The Research On Quantitative Timing Trading Strategy Of Stocks Based On Analysis Of Money Flow

Generally speaking,a large amount of money flows into a stock,the price of the stock will rise,and the money flows out of the stock,the price of the stock will fall.In stock investment,it is often said that "quantity precedes price".This quantity includes the quantity of money flow and the direction of money flow,collectively referred to as money flow.The calculation and determination of the money flow has always been a difficult problem in the world and there are many methods to calculate t money flow,but there is no unified and authoritative calculation standard so far.Firstly,this paper analyses the definition of money flow,analyses the impact of macro-level funds,market-level funds and transaction-level funds on stock prices,and summarizes several basic forms of money flow and stock fluctuations.Secondly,fully considering the relationship between transaction volume and price change,the index of money flow is established,which can reasonably reflect the law of money flow in the stock market.The econometric analysis shows that the money flow is the reason that affects the stock return rate in the short term.The stock return rate is positively correlated with the money flow,and the existence of the money flow is persistent,but the persistence is not strong.Thirdly,according to the index of money flow,the paper designs the strategy of quantitative timing trading of stock investment.The basic method is to calculate the average value of money flow for several days through the index of capital flow of stocks,and then determine the combination of fast and slow lines of capital flow through the adjustment of parameters.When the combination of the mean lines appears "golden crossing"(fast line breaks through slow line upward),buy and sell when "dead crossing"(fast line breaks through slow line downward).Finally,we use the daily data of 769 trading days of Shanghai 50 component stocks as samples to verify the effectiveness of the strategy.The results show that this strategy can achieve higher returns than Benchmark return and it has a better ability to avoid downside risks especially when the market is in a downturn.