本文選題：凈資產(chǎn)收益率 + 波動率　； 參考：《成都理工大學》2014年碩士論文

【摘要】：凈資產(chǎn)收益率是一個綜合性極強的財務指標，直接反應了一個公司的盈利能力，是現(xiàn)代成熟市場中廣大投資者最為倚重的參考指標，在投資領域一直備受各界關注。本文借助已有研究成果，選取44家中國上市公司1994年--2013年凈資產(chǎn)收益率數(shù)據(jù)為研究對象，對凈資產(chǎn)收益率波動情況進行了實證研究，并分析了凈資產(chǎn)收益率波動率與現(xiàn)金流相互之間的動態(tài)關系，為投資者、經(jīng)營管理者以及后續(xù)研究提供實證經(jīng)驗和建議。 本文主要研究內(nèi)容有： （1）引言。該部分首先闡述了本文的研究背景、意義，包括問題的提出，并明確界定了相關概念，然后介紹了本文的研究思路及方法，最后是本文的創(chuàng)新點及不足。 （2）文獻綜述。該部分主要是對國內(nèi)外關于凈資產(chǎn)收益率、波動率模型以及向量自回歸模型的文獻的研究，并歸納其主要觀點和研究方法，為本文實證研究指明方向。 （3）波動率模型概述。該部分詳細介紹了各種廣泛應用于金融領域的主流波動率模型，并通過分析比較，評選出最適合本文建模的類型。 （4）凈資產(chǎn)收益率波動率實證分析。該部分建立了多個波動率模型，并對其進行綜合評價，找出相對較優(yōu)的模型，用以凈資產(chǎn)收益率波動率預測以及檢驗凈資產(chǎn)收益率波動率中的不對稱性影響。 （5）凈資產(chǎn)收益率波動率與現(xiàn)金流之間的動態(tài)關系的實證研究。該部分先是以凈資產(chǎn)收益率波動率和現(xiàn)金流為變量建立向量自回歸模型，并借助Granger因果關系分析法和脈沖響應函數(shù)法進行結(jié)構(gòu)分析；再以凈資產(chǎn)收益率和現(xiàn)金流為變量建立向量自回歸模型，并借助方差分解進行結(jié)構(gòu)分析。 （6）結(jié)論。該部分對本文所做研究做出總結(jié)，并對存在的問題進行說明，最后指出未來研究方向。 本文首先通過文獻比較以及理論演繹，得出結(jié)論：GARCH模型對金融數(shù)據(jù)時間序列的擬合效果和預測能力較好，且預測期限越短預測能力越好；EGARCH模型在捕捉波動率中的非對稱性影響中表現(xiàn)較好；已實現(xiàn)波動率對高頻交易數(shù)據(jù)的預測能力較好。本文借助GARCH模型和EGARCH（1，1）模型，以及另外幾種基本的GARCH擴展模型--GARCH-M模型、TGARCH模型和PGARCH模型來實證分析凈資產(chǎn)收益率波動情況，結(jié)果表明：GARCH（1，1）模型對中國上市公司凈資產(chǎn)收益率的擬合效果和預測能力相對較好，，EGARCH（1，1）模型證實了中國上市公司凈資產(chǎn)收益率波動率中存在較為顯著的非對稱性影響。 關于凈資產(chǎn)收益率波動率與現(xiàn)金流之間的相互關系的實證研究。本文先是以凈資產(chǎn)收益率波動率和現(xiàn)金流為變量建立VAR模型，并借助Granger因果關系分析法和脈沖響應函數(shù)分析法進行結(jié)構(gòu)化分析，結(jié)論顯示：凈資產(chǎn)收益率波動率與現(xiàn)金流之間存在雙向的Granger因果關系，即二者互為對方的Granger原因；凈資產(chǎn)收益率波動率受自身殘差沖擊的影響大于受現(xiàn)金流殘差的影響，且受自身影響時響應更為迅速，同時，現(xiàn)金流受自身殘差沖擊影響大于受凈資產(chǎn)收益率波動率的殘差影響。其次以凈資產(chǎn)收益率和現(xiàn)金流為變量建立VAR模型，并利用方差分解進行結(jié)構(gòu)化分析，結(jié)論顯示：凈資產(chǎn)收益率波動率變動由自身殘差所導致的比例遠大于由現(xiàn)金流殘差所導致的比例，同樣現(xiàn)金流方差變動由自身殘差貢獻的比例也更大，這種貢獻比例在沖擊產(chǎn)生時會發(fā)生適當?shù)淖兓�，并在未來某期保持穩(wěn)定。
[Abstract]:Net asset yield is a comprehensive financial index, which directly reflects the profitability of a company. It is the most important reference index for the majority of investors in the modern mature market. In the field of investment, all walks of life have been paid attention to. In this paper, the net assets income of 44 Chinese listed companies in 1994 is selected with the help of the existing research results. The rate data is the research object, the fluctuation of net asset returns is empirically studied, and the dynamic relationship between the volatility of net assets yield and the cash flow is analyzed. The empirical experience and suggestions are provided for the investors, managers and follow-up research.
The main contents of this paper are as follows:
(1) introduction. This part first expounds the background and significance of this paper, including the proposal of the problem, and clearly defines the relevant concepts, and then introduces the research ideas and methods of this article, and finally is the innovation and deficiency of this article.
(2) literature review. This part mainly studies the literature on net asset returns, volatility model and vector autoregressive model, and sums up its main viewpoints and research methods, which indicates the direction of the empirical study.
(3) an overview of the volatility model. This section introduces a variety of mainstream volatility models widely used in the financial field, and selects the most suitable models for this model through analysis and comparison.
(4) an empirical analysis of the volatility of net asset returns. This part sets up multiple volatility models and makes a comprehensive evaluation to find out a relatively superior model, which is used to predict the volatility of net asset returns and to test the asymmetry in the volatility of net asset returns.
(5) an empirical study of the dynamic relationship between the volatility of net asset returns and the cash flow. This part first establishes a vector autoregressive model with the volatility of net asset returns and cash flow as a variable, and uses the Granger causality analysis and impulse response function to analyze the structure, and then changes in the net assets yield and cash flow. Vector auto regression model is established and variance analysis is used for structural analysis.
(6) conclusion. This part summarizes the research done in this paper, explains the existing problems, and points out the future research direction.
Through literature comparison and theoretical deduction, this paper draws a conclusion that the GARCH model is better for the fitting effect and prediction ability of the time series of financial data, and the better the prediction time limit is, the better the EGARCH model is in the unsymmetry effect in the capture of the volatility; it has realized the preview of the volatility rate to the high frequency transaction data. With the help of GARCH model and EGARCH (1,1) model, and several other basic GARCH expansion model --GARCH-M models, TGARCH model and PGARCH model, this paper empirically analyses the fluctuation of net asset returns. The results show that the fitting effect and prediction ability of GARCH (1,1) model to the net asset returns of Chinese listed companies are relative. The EGARCH (1,1) model confirms that there is a significant asymmetric effect in the volatility of net asset yield in China's listed companies.
An empirical study on the relationship between the volatility of net assets yield and cash flow is studied in this paper. In this paper, the VAR model is established with the volatility of net asset returns and the cash flow as variables, and the structural analysis is carried out by means of Granger causality analysis and impulse response function analysis. There is a two-way Granger causality between the gold flow, that is, the two parties are each other's Granger reasons, and the volatility of the net asset returns is more affected by the impact of their own residual impact than the residual of the cash flow, and the response is more rapid when they are affected by themselves. At the same time, the impact of the cash flow on its own residual impact is greater than the volatility of the net assets. Secondly, the VAR model is set up with the net asset returns and cash flow as variables, and the structural analysis is carried out by variance decomposition. The conclusion shows that the ratio of volatility of net assets yield fluctuation is far greater than that caused by the residual of cash flow, and the change of the variance of cash flow is contributed by its own residuals. The ratio is also greater, and this contribution ratio will change appropriately when the impact arises, and will remain stable in the future.
【學位授予單位】：成都理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F224;F832.51

