本文選題：因子分析 + 多因子模型　； 參考：《華東師范大學》2017年碩士論文

【摘要】：本文運用量化投資中的多因子模型理論架構和方法,通過非線性的因子分析方法,將提取出的因子用于選股投資,力求賺取選股收益。通過線性和非線性兩種因子分析結果和股票分層收益率的實證分析,比較兩種分析方法的效果。全文一共分五個部分進行闡述。第一部分,簡要介紹量化投資的基本概念和常用的量化選股模型,為本文的重點—多因子模型做鋪墊。第二部分,詳細介紹多因子模型的理論架構和方法,給出因子模型及其風險結構的數學表達。第三部分,回顧傳統線性因子分析理論,推導因子載荷的求法,介紹因子旋轉的方法和因子得分的求法。第四部分,引入非線性因子分析理論,著重介紹兩種因子分析在思路和邏輯上的差別,通過證明正交因子定理以及引入貢獻率的概念,完善因子分析的體系,使之可以應用到實際問題中。第五部分,對股票指標進行實證分析。首先對指標進行處理,然后分別用線性和非線性因子分析提取公共因子,根據這些因子對股票進行聚類,找出預期收益率最高的一類進行投資。最后對2014年至2015年中國滬深300成分股進行回測驗證,比較兩種分析方法的效果。
[Abstract]:In this paper, we use the theory and method of multi-factor model in quantitative investment, through nonlinear factor analysis method, to extract the factors for stock selection investment, and strive to earn stock selection income. The results of linear and nonlinear factor analysis and the empirical analysis of stock returns are compared. The full text is divided into five parts. In the first part, the basic concept of quantitative investment and the commonly used quantitative stock selection model are briefly introduced, which pave the way for the multi-factor model of this paper. In the second part, the theoretical framework and method of the multi-factor model are introduced in detail, and the mathematical expression of the factor model and its risk structure is given. In the third part, the traditional theory of linear factor analysis is reviewed, the calculation method of factor load is deduced, the method of factor rotation and the method of factor score are introduced. In the fourth part, the theory of nonlinear factor analysis is introduced, and the differences between the two kinds of factor analysis in thought and logic are introduced. By proving the orthogonal factor theorem and introducing the concept of contribution rate, the system of factor analysis is improved. So that it can be applied to practical problems. The fifth part, carries on the empirical analysis to the stock index. First, the indexes are processed, then the common factors are extracted by linear and nonlinear factor analysis, according to these factors, the stocks are clustered to find out the highest expected return rate of investment. Finally, the back test of China's Shanghai and Shenzhen 300 component stock from 2014 to 2015 is carried out to compare the results of the two analysis methods.
【學位授予單位】：華東師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F832.51;F224

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本文編號：1853457