Price dynamics, informational efficiency and wealth distribution in continuous double auction markets

This paper studies the properties of the continuous double auction trading mechanishm using an artificial market populated by heterogeneous computational agents. In particular, we investigate how changes in the population of traders and in market microstructure characteristics affect price dynamics, information dissemination and distribution of wealth across agents. In our computer simulated market only a small fraction of the population observe the risky asset's fundamental value with noise, while the rest of agents try to forecast the asset's price from past transaction data. In contrast to other artificial markets, we assume that the risky asset pays no dividend, so agents cannot learn from past transaction prices and subsequent dividend payments. We find that private information can effectively disseminate in the market unless market regulation prevents informed investors from short selling or borrowing the asset, and these investors do not constitute a critical mass. In such case, not only are markets less efficient informationally, but may even experience crashes and bubbles. Finally, increased informational efficiency has a negative impact on informed agents' trading profits and a positive impact on artificial intelligent agents' profits

Contribution of Agroforestry Biomass Valorisation to Energy and Environmental Sustainability

According to data provided by the International Energy Agency, buildings consume more than one-third of the energy produced globally and represent a major source of carbon dioxide-related emissions [...

Advances in Leakage Control and Energy Consumption Optimization in Drinking Water Distribution Networks

Water is an essential element for life [...

Formación de Precios en un Mercado Artificial de Doble Subasta Continua

En este trabajo se estudia la formación de precios en un mercado artificial de doble subasta continua con agentes heterogéneos, tanto en términos de eficiencia informativa como en términos de sus propiedades estadísticas. A diferencia de otros mercados artificiales propuestos en la literatura, en este mercado existe información asimétrica tanto ex-ante como ex-post,puesto que los agentes no informados observan únicamente precios de transacción pasados. En consecuencia, su capacidad predictiva sobre el proceso fundamental está limitada por el grado de eficiencia informativa de los precios de transacción, endógena al mercado. Nuestro mercado es capaz de replicar los hechos estilizados observados comúnmente en las series reales de rendimientos (colas gruesas, persistencia en la volatilidad, correlación serial y efectos ARCH), y nos permite extraer predicciones teóricas con respecto al efecto de la distribución de la población de agentes sobre dichas propiedades estadísticas. Una diferencia del trabajo es la modelización del precio fundamental como un proceso estocástico, lo cual permite calibrar los parámetros del mercado artificial a datos reales. La principal conclusión del trabajo es que el mecanismo de doble subasta continua permite un elevado grado de eficiencia informativa cuando existe información asimétrica, además se observa que la eficiencia del mercado puede mejorar introduciendo inversores sin información privilegiada pero que explotan la información contenida en los precios de transacción pasados (por ejemplo, analistas técnicos y agentes con capacidad de aprendizaje), aunque ello disminuya el valor de la información privada y por tanto la riqueza de aquellos con información privilegiada.This paper studies price formation in an artificial continuous double auction market with heterogeneous agents, in terms of its informational efficiency as well as its statistical properties. Unlike other arificial markets in the literature, in this market there is both ex-ante and ex-post asymmetric information, since uninformed agents only observe past transaction prices. Consequently, their predictive capability about the fundamental process is limited by the degree of informativeness of transaction prices, which is endogenous to the market. Our market can replicate stylized facts commonly observed in real return series (thick tails, volatility persistence, serial correlation and ARCH effects), and enables us to extract theoretical predictions regarding the effect of the agent population’s distribution on such statistical properties. This paper differs from others in that the fundamental price is modeled as a stochastic process, which enables us to calibrate the artificial market’s parameters to real data. The paper’s main conclusion is that the continuous double auction mechanism ensures a high degree of informational efficiency when there is asymmetric information. We also observe that market efficiency may improve in the presence of agents with no inside information but who exploit the information contained in past transaction prices (i.e., technical analysts and agents endowed with learning capabilities), even though this diminishes the value of private information, and, therefore, insider traders’ wealth.Publicad

Mercados de agentes computacionales

La microestructura de mercado analiza, entre otros aspectos, el impacto que la estructura de mercado o conjunto de reglas que gobiernan el funcionamiento de un mercado tiene sobre el comportamiento de los inversores y los costes que estos inversores sufren a la hora de realizar transacciones. Los mercados financieros de agentes computacionales o mercados financieros artificiales, basados en simulación, emergen como una novedosa y prometedora herramienta para el estudio de la microestructura. Los autores presentan la aplicación de esta técnica para el caso de un mercado financiero donde se negocia un único activo con riesgo.Publicad

