本文選題：最壞情況下的條件風(fēng)險(xiǎn)（WCVaR） + 混合分布　； 參考：《廣東財(cái)經(jīng)大學(xué)》2014年碩士論文

【摘要】：風(fēng)險(xiǎn)度量模型CVaR(Conditional-value-at-risk,條件在險(xiǎn)價(jià)值)有很多優(yōu)點(diǎn)，它即彌補(bǔ)了VaR（Value-at-risk，在險(xiǎn)價(jià)值）模型的不足，也滿足一致性風(fēng)險(xiǎn)度量的要求，故一度受風(fēng)險(xiǎn)管理者的追捧。但在計(jì)算過(guò)程中，要求隨機(jī)變量分布情況已知的前提下進(jìn)行度量的，而現(xiàn)實(shí)中的金融市場(chǎng)常常受到各種復(fù)雜因素的影響，尤其我國(guó)目前證券市場(chǎng)發(fā)展不完善，金融市場(chǎng)波動(dòng)較大，，隨機(jī)變量分布信息無(wú)法完全知道，CVaR風(fēng)險(xiǎn)度量模型度量效率較低。隨后，Zhu-FuKushima率先提出了最壞情境下的條件在險(xiǎn)價(jià)值，簡(jiǎn)稱WCVaR（Worst-case CVaR），它刻畫了非完全信息下的風(fēng)險(xiǎn)，在現(xiàn)實(shí)中，我們無(wú)法預(yù)知某件事情的結(jié)果時(shí)，常常會(huì)考慮最壞情況發(fā)生時(shí)的情況，從而更好預(yù)知風(fēng)險(xiǎn)。 本文考慮現(xiàn)實(shí)中資產(chǎn)收益率服從混合分布下的WCVaR模型，并在模型中加入比例交易費(fèi)用函數(shù)，使得加入交易費(fèi)用后的模型研究更貼近現(xiàn)實(shí)。然后利用向量自回歸構(gòu)建收益率未來(lái)路徑，再根據(jù)上述回歸后殘差分布，判別殘差可能服從哪幾種概率分布情況，結(jié)合蒙特卡羅方法隨機(jī)生成未來(lái)資產(chǎn)收益率情景�？紤]損失函數(shù)為線性的情況下，從而將不確定的線性規(guī)劃問(wèn)題轉(zhuǎn)化為確定的線性規(guī)劃問(wèn)題，利用Matlab中LP模塊，即可求出模型最優(yōu)解。模型結(jié)果證明，加入交易費(fèi)用后，同等情況下風(fēng)險(xiǎn)相應(yīng)有一定幅度增加，說(shuō)明交易費(fèi)用加入會(huì)相應(yīng)增加風(fēng)險(xiǎn)，對(duì)現(xiàn)實(shí)中人們投資有一定指導(dǎo)性意義。
[Abstract]:The risk measurement model CVaRN Conditional-value-at-risk (conditional at risk value) has many advantages. It not only makes up for the deficiency of VaRN Value-at-riskmodel, but also meets the requirements of consistent risk measurement, so it was once sought after by risk managers. However, in the course of calculation, it is necessary to measure the distribution of random variables, but the real financial market is often affected by various complicated factors, especially the development of securities market is not perfect. Because of the volatility of the financial market, the risk measurement model of CVaR is less efficient because of the uncertainty of the random variable distribution information. Later, Zhu-Fuuseo first proposed that the worst-case condition is at risk value, or WCVaR(Worst-case Cvar Rao, which depicts the risk under incomplete information. In reality, when we cannot predict the outcome of something, we often take into account the worst-case scenario. Thus better anticipating the risks. In this paper, we consider the WCVaR model under the mixed distribution of the return rate of assets, and add the proportional transaction cost function to the model, which makes the research of the model closer to the reality after adding the transaction cost. Then the future path of return rate is constructed by using vector autoregressive method. Then according to the above regression residual distribution the probability distribution from which the residual may be obtained is determined and the future asset return scenario is randomly generated by using Monte Carlo method. When the loss function is linear, the uncertain linear programming problem is transformed into a definite linear programming problem. The optimal solution of the model can be obtained by using LP module in Matlab. The results of the model show that after the transaction cost is added, the risk will increase by a certain extent in the same situation, which means that the transaction cost will increase the risk accordingly, which is instructive to people's investment in reality.
【學(xué)位授予單位】：廣東財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F224;F832.51

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