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论文编号：	3137
作者编号：	2120082597
上传时间：	2011/6/1 21:47:32
中文题目：	我国开放式基金投资风险研究
英文题目：	Study on Investment Risk of Open-end Fund in China
指导老师：	马君潞
中文关键字：	开放式基金 投资风险 风险模型 GARCH-M EGARCH
英文关键字：	Open-End Fund Investment Risk Risk Model GARCH-M EGARCH
中文摘要：	随着经济全球化的进程，我国金融市场将对外逐步开放，金融市场和投资环境将变得更加复杂。国际上，西方主权国家和日本的债务危机，以及西方国家的失业率的等问题影响我国金融市场；在国内，房价和CPI居高不下，我国政府频繁加息和提高准备金，但效果不是很明显。抑制房价过快上涨和稳定物价是我国当前两个最棘手的问题。地震、战争等因素给金融市场的投资者带来极大的心理恐慌，进一步增大了金融市场的波动,投资者将更加关注投资风险。银河证券基金研究中心统计数据显示，截至2010年12月31日，包括QDII基金在内的国内基金公司公募基金资产净值为25184.54亿元，其中开放式基金占公募基金资产的90%以上的比重。所以，研究我国开放式基金的投资风险是非常必要的。 本文的研究目的是研究开放式基金不同投资策略的风险，通过了解不同类型开放式基金的投资策略，熟悉不同类型的开放式基金的风险特性。分析不同类型开放式基金指数的波动率，让投资者理解开放式基金风险特征，并在此基础上结合自身风险收益偏好选择不同类别开放式基金，对比基准指数进一步估计单只开放式基金波动状况。 本文采用规范研究和实证分析相结合、定量研究和定性分析相结合的研究方法分析我国开放式基金的投资风险。运用GARCH-M模型分析不同类型的开放式基金投资风险，EGARCH模型研究不同类型的开放式基金指数的波动是否存在非对称型。 本文的研究结论：1）GARCH-M模型对开放式基金指数的拟合效果较好，在本文研究的中证开放式基金指数体现出金融理论中高风险高收益的有：股票型基金指数、混合型基金指数、货币型基金指数、ETF基金指数和QDII基金指数，只有债券型基金指数估计出的均值方程方差前的系数为负，众所周知，债券型基金风险最小。2）信息冲击非对称性在开放式基金指数中比较复杂，本文的研究结果表明对于绝大多数策略的开放式基金“利空消息”和“利好消息”都会加大指数的波动率，但是本文没有得出“利空消息”作用大于“利好消息”作用的非对称性的结论， ETF和QDII表现出了“利空消息”作用大于“利好消息”。通过分析得出我国基金经理们在利好或利空时都表现出了羊群效应的结论，他们没有合理地控制风险，跟散户一样追涨杀跌，而且利空弱于利好，说明基金经理追涨时更疯狂。因此，建议我国投资者在牛市中选择 值较高的股票会收益更好，在熊市中选择 值较低的股票风险更少。
英文摘要：	With the process of economic globalization, Chinese financial market will gradually open up outside, the financial market and investment environment will become even more complicated. Internationally, the Western countries and Japanese sovereign debt crises, and the unemployment rate in Western countries and other issues affect our financial markets; In China, housing prices and CPI remain high, our government raising interest rate and the deposit reserve ratio frequently, but the effect is not very significant, controlling housing prices raised too soon and stabilizing prices is our current two most intractable problems. Earthquake, war and other factors to the financial market investors tremendous psychological panic, further increasing the volatility of financial markets, investors will pay more attention to investment risks. Galaxy Securities Funds Research Center statistics shows, up to December 31, 2010, including the QDII funds, net asset value of the domestic public offering funds 2.518454 trillion yuan, of which open-end fund accounted for more than 90%. Therefore, the research of open-end fund's investment risk is very necessary. Purpose of this thesis is to research the open-end funds risk with different investment strategies, understanding the different types of open-end fund's investment strategy, be familiar with different types of open-end fund risk characteristics. Analysis of different types open-end fund indexes' volatility, so that investors understand the risk characteristics of open-End funds, and on this basis with their risk return preference, choose different types open-end funds, compared to the benchmark index further estimated the volatility of single open-end fund. This thesis uses combining of standardize research and empirical analysis, combining of quantitative and qualitative analysis methods to research the open-end fund's investment risk. I use GARCH-M model to Analysis different types open-end funds' investment risk, and use EGARCH model to find different types open-end fund indexes' volatility whether is asymmetric. This thesis' conclusions: 1) the effect of which GARCH-M model fits open-end fund index is better, China Security open-end fund indexes reflects the financial theory of high risk and high return are: Equity fund index, hybrid fund index, currency fund index, ETF fund index and QDII fund index, only bond fund index to estimate the variance of the mean equation of the coefficient is negative, as we all know, the minimum risk of bond funds. 2) The impact of information asymmetry in open-end fund indexes is more complex, the results of this study show that the vast majority of open-end fund "bad news" and "good news" will increase volatility, but did not show that effect of "bad news" is greater than effect of "good news", ETF and QDII show that effect of "bad news" is greater than effect of "good news". Obtained by analysis that fund managers show Herding Behaviors whether in the good news or bad news, they did not control the risk reasonably, with the same of retail investors, chase the rising and sell the drop. They are more crazied chasing the rising than selling the drop. Therefore, we suggest investors to select stocks of high value in a bull market, yield a higher return, choice stocks of lower value in the bear market, reduce investment risk.
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