中国开放式基金投资组合风险值的实证——基于Copula-GARCH的分析

结合Copula技术和GARCH模型,建立了投资组合风险分析的Gopula-GARCH模型.由于该模型可以捕捉金融市场间的非线性相关性,因而可用于投资组合VaR的分析.利用这个模型,结合Monte Carlo,模拟技术,对我国第一支开放式基金一华安创新基金的投资组合进行了风险分析.     

基于Copula的投资组合选择模型研究

基于概率收益率与概率风险的定义,建立基于风险与收益率的投资组合模型,为了更好拟合联合分布,在具体解法中采用Copula函数来构造多个资产收益率的联合分布。由于不要求收益率服从维纳过程,因此基于Copula的Markowitz投资组合选择模型具有更广的适用性。通过对上证领先指数与深证领先指数收盘数据实证分析发现,在收益率(基于概率ρ0的收益率)一定的情况下,通过投资组合可以降低风险。     

二元Copula函数的投资组合模型选择

Coplua模型是组合投资风险评估中常用模型,它具有多种不同的类型,模型选择的好坏对风险评估结果具有至关重要的影响.本文主要比较了二元正态Copula模型和二元t-Copula模型对中国股市数据拟合的优劣程度.针对这两种模型,利用上证综指、深证成指、上证基金、深证基金、东风汽车、中国石化、宝钢股份和万家乐的日收盘价数据估计相应的参数得到相应的拟合分布,然后分别与经验Copula函数作比较,通过计算拟合分布与经验分布之间的距离,得出二元t-Cop-ula函数能更好地拟合两组投资组合的日收益率数据的结论.     

基于CvaR模型投资组合保险的绩效实证研究

经济全球化和金融市场一体化带来金融市场波动加大。投资者期望一个在价格下跌的时候能够维持最低保障,同时又能够在市场上涨时带来收益的投资理财产品。投资组合保险策略正是能够满足大家的这种期望。通过将CvaR与投资组合保险相结合,将投资组合保险策略进行动态的改良,考量改良后的投资组合保险在金融市场中对于风险度量的实际应用情况。     

基于EGARCH-Copula模型的VaR方法在投资组合风险分析中的应用

GARCH族模型是金融计量学中用来描述或预测金融资产收益率波动的模型,通过对金融资产收益率波动的建模,可以得出未来金融资产收益率的条件分布。Copula函数可以用来描述多个随机变量间的相依结构,进而得出他们的联合分布。Copula自被引入金融产品分析以来,以取得了很多成果也被广泛使用。运用GARCH族模型进行资产组合中边缘分布的建模,继而使用Copula得到组合资产联合分布的方法来计算资产组合VaR值最早被吴振翔（2006）系统性地提出,但其中有许多问题仍需要完善。本文将继续这个思路,通过EGARCH模型更好地描述资产收益率的杠杆效应,以及考虑Copula函数中参数的时变性,来完善这一方法。     

对单指数模型投资组合优化方法的修正——以开放式基金为例

本文根据单指数模型在投资组合优化中的局限性,提出了修正的单指数投资组合优化模型。通过构造双目标规划函数,同时实现对风险和收益的优化。实证结果显示,修正模型的最优投资组合要优于基金原始组合与单指数模型优化组合。本文提出的单指数修正模型在实用性和适用性上有了一定的提升,能够很好地适应我国不允许卖空的机制,对于一些基金组合的特殊情况也能够得到较好的结果。     

基于copula的投资组合选择模型的研究

本文首先介绍了投资组合理论与copula,然后给出基于概率P0的收益率等定义,建立基于概率P0的收益率的投资组合选择模型并给出具体解法,接着通过选取上证领先指数与深证领先指数2004年9月1日至2006年5月26日的日收盘数据进行实证分析,发现在收益率(基于概率的收益率)一定的情况下,通过投资组合可以降低风险.     

