Pricing catastrophe options with counterparty credit risk in a reduced form model

In this paper, we study the price of catastrophe options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model. We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.     

Reexamining the feasibility of diversification and transfer instruments on smoothing catastrophe risk

The present study discusses the effects of diversification and transfer of risk by global insurers on smoothing the peak of catastrophic claims. Empirical experiments indicate that the occurrence frequency of natural catastrophes (NatCat) has a serially dependent trend and that the Cox–Ingersoll–Ross square-root model for global insured losses is best fit than any other static distributions. The results are used to develop a NatCat risk insurance model that sets up a NatCat premium formula, uses the serially dependent dynamics of insured loss and establishes the cash flow of all involved parties while considering corporate income tax and no additional risk premium. The simulation results based on this model shows that fluctuation reserves, catastrophe bonds and catastrophe funds with payback schemes are feasible options for smoothing risk because they can benefit all long-term involved parties, including insurance company shareholders, the insured, bondholders, the fund and the government (i.e. taxpayers).     

Valuation of catastrophe reinsurance with catastrophe bonds

This study develops a contingent-claim framework for valuing a reinsurance contract and examines how a reinsurance company can increase the value of a reinsurance contract and reduce its default risk by issuing catastrophe (CAT) bonds. The results also show how the changes in contract values and default risk premium are related to basis risk, trigger level, catastrophe risk, interest rate risk, and the reinsurer’s capital position.     

Counterparty risk valuation on credit-linked notes under a Markov Chain framework

A credit-linked note(CLN) is a note paying an enhanced coupon to investors for bearing the credit risk of a reference entity. In this paper, we study the counterparty risk on CLNs under a Markov chain framework, and introduce a Markov copula model to describe joint defaults between the reference entity underlying the CLN and CLN issuer. Assuming that the respective default intensities are directly and inversely proportional to the interest rate, which follows a CIR process, we obtain the explicit formulae for CLN values through a PDE approach.Finally, credit valuation adjustment(CVA) formula is derived to price counterparty credit risk.     

突变理论应用于腔室火灾中的回燃现象

回燃是在通风受限的建筑火灾中，由于补充新鲜空气再次燃烧热烟气的现象．这种转捩现象是典型的突变行为．该文基于能量平衡方程建立了腔室火灾中回燃现象的简化数学模型，并利用突变理论建立了其突变拓扑空间函数方程，讨论了系统控制因子与工况状态之间的对应关系．结果表明回燃现象的突变形式是燕尾突变，并可依据其分岔集确定回燃现象的产生与否．     

Optimal reinsurance with regulatory initial capital and default risk

In a reinsurance contract, a reinsurer promises to pay the part of the loss faced by an insurer in exchange for receiving a reinsurance premium from the insurer. However, the reinsurer may fail to pay the promised amount when the promised amount exceeds the reinsurer’s solvency. As a seller of a reinsurance contract, the initial capital or reserve of a reinsurer should meet some regulatory requirements. We assume that the initial capital or reserve of a reinsurer is regulated by the value-at-risk (VaR) of its promised indemnity. When the promised indemnity exceeds the total of the reinsurer’s initial capital and the reinsurance premium, the reinsurer may fail to pay the promised amount or default may occur. In the presence of the regulatory initial capital and the counterparty default risk, we investigate optimal reinsurance designs from an insurer’s point of view and derive optimal reinsurance strategies that maximize the expected utility of an insurer’s terminal wealth or minimize the VaR of an insurer’s total retained risk. It turns out that optimal reinsurance strategies in the presence of the regulatory initial capital and the counterparty default risk are different both from optimal reinsurance strategies in the absence of the counterparty default risk and from optimal reinsurance strategies in the presence of the counterparty default risk but without the regulatory initial capital.     

多层次统计-动力建模及其应用

该文将子波变换技术和平衡态动力理论结合起来，提出了以气候突变点数为核心的代层次气候建模技术。该技术不仅具有纯粹的动力学意义，而且模式的物理意义十分清楚 ，计算简单。     

Closed-form pricing formula for exchange option with credit risk

In this paper, we study the valuation of Exchange option with credit risk. Since the over-the-counter (OTC) markets have grown rapidly in size, the counterparty default risk is very important and should be considered for the valuation of options. For modeling of credit risk, we use the structural model of Klein [13]. We derive the closed-form pricing formula for the price of the Exchange option with credit risk via the Mellin transform and provide the experiment results to illustrate the important properties of option with numerical graphs.     

