ByPaul Cottrell, BSc, MBA, ABD

Complexity Science &

The Art of Trading

Author Complexity Science, Behavioral

Finance, Dynamic Hedging, Financial Statistics, Chaos Theory

Proprietary Trader Energy and Currency

Dissertation Dynamically Hedging Oil and

Currency Futures Using Receding Horizontal Control and Stochastic Programming

Introduction

The study of complex systems Using simple rules for agentsSelf organizing behavior Interactions that have a magnifying effect

What is Complexity Science?

Agents are the atoms of the complex systemCan be programmed to interact with

External environmentInternal environment

Complex behavior can emergeWith simple interaction rule

Agents should be able to morph their behavior (DNA)Exhibits evolutionary pathways and allows for

diversity

Agents

Simple AutomataIs a cybernetic systems

Does not evolve and communicate with environment

Complex AutomataIs an evolving system

Communicates with internal and external environment

Automata

Simple Automata & Complex Automata

Simple Automata

Complex Automata

How do we optimize trading strategies?Local optimum Global optimum

Current strategies Compare trading strategies with P/L

performanceMACD vs. RSI, MA vs. Fibonacci Problem with this optimization method

The selection set is limitedNot very efficient to evaluate

For all possible parameter options

The Optimization Problem

Ant Algorithms A programming method were an agent crawls

the landscape to find a solutionStores the location of the solution with a

pheromone trail.Strongest pheromone scent is considered the most

optimized.Does have a local optimum issue in certain cases

Need to run simulation multiple times to get optimum convergence.

Simulation Methods

Stochastic SimulationRandom select parameters and add a

stochastic process to evaluate P/L change.Artificial Neural Network

Used to determine optimum weights for inputs to produce best trading signal

Genetic AlgorithmsTakes a solution population and ranks them

Combines the top 10% to produce possible better solutions

Other Simulation Methods

ANN vs. GA

Genetic AlgorithmArtificial Neural Network

But strategies can combine both methods.

The problemHow to pick the best trading strategy?

Use complexity scienceLet the agents provide a solution.

Program simple trading rules for the automata Random selection of risk taking personality Start with equal equity in account Let agents select a particular strategy from defined strategy landscape Let agents learn which strategies work and which do not

Store working strategies in a data array with parameters used in “winning strategy”

Need many simulations to develop a global optimum. Can implement ANT, ANN, and GA methods.

Price action can be a stochastic simulation or historic dataBut verification should be conducted with out-of-sample testing.

Strategy Filtering

Complexity Science can help with optimization

Brute force with determining best strategy is not computationally efficient

Agents can be programmed with certain personalities and can evolve through time

Can gain unexpected knowledge about optimized parameters for certain trading strategies.

Allows for machine learning

Conclusion