Research On Simple Moving Averagetrading System Based On Nolinear Method And VaR

Chinese financial market is in the midst of a rapid developing period while global financial market is also experiencing profound changes.As the traditional theory is unable to keep up with the rapid development of financial market, the program trading system is playing a much more important part in the market, and the trading system has already been appliedwidely in Europe and America by now. According to the reporting data published by NYSE, the average amount of dailytrading exchangingviaprogram tradinghas reached28.6%of the weekby20th May2011. A successfully operatingtrading system would generate stable and excessive returns in stock market. According to the trading system ranking of2011released by a respected trading system evaluation magazine, the annual rate of return of the top three models were above200%.Currently, the research hot points of domestic and overseasstill focus on trend prediction in trading system area, but the issues of prediction accuracy remain unresolved big challenge.Thoughthe researches mainly attempt to make profit in any trend by using consistent method, the defects of the trading system are not been paidenough attention to. As a result, the risk control of the trading system lacks a scientific and effective method and no researches with VaRmodels and tools are applied in this field.To make up for the deficiency of the above researches and based on the simple moving average trading method of traditional technical analysis, support vector machine (SVM), the non-dominated solution of multi-objective optimization algorithm and VaR method of risk management are applied to develop two important models in the trading system including alpha model and risk control model and constitute the moving average trading system based on nonlinear method and VaR.The Alpha refers to the investment return deducing the market benchmark return. Alpha model represents a trading system used forselectinga trading timing during the investment to make profit. Risk management is not only used to avoid the risk or minimize losses, but also to implement purposeful selection and scale control on risk exposures thus to improve the quality and continuity of return. Although the profit would be influenced by risk control model, more robust benefit is brought out by reducing return volatility.The simple moving average trading system has obvious profitable effect in trend market, but would suffer from repeated losses in sideways market. In order to filter the unfavorable trends, SVM classifier is used to identify market trends, and5tendency technical indicators including RAVI are used to map the share prices time series to a high-dimensional feature space.Then, support vector machine classifier is constructed to classify and filter trends through which fluctuation trend and downward trend are filtered (short position). Taking SSE composite index as research object and5-60days moving average as the basic rules, the simple moving average system based on trend following is improved and SVM classifier is established.On this basis, non-dominated solution approach is used to optimize the parameters of the simple moving average system based on SVM classifier. During parameters optimization process, two common and important evaluation indicators in the trading system, maximum return and continuous maximum drawdown, are taken as objectives in order to prevent the over fitting of parameters. Therefore, the non-dominated solution approach in multi-objective optimization algorithm is used for further optimizing parameters. The construction of an important integral part of the trading model–alpha model–is accomplished through optimization.With the purpose of establishing a risk control model, nonspecific time dynamic VaR model specific to the simple moving average trading system is built up. Taking5-60days moving average as research object, the nonspecific time dynamic VaR model is built and nearly3000trading rate of return data are generated and the distribution characteristics of the nonspecific time dynamic VaR rate of turn are analyzed by Monte Carlo method.Furthermore, the accuracy tests are conducted on the models respectively.Risk management via nonspecific time dynamic VaR model would optimize the trading strategies.By building nonspecific time dynamic VaR model and testing the accuracy of the model, VaR model is well applied in nonspecific time dimension and makes significant application value in the risk control for the trading system. Finally, by combining optimized moving average trading model based on SVM which is the alpha model and the nonspecific time dynamic VaR model which is risk control model, a simple moving average trading system based on nonlinear method and VaR is formed. To imply nonspecific time dynamic VaR model, Wilcoxon’s rank sum test is used to compare the results before and after SVM and it is found that there is no statistical difference between the VaR values of return series generated by the trading system under the condition of confidence. After that, the moving average system with parameter optimization is modeled by dynamic VaR and solved.The results show that it is efficient to apply nonlinear method and VaR into the simple moving average trading model in order to make compound return and risk control. Meanwhile, the return profit is improved and risk is reduced.This trading system proposed above is contributed to the establishing process of Chinese financial market, especially to improve the efficiency of resources allocation. It is also a certain new concept and of realistic value. From a microscopic view, the results is helpful to the investors to behave more rationally in the trading market. On the other hand,it facilitates the perfection of market regulation and the resource allocation optimization from the macroscopic view.Combining the nonlinear methodologies withVaR method and applied the new model into the investment trading system is helpful top romote the application of nonlinear science in the investment field.Meanwhile, the building of thesimple moving average trading model based on nonlinear method and VaR also provides investors with a complete set of scientific investment method and enriching investment research techniques,which is alsoaccumulating experiences in applying program trading in Chinese stock market.