基于条件在险价值(CVaR)建立新的基金业绩测度指标，该指标在理论上拓展了经典的夏普比率。在正态分布下，该指标是夏普比率的增函数，二者对于基金业绩排名是一致的；在非正态分布下，该指标克服夏普比率没考虑高阶矩、不满足随机占优单调性的缺陷，能给出更为合理的基金业绩排名。利用方差法、经验分布法和核估计法对新指标进行估计，蒙特卡洛模拟结果表明，方差法仅在正态分布下有效，在非正态分布下其估计结果存在系统性偏差；同属于非参数方法的经验分布法和核估计方法在任意分布下都具有大样本性质且估计精度相当。最后运用新指标对我国开放式基金的业绩进行测算和排名，结果显示：当各基金的偏度系数和峰度系数差异较小时，夏普比率和新指标给出的基金业绩排名基本一致；而当各基金的偏度系数和峰度系数差异较大时，二者给出的基金业绩排名差异较大，新指标因考虑了高阶矩信息给出的排名更为合理，这与理论预期是一致的

This research explores the effects of adding bitcoin to an optimal portfolio (naïve, long-only, unconstrained and semi-constrained) of by relying on mean-CVaR approach in Chinese market. Then backtesting to compare the performance of portfolios with and without bitcoin for each scenario is performed. Results show significant but weak correlations between various asset classes and bitcoin, implying a more mature financial profile of bitcoin in China compared to that in the west. Backtesting results show that the effect of adding bitcoin to optimal portfolios is not consistent over the entire out-of-sample period. The naïve and the long-only strategy improved the risk reward ratio up until the late 2013 price-crash with no significant advantages thereafter. Shorting strategies on the other hand, with or without leverage, fail to produce more efficient portfolios when bitcoin is added, and this is consistent over the entire out-of-sample period. The results also show that semi-annual rebalancing amplifies the advantages of adding bitcoin to most portfolios except for the semi-constrained portfolio, although the weights analysis show significant shifts in weights which might not represent a feasible strategy in realistic scenarios.

This research explores the effects of adding bitcoin to an optimal portfolio (naïve, long-only, unconstrained and semi-constrained) of by relying on mean-CVaR approach in Chinese market. Then backtesting to compare the performance of portfolios with and without bitcoin for each scenario is performed. Results show significant but weak correlations between various asset classes and bitcoin, implying a more mature financial profile of bitcoin in China compared to that in the west. Backtesting results show that the effect of adding bitcoin to optimal portfolios is not consistent over the entire out-of-sample period. The naïve and the long-only strategy improved the risk reward ratio up until the late 2013 price-crash with no significant advantages thereafter. Shorting strategies on the other hand, with or without leverage, fail to produce more efficient portfolios when bitcoin is added, and this is consistent over the entire out-of-sample period. The results also show that semi-annual rebalancing amplifies the advantages of adding bitcoin to most portfolios except for the semi-constrained portfolio, although the weights analysis show significant shifts in weights which might not represent a feasible strategy in realistic scenarios.

本文提出国债组合投资的多阶段随机规划模型，导出基于未来利率市场不确定信息的具备动态调整 特点的国债组合积极投资策略。该模型采用利率水平、斜率和曲率的“三位一体”的离散情景树刻画未来 利率期限结构动态演化过程，其中特别考虑了广义货币供给变动的影响；通过最小化国债组合收益的CVaR 风险，对国债组合进行积极动态配置；同时兼顾国债投资安全性、流动性和收益性等要求，实现了国债组 合投资与管理中利率风险规避和收益能力的有效匹配。实证研究表明，与传统久期配比免疫模型相比，该 模型确定的最优策略不仅能够为国债组合提供更强的抵御利率风险能力，同时能够稳步提升其收益空间， 对于金融机构实现国债投资的积极管理具有重要参考价值。

当资产回报率服从椭圆分布和投资者具有二次效用函数的假设都不满足时，方差（标准差）不再是风险的一个恰当度量方法，而这会导致传统的最小方差套期保值存在缺陷。本文提出了一个新的基于核密度估计的计算最小VaR 和最小CVaR 套期保值比率的非参数方法。基于沪深300 现指日收盘价格数据和沪深300 股指期货合约仿真交易日结算价格数据的实证结果表明，本文提出的改进的非参数方法表现最优，最大程度上降低了套期保值投资组合的标准差、VaR 和CVaR。

随着风险度量一致性原则的提出，研究发现金融机构广泛采用的VaR模型存在严重不足，尤其针对分布具有厚尾特征的极端金融风险无法有效度量。本文采用极值理论（EVT）解决VaR方法的尾部度量不足问题，利用CVaR-EVT和BMM模型分析美国、香港股票市场和我国沪深两市指数18年的日收益数据，研究发现：（1）在95％置信区间及点估计中，分位数为99%的CVaR-EVT所揭示的极端风险优于VaR的估计值；且BMM方法为实施长期极端风险管理提供了有力决策依据，其回报率受分段时区的影响，期间越长，风险估计值越高；（2）模型采用ML和BS方法统计估值显示，我国股票市场极端风险尾部估计值高于香港和美国市场；但是，国内市场逐步稳定，并呈现出跟进国际市场且差距缩小的发展趋势。

The ignorance of market friction causes the invalid portfolio investment, and whether the arrangement of capital structure is reasonable will influence the income of funding cost, effective utilization of non-selfowned and funding risk level. Therefore, portfolio model under the assumption of complete market lacks of practically instructiveness. Capital structure factor and transaction cost do influence the portfolio decision in the capital market. On the basis of capital structure factor and transaction cost during the process of investment, this article improve the portfolio model that CVaR control proposed by Rockafeller and Uryasev, built a CVaR portfolio model with capital structure factor and transaction cost. Empirical studies indicates that the changes of capital structure factor and transaction cost lead to the movement of efficient frontier on CVaR portfolio model and the changes of upper and lower limit.

整合风险的量化管理已成为现代商业银行风险管理的发展趋势，信用风险与市场风险是其面临的两种极为重要的风险，对二者进行整合度量是全面风险管理的重要内容。Copula函数能够描述两不同类型风险间的相依结构，本文以单一Copula为基础构造混合Copula函数，并构建基于混合Copula函数的VaR及CVaR模型, 以用于度量整合风险值。实证研究表明，混合Copula函数是描述两不同类型风险相依结构的最优模型，且基于混合Copula的VaR及CVaR估计值也是最有效的，由此可知混合Copula比单一Copula函数能更全面的反映整合风险间的相依程度与相依模式。

本文研究了沪深300股指和股指仿真交易收益率极端风险和相依关系。用DCC-GARCH模型描述了股指期货和现货之间动态的条件相关系数，并以极值分布为边际分布对四种常用的Copula函数进行了拟合，发现Frank Copula的拟合效果最好，其次为Clayton Copula。在此基础之上，对不同组合的VaR和CvaR进行测度，发现投资组合比例与风险之间呈现“U”型特征，这也为套期保值提供了一种新的研究方式。

内容摘要：养老基金、公益基金是典型的风险厌恶者，需要刚性规则进行限制和管理风险，同时需要追踪和匹配适当负债。作者综述资产负债匹配的一般模型以及最新模型，并发展CVAR限制下组合优化模型，研究养老基金和公益基金的动态资产配置。 关键词： 养老基金 公益基金 资产配置 ABSTRACT: As typical risk-aversion，we need rigid rules to restrict and manage risks of pension funds，public welfare funds meanwhile tracking and matching equity, this paper develops the asset-liability matching models of pension funds，public welfare funds using CVAR constrains and indexation method ,furthermore to achieve dynamic equity matching.