Cross-markets Risk Transfer Using Agent-based Computational Finance Method

On April 16, 2010, the first stock index futures on China financial market,Shanghai and Shenzhen 300 stock index futures contracts traded on the official. Themovement indicates that China will appear the coexistence of stock index futuresmarket and the stock market named crosse-market-structure. Many financial riskevents are caused by this crosse-market-structure. Not only because of these riskevents, but also to ensure that our financial markets will develop healthy andorderly ,the research on such crossed-market-risk is essential. Then the previousresearch on crosse-market risk often use statistical methods, so they could not study indepth the core of the market----behavior of investors.ACF solves this problem.This thesis uses an artificial stock market Netlogo, followed by the artificialstock market fluctuations in import prices resulting from artificial stock index futuresmarket to, where stock index futures market using artificial U-Mart platform.The main conclusion is the reverse for the momentum investors and investorshave tended to the median observation period, the smaller the volatility of stock indexfutures and futures investors tend to median income.If the observation period tooshort or too long ,the return of investors tend to extreme loss. In addition, the accuracyhow the investors tend to judge is higher and prices of future less volatile; when thecorrect rate decline, futures volatility significantly increas.In addition, futuresinvestors on high income level accuracy tends to intermediate values and when thecorret rate is low,gains and losses is low and gains and losses of investors in futurestend to extreme .