Price dynamics, informational efficiency and wealth distribution in continuous double-auction markets

This paper studies the properties of the continuous double-auction trading mechanism using an artificial market populated by heterogeneous computational agents. In particular, we investigate how changes in the population of traders and in market microstructure characteristics affect price dynamics, information dissemination, and distribution of wealth across agents. In our computer-simulated market only a small fraction of the population observe the risky asset's fundamental value with noise, while the rest of the agents try to forecast the asset's price from past transaction data. In contrast to other artificial markets, we assume that the risky asset pays no dividend, thus agents cannot learn from past transaction prices and subsequent dividend payments. We find that private information can effectively disseminate in the market unless market regulation prevents informed investors from short selling or borrowing the asset, and these investors do not constitute a critical mass. In such case, not only are markets less efficient informationally, but may even experience crashes and bubbles. Finally, increased informational efficiency has a negative impact on informed agents' trading profits and a positive impact on artificial intelligent agents' profits.Publicad

Worldwide Research Trends on Optimizing Wind Turbine Efficiency

In a world in which electricity is increasingly necessary, it is vitally important to ensure that the supply of this electricity is safe, reliable, sustainable, and environmentally friendly, reducing CO2 emissions into the atmosphere and the use of fossil fuels. Renewable energies, and wind energy, in particular, make a significant contribution to this. Wind energy research dates to the last century, yet efforts to improve wind turbine performance continue around the world. Advances in blade aerodynamics and wind resource assessment are outstanding [...

Analysis of a novel proposal using temperature and efficiency to prevent fires in photovoltaic energy systems

Fires in photovoltaic (PV) electrical systems are a real and serious problem because this phenomenon can have severe consequences for the safety of people and the environment. In some cases, fires result from a lack of maintenance or improper installation of PV modules. It is essential to consider prevention and continuous monitoring of the electrical parameters to minimize these risks, as these factors increase the temperature of the photovoltaic modules. The use of thermal analysis techniques can prevent hotspots and fires in photovoltaic systems; these techniques allow detecting and correcting problems in the installation, such as shadows, dirt, and poor-quality connections in PVs. This paper presents a case study of the implementation of thermal analysis in an installation of photovoltaic modules connected to a solar pumping system to identify the formation of hotspots through thermal images using an unmanned aerial vehicle (UAV). Here, a novel methodology is proposed based on the comparison of temperature increases concerning the values of short circuit current, open circuit voltage, and real efficiency of each PV module. In addition, an electrical safety methodology is proposed to design a photovoltaic system that prevents fires caused by hotspots, contemplating critical parameters such as photovoltaic power, number of photovoltaic modules, DC:AC conversion ratio, electrical conductor selection, control devices, and electrical protection; the performance power expected was obtained using standard power test conditions, including irradiance factor, photovoltaic module (PVM) temperature factor, and power reduction factor

Mechanical thrombectomy during ischaemic stroke due to a calcified cerebral embolism

Carta al editor de Neurología, en la que los autores hacen el estudio de un caso al que han aplicado oclusión de la arteria cerebral media (ACM) por un émbolo cálcico tras cirugía de válvula aórtica, mediante neurointervencionismo.Letter to the editor of Neurology, in which the authors make the study of a case to which they have applied occlusion of the cerebral artery media (ACM) by a calcium embolus after aortic valve surgery, by neurointervention.peerReviewe

Application of time-controlled critical point in pressure reducing valves: a case study in North Spain

Potable water utilities are currently making great efforts to reduce leakage rates and assure long-term supply to the population due to the challenges of climate change, growing population and water shortage scenarios that have been on them over the last years. One of the most employed methods to reduce leakage includes the installation of pressurereducing valves along the water distribution network and the utilization of pressure management schemes. Pressure management includes different types of control models, which are applied according to the requirements of each site. The most advanced and sophisticated scheme is critical point control, which relies on a flow signal from a measuring device or online communication between the critical point and the valve. This paper proposes the utilization of a seasonal autoregressive integrated moving average, or the SARIMA model, to correlate pressure at the outlet of the valve and pressure on the critical point of the area supplied, aiming to set a fixed pressure in the critical point. The SARIMA model is developed according to historical data logged in the field and then validated. Later, the SARIMA model was tested on a real location in the village of Noja, Spain. The analysis of the field test results prove that the proposed model is feasible to be used since there is no significance difference between the target values set in the critical point and the real values measured in the field. The research proves that the SARIMA model can be used as an alternative for critical point control in water distribution networks when no flow signal is available or when communication between the critical point and the pressure reducing valve is not an option