【摘要】：在我國股票市場，股價常常在一定時期內發(fā)生劇烈波動，給個人投資者帶來不可預料的損失。Markowitz投資組合理論奠定了現(xiàn)代投資組合理論的基礎，然而投資組合只能有效降低非系統(tǒng)風險，對系統(tǒng)風險的規(guī)避卻無能為力。本論文以中小企業(yè)板為研究對象，對股票價格波動過程中低點、高點的出現(xiàn)及出現(xiàn)的規(guī)律進行了系統(tǒng)分析和深入研究。首先在對Markowitz投資組合理論和股票價格波動理論的研究基礎上，以不同時長股票階段成本作為參考值，在前提條件約束下，設計了一系列股票價格波動過程中階段周期低點、高點回歸預測模型。然后采用點估計、區(qū)間估計等對符合采樣條件的樣本進行檢驗和比較，驗證不同模型對價格極值進行預測的真實性并得到最優(yōu)模型。最后應用該模型進行股票投資的模擬仿真操作，，對股票選擇和投資組合管理進行對策研究，并分析了這種操作對系統(tǒng)風險的規(guī)避能力。在投資組合基礎上應用該模型進行股票處理的對策研究，對個人投資者有很好的指導意義。本論文的主要研究內容概括如下： 1．考慮到Markowitz投資組合理論在我國的實用性和它在系統(tǒng)風險降低方面的限制性，提出了基于股票價格波動問題的階段周期低點、高點回歸模型。 2．以中小企業(yè)板為背景，設計六種基于不同解釋變量的階段周期回歸預測分析模型。通過t檢驗、F檢驗、擬合優(yōu)度分析和殘差分析等各種統(tǒng)計檢驗初步確定有效模型，然后針對多重共線性問題對階段周期多元回歸預測模型進行修正。 3．應用不同預測方式，使用歷史數(shù)據(jù)對不同模型有效性和精確性進行驗證和分析，并得出修正后的階段周期多元回歸預測模型擬合效果最優(yōu)的結論。 4．針對最優(yōu)的階段周期回歸預測模型，提出三種不同模式的投資操作來進行投資組合的實證研究，包括基于階段周期回歸預測模型的投資、不遵循建議的無作為投資和理想化的指數(shù)化投資。實證研究結果顯示，利用階段周期低點、高點回歸預測模型進行選股和投資操作的投資組合，收益率遠高于其他模式，并且能有效地規(guī)避系統(tǒng)風險。在基于階段周期回歸預測模型的操作過程中，對股票的選購和拋售提出對策建議。
[Abstract]:In the stock market of our country, the stock price often fluctuates violently in a certain period, which brings unexpected losses to individual investors. Markowitz portfolio theory has laid the foundation of modern portfolio theory. However, the portfolio can effectively reduce the non-system risk, but can not avoid the system risk. This paper takes the SME board as the research object, carries on the systematic analysis and the thorough research to the stock price fluctuation process low point, the high point appearance and the appearance rule. Firstly, based on the research of Markowitz portfolio theory and stock price fluctuation theory, taking the stage cost of stock with different time and length as reference value, a series of periodic low points in the process of stock price fluctuation are designed under the constraints of preconditions. High point regression prediction model. Then point estimation and interval estimation are used to test and compare the samples that meet the sampling conditions to verify the authenticity of price extremum prediction by different models and to obtain the optimal model. Finally, the model is used to simulate and simulate the stock investment, and the countermeasures of stock selection and portfolio management are studied, and the ability of this operation to avoid the system risk is analyzed. On the basis of investment portfolio, the research on the countermeasures of stock processing based on this model has a good guiding significance for individual investors. The main research contents of this thesis are summarized as follows: 1. Considering the practicability of Markowitz portfolio theory in our country and its limitation in reducing system risk, a phase cycle low based on stock price volatility is proposed. High point regression model. 2. Taking the SME board as the background, six models of stage cycle regression analysis based on different explanatory variables are designed. Through t test, F test, goodness of fit analysis, residual analysis and other statistical tests, the effective model is preliminarily determined, and then the stage periodic multivariate regression prediction model is modified for multi-multiple collinear problems. 3. The validity and accuracy of different models are verified and analyzed by using different forecasting methods and historical data, and the conclusion that the fitting effect of the modified multivariate regression prediction model is optimal is obtained. 4. In view of the optimal stage cycle regression forecasting model, three different investment operations are proposed to carry out portfolio empirical research, including investment based on the stage cycle regression prediction model. Do not follow recommendations for inaction and idealized indexed investments. The empirical results show that the portfolio of stock selection and investment operation by using stage cycle low and high point regression forecasting model is much higher than other models and can effectively avoid systemic risk. In the course of the operation of the forecasting model based on the stage cycle regression, the paper puts forward some countermeasures and suggestions for the stock selection and selling.
【學位授予單位】：天津理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F832.51;F224

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