3D geovisualisation techniques applied in spatial data mining

The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.

Istmo Centroamericano: estadísticas del subsector eléctrico (datos actualizados a 2001)

Incluye Bibliografía

Istmo Centroamericano: estadísticas del subsector eléctrico (datos actualizados a 2004)

Incluye Bibliografía

Um modelo bi-nível para o investimento multi-etapa em capacidade de transmissão e geração de energia elétrica em mercados competitivos

Pós-graduação em Engenharia Elétrica - FEIS

Análise comparativa do mercado imobiliário em Cidades Médias: a oferta de apartamentos, casas e terrenos urbanos em Campina Grande – PB, Mossoró – RN e Passo Fundo – RS

This presente monograph propose the analysis and discussion of the production of urban space and the processes of their structuring intraurbana from the dynamics of the real estate market into three Medium-sized Cities, Campina Grande - PB, Mossoró - RN and Passo Fundo - RS, whereas the various agents producing this space, in a comparative perspective. From this urban dynamic search to analyze the processes and relations present in these spaces, which are important for its production. From the compilation of real estate advertisements in local newspapers, are analyzed offerings of urban land, houses and apartments in each one of these cities by highlighting their locations and differentiated prices. Thus, working with data from real estate ads from the period 1995 - 2010 and a comparative perspective of the characteristics of real estate markets of three medium-sized cities, it tried to apprehend processes that are common between them and other individuals, to each one. Therefore the comparative analysis developed in this monograph sought to verify whether there are similarities between the cities in relation to the trends of concentration/spatial dispersion of bids and movements throughout time, in addition to a further intensification of the activities of real estate agents in face of such trends and offerings. In addition, we sought to remove a set of problematization that allow them to understand with more acute, in this set of medium cities of Brazilian urban network, processes of change that is already being discussed in the recent period by ReCiMe.

Diferenciando o espaço e produzindo cidades: lógicas e agentes da produção do espaço urbano em Ribeirão Preto/SP e Londrina/PR

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Statistical mechanics formalism and methods for the analysis of real networks

This thesis provides a thoroughly theoretical background in network theory and shows novel applications to real problems and data. In the first chapter a general introduction to network ensembles is given, and the relations with “standard” equilibrium statistical mechanics are described. Moreover, an entropy measure is considered to analyze statistical properties of the integrated PPI-signalling-mRNA expression networks in different cases. In the second chapter multilayer networks are introduced to evaluate and quantify the correlations between real interdependent networks. Multiplex networks describing citation-collaboration interactions and patterns in colorectal cancer are presented. The last chapter is completely dedicated to control theory and its relation with network theory. We characterise how the structural controllability of a network is affected by the fraction of low in-degree and low out-degree nodes. Finally, we present a novel approach to the controllability of multiplex networks

U.S. utilities' experiences with the implementation of energy efficiency programs

In the U.S., many electric utility companies are offering demand-side management (DSM) programs to their customers as ways to save money and energy. However, it is challenging to compare these programs between utility companies throughout the U.S. because of the variability of state energy policies. For example, some states in the U.S. have deregulated electricity markets and others do not. In addition, utility companies within a state differ depending on ownership and size. This study examines 12 utilities’ experiences with DSM programs and compares the programs’ annual energy savings results that the selected utilities reported to the Energy Information Administration (EIA). The 2009 EIA data suggests that DSM program effectiveness is not significantly affected by electricity market deregulation or utility ownership. However, DSM programs seem to generally be more effective when administered by utilities located in states with energy savings requirements and DSM program mandates.

