本文關(guān)鍵詞： 投資組合 跟蹤比率 風(fēng)險(xiǎn)容忍參數(shù) 三步循環(huán)估計(jì)法 證券投資基金　出處：《重慶大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：證券投資基金在國(guó)外已有一百多年的發(fā)展歷史，證券投資基金已成為西方發(fā)達(dá)國(guó)家金融投資業(yè)的三大支柱之一。我國(guó)資本市場(chǎng)起步于二十世紀(jì)八十年代，經(jīng)過(guò)十幾年的發(fā)展，我國(guó)證券投資基金業(yè)取得了長(zhǎng)足的發(fā)展，規(guī)模逐漸壯大，但我國(guó)證券投資基金業(yè)起步較晚，市場(chǎng)占有份額較低，其投資管理水平與西方發(fā)達(dá)國(guó)家相比還有較大差距。證券投資基金作為資本市場(chǎng)機(jī)構(gòu)投資力量的生力軍，對(duì)改善資本市場(chǎng)投資環(huán)境，引導(dǎo)先進(jìn)投資理念，規(guī)范市場(chǎng)投資行為有著極其重要的作用�，F(xiàn)代投資組合理論和方法在資產(chǎn)投資和風(fēng)險(xiǎn)分散方面有著舉足輕重的地位，對(duì)我國(guó)證券投資基金的發(fā)展、對(duì)指導(dǎo)投資者理性投資有著重大的現(xiàn)實(shí)意義。因此，，引入和深入研究現(xiàn)代投資組合理論和方法，加強(qiáng)對(duì)宏觀經(jīng)濟(jì)基本面的研究，大力發(fā)展金融(衍生)工具市場(chǎng)對(duì)推動(dòng)我國(guó)證券投資基金的發(fā)展，指導(dǎo)完善我國(guó)資本市場(chǎng)，促進(jìn)我國(guó)社會(huì)的穩(wěn)定和經(jīng)濟(jì)繁榮，推動(dòng)我國(guó)證券市場(chǎng)保持長(zhǎng)期穩(wěn)定的發(fā)展具有重大的理論和現(xiàn)實(shí)意義。 本文研究成果如下： ①提出了基于Copula—EGarch—GPD的投資組合模型。選用EGarch—GPD模型擬合單樣本數(shù)據(jù)，在AIC值意義下確定出能最佳擬合數(shù)據(jù)聯(lián)合分布函數(shù)的Copula函數(shù)，結(jié)合度量風(fēng)險(xiǎn)損失能力強(qiáng)的CVaR指標(biāo)與最優(yōu)化理論運(yùn)用Monte Carlo模擬法計(jì)算出最優(yōu)投資組合權(quán)重。 ②提出了基于期望效用函數(shù)極大化的投資組合模型。運(yùn)用期望效用理論提出了基于期望效用極大化的投資組合模型，新模型的最優(yōu)投資組合權(quán)重運(yùn)用拉格朗日乘子法很易求出。 ③提出了一種新的基金業(yè)績(jī)?cè)u(píng)價(jià)指標(biāo)——跟蹤比率(Tracking Error;簡(jiǎn)稱TR)。從夏普比率和信息比率的定義可知，夏普比率只評(píng)價(jià)了資產(chǎn)管理者總的投資能力，卻無(wú)法衡量管理者在不同行情(牛市或熊市)下超過(guò)大盤(pán)的投資能力，而信息比率盡管準(zhǔn)確度量了資產(chǎn)管理者超過(guò)大盤(pán)的投資能力，卻無(wú)法衡量管理者總的投資能力。跟蹤比率很好地克服了夏普比率(SR)和信息比率(IR)的管理能力評(píng)價(jià)缺陷。 ④提出引入風(fēng)險(xiǎn)容忍參數(shù)討論投資組合模型。文中得到風(fēng)險(xiǎn)容忍參數(shù)的選取并不是全部正實(shí)數(shù)，而是由歷史數(shù)據(jù)的期望收益率、方差-協(xié)方差矩陣和大盤(pán)收益共同確定的正實(shí)數(shù)區(qū)間，由此區(qū)間確定的最低要求收益同時(shí)也是判別投資組合是否為有效組合的必備條件。 ⑤提出了一種新的參數(shù)估計(jì)法——三步循環(huán)估計(jì)法(Repeating MaximumLikelihood，簡(jiǎn)稱RML)。EML參數(shù)估計(jì)法盡管估計(jì)出的參數(shù)值精確度非常高，但EML方法在實(shí)際應(yīng)用中往往很難估計(jì)出參數(shù)值。IFM方法盡管計(jì)算速度快，但其沒(méi)有EML方法估計(jì)精度高。三步循環(huán)估計(jì)法即比EML方法計(jì)算速度快，也比IFM方法更有效。 ⑥選取中國(guó)證券市場(chǎng)中具有代表性的標(biāo)的指數(shù)對(duì)本文提出模型、方法以及所得結(jié)論運(yùn)用Eviews、Matlab等數(shù)據(jù)處理軟件進(jìn)行實(shí)證分析，實(shí)證結(jié)論與理論推導(dǎo)結(jié)論完全吻合。
[Abstract]:The securities investment fund has a history of more than 100 years in foreign countries, securities investment fund has become one of the three pillars of the financial investment industry in western developed countries. China's capital market started in 1980s, after ten years of development, China's securities investment fund industry has achieved great development, gradually expand the scale, but China's securities investment the fund industry started late, the market share is low, the investment management level there is a large gap compared with western developed countries. The new securities investment fund as the capital market investment strength, to improve the capital market investment environment, and guide the advanced investment philosophy, plays an important role in the investment behavior to regulate the market. Modern investment portfolio theory and method of dispersion plays a decisive role in investment and risk, the development of China's securities investment fund, to guide Is of great practical significance to rational investment of investors. Therefore, the introduction and research of modern portfolio theory and methods, to strengthen the research of macroeconomic fundamentals, vigorously develop the financial market (Yan Sheng) tool to promote the development of China's securities investment fund, to guide the perfection of our capital market, promote China's social stability and economic prosperity is of great theoretical and practical significance to maintain long-term stable development and promote China's securities market.
The results of this study are as follows:
The proposed investment portfolio model of Copula EGarch based on GPD. The EGarch - GPD model of single sample data in the AIC value to determine the optimal Copula function can fit the data distribution function, CVaR index and combine the risk measurement ability of the loss theory using Monte Carlo simulation method to calculate the optimal investment the combined weight.
The portfolio model based on expected utility maximization. Using the expected utility theory in portfolio model based on expected utility maximization, the new model of the optimal portfolio weights using the Lagrange multiplier method is easy to calculate.
It presents a new fund performance evaluation index - tracking ratio (Tracking Error; TR). From the SHARP ratio and information ratio definition, SHARP ratio only evaluates the asset managers total investment capacity, but can not measure the managers at different prices (bull or bear) more than the market investment capacity but, although the exact information ratio to measure the asset managers than the market's ability to invest, but can not measure the management ability. The total investment ratio tracking methodovercome SHARP ratio (SR) and information ratio (IR) management ability evaluation of defects.
The proposed risk tolerance parameter on portfolio model. The risk tolerance parameter is not all positive real numbers in the text, but by the historical data of the expected rate of return, variance covariance matrix and the market returns jointly determine the positive real interval, the interval to determine the minimum income and investment portfolio is essential for discrimination the effective combination.
Put forward the method of three step cycle estimation method, a new parameter estimation (Repeating MaximumLikelihood, referred to as RML) method to estimate the.EML parameters while the estimated parameter values of accuracy is very high, but the EML method in the practical application is often difficult to estimate the parameter values of the.IFM method while the calculation speed is fast, but it does not have a EML estimation method high precision. Three step cycle estimation method is better than EML method has fast calculation speed and is more effective than the IFM method.
The selection of representative mark China in the stock market index model is proposed in this paper and the conclusion by using Eviews method, Matlab data processing software to carry out empirical analysis, empirical results consistent with theoretical conclusion.

