Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

MarketOpolis: A market simulation based on investors decisions

This study aims to replicate Apple’s stock market movement by modeling major investment profiles and investors. The present model recreates a live exchange to forecast any predictability in stock price variation, knowing how investors act when it concerns investment decisions. This methodology is particularly relevant if, just by observing historical prices and knowing the tendencies in other players’ behavior, risk-adjusted profits can be made. Empirical research made in the academia shows that abnormal returns are hardly consistent without a clear idea of who is in the market in a given moment and the correspondent market shares. Therefore, even when knowing investors’ individual investment profiles, it is not clear how they affect aggregate markets.

Precursors and prices : structuring the Quebec synthetic drug market

Information recueillie sur les marchés des drogues de synthèse est beaucoup moins avancée que les études sur d'autres marchés de drogues illicites. La classification relativement récente des drogues de synthèse comme substances illicites, couplée avec ses caractéristiques distinctes qui empêchent son observation, a entravé le développement d’évaluations complètes et fiables des caractéristiques structurelles des marchés. Le but de cet article est de fournir un aperçu fiable sur la dynamique interne du marché des drogues synthétiques, en particulier sur ses caractéristiques structurelles et organisationnelles. En utilisant l'information obtenue à partir de 365 drogues de synthèse saisies par les policiers pendant un an, cette étude sera la fusion de deux techniques, soit la composition des drogues illicites et des analyses économiques, afin de tirer des évaluations fiables des caractéristiques structurelles du marché du Québec de drogues synthétiques. Les résultats concernant l'analyse de la composition des drogues indiquent que le marché des drogues synthétiques au Québec est probablement composé d'un nombre élevé de petites structures, ce qui indique un marché compétitif. L'analyse économique a également fourni des informations complémentaires sur le marché des drogues. Selon la région géographique les couts de la production et les relations entre trafiquant et consommateur influencent le prix des drogues. Les résultats de cette recherche mettent l'accent sur la nécessité de concevoir des politiques qui tient compte des différences régionales dans la production de drogue et reflète la nature compétitive de ce marché.

Master Plan for Renewable Energy based Electricity Generation in The Gambia

The principal objective of this paper is to develop a methodology for the formulation of a master plan for renewable energy based electricity generation in The Gambia, Africa. Such a master plan aims to develop and promote renewable sources of energy as an alternative to conventional forms of energy for generating electricity in the country. A tailor-made methodology for the preparation of a 20-year renewable energy master plan focussed on electricity generation is proposed in order to be followed and verified throughout the present dissertation, as it is applied for The Gambia. The main input data for the proposed master plan are (i) energy demand analysis and forecast over 20 years and (ii) resource assessment for different renewable energy alternatives including their related power supply options. The energy demand forecast is based on a mix between Top-Down and Bottom-Up methodologies. The results are important data for future requirements of (primary) energy sources. The electricity forecast is separated in projections at sent-out level and at end-user level. On the supply side, Solar, Wind and Biomass, as sources of energy, are investigated in terms of technical potential and economic benefits for The Gambia. Other criteria i.e. environmental and social are not considered in the evaluation. Diverse supply options are proposed and technically designed based on the assessed renewable energy potential. This process includes the evaluation of the different available conversion technologies and finalizes with the dimensioning of power supply solutions, taking into consideration technologies which are applicable and appropriate under the special conditions of The Gambia. The balance of these two input data (demand and supply) gives a quantitative indication of the substitution potential of renewable energy generation alternatives in primarily fossil-fuel-based electricity generation systems, as well as fuel savings due to the deployment of renewable resources. Afterwards, the identified renewable energy supply options are ranked according to the outcomes of an economic analysis. Based on this ranking, and other considerations, a 20-year investment plan, broken down into five-year investment periods, is prepared and consists of individual renewable energy projects for electricity generation. These projects included basically on-grid renewable energy applications. Finally, a priority project from the master plan portfolio is selected for further deeper analysis. Since solar PV is the most relevant proposed technology, a PV power plant integrated to the fossil-fuel powered main electrical system in The Gambia is considered as priority project. This project is analysed by economic competitiveness under the current conditions in addition to sensitivity analysis with regard to oil and new-technology market conditions in the future.

2007-2026 Global market forecast : Airbus

The main drivers of tomorrow's traffic growth - Growing Middle East passenger and cargo hubs - Asia: a new economic paradigm in the making - LCCs in Asia growing in number and traffic share - Accelerating deregulation in Asia - Continuing high growth rate for domestic China and emerging China international outbound traffic.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Analysing UK real estate market forecast disagreement

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The results suggest that real estate forecasts are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that real estate forecasters display the characteristics associated with a consensus indicating herding.

The case of negative day-ahead electricity prices

In recent years, Germany has significantly increased its share of electricity produced from renewable sources, which is mainly due to the Renewable Energy Act (EEG). The EEG substantially impacts the dynamics of intra-day electricity prices by increasing the likelihood of negative prices. In this paper, we present a non-Gaussian process to model German intra-day electricity prices and propose an estimation procedure for this model. Most importantly, our model is able to generate extreme positive and negative spikes. A simulation study demonstrates the ability of our model to capture the characteristics of the data.

Commodity futures prices: more evidence on forecast power, risk premia and the theory of storage

In this paper, we examine the temporal stability of the evidence for two commodity futures pricing theories. We investigate whether the forecast power of commodity futures can be attributed to the extent to which they exhibit seasonality and we also consider whether there are time varying parameters or structural breaks in these pricing relationships. Compared to previous studies, we find stronger evidence of seasonality in the basis, which supports the theory of storage. The power of the basis to forecast subsequent price changes is also strengthened, while results on the presence of a risk premium are inconclusive. In addition, we show that the forecasting power of commodity futures cannot be attributed to the extent to which they exhibit seasonality. We find that in most cases where structural breaks occur, only changes in the intercepts and not the slopes are detected, illustrating that the forecast power of the basis is stable over different economic environments.

The cyclical relations between traded property stock prices and aggregate time-series

This paper examines the cyclical regularities of macroeconomic, financial and property market aggregates in relation to the property stock price cycle in the UK. The Hodrick Prescott filter is employed to fit a long-term trend to the raw data, and to derive the short-term cycles of each series. It is found that the cycles of consumer expenditure, total consumption per capita, the dividend yield and the long-term bond yield are moderately correlated, and mainly coincident, with the property price cycle. There is also evidence that the nominal and real Treasury Bill rates and the interest rate spread lead this cycle by one or two quarters, and therefore that these series can be considered leading indicators of property stock prices. This study recommends that macroeconomic and financial variables can provide useful information to explain and potentially to forecast movements of property-backed stock returns in the UK.

Privatisation and cross-border electricity trade: from internal market to European Supergrid?

he perspective European Supergrid would consist of an integrated power system network, where electricity demands from one country could be met by generation from another country. This paper makes use of a bi-linear fixed-effects model to analyse the determinants for trading electricity across borders among 34 countries connected by the European Supergrid. The key question that this paper aims to address is the extent to which the privatisation of European electricity markets has brought about higher cross-border trade of electricity. The analysis makes use of distance, price ratios, gate closure times, size of peaks and aggregate demand as standard determinants. Controlling for other standard determinants, it is concluded that privatisation in most cases led to higher power exchange and that the benefits are more significant where privatisation measures have been in place for a longer period.