Nerds on Wall Street: Math, Machines, and Wired Markets

3.10. Robots, RoboTraders, and Traders

Often, the best model of something is the thing itself. This is a key concept in robotics. Building a robot that explores a digital model of Mars is very different from building one that explores the actual planet of Mars.

An ever-growing collection of impressive robots have done well in complex dynamic environments.^[] Looking into how these robots "think" is looking at the future of algorithms. Looking at how humans and physical robots interact is a look at how humans and trading robots will coexist.

There are always multiple approaches to robotic tasks. Structuring and coordinating these approaches is the goal of multi-agent systems,^[] a unified approach to controlling complex systems. They are programs that cooperate, coordinate, and negotiate with each other. The list of key features of multi-agent systems reads like a description of key features of algorithmic trading:

• Embedded in the real world. The world in general and markets in particular are not static. Things change; information is incomplete. Everything is dynamic. A reactive agent responds to events rapidly enough for the response to be useful.

• Partial, imperfect models. Models of financial market behavior never have the precision of engineering models. They are statistical, with wide error bands. This is particularly true for equities. Financial models never capture every aspect of market participants' motivations.

• Varied outcomes likely. Simple games like tic-tac-toe can be modeled ...