【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.51;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 張波;陳睿君;路璐;;粒子群算法在投資組合中的應(yīng)用[J];系統(tǒng)工程;2007年08期

2 吳如海,宋逢明;基金分離下中國(guó)股市交易量模型的實(shí)證研究[J];管理科學(xué)學(xué)報(bào);2000年01期

3 陳學(xué)華;韓兆洲;唐珂;;基于VaR和RAROC的保險(xiǎn)基金最優(yōu)投資研究[J];數(shù)量經(jīng)濟(jì)技術(shù)經(jīng)濟(jì)研究;2006年04期

4 曲圣寧,田新時(shí);投資組合風(fēng)險(xiǎn)管理中VaR模型的缺陷以及CVaR模型研究[J];統(tǒng)計(jì)與決策;2005年10期

5 徐緒松,楊小青,陳彥斌;半絕對(duì)離差證券組合投資模型[J];武漢大學(xué)學(xué)報(bào)(理學(xué)版);2002年03期

6 陳金龍,張維;CVaR與投資組合優(yōu)化統(tǒng)一模型[J];系統(tǒng)工程理論方法應(yīng)用;2002年01期

7 曹勇，唐小我，曾長(zhǎng)修;國(guó)際組合證券投資有效邊界研究[J];系統(tǒng)工程理論方法應(yīng)用;1995年01期

8 馬永開(kāi),唐小我;不允許賣空的多因素證券組合投資決策模型[J];系統(tǒng)工程理論與實(shí)踐;2000年02期

9 屠新曙,王鍵;求解證券組合最優(yōu)權(quán)重的幾何方法[J];中國(guó)管理科學(xué);2000年03期

10 王春峰,屠新曙,厲斌;效用函數(shù)意義下投資組合有效選擇問(wèn)題的研究[J];中國(guó)管理科學(xué);2002年02期

本文編號(hào)：1510570