基于极值理论的人民币汇率风险测度

为了克服传统VaR计算方法在处理厚尾分布时的缺陷,本文引入极值理论中的阈值模型建模,对人民币/欧元汇率风险进行测度,然后对使用极值理论方法计算VaR的效果作了返回测试,最后对金融机构和企业的汇率风险管理工作提出了政策建议。     

POT模型在商业银行信用风险度量中的应用

由于银行信用风险的损失分布具有鲜明的厚尾性,所以应用一般的风险计算方法往往会低估银行信用风险、而应用极值理论计算风险时能更有效地捕捉可能导致银行重大损失的尾部风险。所以把极值理论应用于银行信用风险量化分析不失为一种比较理想的方法。     

金融风险度量的主要问题及解决

金融风险度量理论、资产组合理论和资本定价理论奠定了现代金融管理理论的基石,其中风险度量理论更是基石中的基石。随着世界范围内金融市场的不断繁荣和金融环境不稳定性的加剧为金融风险的准确、及时有效的度量提出了迫切要求。本文在介绍金融风险度量的理论研究背景和理论用于实际的具体情况后重点围绕金融资产回报的分布问题及解决问题的方法进行了深入分析,它包括金融资产回报分布的厚尾问题,极值分布的条件,分布的完整性,组合资产回报极值分布。     

基于极值理论的沪综指尾部风险度量

以沪综指为实证研究对象,利用AR-GARCH模型捕获沪综指对数收益序列中的自相关和异方差现象,获得近似独立同分布的残差序列,再利用极值理论中的POT方法对残差序列进行极值分析,并采用给出了极值分布的各参数极大似然估计,进一步计算置信水平下的VaR值,结果表明,根据AR-GARCH-POT方法所得的VaR对沪综指实际损失风险的刻画准确。而基于所得的VaR序列分析沪综指收益率的系统性风险历史波动趋势,结果发现系统性风险历史趋势存在先高后低,且自2006年后逐年升高的特征,目前阶段的总体性风险处于较高水平。     

基于极值理论以MH方法研究我国黄金现货的风险价值

本文针对金融时间序列数据存在的尖峰厚尾特性,应用极值理论对数据尾部进行建模,用GPD分布拟合尾部特征,计算我国黄金现货的风险价值（ value at risk）,以对黄金投资者进行风险提示。针对现有VaR计算中主流方法的缺陷,本文应用基于马尔科夫链蒙特卡洛（ Markov Chain Monte Carlo, MCMC）模拟的方法对POT模型进行估计,以克服传统Monte Carlo模拟的高维、静态性缺陷,以提高估算精度,从而得到相应的风险价值。通过对我国黄金现货Au9995的实证分析和计算,可以根据过去的数据预测未来的在险值。     

应用极值理论度量金融风险价值——用VaR测度认识J．P．morgan的巨额亏损

极值理论EVT是统计学的一个重要分支,它主要关注于极端事件的概率分布及其性质。极值理论现今广泛的应用于破产理论,保险理论、资产分配和风险度量等现在金融理论中。本文旨在通过使用极值理论基于SAS和Matlab编程计算摩根大通（CJ．P．nlor-gan）的风险价值（Value at Risk）并以此来认识摩根大通因交易员操作失误带来的巨大亏损的现象,从而在理论和实际操作上掌握风险价值度的相关知识。     

基于极值理论的可转债在险价值动态预测研究

在对可转换债券指数统计特性分析的基础上,针对其收益率的左偏及尖峰现象,利用极值分布GPD对其尾部有效拟合,充分考虑极端值对VaR估计的影响,并利用滑动窗口方法进行VaR动态预测。采用kupiec的失败频率检验法进行VaR样本内和样本外检验,发现基于极值理论的可转债VaR方法,其估计和动态预测结果都明显优于基于偏t分布的Risk Metrics方法的测试结果,控制风险的能力适合可转债市场的要求。     

