The Quantitative Timing-choose Strategy Based On Hidden Markov Model

The rapid development of artificial intelligence has promoted the technological progress,making all walks of life have undergone tremendous changes,also has an important impact on financial investment.In the investment practice,quantitative investment and algorithm trading have been favored by banks,insurance,investment banks and other top institutions,and become the normal mode of operation.The fund named Huatai Borui quantitative enhanced,established in 2013,had achieved 170 percent of the return on investment by the end of 2017.Quantitative investment is being paid more and more attention by academic and practical circles because of its discipline,systematicness,timeliness and accuracy.The trend timing strategy discussed in this paper is an important part of the investment strategy.Hidden Markov model was first used in the field of speech recognition.Its theoretical basis is Markov random process,is the quantitative description of the dynamic relationship of a series of random events.The prediction object of Hidden Markov Model theory is a dynamic system of random changes.Its' prediction is based on the transition probability between states to predict the future development of the system.When it comes to Hidden Markov Model,domestic financial investment researches use it for time series analysis,have not been combined with quantitative timing strategy research.In addition,the relevant literature focuses on the research of model algorithm,ignoring the practical application of the combination of model and strategy.Therefore,this paper studies the existing quantitative trend timing strategy and hidden Markov model,and combines them to construct a quantitative trend timing strategy based on Hidden Markov Model.First of all,this paper introduces the concept of quantitative investment,a brief review of the research achievement,the characteristics of quantitative timing strategy and the existing timing strategies classified.Then,the concept and theoretical basis of Hidden Markov Model are explained.Three basic problems and related algorithms that need to be solved in Hidden Markov Model are introduced in detail.Finally,the model and strategy are combined to construct a quantitative timing strategy system based on Hidden Markov Model.At the same time,the trading data of the Shanghai Composite index,HS300 index,stock and commodity futures will be used into the model for training and simulation to verify the effectiveness of the strategy.The innovation of this paper lies in the application of Hidden Markov Model,which is widely used in physics,biology and environmental science,in the field of financial research.Hidden Markov Model has shown its excellent pattern recognition ability in other fields.In the context of quantitative investment,it is of great practical significance to introduce this model into the time series analysis of financial transaction data.More importantly,this paper combines the mathematical model with the investment strategy,which embodies the great value of applying theory to practice.