Desarrollo de un modelo de formación del valor inmobiliario en áreas de crecimiento suburbano. Aplicación a la comarca de la Vega Baja del Segura en el litoral alicantino

Una de las principales líneas de investigación de la economía urbana es el comportamiento del mercado inmobiliario y sus relaciones con la estructura territorial. Dentro de este contexto, la reflexión sobre el significado del valor urbano, y abordar su variabilidad, constituye un tema de especial importancia, dada la relevancia que ha supuesto y supone la actividad inmobiliaria en España. El presente estudio ha planteado como principal objetivo la identificación de aquellos factores, ligados a la localización que explican la formación del valor inmobiliario y justifican su variabilidad. Definir este proceso precisa de una evaluación a escala territorial estableciendo aquellos factores de carácter socioeconómico, medioambiental y urbanístico que estructuran el desarrollo urbano, condicionan la demanda de inmuebles y, por tanto, los procesos de formación de su valor. El análisis se centra en valores inmobiliarios residenciales localizados en áreas litorales donde la presión del sector turístico ha impulsado un amplio. Para ello, el ámbito territorial seleccionado como objeto de estudio se sitúa en la costa mediterránea española, al sur de la provincia de Alicante, la comarca de la Vega Baja del Segura. La zona, con una amplia diversidad ecológica y paisajística, ha mantenido históricamente una clara distinción entre espacio urbano y espacio rural. Esta dicotomía ha cambiado drásticamente en las últimas décadas, experimentándose un fuerte crecimiento demográfico y económico ligado a los sectores turístico e inmobiliario, aspectos que han tenido un claro reflejo en los valores inmobiliarios. Este desarrollo de la comarca es un claro ejemplo de la política expansionista de los mercados de suelo que ha tenido lugar en la costa española en las dos últimas décadas y que derivado en la regeneración de un amplio tejido suburbano. El conocimiento del marco territorial ha posibilitado realizar un análisis de variabilidad espacial mediante un tratamiento masivo de datos, así como un análisis econométrico que determina los factores que se valoran positivamente y negativamente por el potencial comprador. Estas relaciones permiten establecer diferentes estructuras matemáticas basadas en los modelos de precios hedónicos, que permiten identificar rasgos diferenciales en los ámbitos económico, social y espacial y su incidencia en el valor inmobiliario. También se ha sistematizado un proceso de valoración territorial a través del análisis del concepto de vulnerabilidad estructural, entendido como una situación de fragilidad debida a circunstancias tanto sociales como económicas, tanto actual como de tendencia en el futuro. Actualmente, esta estructura de demanda de segunda residencia y servicios ha mostrado su fragilidad y ha bloqueado el desarrollo económico de la zona al caer drásticamente la inversión en el sector inmobiliario por la crisis global de la deuda. El proceso se ha agravado al existir un tejido industrial marginal al que no se ha derivado inversiones importantes y un abandono progresivo de las explotaciones agropecuarias. El modelo turístico no sería en sí mismo la causa del bloqueo del desarrollo económico comarcal, sino la forma en que se ha implantado en la Costa Blanca, con un consumo del territorio basado en el corto plazo, poco respetuoso con aspectos paisajísticos y medioambientales, y sin una organización territorial global. Se observa cómo la vinculación entre índices de vulnerabilidad y valor inmobiliario no es especialmente significativa, lo que denota que las tendencias futuras de fragilidad no han sido incorporadas a la hora de establecer los precios de venta del producto inmobiliario analizado. El valor muestra una clara dependencia del sistema de asentamiento y conservación de las áreas medioambientales y un claro reconocimiento de tipologías propias del medio rural aunque vinculadas al sector turístico. En la actualidad, el continuo descenso de la demanda turística ha provocado una clara modificación en la estructura poblacional y económica. Al incorporar estas modificaciones a los modelos especificados podemos comprobar un verdadero desmoronamiento de los valores. Es posible que el remanente de vivienda construida actualmente vaya dirigido a un potencial comprador que se encuentra en retroceso y que se vincula a unos rasgos territoriales ya no existentes. Encontrar soluciones adaptables a la oferta existente, implica la viabilidad de renovación del sistema poblacional o modificaciones a nivel económico. La búsqueda de