The Research On The Effectiveness Of Stock Options Market In China Based On The Agent-based Computational Finance

In the context of the rapid development of domestic financial market,this paper studies the important components of the options market in the financial derivatives market.Because there is no domestic product launch traded stocks options,and since the market structure of China's financial markets and trajectory with significant differences between the foreign developed countries.Therefore,the research method of this paper is to use the method of computational experiment to construct the artificial individual stock options simulation platform in the context of domestic financial market.Validity analysis of the simulated data generated by the platform;Draw conclusions and put forward policy Suggestions.Firstly,this paper has compiled the current status and trading rules of the domestic options market,and has carried out a thorough study of the method of computational experimental finance.Then,on this basis to build based on artificial options market under continuous double auction trading mechanism,and the simulation data platform compared with Shanghai 50 etf option data,verify the effectiveness of the simulated data in statistical sense;Then,there is no risk arbitrage on the data produced in the simulated options market using bull spreads,box spreads,and butterfly spreads.By changing the parameters of the artificial stock option model set,the different market environment of stock option market effectiveness is studied,get the following conclusions: distance closer to the vesting date options contracts has stronger stability;Increasing the market noise volatility of the underlying stock can significantly increase the arbitrage opportunities for the corresponding option contracts.The increase in the number of agents has no significant effect on the arbitrage room in the option contracts.Finally,in view of the above research conclusion put forward regulatory Suggestions and investment advice,and this research problems and future research direction.