The Research Of Trend Following Trading Strategy Based On Moving Average

After more than 30 years of development, algorithmic trading(generalized) has been widely used now in the financial markets of Europe and America. Algorithmic trading includes the decision-making algorithms and execution algorithms. The decision-making algorithm is to solve when to buy or sell and what to buy or sell; and execution algorithm is to solve the question of how to buy or sell. This essay is a study of a typical decision algorithm strategy- trend following strategy. Trend following trading strategies have been fully studied and applied domestic and abroad, and proved its effectiveness.Firstly, the background and concepts of algorithmic trading are introduced before doing a detailed analysis of typical decision-making algorithmic trading models as groundwork for the later model design. Then, using the autocorrelation coefficients, I found the CSI 300 Index with the characteristics of its return being persistent in short to middle term while mean reversing in long term. In this essay I use the 10 years’ trading data of CSI 300 Index as a whole and separated to several phases to do back test. Technical analysis based traditional trend-following strategy is analyzed, comparing the simple moving average and exponential moving average at the effect of the application of this strategy. It is found that after-exponential-smoothed moving average is more effective than a simple moving average. The strategy is improved by adding stop-loss rules and position control rules. Trading position is in accordance with the strength of the trend which is assessed by adjusted difference between short and long moving averages. Stop-loss rule can effectively reduce losses and increase revenue; position control rule can largely decrease the risk and also reduce losses, especially for the sample interval with high return volatility. The strategy achieves more gains than buy-and-hold strategy and is verified to be stable across phases. The analysis in this essay is useful to both academic research and application with regard to trend following strategies.