Mathematical analysis of a nonlinear PDE model for European options with counterparty risk

In this work, we analyze a nonlinear partial differential equation (PDE) model for the total value adjustment on European options in the presence of a counterparty risk. We transform the nonlinear PDE into an equivalent one, involving a sectorial operator, and prove the existence and uniqueness of a solution.     

Bilateral Counterparty Risk Valuation on a CDS with a Common Shock Model

In this paper, we study the counterparty risk on a CDS in a common shock model. We introduce the general arbitrage-free valuation framework for counterparty risk adjustments in presence of bilateral default risk. Especially, we consider the pricing problem of credit default swap with counterparty risk under a common shock model with regime switching. The arrivals of the shock events are modeled by conditionally independent Cox processes whose stochastic intensities depend on the state of the economy described by a Markov chain. We give the explicit formula for the credit valuation adjustment (CVA) and examine the impact of the change of economic state on the CVA.     

Pricing catastrophe swaps: A contingent claims approach

In this paper, we comprehensively analyze the catastrophe (cat) swap, a financial instrument which has attracted little scholarly attention to date. We begin with a discussion of the typical contract design, the current state of the market, as well as major areas of application. Subsequently, a two-stage contingent claims pricing approach is proposed, which distinguishes between the main risk drivers ex-ante as well as during the loss reestimation phase and additionally incorporates counterparty default risk. Catastrophe occurrence is modeled as a doubly stochastic Poisson process (Cox process) with mean-reverting Ornstein–Uhlenbeck intensity. In addition, we fit various parametric distributions to normalized historical loss data for hurricanes and earthquakes in the US and find the heavy-tailed Burr distribution to be the most adequate representation for loss severities. Applying our pricing model to market quotes for hurricane and earthquake contracts, we derive implied Poisson intensities which are subsequently condensed into a common factor for each peril by means of exploratory factor analysis. Further examining the resulting factor scores, we show that a first order autoregressive process provides a good fit. Hence, its continuous-time limit, the Ornstein–Uhlenbeck process should be well suited to represent the dynamics of the Poisson intensity in a cat swap pricing model.     

A tractable LIBOR model with default risk

We develop a model for the dynamic evolution of default-free and defaultable interest rates in a LIBOR framework. Utilizing the class of affine processes, this model produces positive LIBOR rates and spreads, while the dynamics are analytically tractable under defaultable forward measures. This leads to explicit formulas for CDS spreads, while semi-analytical formulas are derived for other credit derivatives. Finally, we give an application to counterparty risk.     

利用传染模型对含有对手风险的信用证券定价(英文)

本文利用传染模型研究了可违约债券和含有对手风险的信用违约互换的定价。我们在约化模型中引入具有违约相关性的传染模型,该模型假设违约过程的强度依赖于由随机微分方程驱动的随机利率过程和交易对手的违约过程.本文模型可视为Jarrow和Yu(2001)及Hao和Ye(2011)中模型的推广.进一步地,我们利用随机指数的性质导出了可违约债券和含有对手风险的信用违约互换的定价公式并进行了数值分析.     

Pricing catastrophe swaps: A contingent claims approach

In this paper, we comprehensively analyze the catastrophe (cat) swap, a financial instrument which has attracted little scholarly attention to date. We begin with a discussion of the typical contract design, the current state of the market, as well as major areas of application. Subsequently, a two-stage contingent claims pricing approach is proposed, which distinguishes between the main risk drivers ex-ante as well as during the loss reestimation phase and additionally incorporates counterparty default risk. Catastrophe occurrence is modeled as a doubly stochastic Poisson process (Cox process) with mean-reverting Ornstein-Uhlenbeck intensity. In addition, we fit various parametric distributions to normalized historical loss data for hurricanes and earthquakes in the US and find the heavy-tailed Burr distribution to be the most adequate representation for loss severities. Applying our pricing model to market quotes for hurricane and earthquake contracts, we derive implied Poisson intensities which are subsequently condensed into a common factor for each peril by means of exploratory factor analysis. Further examining the resulting factor scores, we show that a first order autoregressive process provides a good fit. Hence, its continuous-time limit, the Ornstein-Uhlenbeck process should be well suited to represent the dynamics of the Poisson intensity in a cat swap pricing model.     

