The Optimization Of Program Trading Strategies

With the development of economy and the rise of financial markets, program trading has been gotten more and more attention in the domestic and international markets, it is also increasingly applied to various transactions.Program trading from the beginning of’Transfer and combination transactions" to high-frequency program trading day, has experienced for many years, and the various studies are also endless.About the program trading, the currently accepted concept of investors is that investors use computer assembly language,through the computer code,to quantify some of the factors about investors’ investment ideas and investment preferences,etc.,then form a trading strategy, so that investors can take advantage of this trading strategy, through the sale of computer automated order selection opportunity to carry out a way to deal.For program trading, whether the domestic market or the international market, program trading in recent years of development can be described by leaps and bounds.Compared with traditional trading, a bit more complex program trading achieves the automated order and timing of the sale of rational choice function, avoiding the long face of the computer to read the tape problems,as well as has a prominent upper Advantage on the timeliness and stability.Program trading strategy refers to complete the entire program trading system as a core technology exists,and it is the investors to use program trading mode kernel.From the current financial market, program trading strategies can be divided into two types,the technical indicator model types and the statistical categories model.Among them, the technical specifications for the model program trading strategies into the average transaction model,shock class index model,popular type indicator model,Bollinger class index model.By introducing the above four categories of indicators of technical analysis model,and optimize it,to ensure that program trading could void investment risks more effectively and overcome mental defect about the transaction subjective of investors generated in the transaction, etc. In the average transaction model, we select the BBI indicator, analysis the BBI indicator according to the risk appetite of investors,and modifying the weight as well as other methods to overcome its securities that are not price sensitive and other defects about BBI; In the shock category index model, this paper selects the MACD indicators, with the KDJ, avoiding some of the risks; In BOLL channel model, the BOLL indicators are selected through research on the relationship between its price and BOLL;In Popularity type indicators, the paper selects a more influential indicator, it is OBV. And through the optimization of these models, finally empirical analysis using TDX, it will be applied to each index optimization simulated trading to obtain a stable income.