本文選題：譜風險度量 + G-H分布　； 參考：《北京化工大學》2012年碩士論文

【摘要】：在金融市場中，由于受到市場波動的影響，投資者和金融機構正面臨著更加嚴峻的金融風險。如此一來，如何準確度量市場風險，來幫助投資者及金融機構的管理者規(guī)避風險，是經濟學家們不斷探索研究的主要工作。本文選用譜風險度量模型，，引入G-H分布，來作為對金融市場風險度量的主要方法。 風險譜函數(shù)用來反應投資者對風險的厭惡程度，主要形式有三種，分別為指數(shù)型、冪型和雙曲型風險譜函數(shù)。本文分別采用指數(shù)型和雙曲型風險譜函數(shù)，選用G-H分布，結合譜風險度量方法，得到投資組合度量模型，并分別利用復化梯形法得到離散形式。 對單支股票的風險度量分析，本文選取康美藥業(yè)收益率序列作為樣本數(shù)據(jù)，分別采用分位點估計法和矩估計法做G-H分布的參數(shù)估計，并分別與基于正態(tài)分布的譜風險度量模型進行對比，得到結論：選用G-H分布，并采用矩估計法估計參數(shù)，擬合效果最優(yōu)。選用Kupiec失敗率檢驗法，在一定置信水平下，利用樣本內數(shù)據(jù)做譜風險度量分析，并與樣本外數(shù)據(jù)進行比較，得到預測失敗個數(shù)，得到結論。 對于投資組合的風險度量分析，本文選取上海家化等四支證券收益率序列，分別采用指數(shù)型和雙曲型風險譜函數(shù)，得到投資組合風險度量模型，得到結論：隨著期望收益率的增加或絕對風險厭惡因子的增加，譜風險度量值也會相應增加，并且分配權重會向平均收益率高的證券轉移。 運用copula函數(shù)來度量不同證券之間相關性。選取萬科A和海螺水泥兩支證券，選取適當copula函數(shù)，建立投資組合模型。實證結果表明，由于考慮了證券收益的尾部相關性，可以得到更加貼近市場實際情況的風險度量結果。
[Abstract]:In the financial market, investors and financial institutions are facing more severe financial risks due to the influence of market fluctuations. Thus, how to measure the market risk accurately and help the investors and the managers of the financial institutions to avoid risk is the main work of the economists. This paper selects the spectrum risk measurement. The G-H distribution is used as the main method to measure the risk of financial market.
The risk spectrum function is used to reflect the degree of investor aversion to risk. There are three main forms, which are exponential type, power type and hyperbolic risk spectrum function. This paper uses exponential and hyperbolic risk spectrum functions, selects G-H distribution and combines spectral risk measurement method to obtain portfolio measurement model, and uses complex trapezoid method respectively. To the discrete form.
In the analysis of the risk measurement of single stock, this paper selects the recovery sequence of Kangmei pharmaceutical industry as the sample data, uses the point estimation method and the moment estimation method to estimate the parameters of the G-H distribution, and compares it with the spectral risk measurement model based on the normal distribution, and obtains the conclusion: the G-H distribution is selected and the moment estimation method is used to estimate the parameters. The fitting effect is optimal. The Kupiec failure rate test method is selected. Under certain confidence level, the spectrum risk measurement is analyzed by using the data in the sample, and compared with the data from the sample, the number of failure prediction is obtained and the conclusion is obtained.
For the risk measurement analysis of portfolio, this paper selects four stock return sequences, such as Shanghai domestication, and uses exponential and hyperbolic risk spectrum functions to get the portfolio risk measurement model. The conclusion is that as the expected return rate increases or the absolute risk aversion factor increases, the spectral risk measurement will also increase accordingly. And the distribution weights will be transferred to the securities with high average returns.
The copula function is used to measure the correlation between different securities. Two securities of Vanke A and conch cement are selected and appropriate Copula Functions are selected to establish an investment portfolio model. The empirical results show that the risk measurement results which are closer to the actual situation of the market can be obtained because of the tail correlation of stock returns.

【學位授予單位】：北京化工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F832.51

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