给定效用函数条件下确定风险资产最优投资比例的方法

传统上投资组合风险资产与无风险资产之间投资比例的确定采用的是非线性约束下求极值的方法,但在具体运用时比较繁杂。本文提出在特定的假设下引入效用函数计算风险资产投资比例,大大简化了其计算过程。     

基于FIGARCH-EVT模型的极端风险度量

多项实证研究表明多数金融资产的收益率序列呈现尖峰厚尾的非正态分布,波动率具有聚集性和持续性等特点,因此传统的基于正态分布的VaR和ES模型无法有效捕捉收益率序列的尾部信息,忽视了波动的时变性,从而低估金融资产存在的风险。考虑到金融资产收益序列的时变性和尖峰厚尾的特点,本文采用FIGARCH模型与极值理论中的EVT模型相结合的方法来研究我国证券市场存在的市场风险,并进行有效合理的度量。通过比较分析与返回检验发现,基于FIGARCH-EVT模型的风险度量方法要明显优于传统的纯极值理论方法和GARCH-EVT模型。     

基于调制域的雷达信号脉内特征提取新方法

针对传统调制域检测法在提取雷达信号脉内特征中的不足,提出了一种通过检测极值点来提 取信号脉内特征的方法。首先通过检测出信号极值点,再对极值点进行运算处理,进而提取 出极值点中包含的脉内特征信息。该方法借助于极值点具有最大信息量的优势,并运用二次 提取频率来估计码元宽度,使得算法的信噪比性能得到有效改善。仿真结果表明,与传统调 制域检测法相比,该方法在低信噪比下对于多种类型信号的脉内特征参数的估计精度平均提 高30%。     

基于极值理论的沪深股市VaR和CVaR分析

将VaR和CVaR结合起来能全面描述金融时间序列与尾部相关的风险。考虑沪深股指收益序列胖尾特性,极值理论方法能够对沪深股市VaR和CVaR进行较好估计,运用基于Boot strap和极大似然估计方法解决极值理论数据不足的缺陷,从而给出对VaR和CVaR的点估计和区间估计。     

Back to the future: Futures margins in a future credit default swap index futures market

The introduction of exchange‐traded credit default swap (CDS) index futures is eminent and this development in the credit market is the subject of this article. A theoretically appealing and practically implementable approach to computing accurate futures margins based on extreme value theory is suggested. The approach is then exemplified with a study of the increasingly popular iTraxx Europe CDS index market. Although this market is not organized through an exchange and is not a futures market, the empirical results together with an arbitrage argument nonetheless suggest margin levels in a future exchange‐traded CDS index futures market computed using extreme value theory to be superior to those computed using the traditional normal distribution or the actual historical distribution. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:85–104, 2007     

权证定价中基于GARCH模型族的波动率研究

传统的权证定价方法假定标的证券收益率服从对数正态分布。但现实世界中标的证券收益率却具有尖峰厚尾分布,波动率的聚集性,证券市场的"杠杆作用"等特征,因而传统定价结果可能导致偏差较大。为此,本文以随机波动率代替历史波动率的假设,消除金融时间序列的异方差性的影响;运用GARCH模型族中的3种模型(GARCH,EGARCH,GJR-GARCH)对其进行参数估计,及权证定价对比;还分别就历史与随机波动率的差别、对称型与非对称型GARCH模型的差别,以及理论与实际的差别进行了比较分析。结论得出这种差别的来源,并对此进行了探讨。     

Are regional trading arrangements trade creating?: An application of extreme bounds analysis

In this study, we use extreme bounds analysis to test the robustness of the hypothesis that regional trading arrangements (RTAs) are trade creating. Extreme bounds analysis provides a more rigorous test of specification uncertainty than traditional econometric theory by incorporating prior information and using a systematic approach to testing the fragility of coefficient estimates. The results show that the trade creation effect of most RTAs is fragile. Using a least squares estimator where all weight is attached to the sampling distribution, eight or more of the twelve RTAs considered are found to be trade creating. When the relative weight in the estimation is shifted from the sampling to the prior distribution, the number of RTAs that are trade creating falls to six at the 95 percent likelihood ellipsoid. Moreover, when we specify that not all RTAs are trade creating, four RTAs increase trade at the 95 percent likelihood ellipsoid. At the extreme bounds, when all weight is attached to the prior distribution, none of the RTAs are found to be trade creating. As a result, we conclude that the pervasive trade creation effect found in the literature reflects not the information content of the data but rather the unacknowledged beliefs of the researchers.     