The valuation of contingent capital with catastrophe risks

The Intergovernmental Panel on Climate Change Fourth Assessment Report (2007) indicates that unanticipated catastrophic events could increase with time because of global warming. Therefore, it seems inadequate to assume that arrival process of catastrophic events follows a pure Poisson process adopted by most previous studies (e.g. [Louberge, H., Kellezi, E., Gilli, M., 1999. Using catastrophe-linked securities to diversify insurance risk: A financial analysis of lCAT bonds. J. Risk Insurance 22, 125–146; Lee, J.-P., Yu, M.-T., 2002. Pricing default-risky CAT bonds with moral hazard and basis risk. J. Risk Insurance 69, 25–44; Cox, H., Fairchild, J., Pedersen, H., 2004. Valuation of structured risk management products. Insurance Math. Econom. 34, 259–272; Jaimungal, S., Wang, T., 2006. Catastrophe options with stochastic interest rates and compound Poisson losses. Insurance Math. Econom., 38, 469–483]. In order to overcome this shortcoming, this paper proposes a doubly stochastic Poisson process to model the arrival process for catastrophic events. Furthermore, we generalize the assumption in the last reference mentioned above to define the general loss function presenting that different specific loss would have different impacts on the drop in stock price. Based on modeling the arrival rates for catastrophe risks, the pricing formulas of contingent capital are derived by the Merton measure. Results of empirical experiments of contingent capital prices as well as sensitivity analyses are presented.     

基于蜱虫效应的Sgn函数突变模型

通过医疗决策中由于受代表性启发方式影响误诊引起的“蜱虫效应”,建立了Sgn函数的突变模型,基于此模型发展了一种新的突变理论．论文分析了代表性启发方式引起的五种偏差,运用Sgn函数突变模型对中国用工荒这一“蜱虫效应”反映的复杂社会经济问题进行了系统研究．     

基于高维突变模型的海上通道安全预警研究

为了在海上通道突发事件发生前给出可能的危险等级,减少海上通道突发事件造成的损失和提高海上通道预警与应急管理能力,本文针对海上通道安全突发事件的复杂性,提出一种历史案例分析与高维突变级数相结合的新方法。首先,通过对历史突发事件案例的统计分析,得出海上通道安全的主要风险源因素,并由此建立了海上通道安全预警指标体系。其次,将突变级数法在高维指标应用方面进行了推广,建立海上通道安全预警模型,并根据历史案例数据计算模型的预警阈值。最后,选取了实际案例对预警模型进行了检验,检验结果表明模型可以对海上通道突发事件进行有效预警。     

Equilibrium in natural catastrophe insurance market under disaster-resistant technologies,financial innovations and government interventions

Natural disasters increase in number and severity. Studies have shown the failure of the catastrophe insurance market by listing many causes or through developing economic models (Charpentier and Le Maux, 2014; Kousky and Cooke, 2012; Ibragimov et al., 2009). However, they have not considered the effect of the following factors on market equilibrium: advanced disaster-resistant technologies used by insureds, alternative financial innovations employed by insurers, and various disaster policies that are implemented by governments. To fill this gap, this study examines how these three factors affect the market equilibrium by changing the supply of, and demand for insurance and determines which factor(s) contributes to the market equilibrium. Furthermore, we derive the formula of position size which gives criteria for selecting index-based contracts. Overall annual numbers and insured losses of catastrophes are collected by peril type and by occurrence region listed in Sigma, which is issued by Swiss Re annually. The comparative static equilibrium analysis demonstrates that the improvement of market equilibrium is significant at low level of loss correlation in all cases. The empirical findings give insurers good references for business and geographical diversification in portfolio of catastrophe insurance policies.     

Stochastic Optimization of Insurance Portfolios for Managing Exposure to Catastrophic Risks

A catastrophe may affect different locations and produce losses that are rare and highly correlated in space and time. It may ruin many insurers if their risk exposures are not properly diversified among locations. The multidimentional distribution of claims from different locations depends on decision variables such as the insurer's coverage at different locations, on spatial and temporal characteristics of possible catastrophes and the vulnerability of insured values. As this distribution is analytically intractable, the most promising approach for managing the exposure of insurance portfolios to catastrophic risks requires geographically explicit simulations of catastrophes. The straightforward use of so-called catastrophe modeling runs quickly into an extremely large number of what-if evaluations. The aim of this paper is to develop an approach that integrates catastrophe modeling with stochastic optimization techniques to support decision making on coverages of losses, profits, stability, and survival of insurers. We establish connections between ruin probability and the maximization of concave risk functions and we outline numerical experiments.     

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Credit valuation adjustment is the price adjustment of financial contract considering possible default of counterparty and it is an important way to measure counterparty risk. It is the key to establish a reasonable default dependence structure model. We introduce an economic state variable and shot noise processes in a Markov copula model and establish a regime switching Markov copula model with shot noise, where we can not only describe the impact of common economic conditions characteristics but also describe the credit name's characteristic. In this proposed model, we study martingale property of the model and the collateralized CVA of credit default swaps, and furthermore, we perfer some numerical calculations on the collateralized CVA and examine the impact of some model parameters on the CVA.