Simulation Statistical Based On Method To Shanghai Composite Index Pricing And VaR Estimation

As the development of financial market, more and more financialproduct appeared and the volume of financial products exchanged in themarket is also increasing. In order to study the problem of finance, wemust analyze the days of financial data. Therefore, in the field of finance,statistical simulation technology had been widely used. It is used tosimulate the actual mechanism of the financial system, making thecomplex financial system modeling can be achieved.The classical portfolio theory assumes that composite prices obeyBrownian motion model. This assumption can’t explain the fluctuation incomposite price has self-similarity, long dependency and so on. It hasbeen proved that fractional Brownian motion can explain the change offinancial market well.We study and improve the Monte Carlo simulation algorithm whichwas widely used in the statistical simulation. Then this paper createfinancial product pricing models and financial risk management modelsbased on simulation algorithm.We apply Monte Carlo simulation algorithm in financial productpricing and introduce fractional Brownian motion which can explain thechange of financial market well. Using Brownian motion model,fractional Brownian model and improve simulation model to estimate the Shanghai composite index and compare the results. In the process ofcalculation, stochastic representation method and the spectral densitiesmethod are used to discrete fractional Brownian motion model.We apply Monte Carlo simulation algorithm in financial riskmanagement. Monte Carlo simulation algorithm is used to value the riskof composite market, using the models which can get better effect infinancial product pricing to value the VaR of Shanghai composite index.