基于GP分布拟合检验的BPSK/QPSK信号调制识别

针对二进制相移健控(Binary Phase Shift Keying,BPSK)/正交相移键控(Quadrature Phase Shift Keying,QPSK)相位编码信号的调制识别问题,提出了一种基于广义帕雷托(General Pareto,GP)分布拟合优度检验的识别算法。基于极值分布理论,利用观测信号的平方幅度谱构建其超阈值序列,通过检验超阈值序列的分布是否近似服从GP-I分布来实现对BPSK/QPSK调制方式的分类识别。在不同条件下,大量仿真结果证明了所提算法的有效性,并且和已有的调制信号识别算法相比,所提算法具有更好的识别性能。     

Value at risk and conditional extreme value theory via markov regime switching models

This study develops a new conditional extreme value theory‐based (EVT) model that incorporates the Markov regime switching process to forecast extreme risks in the stock markets. The study combines the Markov switching ARCH (SWARCH) model (which uses different sets of parameters for various states to cope with the structural changes for measuring the time‐varying volatility of the return distribution) with the EVT to model the tail distribution of the SWARCH processed residuals. The model is compared with unconditional EVT and conditional EVT‐GARCH models to estimate the extreme losses in three leading stock indices: S&P 500 Index, Hang Seng Index and Hang Seng China Enterprise Index. The study found that the EVT‐SWARCH model outperformed both the GARCH and SWARCH models in capturing the non‐normality and in providing accurate value‐at‐risk forecasts in the in‐sample and out‐sample tests. The EVTSWARCH model, which exhibits the features of measuring the volatility of a heteroscedastic financial return series and coping with the non‐normality owing to structural changes, can be an alternative measure of the tail risk. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:155–181, 2008     

审计功能的管理学基础研究

审计的产生源于管理实践的需要,并随着管理实践的发展而发展,管理是审计的基础和出发点。因此,审计功能的拓展也是以管理实践的发展为基础,并且随着管理理论的发展而突破传统审计功能的范畴,产生了与传统经济责任事后监督有着本质区别的社会经济责任审计功能,管理理论的不断发展推动着审计理论的发展,产生建立在现代管理学基础之上的新的审计理论和审计方法,审计学科的建设应当顺应大管理需要大审计的发展趋势。     

Time variation in the tail behavior of Bund future returns

The literature on the tail behavior of asset prices focuses mainly on the foreign exchange and stock markets, with only a few articles dealing with bonds or bond futures. The present article addresses this omission. It focuses on three questions using extreme value analysis: (a) Does the distribution of Bund future returns have heavy tails? (b) Do the tails change over time? (c) Does the tail index provide information that is not captured by a standard VaR approach? The results are as follows: (a) The distribution of high‐frequency returns of the Bund future is indeed characterized by heavy tails. The tails are thinner for lower frequencies, but remain significantly heavy even for daily data. (b) There are statistically significant breaks in the tails of the return distribution. (c) The likelihood of extreme price movements suggested by extreme value theory differs from that obtained by standard risk measures. This suggests that the tail index does indeed provide information not contained in volatility measures. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:387–398, 2004     

基于系统动力学的平衡计分卡理论及其应用

当今时代急剧变化的外部环境对企业的绩效管理水平提出了新的要求,传统的绩效管理方法已经不能满足企业的需要。平衡计分卡作为一种重要的战略绩效管理方法,一经提出就受到了广泛的关注和应用,但是平衡计分卡自身也存在动态复杂性不足等理论缺陷。在分析平衡计分卡和系统动力学两者关系的基础上,给出两者相结合的实施步骤,为战略绩效管理提供决策支持。