A Study On The Investment Strategy Of Moving Average

The effectiveness of financial markets has been debated for many years in academic circles. The traditional financial theory holds the views that markets are efficient and stock prices can fully reflect the all available information, so any available information can bring the excess returns. While technical analysis experts consider that operational status, policy orientation and profession situation has reacted in the stock price. The price of the stock price movements are always repeated in the history of the trend, the market is not valid. Moving average investment theory was proposed by the famous American investment expert E. Granville Joseph in the middle of twentieth Century, which is one of the most widely used technical indexes in today's application. Moving average is a cost concept that represents the average cost of the stock in the past period of time. Its feature is to be able to track trends, good stability, can contribute to the decline, but there is a lag at the same time. Moving average can help traders identify existing trends, and then determine the trend of the trend and the trend of the reversal of the trend of the transition. Stand on the angle of technical analysis, this paper aims to further analyses and validate the effectiveness of China's stock market by introducing new variables, at the same time puts up with the method to obtain excess returns and test it.Moving Average is a curve that is connected to the average value of the stock closing price or the closing point of the index in a certain time period. It shows the historical trend of the stock price also reflects the trend of future changes in the stock price. It is also an important indicator in the Dow index analysis theory. Easy to learn and easy to use, moving average strategy has been adopted by most investors the same to our country. Those investors are the main force of the market structure in our country. The application of moving average strategy in China began from the date of the birth of the stock market, most of the previous studies tend to study the effectiveness of strategies. And less investment strategy based on Moving average. On the other hand, the research on this aspect of domestic scholars in time before 2010 are relatively old. The theoretical significance of this paper lies in:(1) the predecessor research rarely in the moving average strategy by introducing a buffer zone to optimize the moving average line strategy. This study can enrich the moving average theory research. Previous time range for the moving average strategy study relatively early, mostly in 2010 before the historical data analysis, due to the technical analysis has a certain amount of time effectiveness, within a period of time effective strategy after a period of time may be on the failure. This paper uses the research on the strategy from 2007 to 2016, on the current A stock market moving average strategy research is more timely. (3) previous studies focused on the Shanghai market, but for the small board and gem Shenzhen market research is not much. And this paper, respectively, on behalf of the Shanghai Composite Index, SME ETF and GEM ETF, more enriched the breadth of research. The practical significance of this study lies in, with the continuous reform of A stock market, transaction rules change, emotion and external market market impact on the stock market and Chinese stock market, the uncertainty risk of long-term trading is increasing, the proportion of short-term trading behavior is more and more large. The short-term trend of stock price forecasts are increasingly subject to the attention of ordinary investors and professional institutions. Short term trading is mainly to technical analysis, moving average strategy as an important method of the analytical technique, research results to guide investors to raise revenue risk averse, regulators to enrich and improve supervision and have strong practical significance.On this basis, this paper proposes a moving average based investment strategy for the Chinese stock market. The average holding period of fixed strategy refers to buy bonds when short-term line above long-term average by a certain percentage and sell it after holding a fixed time. This strategy is the simpler one between the above two strategies, which only needs to buy bonds by signal and hold to maturity to sell. Compared with rapidly changing market, this strategy lacks flexibility. More flexible than the former, holding period of fixed moving average line strategy means buy bonds when short-term line above long-term average by X percentage and sell it in reversal cases. But it is not flexible enough since the same percentage applied in an information dissymmetry market, which is clearly not the best choice.The idea of introducing buffer space to the moving average is derived from the percentage of transactions in moving average strategy with variable holding period. Adding percentage of transactions is to avoid the overly frequent crosses of the long-term and short-term moving average. Actually, the parameter of transactions percentage serves as the introduction of a buffer space at the point of sale of the moving average. The long and short term moving average in the buffer space is ignored as a false signal, and the cross signal over the buffer space is used as a real transaction signal. The train of this paper is that first, try to find the better sales percentage parameter combination by the moving average strategy in the history period, then make the second selection to form the best combination of strategies according to the relationship