of low volatility of demand, forwards can either trade at a relatively small premium or, even in some cases, at a discount, i.e. they exhibit a negative forward premiumPower prices; Demand; Capacity; Forward premium; Forward bias; Market price of capacity risk; Market price of demand risk; PJM; England and Wales; Nord pool;

MODELING ELECTRICITY PRICES: INTERNATIONAL EVIDENCE

This paper analyses the evolution of electricity prices in deregulated markets. We present a general model that simultaneously takes into account the possibility of several factors: seasonality, mean reversion, GARCH behaviour and time-dependent jumps. The model is applied to equilibrium spot prices of electricity markets from Argentina, Australia (Victoria), New Zealand (Hayward), NordPool (Scandinavia), Spain and U.S. (PJM) using daily data. Six different nested models were estimated to compare the relative importance of each factor and their interactions. We obtained that electricity prices are mean-reverting with strong volatility (GARCH) and jumps of time-dependent intensity even after adjusting for seasonality. We also provide a detailed unit root analysis of electricity prices against mean reversion, in the presence of jumps and GARCH errors, and propose a new powerful procedure based on bootstrap techniques.

Modeling electricity prices: international evidence

This paper analyses the evolution of electricity prices in deregulated markets. We present a general model that simultaneously takes into account the possibility of several factors: seasonality, mean reversion, GARCH behaviour and time-dependent jumps. The model is applied to equilibrium spot prices of electricity markets from Argentina, Australia (Victoria), New Zealand (Hayward), NordPool (Scandinavia), Spain and U.S. (PJM) using daily data. Six different nested models were estimated to compare the relative importance of each factor and their interactions. We obtained that electricity prices are mean-reverting with strong volatility (GARCH) and jumps of time-dependent intensity even after adjusting for seasonality. We also provide a detailed unit root analysis of electricity prices against mean reversion, in the presence of jumps and GARCH errors, and propose a new powerful procedure based on bootstrap techniques

Valoración y gestión de riesgos en mercados eléctricos liberalizados

Esta Tesis Doctoral analiza el comportamiento del precio de la electricidad en mercados eléctricos liberalizados, así como el desarrollo de modelos de valoración de derivados eléctricos. El cuerpo central de esta Tesis Doctoral está formado por tres artículos independientes. En el primer capítulo, se presenta un modelo eco no métrico para las series de precios, que captura simultáneamente la posible presencia de varios factores: estacionalidad, reversión a la media, heterocedasticidad (GARCH) y saltos (dependientes en el tiempo). Posteriormente se propone un modelo para la valoración de contratos de futuros eléctricos que incorpore la posibilidad de saltos. La modelización propuesta introduce la posibilidad de saltos en una de las variables de estado y permite obtener fórmulas analíticas para el precio de futuros. Los resultados del modelo muestran la importancia de la prima de riesgo por salto. Finalmente, se propone un modelo de valoración de derivados donde las variables relevantes son la demanda y la capacidad de generación (oferta). Se obtienen fórmulas analíticas de valoración y se analizan los efectos de las variables de estado sobre el precio del contrato de futuro y sobre la prima de riesgo

A search for an unexpected asymmetry in the production of e(+)mu(-) and e(-)mu(+) pairs in proton-proton collisions recorded by the ATLAS detector at root s=13 TeV

This search, a type not previously performed at ATLAS, uses a comparison of the production cross sections for e(+)mu(-) and e(-)mu(+) pairs to constrain physics processes beyond the Standard Model. It uses 139 fb(-1) of proton-proton collision data recorded at root s = 13 TeV at the LHC. Targeting sources of new physics which prefer final states containing e(+)mu(-) and e(-)mu(+), the search contains two broad signal regions which are used to provide model-independent constraints on the ratio of cross sections at the 2% level. The search also has two special selections targeting supersymmetric models and leptoquark signatures. Observations using one of these selections are able to exclude, at 95% confidence level, singly produced smuons with masses up to 640 GeV in a model in which the only other light sparticle is a neutralino when the R-parity-violating coupling lambda(23)(1)' is close to unity. Observations using the other selection exclude scalar leptoquarks with masses below 1880 GeV when g(1R)(eu) = g(1R)(mu c) = 1, at 95% confidence level. The limit on the coupling reduces to g(1R)(eu) = g(1R)(mu c) = 0.46 for a mass of 1420 GeV

Pricing Power Derivatives: A Two-factor Jump-diffusion Approach

We propose a two-factor jump-diffusion model with seasonality for the valuation of electricity future contracts. The model we propose is an extension of Schwartz and Smith (Management Science, 2000) long-term / short-term model. One of the main contributions of the paper is the inclusion of a jump component, with a non-constant intensity process (probability of occurrence of jumps), in the short-term factor. We model the stochastic behaviour of the underlying (unobservable) state variables by Affine Diffusions (AD) and Affine Jump Diffusions (AJD). We obtain closed form formulas for the price of futures contracts using the results by Duffie, Pan and Singleton (Econometrica, 2000). We provide empirical evidence on the observed seasonality in risk premium, that has been documented in the PJM market. This paper also complements the results provided by the equilibrium model of Bessembinder and Lemmon (Journal of Finance, 2002), and provides an easy methodology to extract risk-neutral parameters from forward data, that may be used for calibration of real options models. The model may also be used for scenario generation, valuation of financial options (trough inversion of the characteristic function) and real options applications

Diseño y desarrollo de un portal web para el trabajo colaborativo

[ES] En este trabajo se ha planteado una solución para equipos de desarrolladores de software noveles en metodologías ágiles, donde el trabajo pueda dividirse y llevar un seguimiento de forma simple, pero eficiente. Esta aplicación permite gestionar los proyectos, las tareas y estadísticas de un modo sencillo y accesible desde cualquier dispositivo con navegador web utilizando las últimas tecnologías.[EN] En este trabajo se ha planteado una solución para equipos de desarrolladores de software noveles en metodologías ágiles, donde el trabajo pueda dividirse y llevar un seguimiento de forma simple, pero eficiente. Esta aplicación permite gestionar los proyectos, las tareas y estadísticas de un modo sencillo y accesible desde cualquier dispositivo con navegador web utilizando las últimas tecnologías.Ramos Villaplana, P. (2017). Diseño y desarrollo de un portal web para el trabajo colaborativo. http://hdl.handle.net/10251/89397.TFG