respuestas a estas cuestiones señala la necesidad de recanalizar el desarrollo, sin obviar la potencialidad del ámbito. SUMMARY One of the main lines of research regarding the urban economy focuses on the behavior of the real estate market and its relationship to territorial structure. Within this context, one of the most important themes involves considering the significance of urban property value and dealing with its variability, particularly given the significant role of the real estate market in Spain, both in the past and present. The main objective of this study is to identify those factors linked to location, which explain the formation of property values and justify their variability. Defining this process requires carrying out an evaluation on a territorial scale, establishing the socioeconomic, environmental and urban planning factors that constitute urban development and influence the demand for housing, thereby defining the processes by which their value is established. The analysis targets residential real estate values in coastal areas where pressure from the tourism industry has prompted large-scale transformations. Therefore, the focal point of this study is an area known as Vega Baja del Segura, which is located on the Spanish Mediterranean coast in southern Alicante (province). Characterized by its scenic and ecological diversity, this area has historically maintained a clear distinction between urban and rural spaces. This dichotomy has drastically changed in past decades due to the large increase in population attributed to the tourism and real estate markets – factors which have had a direct effect on property values. The development of this area provides a clear example of the expansionary policies which have affected the housing market on the coast of Spain during the past two decades, resulting in a large increase in suburban development. Understanding the territorial framework has made it possible to carry out a spatial variability analysis through massive data processing, as well as an econometric analysis that determines the factors that are evaluated positively and negatively by potential buyers. These relationships enable us to establish different mathematical systems based on hedonic pricing models that facilitate the identification of differential features in the economic, social and spatial spheres, and their impact on property values. Additionally, a process for land valuation was established through an analysis of the concept of structural vulnerability, which is understood to be a fragile situation resulting from either social or economic circumstances. Currently, this demand structure for second homes and services has demonstrated its fragility and has inhibited the area’s economic development as a result of the drastic fall in investment in the real estate market, due to the global debt crisis. This process has been worsened by the existence of a marginal industrial base into which no important investments have been channeled, combined with the progressive abandonment of agricultural and fishing operations. In and of itself, the tourism model did not inhibit the area’s economic development, rather it is the result of the manner in which it was implemented on the Costa Brava, with a land consumption based on the short-term, lacking respect for landscape and environmental aspects and without a comprehensive organization of the territory. It is clear that the link between vulnerability indexes and property values is not particularly significant, thereby indicating that future fragility trends have not been incorporated into the problem in terms of establishing the sale prices of the analyzed real estate product in question. Urban property values are clearly dependent on the system of development and environmental conservation, as well as on a clear recognition of the typologies that characterize rural areas, even those linked to the tourism industry. Today, the continued drop in tourism demand has provoked an obvious modification in the populational and economic structures. By incorporating these changes into the specified models, we can confirm a real collapse in values. It’s possible that the surplus of already-built homes is currently being marketed to a potential buyer who is in recession and linked to certain territorial characteristics that no longer exist. Finding solutions that can be adapted to the existing offer implies the viability of renewing the population system or carrying out modifications on an economic level. The search for answers to these questions suggests the need to reform the development model, without leaving out an area’s potentiality.

Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting

In this work, we propose the Seasonal Dynamic Factor Analysis (SeaDFA), an extension of Nonstationary Dynamic Factor Analysis, through which one can deal with dimensionality reduction in vectors of time series in such a way that both common and specific components are extracted. Furthermore, common factors are able to capture not only regular dynamics (stationary or not) but also seasonal ones, by means of the common factors following a multiplicative seasonal VARIMA(p, d, q) × (P, D, Q)s model. Additionally, a bootstrap procedure that does not need a backward representation of the model is proposed to be able to make inference for all the parameters in the model. A bootstrap scheme developed for forecasting includes uncertainty due to parameter estimation, allowing enhanced coverage of forecasting intervals. A challenging application is provided. The new proposed model and a bootstrap scheme are applied to an innovative subject in electricity markets: the computation of long-term point forecasts and prediction intervals of electricity prices. Several appendices with technical details, an illustrative example, and an additional table are available online as Supplementary Materials.

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.

A Propose-and-revise System for Real-time Traffic Management

The aim of this paper is to describe an intelligent system for the problem of real time road traffic control. The purpose of the system is to help traffic engineers in the selection of the state of traffic control devices on real time, using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based approach that implements an abstract generic problem solving method, called propose-and-revise, which was proposed in Artificial Intelligence, within the knowledge engineering field, as a standard cognitive structure oriented to solve configuration design problems. The paper presents the knowledge model of such a system together with the strategy of inference and describes how it was applied for the case of the M-40 urban ring for the city of Madrid.

Mixed models for short-run forecasting of electricity prices: Application for the Spanish market

Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well

Propuestas regulatorias para el diseño de un mercado ibérico a plazo eficiente de la energía = Regulatory proposals for the development of an efficient iberian energy forward market

