Statistical Simulation Algorithm Research And Its Applications In Finance Analysis

As the development of financial liberalization and financial innovation, more and more financial product appeared, the volume of financial products exchanged in the market is also increasing. As a result, financial data increase rapidly. In order to study the problem of finance, we must analyze the financial data. Therefore, modern finance take statistics and computer science as more and more important. In the field of financial statistics, statistical simulation technology came into being, and developing very rapidly. It is used to simulate the actual mechanism of the financial system, making the complex financial system modeling can be achieved.Based on this, first this paper study and improve the statistical simulation algorithm. Then this paper create statistical models of financial product pricing, financial risk management models, securities investment strategy analysis model and optimal portfolio selection model based on simulation algorithm.This paper apply Statistical simulation algorithm in financial asset pricing, use standard Monte Carlo, the BS option pricing model and improve simulation model to estimate the option and Convertible Bonds price in China's financial markets.This paper apply Statistical simulation algorithm in financial risk management and securities investment strategy analysis, statistical simulation algorithm is used to value the risk of Chinese stock market. Value the VaR of ShangHai stock index before and after the introduction of index futures. The channel structure of the stock market is built based on VaR, and the investment strategy is proposed.This paper apply statistical simulation algorithm in the model of select the optimal portfolio, establish some expected return of the portfolio, and risk minimization objective. Most of the non-linear programming problems are multi-peaks, get a global optimal solution is more difficult. The simulated annealing algorithm which this paper introduces can solve the problem of optimal portfolio choice well.