本文關(guān)鍵詞：基于VaR和CVaR的我國(guó)開放式基金績(jī)效評(píng)價(jià)　出處：《浙江工商大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 開放式基金 業(yè)績(jī)?cè)u(píng)價(jià) GARCH模型 VaR CVaR RAROC

【摘要】：隨著開放式基金的發(fā)展,開放式基金日趨成為主流的投資產(chǎn)品,加之投資開放式基金能夠獲得免稅等有利條件,它逐漸獲得大眾的青睞�；鸬漠a(chǎn)品種類繁多,我國(guó)目前已有的開放式基金更是數(shù)以百計(jì)。面對(duì)紛繁復(fù)雜的基金產(chǎn)品,如何做出合理的投資選擇,基金的績(jī)效評(píng)價(jià)就顯得尤為的重要�，F(xiàn)代的很多投資者都認(rèn)為基金是一種不可靠的投資方式,這主要是投資者在對(duì)基金的認(rèn)識(shí)上還有些偏差。他們認(rèn)為基金投資基本上是無(wú)風(fēng)險(xiǎn)的投資,而事實(shí)上任何的理財(cái)產(chǎn)品或者投資的金融產(chǎn)品都是有風(fēng)險(xiǎn)的,只是分風(fēng)險(xiǎn)大小不同而已。目前我國(guó)現(xiàn)有的基金業(yè)績(jī)?cè)u(píng)價(jià)指標(biāo)過度側(cè)重基金凈值,把關(guān)注點(diǎn)都放在了基金的收益上,忽略了基金存在的風(fēng)險(xiǎn)。本論文引入了由傳統(tǒng)Sharp比率演變而來(lái)的基金業(yè)績(jī)?cè)u(píng)價(jià)RAROC模型,此模型綜合考慮了基金的收益和風(fēng)險(xiǎn),從而使基金的評(píng)價(jià)更為客觀合理。同時(shí),論文改進(jìn)了RAROC模型中風(fēng)險(xiǎn)度量方法,從而使模型更加的精確。 本論文首先回顧了國(guó)內(nèi)外基金業(yè)績(jī)?cè)u(píng)價(jià)的主要理論與研究成果,提出了以CVaR代替VaR作為RAROC模型的風(fēng)險(xiǎn)度量,并在此基礎(chǔ)上進(jìn)行基金業(yè)績(jī)?cè)u(píng)價(jià)。然后論文對(duì)VaR和CVaR風(fēng)險(xiǎn)度量進(jìn)行了理論介紹,在理論研究的基礎(chǔ)上,論文選取了樣本基金股票型基金、混合型基金和債券型基金各8只用于實(shí)證分析。這24只樣本基金分別用殘差假設(shè)為T分布和GED分布下的參數(shù)模型GARCH、EGARCH、 TARCH和基于峰度法的極值POT模型估計(jì)了VaR和CVaR值。實(shí)證結(jié)果表明,所選參數(shù)模型中GED分布下的GARCH模型擬合效果最好；同時(shí),基于峰度法的極值POT模型也能夠很好地?cái)M合尾部收益分布。然后,通過Lopez(1998)提出的損失函數(shù)方法進(jìn)行模型比較,發(fā)現(xiàn)GED分布下的GARCH模型在估計(jì)VaR時(shí)優(yōu)于極值POT模型；而通過定義的ELC統(tǒng)計(jì)量的比較,發(fā)現(xiàn)極值POT模型在計(jì)算CVaR時(shí)優(yōu)于GARCH-GED模型。最后,在模型比較之后,選出最優(yōu)的風(fēng)險(xiǎn)度量結(jié)果計(jì)算RAROC值再進(jìn)行基金的業(yè)績(jī)?cè)u(píng)價(jià)。
[Abstract]:With the development of open-end fund, open-end fund becomes the mainstream investment product day by day. In addition, the investment open-end fund can obtain tax exemption and other favorable conditions, it gradually gets the favor of the public. There are many kinds of products of the fund. At present, there are hundreds of open-end funds in China. Facing the complicated fund products, how to make a reasonable investment choice. The evaluation of fund performance is particularly important. Many modern investors believe that the fund is an unreliable way of investment. This is mainly because investors still have some misunderstandings about the fund. They think that the fund investment is basically a risk-free investment, but in fact, any financial product or financial product is risky. At present, the existing fund performance evaluation indicators in China focus on the net value of the fund, focusing on the income of the fund. This paper introduces the RAROC model of fund performance evaluation, which is evolved from the traditional Sharp ratio, which considers the return and risk of the fund. Therefore, the evaluation of the fund is more objective and reasonable. At the same time, the paper improves the risk measurement method in the RAROC model, thus making the model more accurate. Firstly, this paper reviews the main theories and research results of fund performance evaluation at home and abroad, and puts forward the risk measurement of using CVaR instead of VaR as RAROC model. Then the paper introduces the risk measurement of VaR and CVaR theoretically, and on the basis of theoretical research, the paper selects the sample fund equity fund. Eight hybrid funds and eight bond funds are used for empirical analysis. The 24 sample funds use the parameter model GARCH-EGARCH under T distribution and GED distribution respectively. TARCH and the extreme value POT model based on kurtosis method estimate the VaR and CVaR values. The empirical results show that the GARCH model with GED distribution is the best one in the selected parameter model. At the same time, the extreme value POT model based on kurtosis method can fit the tail income distribution well. Then, the loss function method proposed by Lopeza 1998 is compared. It is found that the GARCH model under GED distribution is better than the extreme POT model in estimating VaR. By comparing the defined ELC statistics, it is found that the extreme value POT model is superior to the GARCH-GED model in calculating CVaR. Finally, after the model comparison. The optimal risk measurement results are selected to calculate the RAROC value and then evaluate the performance of the fund.
【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F832.51

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