El mercado ibérico de futuros de energía eléctrica gestionado por OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, con sede en Lisboa), también conocido como el mercado ibérico de derivados de energía, comenzó a funcionar el 3 de julio de 2006. Se analiza la eficiencia de este mercado organizado, por lo que se estudia la precisión con la que sus precios de futuros predicen el precio de contado. En dicho mercado coexisten dos modos de negociación: el mercado continuo (modo por defecto) y la contratación mediante subasta. En la negociación en continuo, las órdenes anónimas de compra y de venta interactúan de manera inmediata e individual con órdenes contrarias, dando lugar a operaciones con un número indeterminado de precios para cada contrato. En la negociación a través de subasta, un precio único de equilibrio maximiza el volumen negociado, liquidándose todas las operaciones a ese precio. Adicionalmente, los miembros negociadores de OMIP pueden liquidar operaciones “Over-The-Counter” (OTC) a través de la cámara de compensación de OMIP (OMIClear). Las cinco mayores empresas españolas de distribución de energía eléctrica tenían la obligación de comprar electricidad hasta julio de 2009 en subastas en OMIP, para cubrir parte de sus suministros regulados. De igual manera, el suministrador de último recurso portugués mantuvo tal obligación hasta julio de 2010. Los precios de equilibrio de esas subastas no han resultado óptimos a efectos retributivos de tales suministros regulados dado que dichos precios tienden a situarse ligeramente sesgados al alza. La prima de riesgo ex-post, definida como la diferencia entre los precios a plazo y de contado en el periodo de entrega, se emplea para medir su eficiencia de precio. El mercado de contado, gestionado por OMIE (“Operador de Mercado Ibérico de la Energía”, conocido tradicionalmente como “OMEL”), tiene su sede en Madrid. Durante los dos primeros años del mercado de futuros, la prima de riesgo media tiende a resultar positiva, al igual que en otros mercados europeos de energía eléctrica y gas natural. En ese periodo, la prima de riesgo ex-post tiende a ser negativa en los mercados de petróleo y carbón. Los mercados de energía tienden a mostrar niveles limitados de eficiencia de mercado. La eficiencia de precio del mercado de futuros aumenta con el desarrollo de otros mecanismos coexistentes dentro del mercado ibérico de electricidad (conocido como “MIBEL”) –es decir, el mercado dominante OTC, las subastas de centrales virtuales de generación conocidas en España como Emisiones Primarias de Energía, y las subastas para cubrir parte de los suministros de último recurso conocidas en España como subastas CESUR– y con una mayor integración de los mercados regionales europeos de energía eléctrica. Se construye un modelo de regresión para analizar la evolución de los volúmenes negociados en el mercado continuo durante sus cuatro primeros años como una función de doce indicadores potenciales de liquidez. Los únicos indicadores significativos son los volúmenes negociados en las subastas obligatorias gestionadas por OMIP, los volúmenes negociados en el mercado OTC y los volúmenes OTC compensados por OMIClear. El número de creadores de mercado, la incorporación de agentes financieros y compañías de generación pertenecientes a grupos integrados con suministradores de último recurso, y los volúmenes OTC compensados por OMIClear muestran una fuerte correlación con los volúmenes negociados en el mercado continuo. La liquidez de OMIP está aún lejos de los niveles alcanzados por los mercados europeos más maduros (localizados en los países nórdicos (Nasdaq OMX Commodities) y Alemania (EEX)). El operador de mercado y su cámara de compensación podrían desarrollar acciones eficientes de marketing para atraer nuevos agentes activos en el mercado de contado (p.ej. industrias consumidoras intensivas de energía, suministradores, pequeños productores, compañías energéticas internacionales y empresas de energías renovables) y agentes financieros, captar volúmenes del opaco OTC, y mejorar el funcionamiento de los productos existentes aún no líquidos. Resultaría de gran utilidad para tales acciones un diálogo activo con todos los agentes (participantes en el mercado, operador de mercado de contado, y autoridades supervisoras). Durante sus primeros cinco años y medio, el mercado continuo presenta un crecimento de liquidez estable. Se mide el desempeño de sus funciones de cobertura mediante la ratio de posición neta obtenida al dividir la posición abierta final de un contrato de derivados mensual entre su volumen acumulado en la cámara de compensación. Los futuros carga base muestran la ratio más baja debido a su buena liquidez. Los futuros carga punta muestran una mayor ratio al producirse su menor liquidez a través de contadas subastas fijadas por regulación portuguesa. Las permutas carga base liquidadas en la cámara de compensación ubicada en Madrid –MEFF Power, activa desde el 21 de marzo de 2011– muestran inicialmente valores altos debido a bajos volúmenes registrados, dado que esta cámara se emplea principalmente para vencimientos pequeños (diario y semanal). Dicha ratio puede ser una poderosa herramienta de supervisión para los reguladores energéticos cuando accedan a todas las transacciones de derivados en virtud del Reglamento Europeo sobre Integridad y Transparencia de los Mercados de Energía (“REMIT”), en vigor desde el 28 de diciembre de 2011. La prima de riesgo ex-post tiende a ser positiva en todos los mecanismos (futuros en OMIP, mercado OTC y subastas CESUR) y disminuye debido a la curvas de aprendizaje y al efecto, desde el año 2011, del precio fijo para la retribución de la generación con carbón autóctono. Se realiza una comparativa con los costes a plazo de generación con gas natural (diferencial “clean spark spread”) obtenido como la diferencia entre el precio del futuro eléctrico y el coste a plazo de generación con ciclo combinado internalizando los costes de emisión de CO2. Los futuros eléctricos tienen una elevada correlación con los precios de gas europeos. Los diferenciales de contratos con vencimiento inmediato tienden a ser positivos. Los mayores diferenciales se dan para los contratos mensuales, seguidos de los trimestrales y anuales. Los generadores eléctricos con gas pueden maximizar beneficios con contratos de menor vencimiento. Los informes de monitorización por el operador de mercado que proporcionan