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.

What drives information dissemination in continuous double auction markets?.

In this paper, we investigate further the way information disseminates from informed to uninformed traders in a market populated by heterogeneous boundedly rational agents. In order to achieve the goal, a computer simulated market where only a small fraction of the population observe the risky asset's fundamental value with noise was constructed, while the rest of agents try to forecast the asset's price from past transaction data. The paper departs from previous studies in that the risky asset does not pay a dividend every period, so agents cannot learn from past transaction prices and subsequent dividend payments. The main finding is that information can potentially disseminate in the market as long as: (1) informed investors' trades tilt transaction prices in the fundamental path direction; and (2) the median investor's expectation is very responsive to transaction prices. Otherwise, markets may display crashes or bubbles. It is found that the first condition requires a minimal amount of informed investors, and is severely limited by short selling and borrowing constraints.

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.Artificial financial markets; Information dissemination; Artificial neural networks; Heterogeneous agents;

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

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.

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.Microestructura de mercados; Mercados artificiales; Eficiencia; Aprendizaje; Market microstructure; Artificial markets; Efficiency; Learning;

Potential of noble fir, Norway spruce, western red cedar and western hemlock grown for timber production in Great Britain

The limited range of commercial timber species in Great Britain has led the forestry sector to consider wider planting of other species. This research addresses wood properties, particularly relevant to structural timber, of noble fir, Norway spruce, western red cedar and western hemlock in Great Britain. Sampling covered three regions to get a representative sample for the country. Bending stiffness, bending strength, density and twist distortion from drying were assessed. The results showed high yields of C16 for all these species, with Norway spruce and western hemlock performing comparatively well to typical British-grown Sitka spruce. Within this dataset, variation of mechanical properties within trees was more important than differences between species. Strength and stiffness increased with age, whereas density followed different trends in the inner and outerwood. The three properties were modelled based on ring number. The use of acoustic techniques to assess the mechanical properties of wood (in particular stiffness), was investigated in clears, sawn timber, logs and trees. The best results were found combining density with acoustic velocity in sawn timber. The use of acoustic techniques in standing trees was more reliable measuring distances of two or three metres, rather than the commonly used one metre; most likely due to a change in the wave propagation. Tree architecture was studied for timber production and quality. Noble fir described the highest merchantable taper profile. Branchiness varied importantly with height in the stem, and models were built for number, diameter and angle of branches. Western red cedar and western hemlock had fewer but thicker branches compared to noble fir and Norway spruce. Future work should produce grading machine settings and address the variation of timber quality and merchantability under different silvicultural regimes. This thesis concludes that the four species investigated can contribute to diversity the timber industry in Great Britain

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

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