Artificial Economics Agent-Based Methods in Finance, Game Theory and
Agent-based Computational Economics (ACE) is a new discipline of economics, largely grounded on concepts like evolution, auto-organisation and emergence: it intensively uses computer simulations as well as artificial intelligence, mostly based on multi-ag
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,661 ,6%16SULQJHU%HUOLQ+HLGHOEHUJ1HZ and a synchronous run of the market price with the fundamental price (with /(o.97,1.03])The sum of all / is chosen to be equal or less than 1, e.g. /(o,o.85] = 0.137 means that at least 13.7% of time periods the price pt of the risky asset deviates from p* by at least -15%. Over all simulations, overvaluation occurs more rarely than undervaluation. The reason for this is that the fundamental price reflects the valuation of a risk-neutral investor, whereas the market price is determined by supply and demand of agents who use a risk-averse utility function. One exception of this market behavior can be observed, if supply and demand would result in a negative market price (which is prohibited and set equals to zero). Figure 2 and figure 3 show the price evolvement and the wealth ratio for the simulation run with k= 1 over 150000 periods. Highfluctuationsoccur with a wealth ratio higher than 0.7. As assumed before a trend is visible that the wealth ratio increases within the simulation run because the parameter setting empowers agents to build up monopolies. Table 1 shows the calculated key ratios for the different market phases in this simulation run. Table 1. Simulation run without taxes and trading restrictions, k = 1 3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
pt 99.86 84.31 99.43 105.17 87.92 98.87 98.70 103.28 96.38 99.75 100.43 95.02 94.31 100.22 96.12 98.78 99.89 103.56 102.69 97.61
Pmax
Pmin
Pt
105.92 105.91 266.42 214.35 183.10 148.83 116.98 196.98 144.40 137.38 132.07 139.31 168.51 149.16 140.78 137.46 135.42 155.02 161.37 141.82
66.64 100.15 21.77 100.28 0 100.16 0 100.28 0 99.99 0 100.08 85.65 99.71 0 99.88 0 99.56 0 99.77 72.13 100.27 0 100.00 0 100.08 11.04 100.08 0 100.30 85.16 100.06 80.15 99.93 72.65 99.87 0 100.15 0 99.73
P^ax
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P 0. He then elects one of these rules with a random process proportional to their strength. The action aik associated with the elected rule gives the agent decision. If there are no rules activated by the current ma
