發(fā)布時間：2018-04-30 14:06

  本文選題：β系數(shù) + 量化投資策略　； 參考：《重慶工商大學》2017年碩士論文

【摘要】：自從馬科維茨的投資組合理論提出到現(xiàn)在已經(jīng)有了六十多年,該理論在很多方面已經(jīng)取得了很大的進步和發(fā)展。比如:從單期研究到多期的研究,通過各種方法簡化均值-方差模型的求解過程,對風險衡量方法的修正以及對原假設條件的逐漸放松等方面。在實踐方面,投資組合理論問世以后,它開始為金融機構(gòu)和投資者所廣泛采用;金融學也開始了它在實際投資中的量化階段。本文給出了基于定量的投資組合的管理方法,該方法主要包括兩個階段,一是行業(yè)和股票優(yōu)選階段,二是對股票進行投資組合,主要是確定所選股票最優(yōu)投資權(quán)重的。上述兩個階段主要在本研究的第3章和第4章進行論述。第3章選取申銀萬國一級分類行業(yè)指數(shù)2014年6月3日至2015年9月30日這樣一個涵蓋市場上升階段和下跌階段的完整投資周期數(shù)據(jù)為樣本。通過對這些樣本數(shù)據(jù)的檢驗,得出了這些一級分類行業(yè)指數(shù)受市場態(tài)勢的影響;并計算了行業(yè)指數(shù)的上升β系數(shù)(up-marketβ,+?)和下降β系數(shù)(down-marketβ,?-)。最后,根據(jù)上升β系數(shù)和下降β系數(shù)的比值構(gòu)建了一個指標并從中選出了6個優(yōu)質(zhì)的行業(yè)。第4章引入?yún)⒖紩r間窗口長度L和持有期限窗口長度H兩個外生的時間參數(shù)構(gòu)建了動態(tài)的均值-方差投資組合模型,并利用遍歷法求解最優(yōu)時間窗口參數(shù)。然后采用了第三章優(yōu)選行業(yè)的代表性股票進行動態(tài)投資組合實證。在假定投資者風險容忍水平一定的情形下,以投資者效用最大化為衡量標準,利用MATLAB軟件程序來尋求收益最優(yōu)的外生參數(shù)及每次調(diào)整資產(chǎn)的權(quán)重。最后,利用計算所得最優(yōu)參數(shù)進行投資,并通過多項業(yè)績評價指標(包括投資期年收益率、風險調(diào)整收益率和預測收益率等)對比分析動態(tài)投資組合策略和被動投資的收益情況。結(jié)果表明本文的動態(tài)投資組合策略在風險調(diào)整后的收益率以及預測收益率等方面表現(xiàn)均優(yōu)于被動投資。總之,本文研究為投資者提供了一種定量的投資組合管理方法,具有一定的理論意義及實用價值:一方面,通過實證分析驗證了我國股市的非有效性;另一方面,為投資者如何分配各股票投資權(quán)重提供了有益的借鑒。
[Abstract]:It has been more than 60 years since Markowitz's portfolio theory was put forward. It has made great progress and development in many aspects. For example, from single-period study to multi-period study, the solution process of mean-variance model is simplified by various methods, the risk measurement method is modified, and the original assumptions are gradually relaxed. In practice, portfolio theory began to be widely used by financial institutions and investors, and finance began its quantitative stage in actual investment. In this paper, a quantitative portfolio management method is presented. The method mainly includes two stages, one is the industry and the stock selection stage, the other is the stock portfolio, which is mainly to determine the optimal investment weight of the selected stock. The above two stages are mainly discussed in chapters 3 and 4 of this study. The third chapter selects the whole investment cycle data from June 3, 2014 to September 30, 2015, which covers both the rising and falling stages of the market. Based on the test of these sample data, the influence of market situation on the industry index is obtained, and the rising 尾 coefficient of industry index is calculated by up-market 尾. And decreasing 尾 -market. Finally, according to the ratio of rising 尾 coefficient and decreasing 尾 coefficient, an index was constructed and six high quality industries were selected. In chapter 4, the dynamic mean-variance portfolio model is constructed by introducing two exogenous time parameters: the reference window length L and the holding term window length H, and the optimal time window parameters are solved by traversal method. Then we use the third chapter to select the representative stocks in the industry to carry out dynamic portfolio demonstration. Under the assumption that the level of investor risk tolerance is constant, taking the maximization of investor utility as the criterion, the MATLAB software program is used to find the optimal exogenous parameters of income and the weight of assets adjusted every time. Finally, using the calculated optimal parameters to invest, and through a number of performance evaluation indicators (including the annual rate of return on the investment period, Risk adjusted rate of return and forecast rate of return are compared to analyze the dynamic portfolio strategy and the return of passive investment. The results show that the dynamic portfolio strategy performs better than passive investment in terms of risk-adjusted return rate and prediction rate of return. In short, this paper provides a quantitative portfolio management method for investors, which has certain theoretical significance and practical value: on the one hand, it verifies the non-validity of China's stock market through empirical analysis; on the other hand, For investors how to allocate the weight of each stock investment provides a useful reference.
【學位授予單位】：重慶工商大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F224;F832.51

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本文編號：1824854