14 March 2018
- 15 minute read

Data derived from Hudson Bay Company records [4] [5]. Scanned data from http://people.whitman.edu/~hundledr/courses/M250F03/M250.html

Three return series, scaled to the same standard deviation. The Gaussian returns (middle) are easy to spot. Both the ABM (bottom) and coffee futures (top) display heavy-tailed return distributions and volatility clustering.

Price history and open interest for 30,000 steps of a typical run of our agent-based model.

Change in notional wealth of agents for the market shown in Figure 3 between timesteps 10,000 and 100,000. Value traders are ordered from least skilful to most skilful; technical traders are ordered from the slowest to fastest moving-average crossover system. Noise traders (not shown) all made small losses.

The performance of the 10 value traders improves once the 10 trend-following technical traders are switched on at timestep 10,000.

The distributions of simple returns for coffee and 10-year Treasury note futures (top left and right, respectively) share similarities with distributions created by the agent-based model (ABM) from Figure 2 (bottom left) and the ABM of Figures 3 and 4, for timestep 15,000 onwards (bottom right).

Two identical runs of the simulation, with one exception. In the second run, the price is rounded to the third decimal place after timestep 50,000, then allowed to continue as before, with the same random numbers throughout.

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