内部附加信息下的风险最小套期保值策略

在跳扩散价格模型下,利用扩大信息流方法解决了内部信息者的风险最小套期保值问题.首先构建了内部信息市场模型,提出了内部附加信息下的风险最小套期保值问题.然后利用利用风险资产价格的Markov性、Ito公式得到了内部信息下的风险最小套期保值策略的显式表示.     

基于蒙特卡罗模拟的供应链风险估计研究

以市场需求波动风险为例,基于蒙特卡罗模拟研究了供应链风险估计问题.首先,对市场需求波动风险及其损失度量进行理论分析,利用市场需求波动风险情境下的供应链系统库存成本损失来度量市场需求波动风险的损失.其次,选择供应链末端需求为蒙特卡罗方法待模拟的随机变量,基于需求建立了市场需求波动风险概率测度模型和风险损失度量模型,确定了市场需求波动风险概率和风险损失为需求的相关量.然后,通过实例的仿真求解验证了模型.最后,给出了利用本模型方法进行供应链风险估计时需要注意的问题及进一步研究的问题.研究表明:蒙特卡罗方法对供应链风险估计具有较强的鲁棒性.     

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本文讨论了信用衍生产品之一的总收益互换的定价问题. 其中涉及到利率风险和违约风险, 本文利用HJM利率模型来刻画利率风险, 并利用强度模型和混合模型对违约风险进行建模. 分别考虑了违约时间与利率无关时总收益互换合约的定价问题, 以及违约时间与利率相关时总收益互换合约的定价问题, 给出了相应的定价模型, 并用蒙特卡罗模拟方法得到定价问题的数值解.     

具有投资限制的风险资产模糊随机投资组合模型

研究了模糊随机环境下风险资产投资组合选择问题.利用模糊随机变量刻画风险资产的收益率,建立了具有投资限制的风险资产投资组合选择的一般模糊随机均值-方差模型,该模型包括了是否允许卖空及具有投资比例下界约束的情况.在此基础上,提出了具有梯形模糊随机收益率的具体投资组合优化模型,这些模型能够转化为二次规划问题求解.最后,利用上证50指数中的9种股票对模型进行了实证分析,结果表明模型能够有效分散非系统性风险.     

离散时多元风险模型的破产概率

本文研究了离散时多元风险模型的破产概率问题.利用经典大偏差的方法,获得了有限水平的破产概率,推广了离散时一元风险模型的相应结论.     

离散时多元风险模型的破产概率

本文研究了离散时多元风险模型的破产概率问题. 利用经典大偏差的方法, 获得了有限水平的破产概率, 推广了离散时一元风险模型的相应结论.     

一类逐段决定风险模型罚金函数的期望(英)

本文主要考虑了一类逐段决定的风险模型的罚金函数.利用建立的积分-微分方程,我们得出了此类风险模型罚金函数期望的一般解.     

价格一致性系统与风险偏好

本文研究了风险偏好问题.利用简单市场模型,讨论了个人风险偏好和市场风险偏好,给出了两种风险偏好的数学定义,该定义具有自然直观的经济学意义.     

一类推广负风险和模型的破产概率

本文研究了带干扰的两险种负风险和模型的破产问题.利用无穷小方法,给出了该风险模型破产概率所满足的微分-积分方程,并推导出破产概率满足的Lundberg型不等式.最后指出了当索赔服从负指数分布时破产概率的上界,推广了经典风险模型的结果.     

一类带扰动和附索赔风险模型的破产概率

本文研究带扰动和附索赔的风险模型.利用鞅方法,得到了破产概率的指数上界及精确表达式,推广了不带扰动的风险模型相应的结论.     

债券违约是否存在区域传染？——基于中国债券市场融资成本视角

2018年以来中国债券市场违约规模攀升,累计违约金额超2900亿元。债券违约后的负面影响受到投资者、发行人乃至监管部门关注。本文以北京、上海、辽宁等八个辖区为例,选取2016~2019年债券违约及债券发行数据,通过构建违约事件对债券发行价格影响因素模型,分析了债券违约的区域传染效应。研究发现:债券违约引发的信用风险存在区域传染性,主要体现为债券发行前若发行人所属辖区存在违约事件将推升债券融资成本;区域内的传染效应与违约时间距离负相关,当时间距离增长时,传染效应变弱,甚至消失;债券违约风险对不同性质企业的传染效应不同,民营企业受影响尤为显著。     

基于W-SVM的民营环保企业信用风险预警模型

2019年中国绿色债券发行量依旧稳居世界前列,成为民营环保企业重要融资渠道,但是2018年至今,大量环保企业信用风险事件频发为我们敲响了警钟,构建合适的民营环保企业信用风险预警机制迫在眉睫.环保产业属于新兴产业,并以国有企业为主导,民营企业的样本数据具有样本量小,维度高等特征,这导致传统的信用风险模型适用性不强.因此选用加权支持向量机模型,对不同类别样本采取不同权值,选取大量财务特征,最终构建出风险预警模型．研究发现加权支持向量机模型具有十分优秀的预警性能.环保企业本身具有资金回收周期较长并且项目前期投入较高等特点,建议加强财务管理,保障资产流动性,建立完善产业链.     

