VaR与CVaR在商业银行风险度量中的比较分析及应用

本文系统地阐述了时下银行流行的VaR（ValuealRisk）风险度量技术，并分析了该理论存在的缺陷和使用上的局限性，从而提出以CVaR（Conditional Value at Risk）模型作为风险度量的替代方法．详细分析了CVaR的原理、特长以及在银行业应用前景，包括风险度量、绩效分析和行为指引等方面的突出作用。最后研究了CVaR在我国商业银行的具体应用。     

互联网金融风险度量模型选择研究

度量互联网金融风险非常重要,但传统的风险度量模型能否有效度量其风险,何种模型能更有效地度量其风险犹未可知。以余额宝的风险度量为例,分析了在90%和95%置信水平下的最优GARCH-VaR和GARCH-CVaR模型,作为对应置信水平下的VaR和CVaR的度量。结果表明,CVaR模型能更有效地度量互联网风险,其不仅可以很好地度量现有的风险水平,还对风险具有预测性。     

基于加权CVaR下具有不确定退出时间的最优投资组合研究

一、引言 VaR是指在一定的概率(置信)水平下,某一金融资产或投资组合在未来特定的一段时间内遭受的最大可能损失.但是经过后来的研究,发现了VaR具有很多不足之处,于是Artzner(1997)提出了CVaR,CVaR是指投资组合的损失大于某个给定VaR值的条件下,该投资组合的损失平均值.2000年Rockafeller等人证明了基于CVaR的投资组合优化必定存在最小风险的解.CVaR和VaR作为风险测量工具在文献[3]中作了广泛的比较,CVaR现在被认为是比VaR更好的一致性风险度量.     

VaR风险度量方法评价及其修正模型CVaR

本文首先简要介绍VaR风险度量方法,并对其优点和局限性进行分析,然后从一致性风险度量出发,论述了VaR缺乏次可加性的缺陷,最后阐述并分析了VaR的修正模型CVaR模型。     

基于EGARCH-CVaR方法的保险资金直接入市风险分析——以吉林省为例

本文基于EGARCH模型和GED分布下的CVaR模型对保险资金直接入市的风险进行度量,实证测算了八只股票的个股及投资组合的绝对CVaR值和相对CVaR值,描述了各自的极端损失状况;金融机构可以根据个股值和组合值,设置风险资本或提取风险准备金,从而有效地监控潜在的极端损失。     

风险依赖、一致性风险度量与投资组合——基于Mean-Copula-CVaR的投资组合研究

本文把风险依赖、一致性风险度量与投资组合纳入到一个分析框架中,结合Coupla-CVaR模型和Mean-var投资组合理论构建Mean-Copula-CVaR的投资组合模型,能有效同时解决风险度量中的一致性和依赖性关系。采用券商指数、银行指数和保险指数实证分析线性依赖和复杂依赖(Copula依赖)情况下金融机构资产配置的差异性和风险度量的充分性,研究结果表明,纳入Copula函数能够更为稳健和准确地预测投资组合的CVaR。然而,本文没有检验出不同形式Copula之间的差异具有显著性。本文的政策含义在于,忽视复杂风险依赖结构可能会造成风险低估,从而影响资产配置的有效性。     

CVaR风险度量及投资组合优化的实证分析

CVaR法是在VaR法基础上优化改进而来的风险度量方法。通过CVaR法对金融资产风险进行评估,对投资组合资产配置进行优化等成为了金融风险管理的重要内容。本文首先对比了CVaR和VaR法的区别,并通过比较A股和H股收益分布的特征得出A股更适用CVaR模型的结论。通过多因子选股模型选出投资组合成分,再使用均值-CVaR模型对投资组合进行优化,最终得到不同置信度和阀值下投资组合的优化结果。从而证明了该模型的有效性,突出了CVaR法在国内证券市场的使用价值和意义。     

