【摘要】：由于經(jīng)濟(jì)結(jié)構(gòu)轉(zhuǎn)型,金融市場(chǎng)波動(dòng)日趨激烈,想要獲得高額收益,意味著承擔(dān)更大的風(fēng)險(xiǎn)。組合投資規(guī)避的是非系統(tǒng)性風(fēng)險(xiǎn),股指期貨可以規(guī)避系統(tǒng)性風(fēng)險(xiǎn)。對(duì)沖交易最大限度的控制了股票市場(chǎng)的風(fēng)險(xiǎn)�，F(xiàn)在的市場(chǎng)逐步邁入對(duì)沖交易時(shí)代,但由于期貨市場(chǎng)套期保值企業(yè)較少,更多的是投機(jī)散戶,導(dǎo)致期貨市場(chǎng)的發(fā)展受限。再加上交易系統(tǒng)數(shù)據(jù)支持不夠完善,且國(guó)內(nèi)量化基金無法進(jìn)行瞬間利差交易,單純的對(duì)沖交易存在著較大的風(fēng)險(xiǎn)性。市場(chǎng)結(jié)構(gòu)相對(duì)不穩(wěn)定,受股票市場(chǎng)和期貨市場(chǎng)各自波動(dòng)的影響也給對(duì)沖交易帶來了 一定的風(fēng)險(xiǎn)性。因此建立有效的金融模型,對(duì)對(duì)沖交易的波動(dòng)性研究尤其重要。文章把對(duì)沖交易的股指和期指做為組合分析來研究。通過對(duì)收益序列的統(tǒng)計(jì)檢驗(yàn)分析,應(yīng)用GARCH-EVT-Copula模型研究對(duì)沖交易的波動(dòng)性。文章不僅對(duì)模型的定義給予清晰的介紹,而且針對(duì)模型的特性,對(duì)模型的實(shí)際應(yīng)用給予了側(cè)重研究和部分改進(jìn)。文章通過對(duì)波動(dòng)性定量建模,將有效解釋單一資產(chǎn)分布的條件異方差模型和注重極端風(fēng)險(xiǎn)的EVT理論結(jié)合構(gòu)建股指和期指的邊緣分布。先通過GARCH過程得到標(biāo)準(zhǔn)化殘差序列。然后應(yīng)用EVT理論,對(duì)殘差序列上下尾部進(jìn)行擬合,中間部分創(chuàng)新選用t-分布進(jìn)行擬合。再應(yīng)用靈活的二元函數(shù)連接邊緣分布,構(gòu)造聯(lián)合分布。最后,通過t-Copula過程的參數(shù)生成模擬收益率序列,估計(jì)了對(duì)沖風(fēng)險(xiǎn)VaR值。通過返回檢驗(yàn),對(duì)模型的有效性進(jìn)行了分析。通過對(duì)數(shù)據(jù)的分析和統(tǒng)計(jì)檢驗(yàn),應(yīng)用改進(jìn)的GARCH+EVT+tCopula模型估計(jì)對(duì)沖交易的在值風(fēng)險(xiǎn)VaR。估計(jì)得到在顯著水平0.1和0.05的情況下的VaR值。并做了返回檢驗(yàn)和相關(guān)的模型檢驗(yàn),得出GARCH+EVT+tCopula模型能有效評(píng)估對(duì)沖交易的風(fēng)險(xiǎn)。此外,文章還選用其他三種相關(guān)模型來在相同的顯著水平下,對(duì)VaR進(jìn)行估計(jì),用來對(duì)比改進(jìn)處理后的GARCH+EVT+tCopula模型的擬合效果。結(jié)果證實(shí)了,通過EVT擬合尾部后EVT更好的把控了極端風(fēng)險(xiǎn)。GARCH-EVT-Copula模型擬合的效果更接近于實(shí)際,為對(duì)沖交易分析提供了較為有效的模型。
[Abstract]:Due to the structural transformation of the economy, financial market volatility is becoming increasingly fierce, to achieve high returns, means to take on greater risk. Portfolio to avoid non-systemic risk, stock index futures can avoid systemic risk. Hedge trading maximizes the risk of the stock market. Now the market has gradually entered the era of hedging, but because of the futures market hedging enterprises are fewer, more speculative retail investors, resulting in the development of the futures market is limited. In addition, the trading system data support is not perfect, and the domestic quantitative funds can not carry out the instantaneous interest rate difference trading, the pure hedge trading has a greater risk. The market structure is relatively unstable, which is influenced by the fluctuation of stock market and futures market. Therefore, it is very important to establish an effective financial model to study the volatility of hedging transactions. This paper studies the index and index of hedge trading as a combination analysis. Based on the statistical analysis of return series, the volatility of hedge trades is studied by using GARCH-EVT-Copula model. This paper not only gives a clear introduction to the definition of the model, but also focuses on the research and partial improvement of the practical application of the model according to the characteristics of the model. Based on the quantitative modeling of volatility, the conditional heteroscedasticity model which effectively explains the distribution of single assets and the EVT theory focusing on extreme risk are combined to construct the marginal distribution of stock index and futures index. The standardized residuals are obtained by GARCH process. Then the EVT theory is used to fit the upper and lower tail of the residual sequence, and the t- distribution is used to fit the middle part. Then a flexible binary function is used to connect the edge distribution to construct the joint distribution. Finally, the VaR value of hedging risk is estimated by generating the simulated return sequence by the parameters of the t-Copula process. Through the return test, the validity of the model is analyzed. Based on the data analysis and statistical test, the improved GARCH EVT tCopula model is applied to estimate the VaR of hedging transactions. The VaR values were estimated to be 0. 1 and 0. 05 at the significant level of 0. 1 and 0. 05 respectively. A return test and a related model test are made, and it is concluded that the GARCH EVT tCopula model can effectively evaluate the risk of hedging transactions. In addition, the other three models are used to estimate the VaR at the same significant level, and to compare the fitting effect of the improved GARCH EVT tCopula model. The results show that after EVT fitting, EVT can better control the extreme risk. GARCH-EVT-Copula model is closer to reality, which provides a more effective model for hedge trade analysis.
【學(xué)位授予單位】：天津財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F224;F724.5

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