The effect of universal futures on opening and closing stock market price discovery

Purpose – On 29 January 2001, Euronext LIFFE introduced single security futures contracts on a range of global companies. The purpose of this paper is to examine the impact that the introduction of these futures contracts had on the behaviour of opening and closing UK equity returns. Design/methodology/approach – The paper models the price discovery process using the Amihud and Mendelson partial adjustment model which can be estimated using a Kalman filter. Findings – Empirical results show that during the pre-futures period both opening and closing returns under-react to new information. After the introduction of futures contracts opening returns over-react. A rise in the partial adjustment coefficient also takes place for closing returns but this is not large enough to cause over-reaction. Originality/value – This is the first study to examine the impact of a single security futures contract on the speed of spot market price discovery.

Essays on market design and regulation in electricity systems

This thesis discusses market design and regulation in electricity systems, focusing on the information exchange of the regulated grid firm and the generation firms as well as the regulation of the grid firm. In the first chapter, an economic framework is developed to consistently analyze different market designs and the information exchange between the grid firm and the generation firms. Perfect competition between the generation firms and perfect regulation of the grid firm is assumed. A numerical algorithm is developed and its feasibility demonstrated on a large-scale problem. The effects of different market designs for the Central Western European (CWE) region until 2030 are analyzed. In the second chapter, the consequences of restricted grid expansion within the current market design in the CWE region until 2030 are analyzed. In the third chapter the assumption of efficient markets is modified. The focus of the analysis is then, whether and how inefficiencies in information availability and processing affect different market designs. For different parameter settings, nodal and zonal pricing are compared regarding their welfare in the spot and forward market. In the fourth chapter, information asymmetries between the regulator and the regulated firm are analyzed. The optimal regulatory strategy for a firm, providing one output with two substitutable inputs, is defined. Thereby, one input and the absolute quantity of inputs is not observable for the regulator. The result is then compared to current regulatory approaches.

What are the economic prospects of developing aquaculture in Queensland to supply the low price white fillet market? Lessons from the US channel catfish industry

The farming of channel catfish (Ictalurus punctatus) is the largest (by volume and value) and most successful (in terms of market impact) aquaculture industry in the United States of America. Farmed channel catfish is the most consumed (in terms of volume per capita) fish fillet in the U.S. market. Within Australia, it has long been suggested by researchers and industry that silver perch (Bidyanus bidyanus) and possibly other endemic teraponid species possess similar biological attributes for aquaculture as channel catfish and may have the potential to generate a similar industry. The current teraponid industry in Australia, however, shows very little resemblance to the catfish industry, either in production style or market philosophy. A well established budget framework from the literature on U.S. channel catfish farming has been adapted for cost and climate conditions of the Burdekin region, Queensland, Australia. Breakeven prices for the hypothetical teraponid farms were found to be up to 50% higher than those published for catfish farms however were much lower than those reported for silver perch production in Australia using current, endemic styles of production. The breakeven prices for the hypothetical teraponid farms were most sensitive (in order of significance) to feed prices, production rates, interest rates, fingerling prices and electricity prices. At equivalent feed costs the costs of production between the hypothetical catfish farms in the Mississippi, U.S. and the hypothetical teraponid farms in the Burdekin, Australia were remarkably similar. The cost of feeds suitable for teraponid production in Australia are currently around double that of catfish feeds in the U.S. Issues currently hindering the development of a large scale teraponid industry in Australia are discussed.

Least-Cost Planning and electricity industry reform in Australia

Least-Cost Planning played a key role in the development of the energy efficiency and renewable energy industries in the USA, It has not been widely used elsewhere, largely due to differences in other nations' regulatory environments and the emergence of competitive markets as the dominant paradigm for electricity planning, Least-Cost Planning, however may over valuable insights for creating regulatory framework for competitive electricity markers. This paper examines some lessons which may be extracted from an analysis of the Least-Cost Planning experience in the USA and suggests how these lessons might prove beneficial in guiding Australia's electricity industry reform, This analysis demonstrates how market-based reforms may be flawed if they ignore the history of previous reform processes.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Energy and ancillary services joint market simulation

In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM – a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Six thinking hats for electricity markets simulation: adapting meeting tools to agent decision

In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff. © 2014 IEEE.

Power Producers Trading Electricity in Both Pool and Forward Markets

The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.