Oil price and FX-rates dependency

Oil prices and exchange rates against the dollar have both experienced long swings over the recent decade. Regardless of the great amount of research, some issues are still open to debate. In this vein, this paper focuses on the evolution of the relationship between oil prices and dollar exchange rates of 12 oil exporting and oil importing countries based on a dynamic copula approach. We use daily data for two 5-year periods between 2003 and 2013, taking the collapse of Lehman Brothers as the dividing point. Our results have four main implications: first, the intensity of relationship between oil prices and FX-rates has increased over time even if the peak of the financial crisis is included. Second, the increased tail dependency shows that extreme events are likelier to occur simultaneously for both series. Third, the dependency has become more dynamic after the financial crisis and is therefore better characterized by time-varying copulas. Finally, currencies of oil importers and oil exporters display a different dependency structure against the US dollar in the case of rising oil prices with the latter appreciating and the former depreciating.     

Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns

This study investigates the bias adjustment for mean–variance efficient portfolio frontiers due to population mean and variance estimation error in Taiwan stock market. Although Siegel and Woodgate (2007; Management Science, 53, 1005–1015) and Kan and Smith (2008; Management Science, 54, 1364–1380) suggested two portfolio frontiers that improved upon the out-of-sample performance of a traditional sample portfolio frontier. However, this study shows that, using the copula function and Gram-Charlier series, the two frontiers are theoretically biased toward the actual frontier unless returns behave normally, and the bias is related to the return skewness and kurtosis. Indeed, the two frontiers are empirically biased to the lower-left side of the actual ones, because the Taiwan stock returns are right-skewed and highly leptokurtic. Thus, this study thus proposes revised portfolio frontiers that are closer to the actual frontier than unrevised ones. This improvement may enhance the estimation accuracy of the capital market line, and hence this study can provide an effective investment reference.     

资产证券化与银行体系稳定性研究

本文基于美国主要银行资产证券化面板数据的回归模型和单因素联结模型,研究资产证券化对银行个体和系统性风险的影响。研究结果发现,对于银行个体而言,开展资产证券化业务并不会影响其稳定性,而持有证券化资产则会对其稳定性产生不利影响。对于银行系统而言,证券化资产在银行系统内和系统外不同的配置情况将导致不同的风险结果。市场上的过度证券化行为以及由资产证券化引起的银行间收益相关性的上升可能会导致较大的系统性风险。最后,本文基于美国的研究结果对我国银行开展资产证券化业务提出相应的对策建议。     

基于动态VaR模型和Copula函数的省级政府平台公司投资风险测度

省级政府投融资平台公司在城镇化建设中发挥着重要作用,其投融资风险问题亦逐渐引起重视。基于平台公司的投资收益会随着市场等宏观环境的变化而波动的考虑,将平台公司的项目投资资产视为金融资产而度量其风险状况。考虑单笔投资的情形,建立极值理论和SV-t模型的相结合平台公司一维融资风险动态VaR模型;进而考虑多笔投资间的非线性关系,结合Copula函数和蒙特卡洛模拟思路,建立平台公司多维融资风险度量模型。所构建的模型避免了传统研究的强主观性,并实现了投资风险的实时、动态度量。     

An analysis of dynamic risk in the Greater China equity markets

This study looks at the time-varying nature of systematic risk in the Greater China equity markets. The Shanghai and Shenzhen markets both have a low average systematic risk when measured against the world market. The short outbursts in systematic risk for these two markets seem to be directly related to policy shifts. The Hong Kong and Taiwan markets are more integrated with world markets and they show signs of large variations in systematic risk over time. Furthermore, conditional betas in the Shanghai and Shenzhen markets are stationary, while the Hong Kong and Taiwan betas are integrated of order one. In addition, long memory tests show that all four markets exhibit a long-run dependence in their conditional betas. While the two mainland China market betas are covariance stationary, the Hong Kong and Taiwan betas are not.     

一种指数形式时变加权的机载双基雷达STAP算法

针对机载双基雷达杂波距离向分布非平稳,统计型空时自适应处理技术杂波抑制性能急剧下降问题,提出一种基于指数形式时变加权算法。该方法引入距离的非线性函数表示杂波的变化特性,通过对样本数据进行指数形式扩展,实现杂波非平稳分布的补偿。理论分析和仿真实验表明,所提方法能有效抑制来自不同距离的双基杂波,在急剧变化的杂波环境下性能优于时变加权法和局域处理法。     

居民家庭金融资产组合集成风险的测量与波动分析

居民家庭金融资产在不同时期风险的聚集可能会引发宏观金融风险, 甚至导致金融危机。 因此, 文章试图测算家庭金融资产组合风险并描述其变动特点。 首先构建家庭金融资产组合的 Copula 函数, 然后计算其VaR 值, 并比较分析 VaR 值与各金融资产收益的变动关系 , 发现当金融资产中高风险资产的收益低于 VaR 值下限时, 家庭金融资产风险不断积聚并达到高点, 而这个过程与金融危机发生的时间相契合。 家庭金融资产组合风险和资产中的风险资产收益会影响未来的利率和 CPI 的变化。     

资产配置分析中风险度量工具发展研究

现代金融市场的迅猛发展,使全球金融市场联动性增强,同时也使得市场风险成为金融机构和投资者面临的主要风险,20世纪90年代以来发生的一些金融灾难性事件使得人们越发意识到风险管理的重要性。因此,从投资组合理论开始梳理资产配置分析中的风险度量工具。     

两类混合藤Copula模型的比较研究——基于外汇资产投资组合VaR的研究

本文以中国外汇市场上四种主要外汇资产的投资组合作为研究对象,基于Pair Copula高维建模思想,分别建立了两类能真实反映资产组合相关结构差异性的混合藤Copula模型,即混合C藤和混合D藤Copula模型。两类混合藤Copula模型,对传统的藤Copula模型作了进一步的改进,是通过一定的选择标准,确定模型中每个Pair Copula函数的最优函数族,这样可以使得所建立的模型既能考虑资产组合维数的影响,又能捕捉到组合内部各资产相关结构的差异性。为了得到较优的风险分析模型,在实证研究中,将两类模型在资产组合VaR计算精度方面进行比较。     

消费者价格指数和生产者价格指数相关性研究——基于Copula函数

利用Copula函数,基于2004.1-2012.3的消费者价格指数(CPI)和生产者价格指数(PPI)数据,文章实证分析CPI和PPI的相互关系;通过平方欧式距离检验,认为t-Copula函数是所有Copula函数中对CPI和PPI的拟合程度最优,计算结果表明CPI、PPI存在对称的尾部相关性,两者表现出同时上涨或同时下跌的状态;全国消费者价格指数NCPI、城市消费者价格指数UCPI和农村消费者价格指数RCPI与PPI的尾部相关系数分别为0.4192、0.4560和0.2136,农村相对城市自给自足成分较高和消费结构的差异,PPI对RCPI的影响程度要弱于对UCPI的影响程度。