between income and buffer space.To fully verify the effectiveness of the A share market, I select Shanghai Composite Index 50ETF, small and medium board representative of the SME board and the gem fund as the object of my research. Firstly, according to the theory of momentum theory, the method of computer simulation is used to choose the combination of top ten groups of buying parameters and selling parameters, which is named as the advantage combination. Then, the explanatory variables buffer space, namely, the other control variables and the return of the strategy are analyzed especially the impact of buffer space on the policy return. Finally, judge the effect of the buffer space on strategic income according to the coefficient of buffer space. The higher the coefficient is, the higher the strategy of the regular buffer space is. Then make second screening among the advantage combinations and select the maximum buy and sell parameters of the first three combinations as the final strategy.The contents of this article:The first chapter is introduction which mainly introduces the background, purpose and significance of the paper. And the ideas and innovation points of this research are briefly introduced.The second chapter reviews the relevant theories and empirical studies on the efficient market hypothesis, theories and empirical researches on the effective market and moving average theory. The object of this study is Chinese stock market and the vehicle is moving average strategy.The third chapter illustrates the average holding period variable strategy optimization. This chapter mainly contains three parts. Firstly, The moving average theory and its characteristics, basic rules and important assumptions. Secondly, The classification of moving average strategy is listed. Since this study is based on the average holding period variable, relevant strategies are explained. After analysis, raises optimization and improvement measures. Thirdly, Based on the analysis of the above part, optimized strategy of the average holding period variable is proposed.The fourth chapter is empirical study of the strategy. To test the actual situation of the optimization of the holding period of variable average strategy in A share market. This chapter will be divided into four parts to carry out the test strategy. First, search for a combination of advantages in the history period. Second, introduce the buffer space and assesses the impact on strategic income. Third, carries on the second screening according to the relationship between buffer space and benefits and determines the ultimately strategy combination. Last, test the strategy combination in detection period. The main steps are as follow:Sample data preprocessing. First, determine study time and divide time period into the historical period and the verification period. Then, determine the average portfolio of the study. Finally, value the buying percentage a and selling percentage (3.Selection of dominant combination. Pick out the combination of top 10 returns (?,?) as the dominant group by simulative method in the historical period. Calculate corresponding combination (?,?) to each buffer space. Together with several other control variables, take buffer space as explanatory variable and establish the regression equation, exploring the influence of these variables on the revenue strategy.The final strategy of portfolio selection. Make the second screening among combination of advantages according to the coefficient in regression equation of buffer space. When the buffer space coefficient is positive, the first three combinations of the ?+? are selected as strategy combination; on the contrary when the coefficient is negative select the last three combinations.Test of strategy combination. The final strategy combination is brought into the inspection period to carry on the empirical test. Then, verify the benefits difference of strategy combination and hold to maturity by t test.In the fifth chapter, the data is back-tested according to the method of the fourth chapter. Carry out multiple linear regressions and obtain the regression equation. Based on the regression equation and related theory, the empirical results are analyzed and explained.The sixth chapter is the research conclusion and prospect part. Based on the technical indicators, trading strategy can help investors find a statistically significant part in highly fluctuations market, which also assist to overcome errors by investors' mentality change and obtain long-term stable returns. However, optimal parameter is difficult to determine.The major originalities of this paper:1. Method innovation. Buffer space is introduced in variable amount of holding period moving average line strategy, which improve application of the moving average strategy and offer empirical basis for optimization of the strategy.2. Content innovation. The samples and index used in this article are representative in the current A share market, including Shanghai Composite Index 50ETF, small and medium board representative of the SME board and the gem fund. Besides, the research results more comprehensive since index funds are taken into account.3. Long time period. The transaction data is selected from January 2007 to January 2016 which contains two Bull and Bear Market and a long shock.Frequent crosses of moving average lines reflect many false trading signals, reducing the strategic gains. The introduction of buffer space is a valid way to avoid above problems. Based on the previous theory, some improvement and innovation are made in moving average theory in this paper, but there are still some contents need to be optimized.