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  本文關鍵詞： 可轉換債券 GARCH族模型 VaR　出處：《首都經(jīng)濟貿(mào)易大學》2017年碩士論文　論文類型：學位論文

【摘要】：可轉換公司債券以其兼具債性和股性的特殊結構優(yōu)勢越來越受到投資者歡迎,“向下債券保底,向上收益可期”的美譽也被市場中絕大多數(shù)的投資者所認可。然而,這種特殊的結構也使得可轉債面臨諸多復雜的風險因素,這些風險相互影響進而使得可轉債的風險度量工作難度加大�；�于此,本文以我國可轉債市場為研究對象,利用市場的日交易數(shù)據(jù)和數(shù)學模型探索我國可轉債市場的風險度量模型,在此基礎上試圖探尋我國可轉債市場的總體風險水平,并對可轉債和可交換債的風險特點進行研究。本論文共分為六章,前兩章在介紹本文研究背景和意義的基礎上利用收集到的數(shù)據(jù)對我國可轉債的一級和二級市場特點進行總結,分析了可轉債投資所面臨的復雜投資風險并對重點風險進行重點介紹,明確了可轉債風險度量工作的重要意義。第三章引入VaR模型,對VaR的不同計算方法進行綜述并最終決定利用參數(shù)法來測度我國可轉債的風險水平。同時引入基于不同分布的GARCH族模型,以更加精確的模擬可轉債市場波動路徑。第四章以我國中證轉債指數(shù)2004年1月2日至2016年12月30日之間共計3158交易日的收盤數(shù)據(jù)為樣本,在數(shù)據(jù)統(tǒng)計檢驗的基礎上利用基于GARCH族模型的參數(shù)法測度VaR,并進行回測檢驗。最終發(fā)現(xiàn)基于t分布下GARCH族模型均會對市場風險高估,基于正態(tài)分布和GED分布下三種模型計算結果相近,除GED分布下EGARCH(2,2)模型的預測結果略高于5%之外,其他模型均能夠較好的預測中證轉債的市場風險。其中,從風險控制與管理角度,GED分布下的TGARCH模型預測效果最優(yōu),能夠達到最優(yōu)的的風險預測效果。第五章利用兩組相同評級的可轉債和可交換債數(shù)據(jù)嘗試分析二者風險水平差異,實證結果證明可轉債的總體風險水平要小于可交換債,因此投資可交換債更要對風險進行嚴格管控。最后在全文的研究基礎上,本文進行系統(tǒng)總結并提出文章研究的不足之處。
[Abstract]:Convertible corporate bonds are becoming more and more popular among investors because of their special structural advantages of both debt and stock. The reputation of "keeping the bottom down and earning up" is also recognized by the vast majority of investors in the market. This special structure also makes convertible bonds face a lot of complex risk factors, which influence each other and make it more difficult to measure the risks of convertible bonds. Based on this, this paper takes China's convertible bond market as the research object. Based on the daily transaction data and mathematical model of the market, the paper explores the risk measurement model of China's convertible bond market, and then attempts to explore the overall risk level of China's convertible bond market. This paper is divided into six chapters. The first two chapters summarize the characteristics of the primary and secondary markets of China's convertible bonds on the basis of the background and significance of the research. This paper analyzes the complex investment risks faced by convertible bond investment, introduces the key risks, and clarifies the significance of the risk measurement of convertible bonds. Chapter three introduces the VaR model. This paper summarizes the different calculation methods of VaR and finally decides to use the parameter method to measure the risk level of convertible bonds in China. At the same time, the GARCH family model based on different distributions is introduced. Using a more accurate simulation of the volatility path in the convertible bond market. Chapter 4th is based on the closing data of China's China Securities Exchange Index from January 2nd 2004 to December 30th 2016 for a total of 3,158 trading days. On the basis of statistical test of data, the parameter method based on GARCH family model is used to measure VaR, and the back test is carried out. Finally, it is found that the GARCH family model based on t distribution will overestimate the market risk. Based on normal distribution and GED distribution, the calculation results of the three models are similar. Except for the GED distribution, the prediction results of EGARCHX 2 + 2) model are higher than 5%, and all the other models can better predict the market risk of securities to bonds. From the point of view of risk control and management, the TGARCH model under GED distribution has the best prediction effect and can achieve the optimal risk forecasting effect. Chapter 5th tries to analyze the difference of risk level between the two groups of convertible and exchangeable debt data with the same rating. The empirical results show that the overall risk level of convertible bonds is lower than that of exchangeable bonds, so the investment convertible bonds should be strictly controlled. Finally, on the basis of the research of the full text, this paper makes a systematic summary and puts forward the deficiencies of this paper.
【學位授予單位】：首都經(jīng)濟貿(mào)易大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F832.51

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本文編號：1496561