The Design of an Agent-Based System for Capital Markets

Abstract

The trading risk management implies analysing several types of risks: capital, market, liquidity, insolvency, business, credit, operational or financial risk. Trading models and techniques must be seen as tools that can provide an informed manager with useful insights, so they are indispensable in an increasingly integrated and sophisticated market. The main aim of this study is the conceptualization of a generic intelligent agent, based on a neural network and an agent system, applicable to a trading system of the listed companies. The results show that this model can contribute to reducing the transactional risk on the capital market and can offer solutions to improve the managerial decisions.