Application Research Of Programmatic Trading Strategy Based On O-U Model

In the 1970s,with the development of mathematical statistics theory and computer network technology,programmatic transactions were born in the United States.Based on the mature financial markets in Europe and America,programmatic transactions have developed rapidly.Due to the late start of China's securities and futures markets,the short development time makes the development of programmatic trading not in a good market development environment.Therefore,there is still a certain gap between the development of programmatic trading and foreign countries.But on the other hand,it also shows that the development space of China's programmatic trading is very broad.In recent years,the development of China's financial market mechanism has been continuously improved,the pattern of opening up the capital market has gradually opened up,and the overall transaction scale of the capital market has been increasing.Especially in the futures market,with a sound market trading mechanism and a wealth of trading varieties,these favorable conditions have paved the way for the development of programmatic trading.The steady development of programmatic trading,in addition to the need to constantly create a good market development environment,on the other hand,it is necessary to continuously introduce rich and effective programmatic trading strategies,while promoting the development of programmatic trading,it also provides a kind of investor An effective investment method.In recent years,economic theory and mathematical statistics have achieved remarkable development results,which pointed out the direction of the development of programmatic trading,making the establishment of trading strategies and models no longer limited to traditional historical data analysis,technical analysis,etc.Data and methods are collected from mathematics,statistics,physics,and even bionics and psychology.These trading strategies have become more and more mature through in-depth research by many scholars,and have more prominent advantages than traditional individual subjective transactions in grasping market opportunities.This paper follows the development direction of programmatic trading.From the practical application,this paper attempts to transform the O-U model in the statistical arbitrage model into a programmatic trading strategy.Firstly,it introduces the theory of O-U arbitrage model and sample data selection and testing,and finds the O-U model.It has arbitrage in China's soybean oil and palm oil futures.So choose the main price series of soybean oil and palm oil to construct sample data.The sample data range is from October 8,2013 to January 10,2019,a total of 1289,of which the first 600 are used as sample data to build the O-U model.689 data for trading strategy is an extrapolation test.Through the use of cultural win-win program trading platform,the O-U arbitrage model built in the sample is transformed into a static and dynamic programmatic trading strategy.Finally,the strategy is used in the sample and the extrapolation test to verify that the strategy arbitrage in China's agricultural futures.Feasibility.Empirical research has found that both static programmatic trading strategies and dynamic program trading strategies have their own characteristics.The static programmatic trading strategy shows a good arbitrage effect under the stable fluctuation of the spread series.At this time,the spread sequence can fluctuate within the trading interval,and the number of transactions and the income generated by the static programmatic trading strategy in the case of the violent fluctuation of the spread series It is not stable,so the stability of static programmatic trading strategy arbitrage is weak.In contrast,the dynamic program trading strategy is more average and stable due to the dynamic adjustment of the trading signal following the spread sequence,the average position period is reduced,and the position risk is reduced.It can be said that the dynamic program trading strategy is a more stable arbitrage strategy.