【參考文獻】

相關期刊論文 前10條

1 王士偉;;經(jīng)理人持股對公司凈資產(chǎn)收益率影響的實證分析[J];財會通訊;2010年03期

2 華仁海,丁秀玲;我國股票市場收益、交易量、波動性動態(tài)關系的實證分析[J];財貿(mào)經(jīng)濟;2003年12期

3 李付軍,達慶利;中國股市量價波動性關系的實證分析[J];東南大學學報(自然科學版);2005年02期

4 張永東,何榮天;深圳股市波動性與成交量關系的實證分析[J];系統(tǒng)工程;2002年03期

5 王春峰,張慶翠,李剛;中國股票市場收益的長期記憶性研究[J];系統(tǒng)工程;2003年01期

6 葉舟,李忠民,葉楠;期貨市場交易量與收益率及其波動關系的實證研究——ARMA—EGARCH—M模型的應用[J];系統(tǒng)工程;2005年04期

7 戴毓;周德群;;我國燃料油期貨收益、交易量關系的實證研究[J];系統(tǒng)工程;2008年07期

8 周少甫,陳千里;中國股市收益波動的實證研究[J];華中科技大學學報(自然科學版);2002年09期

9 趙留彥,王一鳴;滬深股市交易量與收益率及其波動的相關性:來自實證分析的證據(jù)[J];經(jīng)濟科學;2003年02期

10 陸蓉;徐龍炳;;中國股票市場對政策信息的不平衡性反應研究[J];經(jīng)濟學(季刊);2004年01期

本文編號：2042557