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Challenges

Why agent-based modeling?

There are several market dynamics that traditional methods struggle to model, such as contagion effects, feedback loops and structural changes.

Agent-based models attempt to capture the behavior and interaction of individual entities within an environment and can recreate complex dynamics.

This means that with agent-based modeling, you can solve problems where traditional methods are not sufficient, such as risk management, market execution or financial crime analytics.

01

What is Agent-Based Modeling?

Find out more about the origin of agent-based modeling in this in-depth article.

02

Why are Agent-Based Models useful?

Why do agent-based models give a more robust view of the financial system?

03

How do Agent-Based Models work?

What are the components of an ABM and how do they actually work?

Agent-based modeling with Simudyne
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As its adoption becomes more widespread, Simudyne’s platform will ultimately help cultivate a stronger, more efficient tech-enabled financial services sector.
Andy Challis
MD, principal investments at Barclays Bank
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