基于双因子CIR强度式定价的信用债券投资组合优化

信用风险和利率风险是相互关联影响的。资产组合优化不能将这两种风险单独考虑或简单的相加,应该进行整体的风险控制,不然会造成投资风险的低估。本文的主要工作:一是在强度式定价模型的框架下,分别利用CIR随机利率模型刻画利率风险因素“无风险利率”和信用风险因素“违约强度”的随机动态变化,衡量在两类风险共同影响下信用债券的市场价值,从而构建CRRA型投资效用函数。以CRRA型投资效用函数最大化作为目标函数,同时控制利率和信用两类风险。弥补了现有研究中仅单独考虑信用风险或利率风险、无法对两种风险进行整体控制的弊端。二是将无风险利率作为影响违约强度的一个因子,利用“无风险利率因子”和“纯信用因子”的双因子CIR模型拟合违约强度,考虑了市场利率变化对于债券违约强度的影响,反映两种风险的相关性。使得投资组合模型中既同时考虑了信用风险和利率风险、又考虑了两种风险的交互影响。避免在优化资产组合时忽略两种风险间相关性、可能造成风险低估的问题。     

债券定价及利率风险的市场价格的重构方法

假设利率变化的模型是由随机微分方程给出,则可以用推导Black-Scholes方程的方法来推出债券价格满足的偏微分方程,得到一个抛物型的偏微分方程.但是,在债券定价的方程中隐含有一个参数λ称为利率风险的市场价格.所谓债券定价的反问题,就是由不同到期时间的债券的现在价格来得到利率风险的市场价格.对随机利率模型下债券定价的正问题先给予介绍和差分数值求解方法,并介绍了反问题,且对反问题给出了数值方法.     

带有违约风险的可转换债券的简约型定价

本文考虑简约模型下带有违约风险的可转换债券的定价问题.假定市场中可转换债券的违约强度满足Vasicek模型,利用鞅方法获得了该模型下可转换债券的定价公式.此外,我们通过数值分析显示了模型参数变化对可转换债券价值影响的敏感性程度,结果也表明违约风险将降低可转换债券的价值.     

Credit spreads, endogenous bankruptcy and liquidity risk

In this paper, we consider a bond valuation model with both credit risk and liquidity risk to show that credit spreads are not negligible for short maturities. We adopt the structural approach to model credit risk, where the default triggering barrier is determined endogenously by maximizing equity value. As for liquidity risk, we assume that bondholders may encounter liquidity shocks during the lifetime of corporate bonds, and have to sell the bond immediately at the price, which is assumed to be a fraction of the price in a perfectly liquid market. Under this framework, we derive explicit expressions for corporate bond, firm value and bankruptcy trigger. Finally, numerical illustrations are presented.     

Modelling Specific Interest Rate Risk with Estimation of Missing Data

For the treatment of specific interest rate risk, a risk model is suggested, quantifying and combining both market and credit risk components consistently. The market risk model is based on credit spreads derived from traded bond prices. Though traded bond prices reveal a maximum amount of issuer specific information, illiquidity problems do not allow for classical parameter estimation in this context. To overcome this difficulty an efficient multiple imputation method is proposed that also quantifies the amount of risk associated with missing data. The credit risk component is based on event risk caused by correlated rating migrations of individual bonds using a Copula function approach.     

Multi-population mortality models: A factor copula approach

Modeling mortality co-movements for multiple populations have significant implications for mortality/longevity risk management. A few two-population mortality models have been proposed to date. They are typically based on the assumption that the forecasted mortality experiences of two or more related populations converge in the long run. This assumption might be justified by the long-term mortality co-integration and thus be applicable to longevity risk modeling. However, it seems too strong to model the short-term mortality dependence. In this paper, we propose a two-stage procedure based on the time series analysis and a factor copula approach to model mortality dependence for multiple populations. In the first stage, we filter the mortality dynamics of each population using an ARMA–GARCH process with heavy-tailed innovations. In the second stage, we model the residual risk using a one-factor copula model that is widely applicable to high dimension data and very flexible in terms of model specification. We then illustrate how to use our mortality model and the maximum entropy approach for mortality risk pricing and hedging. Our model generates par spreads that are very close to the actual spreads of the Vita III mortality bond. We also propose a longevity trend bond and demonstrate how to use this bond to hedge residual longevity risk of an insurer with both annuity and life books of business.     

Embedding the Vasicek model into the Cox–Ingersoll–Ross model

The Cox–Ingersoll–Ross (CIR) model and the Vasicek model are two well‐known single factor models of the interest spot rate. In this paper, we construct a mapping by means of which the price of a zero‐coupon bond in the CIR model may be obtained from a corresponding price in the Vasicek model. We use symmetry analysis to construct this mapping and verify it by transforming three arbitrary solutions of the pricing equation in the Vasicek model into solutions of the corresponding equation in the CIR model. Copyright © 2010 John Wiley & Sons, Ltd.     

Longevity bond premiums: The extreme value approach and risk cubic pricing

The purpose of this study is to analyze the securitization of longevity risk with an emphasis on longevity risk modeling and longevity bond premium pricing. Various longevity derivatives have been proposed, and the capital market has experienced one unsuccessful attempt by the European Investment Bank (EIB) in 2004. After carefully analyzing the pros and cons of previous securitizations, we present our proposed longevity bonds, whose payoffs are structured as a series of put option spreads. We utilize a random walk model with drift to fit small variations of mortality improvements and employ extreme value theory to model rare longevity events. Our method is a new approach in longevity risk securitization, which has the advantage of both capturing mortality improvements within sample and extrapolating rare, out-of- sample longevity events. We demonstrate that the risk cubic model developed for pricing catastrophe bonds can be applied to mortality and longevity bond pricing and use the model to calculate risk premiums for longevity bonds.