基于EGARCH模型VaR和CVaR方法的传媒板块风险度量研究

本文以2008年1月2日至2013年5月3日传媒指数日收盘价数据作为实证载体,运用EGARCH模型度量波动性,并计算95%置信水平下传媒指数对数收益率的VaR和CVaR值,从而对我国传媒板块的风险进行实证分析。实证结果表明,EGARCH模型能够较好的描述我国传媒板块的波动情况,并且CVaR方法在覆盖风险方面比VaR方法更优。     

基于GARCH族模型的VaR及CVaR方法在中国大陆股市中的应用

随着美国次贷危机爆发对全世界金融领域的冲击,更加加剧了中国股市的剧融波动和风险,这使得风险管理难度加剧,使得投资者投资更加困惑。为此．研究我国股市的市场波动和风险情况具有重要意义。本文对上证综合指教．上证180指数,深圳成份指数,在GARCH-N,GARCH—t,GAR．CH-GED模型的基础上计算Var值,对其进行了检验分析。发现上证综合指数,上证180指数。深圳成份指数的收益率走势大致相同．且都具有尖峰厚尾陛,适合用GARCH族模型进行建模和分析。因此,本文随后运用cVaR方法进行更加保守性的风险分析。通过对cvaR和VaR计算结果的比较．可以看出CVaR估计值比VaR估计值高得多,因此从总体上说,CVaR是一种可以覆盖更大风险的度量工具,再用CVaR的计算结果与实际风险相比较,可以看出CVaR确实可以有效降低实际失败的次数．并且更加保守严谨的估计股票市场风险。     

CVaR模型的有效边界与组合选择

CVaR模型是经典马柯维茨均值一方差模型的直接推广,即由CVaR来直接代替方差作为风险约束条件,使得投资组合模型在新的度量标准下更加合理。本文证明了基于CVaR约束下投资组合模型有效边界的上凸性,并在收益为正态分布的假定下,结合负指数效用函数,解决了投资组合的选择问题,求得具体的显示解,并得出与均值一方差模型相一致的结论。     

Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective

Internal credit risk modelling is important for banks for the calculation of capital adequacy in terms of the Basel Accords, and for the management of sectoral exposure. We examine Credit Value at Risk (VaR), Conditional Credit Value at Risk (Credit CVaR) and the relationship between market and credit risk. Significant association is found between different Credit CVaR methods, and between market and credit risk. Simpler Credit CVaR methods are found to be viable alternatives to more complex methodology. The relationship between market and credit risk is used to develop a new model that allows banks to incorporate industry risk into transition modelling, without macroeconomic analysis.     

Minimizing CVaR and VaR for a portfolio of derivatives

Value at risk (VaR) and conditional value at risk (CVaR) are frequently used as risk measures in risk management. Compared to VaR, CVaR is attractive since it is a coherent risk measure. We analyze the problem of computing the optimal VaR and CVaR portfolios. We illustrate that VaR and CVaR minimization problems for derivatives portfolios are typically ill-posed. We propose to include cost as an additional preference criterion for the CVaR optimization problem. We demonstrate that, with the addition of a proportional cost, it is possible to compute an optimal CVaR derivative investment portfolio with significantly fewer instruments and comparable CVaR and VaR. A computational method based on a smoothing technique is proposed to solve a simulation based CVaR optimization problem efficiently. Comparison is made with the linear programming approach for solving the simulation based CVaR optimization problem.     

The relationship between conditional value at risk and option prices with a closed-form solution

Options and CVaR (conditional value at risk) are significant areas of research in their own right; moreover, both are important to risk management and understanding of risk. Despite the importance and the overlap of interests in CVaR and options, the literature relating the two is virtually non-existent. In this paper we derive a model-free, simple and closed-form analytic equation that determines the CVaR associated with a put option. This relation is model free and is applicable in complete and incomplete markets. We show that we can account for implied volatility effects using the CVaR risk of options. We show how the relation between options and CVaR has important risk management implications, particularly in terms of integrated risk management and preventing arbitrage opportunities. We conduct numerical experiments to demonstrate obtaining CVaR from empirical options data.     

