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Conditional Density Models Integrating Fuzzy and Probabilistic...

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Title Conditional Density Models Integrating Fuzzy and Probabilistic Representations of Uncertainty
Period 01 / 2007 - 06 / 2014
Status Completed
Dissertation Yes
Research number OND1333794
Data Supplier Website ERIM

Abstract

Most models developed within the growing field of agent-based modelling of financial markets are discrete time and synchronous. Most financial markets, however, are continuous (in the sense that traders can trade any time) and asynchronous (different actors operate autonomously without necessarily synchronising their activities). Hence, important aspects of financial markets are not captured by the current agent-based models. In this research, we will develop continuous, asynchronous agent-based models of financial markets to bridge the gap mentioned, by following a micro-simulation approach based on the roles of the actors in the financial markets and the specific organization (microstructure) thereof.

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Classification

A53000 Banking and insurance business
D43000 Economics

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