From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
2006-03-06
Research Paper
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Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with information asymmetry, and investigate the difference caused in the market dynamics between the discrete-time simulation and continuous-time, asynchronous simulation. We show that the characteristics of the market prices are different in the two cases, and observe that additional information is being revealed in the continuous-time, asynchronous models, which can be acted upon by the agents in such models. Since most financial markets are continuous and asynchronous in nature, our results indicate that explicit consideration of this fundamental characteristic of financial markets cannot be ignored in their agent-based modelling.
- Agent-Based Computational Finance
- Artificial Stock Markets
- Autonomous Behaviour
- Continuous Trading
- Glosten and Milgrom Model
- Informational Asymmetry
- Market Microstructure
- O32 : Management of Technological Innovation and R&D
- M : Business Administration and Business Economics; Marketing; Accounting
- F37 : International Finance Forecasting and Simulation
- L15 : Information and Product Quality; Standardization and Compatibility
- market
- market maker
- trader
- value
- order
- maker
- model
- price
- probability
- investor
- simulation
- figure
- asynchronou
- probability density estimate
- spread
- stock
- trade
- information
- experiment
- bid-ask spread