transparencia post-operacional, el acceso a datos OTC por el regulador energético, y la valoración del riesgo regulatorio pueden contribuir a ganancias de eficiencia. Estas recomendaciones son también válidas para un potencial mercado ibérico de futuros de gas, una vez que el hub ibérico de gas –actualmente en fase de diseño, con reuniones mensuales de los agentes desde enero de 2013 en el grupo de trabajo liderado por el regulador energético español– esté operativo. El hub ibérico de gas proporcionará transparencia al atraer más agentes y mejorar la competencia, incrementando su eficiencia, dado que en el mercado OTC actual no se revela precio alguno de gas. ABSTRACT The Iberian Power Futures Market, managed by OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, located in Lisbon), also known as the Iberian Energy Derivatives Market, started operations on 3 July 2006. The market efficiency, regarding how well the future price predicts the spot price, is analysed for this energy derivatives exchange. There are two trading modes coexisting within OMIP: the continuous market (default mode) and the call auction. In the continuous trading, anonymous buy and sell orders interact immediately and individually with opposite side orders, generating trades with an undetermined number of prices for each contract. In the call auction trading, a single price auction maximizes the traded volume, being all trades settled at the same price (equilibrium price). Additionally, OMIP trading members may settle Over-the-Counter (OTC) trades through OMIP clearing house (OMIClear). The five largest Spanish distribution companies have been obliged to purchase in auctions managed by OMIP until July 2009, in order to partly cover their portfolios of end users’ regulated supplies. Likewise, the Portuguese last resort supplier kept that obligation until July 2010. The auction equilibrium prices are not optimal for remuneration purposes of regulated supplies as such prices seem to be slightly upward biased. The ex-post forward risk premium, defined as the difference between the forward and spot prices in the delivery period, is used to measure its price efficiency. The spot market, managed by OMIE (Market Operator of the Iberian Energy Market, Spanish Pool, known traditionally as “OMEL”), is located in Madrid. During the first two years of the futures market, the average forward risk premium tends to be positive, as it occurs with other European power and natural gas markets. In that period, the ex-post forward risk premium tends to be negative in oil and coal markets. Energy markets tend to show limited levels of market efficiency. The price efficiency of the Iberian Power Futures Market improves with the market development of all the coexistent forward contracting mechanisms within the Iberian Electricity Market (known as “MIBEL”) – namely, the dominant OTC market, the Virtual Power Plant Auctions known in Spain as Energy Primary Emissions, and the auctions catering for part of the last resort supplies known in Spain as CESUR auctions – and with further integration of European Regional Electricity Markets. A regression model tracking the evolution of the traded volumes in the continuous market during its first four years is built as a function of twelve potential liquidity drivers. The only significant drivers are the traded volumes in OMIP compulsory auctions, the traded volumes in the OTC market, and the OTC cleared volumes by OMIClear. The amount of market makers, the enrolment of financial members and generation companies belonging to the integrated group of last resort suppliers, and the OTC cleared volume by OMIClear show strong correlation with the traded volumes in the continuous market. OMIP liquidity is still far from the levels reached by the most mature European markets (located in the Nordic countries (Nasdaq OMX Commodities) and Germany (EEX)). The market operator and its clearing house could develop efficient marketing actions to attract new entrants active in the spot market (e.g. energy intensive industries, suppliers, small producers, international energy companies and renewable generation companies) and financial agents as well as volumes from the opaque OTC market, and to improve the performance of existing illiquid products. An active dialogue with all the stakeholders (market participants, spot market operator, and supervisory authorities) will help to implement such actions. During its firs five and a half years, the continuous market shows steady liquidity growth. The hedging performance is measured through a net position ratio obtained from the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain – MEFF Power, operating since 21 March 2011, with a new denomination (BME Clearing) since 9 September 2013 – show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). The net position ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation on Energy Market Integrity and Transparency (“REMIT”), in force since 28 December 2011. The ex-post forward risk premium tends to be positive in all existing mechanisms (OMIP futures, OTC market and CESUR auctions) and diminishes due to the learning curve and the effect – since year 2011 – of the fixed price retributing the indigenous coal fired generation. Comparison with the forward generation costs from natural gas (“clean spark spread”) – obtained as the difference between the power futures price and the forward generation cost with a gas fired combined cycle plant taking into account the CO2 emission rates – is also performed. The power futures are strongly correlated with European gas prices. The clean spark spreads built with prompt contracts tend to be positive. The biggest clean spark spreads are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity. Market monitoring reports by the market operator providing post-trade transparency, OTC data access by the energy regulator, and assessment of the regulatory risk can contribute to efficiency gains. The same recommendations are also valid for a potential Iberian gas futures market, once an Iberian gas hub – currently in a design phase, with monthly meetings amongst the stakeholders in a Working Group led by the Spanish energy regulatory authority since January 2013 – is operating. The Iberian gas hub would bring transparency attracting more shippers and improving competition and thus its efficiency, as no gas price is currently disclosed in the existing OTC market.