Trend Strategy Design Based On Asymmetric Bollinger Bands

Academics have argued for years that the effectiveness of the stock market has been debated for many years.Traditional financial theory holds the view that the market is effective and believes that the stock price fully reveals all available information.It is not feasible to obtain excess returns through any available information.The technical analysts believe that the company's operating conditions,policy guidance,industry conditions and other information has been reflected in the historical prices among them,by studying the historical trend of stock prices can guide the future investment and obtain excess returns,so that the market is invalid.At present,technical analysis has become an important investment analysis method in stock investment,which is widely used in all countries in the world.Therefore,the study of technical analysis has important theoretical and practical significance.Bollinger Bands is the trend class indicator put forward by the famous American stock market analyst John Brin in the eighties of last century.Based on the predecessors' banded analysis of securities prices and the related concepts of standard deviation in statistics,he designed a very simple and practical technical analysis index,which has been the most widely used trend index in banded analysis.In this paper,we use MTLAB as the programming software and select seven kinds of important stock indices both at home and abroad as the research object.We design a trend investment strategy based on asymmetric Bollinger Bands.In the traditional Bollinger Bands model,the same parameters are used for the middle rail and the upper rail and the lower rail.When the rail trend is upward,the stock price is mostly distributed in the upper half of the Bollinger Band.When the rail trend is downward,the stock price is mostly distributed in the Lower half of the line of Bollinger Band.In the uptrend,the lower rail has few reference value,and vice versa.Therefore,based on the traditional Bollinger Bands model,this paper adds two additional parameters that determine the upper and lower rails separately.The Asymmetric Bollinger Bands makes the strategy more flexible.This paper constructs a trend investment strategy based on the asymmetric Bollinger model and the moving average indicators.Firstly,using the middle track of Bollinger Bands to determine the main trend of the ups and downs of the security price,and to determine the local trend of the security price based on the position relationship between the short cycle moving average and the Bollinger Bands.Secondly,combine the relevant theories and trading principles of the Bollinger Band to determine the signal indicators,namely the opening and closing thresholds;divide the sample data of the stock index into training data and test data,and use the training data to search out the combination of excellent parameters,and then use the test data backtest the strategy results;through the analysis and comparison of strategy backtest results,found that the domestic stock index back test results are more ideal,while the foreign stock index back test results are poor;prove that the trend of the strategy is more suitable Cattle bear a clear domestic market.Finally,comparing the asymmetric Bollinger Bands investment strategy of this article with the performance indicators of the traditional Bollinger Strategy,it is found that the simulation results of the asymmetric Bollinger Lines Strategy based on the traditional Bollinger Bands improvement are more effective as a whole.The designed trend investment strategy needs improvement directions and usage suggestions.The asymmetric Bollinger Trend Investment Strategy designed in this paper not only enriches the research results of the Bollinger Theory and Trend Strategy,but also guides and optimizes real investment transactions and helps investors in highly random or non-random prices.It is of great practical significance to look for clear and reliable trading signals to avoid technological pitfalls and reduce mistakes in decision making so as to guide investors to increase risk aversion.