基于Copula的商业银行信用-汇率风险整合的实证研究

本文对不同族类、不同种类Copula函数进行比较分析,基于深圳发展银行、上海浦东发展银行、中国民生银行信用收益率和汇率收益率的经验数据进行实证研究与分析,用经验累积分布函数拟合信用收益率和汇率收益率的边缘分布,ArchimedeanCopula函数描述三家银行的信用收益率和汇率收益率的相关关系。在各个置信度下,运用拟合度最优的Copula函数求出各自的信用-汇率风险的VaR（Value—at—risk）值和CVaR（Condifonal Value-at-risk）值,并比较三家银行整合风险的大小,为金融机构决策者的监管提供参考。     

利率市场化条件下我国商业银行资产负债管理技术研究

随着货币市场的完善和利率市场化的发展,利率对我国商业银行收益水平的影响开始显现,适时引入资产负债管理技术对我国商业银行盈利水平的提高具有重要的现实意义和应用价值。本文以我国部分商业银行收益状况分析为基础,通过对目前国外主要资产负债管理技术的回顾,提出了符合我国国情的商业银行资产负债管理技术策略。     

国有商业银行信贷评级模型的构建及实证检验

信贷评级是信贷风险管理的前提,目前我国国有商业银行都采用这一方式管理信贷风险.本文在对国有商业银行当前信用评级方法存在问题和国内外相关研究成果进行分析的基础上,提出了构建国有商业银行内部信用评级模型,提高信贷风险管理水平的建议.作者利用贷款历史数据,通过因子分析和聚类分析等方法构建内部信用评级模型;通过因子分析方法构建的模型使评级指标体系更加科学、合理,避免了反映风险信息的冗余与遗漏;聚类分析使评级模型直接与违约概率挂钩,度量风险的准确性进一步提高.论文最后对模型进行了实证分析,使其有效性得到了检验.     

Long-only equal risk contribution portfolios for CVaR under discrete distributions

Portfolios in which all assets contribute equally to the conditional value-at-risk (CVaR) represent an interesting variation of the popular risk parity investment strategy. This paper considers the use of convex optimization to find long-only equal risk contribution (ERC) portfolios for CVaR given a set of equally likely scenarios of asset returns. We provide second-order conic and non-linear formulations of the problem, which yields an ERC portfolio when CVaR is both positive and differentiable at the optimal solution. We identify sufficient conditions for differentiability and develop a heuristic that obtains an approximate ERC portfolio when the conditions are not satisfied. Computational tests show that the approach performs well compared to non-convex formulations that have been proposed in the literature.     

A theory of systemic risk and design of prudential bank regulation

Systemic risk is modeled as the endogenously chosen correlation of returns on assets held by banks. The limited liability of banks and the presence of a negative externality of one bank’s failure on the health of other banks give rise to a systemic risk-shifting incentive where all banks undertake correlated investments, thereby increasing economy-wide aggregate risk. Regulatory mechanisms such as bank closure policy and capital adequacy requirements that are commonly based only on a bank’s own risk fail to mitigate aggregate risk-shifting incentives, and can, in fact, accentuate systemic risk. Prudential regulation is shown to operate at a collective level, regulating each bank as a function of both its joint (correlated) risk with other banks as well as its individual (bank-specific) risk.     

When more is less: Using multiple constraints to reduce tail risk

Financial institutions suffered large trading losses during the 2007–2009 global financial crisis. These losses cast doubt on the effectiveness of regulations and risk management systems based on a single Value-at-Risk (VaR) constraint. While some researchers have recommended using Conditional Value-at-Risk (CVaR) to control tail risk, VaR remains popular among practitioners and regulators. Accordingly, our paper examines the effectiveness of multiple VaR constraints in controlling CVaR. Under certain conditions, we theoretically show that they are more effective than a single VaR constraint. Furthermore, we numerically find that the maximum CVaR permitted by the constraints is notably smaller than with a single constraint. These results suggest that regulations and risk management systems based on multiple VaR constraints are more effective in reducing tail risk than those based on a single VaR constraint.