A simple trading model based on pair pattern strategy space with holding periods is proposed. Power-law behaviors are observed for the return variance $sigma^2$, the price impact $H$ and the predictability $K$ for both models with linear and square r
oot impact functions. The sum of the traders wealth displays a positive value for the model with square root price impact function, and a qualitative explanation is given based on the observation of the conditional excess demand $<A|u>$. An evolutionary trading model is further proposed, and the elimination mechanism effectively changes the behavior of the traders highly performed in the model without evolution. The trading model with other types of traders, e.g., traders with the MGs strategies and producers, are also carefully studied.
We consider models of financial markets in which all parties involved find incentives to participate. Strategies are evaluated directly by their virtual wealths. By tuning the price sensitivity and market impact, a phase diagram with several attracto
r behaviors resembling those of real markets emerge, reflecting the roles played by the arbitrageurs and trendsetters, and including a phase with irregular price trends and positive sums. The positive-sumness of the players wealths provides participation incentives for them. Evolution and the bid-ask spread provide mechanisms for the gain in wealth of both the players and market-makers. New players survive in the market if the evolutionary rate is sufficiently slow. We test the applicability of the model on real Hang Seng Index data over 20 years. Comparisons with other models show that our model has a superior average performance when applied to real financial data.
