Publication: Formación de Precios en un Mercado Artificial de Doble Subasta Continua
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2007
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Asociación Española de Contabilidad y Administración de Empresas
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Abstract
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.
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.
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Microestructura de mercados, Mercados artificiales, Eficiencia, Aprendizaje, Market microstructure, Artificial markets, Efficiency, Learning
Bibliographic citation
Revista española de financiación y contabilidad, 2007, 36, 134, p. 235-260.