VaR理论模型在证券组合投资中实证分析

目前我国的证券投资市场还存在众多不规范的地方,加强金融市场尤其是证券交易市场的风险管理势在必行。目前在国际市场上存在着很多的风险测量的方式,其中VaR模型已成为金融市场上非常重要的测量方式。首先介绍了关于证券组合投资的基本概念及面临的主要风险,再介绍了VaR模型的主要计算方式、优缺点以及VaR模型主要的获取方法。最后重点分析了在VaR约束下使用方差-协方差法的投资组合决策。     

VaR理论模型在证券组合投资中实证分析

目前我国的证券投资市场还存在众多不规范的地方,加强金融市场尤其是证券交易市场的风险管理势在必行。目前在国际市场上存在着很多的风险测量的方式,其中VaR模型已成为金融市场上非常重要的测量方式。首先介绍了关于证券组合投资的基本概念及面临的主要风险,再介绍了VaR模型的主要计算方式、优缺点以及VaR模型主要的获取方法。最后重点分析了在VaR约束下使用方差-协方差法的投资组合决策。     

组合投资正当时

时下最好的理财产品是什么?有人会说是基金,有的人会说是股票或人民币理财……其实这些回答都不完全正确,最好的理财产品应该是投资组合!随着开放式基金的火爆,很多人把家里所有的积蓄全部买成了基金,期望以此来一夜暴富.     

Varying the VaR for unconditional and conditional environments

Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from 12 European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates accounting for volatility clustering are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law. The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting.     

Value at risk methodology of international index portfolio under soft conditions (fuzzy-stochastic approach)

The approach to modelling uncertainty of the international index portfolio by the value at risk (VAR) methodology under soft conditions by fuzzy-stochastic methodology is described in the paper. The generalised term uncertainty is understood to have two aspects: risk modelled by probability (stochastic methodology) and vagueness sometimes called impreciseness, ambiguity, softness is modelled by fuzzy methodology. Thus, hybrid model is called fuzzy-stochastic model. Input data for a stochastic model are unique distribution functions and crisp (real) data. Input data for fuzzy model are fuzzy numbers and crisp (real) data. Input data for hybrid model are fuzzy probability distribution functions, unique distribution functions, and crisp (real) data. Softly defined VAR model is constructed as hybrid model because it is supposed that the input data are difficult to determine as crisp numbers or as some unique distribution functions. Risk is modelled by stochastic methodology on the VAR basis and vagueness is modelled through the fuzzy numbers. The analytical delta normal VAR methodology for international index portfolio under soft conditions is described including illustrative example. It is shown, that methodology described could be considered to be generalised sensitivity analysis.     

基于经济资本的我国保险公司投资风险限额配置研究

投资风险限额管理是保险公司对投资风险进行管理的重要手段,是保险公司建立有效风险管理体系不可或缺的组成部分。保险公司投资风险限额管理主要包括投资风险限额配置、风险限额监控和风险限额动态调整三个环节,其中风险限额配置是整个风险限额管理流程的基础。运用GARCH模型和GJR模型,并结合Copula理论,探讨了投资风险限额配置的方法,通过实证分析证实投资组合之间存在分散化效应,各投资风险限额之和大于总风险限额,并得出投资风险限额优化配置模型调整资产配置,可以显著提高保险公司投资绩效。     

Does sustainable investing reduce portfolio risk? A multilevel analysis

This study complements and extends prior research on the risk mitigation role of sustainable investing. We use a continuous measure of funds' sustainability traits, rather than a categorical approach, and assess impact on risk directly rather than by looking at fund performance in up versus down markets. We find that sustainable investing plays a significant role in mitigating total, systematic, and idiosyncratic risk of equity funds, even after controlling for other fund characteristics. Further evidence indicates that the explanation for the risk reduction role of sustainable funds largely runs through traits of the firms held in the funds.     

The Effect of Shortfall as a Risk Measure for Portfolios with Hedge Funds

Abstract:  Current research suggests that the large downside risk in hedge fund returns disqualifies the variance as an appropriate risk measure. For example, one can easily construct portfolios with nonlinear pay-offs that have both a high Sharpe ratio and a high downside risk. This paper examines the consequences of shortfall-based risk measures in the context of portfolio optimization. In contrast to popular belief, we show that negative skewness for optimal mean-shortfall portfolios can be much greater than for mean-variance portfolios. Using empirical hedge fund return data we show that the optimal mean-shortfall portfolio substantially reduces the probability of small shortfalls at the expense of an increased extreme crash probability. We explain this by proving analytically under what conditions short-put payoffs are optimal for a mean-shortfall investor. Finally, we show that quadratic shortfall or semivariance is less prone to these problems. This suggests that the precise choice of the downside risk measure is highly relevant for optimal portfolio construction under loss averse preferences.     

基于风险价值法和压力测试法的企业风险管理方法研究

本文提出风险价值法和压力测试法的企业风险管理方法,克服了传统方法只给出风险相对严重程度的不足。建立风险量化评估、预警和控制体系,采用优化组合方法,实施一体化风险管理,规避重大风险事件的发生。