具有一般跳过程的期权无差异效用价值过程的定价模型

本文采用指数效用最大化的方法研究了期权的动态无差异效用价值过程Ct(H;α).考虑股票价格过程为具有基于随机测度的一般跳的半鞅模型,且期权的无差异效用价值过程的Doob-Meyer分解的鞅部分的GKW(Galtchouk-Kunita-Watanabe)分解满足Jacod鞅表示定理.利用无差异效用价值过程在最小熵测度和最优投资策略下为鞅的事实构建了一个倒向随机微分方程.通过概率测度变换将方程的鞅部分和生成元转化为BMO(bounded mean oscillation)鞅,证明了该方程的解的唯一性.并将方程的生成元分成[?A=0]和[?A≠0],证明了最优投资策略存在.从而给出期权无差异效用价值过程的倒向随机微分方程的表达形式.     

B 值复测度拟鞅的原子分解

设P 是一个概率测度,ψ是一个复值可积函数,dμ =ψdP是一个复值测度. 在权函数ψ∈a₁∩b_∝⁺和Banach空间X 具有适当的凸性和光滑性的条件下, 作者证明了关于复测度μ 的X值拟鞅空间D_α(X) 和_pQ_α(X) 上的原子分解定理. 并且利用复测度拟鞅的原子分解定理, 在0<α≤ 1 的情形, 证明了关于X 值复测度拟鞅的两个重要不等式.     

违约风险的交换期权的定价模型与解法

含交易对手违约风险的交换期权采用混合模型定价,借助公司价值模型中的补偿率,同时采用以强度为基础的违约函数来确定违约的发生.假定违约强度遵从均值回复的重随机Poisson过程：且违约强度过程与标的资产,企业价值都相关.利用等价鞅测度变换方法导出含有违约风险的交换期权的价格闭解.     

一类半鞅的自然σ-域流

设X=(X_t)_t≥0为关于其自然σ-域流(J_t)_t≥0为半鞅。假设X具有弱可料表示性,即任一连续局部鞅可表为关于X的连续鞅部分的可料积分,任一纯断局部鞅可表为关于X的跳测度μ与其可料对偶投影v之差的可料积分。对于这类半鞅,利用它的局部可料特征,给出了其自然σ-域流为拟左连续、全连续与具有可料表示性的充要条件。     

特殊半鞅的可料表示性

设X为一(■_t)特殊半鞅,X=A+M为其典则分解.称X有可料表示性,如果一切零初值(■_t)局部鞅可表为一可料过程对M的随机积分.本文刻划了一类特殊半鞅的可料表示性(定理1.3及2.2);推广了Yoeurp-Yor定理(定理4.4).作为这些结果的应用,文中给出了Fujisaki-Kallianpur-Kunita定理的一个新证明(定理5.3).     

一类超一致椭圆扩散过程的极限定理

本文研究了分支特征为ψ（x,z）=γz^1+β（0<β≤1）形式的超一致椭圆扩散过程,当初始值X₀（dx）为底过程的某类不变测度时,给出了当空间维数d满足βd≤2时,超过程X_t依分布收敛于0测度,当βd>2时,X_t则依分布收敛于一个非退化的随机测度.     

局部鞅的绝对值特征

本文利用一种特殊的时间变换方法,推广了文献[1]中结果。指出对任何非负局部下鞅(X_t,y_t^|X|)都存在某个相应的局部鞅(M_t,y_t^|M|),使得(|M_t|)与(X_t)分布相同。     

支付连续红利的欧式和美式期权定价问题的研究

本文从投资策略的角度出发,针对支付连续红利欧式和美式期权,通过构造等价鞅测度,进而构造出最小保值策略即复制策略,由此得到相应的期权的一般定价公式,并在此基础上运用概率求期望和方程代换这两种方法推导出带红利标准欧式看涨期权的定价B-S公式.     

两指标鞅差序列的中心极限定理及其在平稳随机场上的应用

本文讨论了两指标鞅差序列及平稳随机场上的中心极限定理.所考虑的鞅差是根据平面格点的序:(s₁,s₂)<(t₁,t₂)当且仅当s_1...     

跳扩散模型下的欧式障碍期权的定价

本文在标的资产价格服从跳扩散模型的假设下,运用Girsanov定理获得了价格过程的等价鞅测度,用期权定价的鞅方法得出障碍期权的定价公式.     

The Mean-Variance Hedging of a Defaultable Option with Partial Information

Abstract

We consider the mean-variance hedging of a defaultable claim in a general stochastic volatility model. By introducing a new measure Q ⁰, we derive the martingale representation theorem with respect to the investors' filtration . We present an explicit form of the optimal-variance martingale measure by means of a stochastic Riccati equation (SRE). For a general contingent claim, we represent the optimal strategy and the optimal cost of the mean-variance hedging by means of another backward stochastic differential equation (BSDE). For the defaultable option, especially when there exists a random recovery rate we give an explicit form of the solution of the BSDE.     

A new existence result for quadratic BSDEs with jumps with application to the utility maximization problem

In this study, we consider the exponential utility maximization problem in the context of a jump–diffusion model. To solve this problem, we rely on the dynamic programming principle to express the value process of this problem in terms of the solution of a quadratic BSDE with jumps. Since the quadratic BSDE¹ under study is driven by both a Wiener process and a Poisson random measure having a Lévy measure with infinite mass, our main task is therefore to establish a new existence result for the specific BSDE introduced.     

On the orthogonal component of BSDEs in a Markovian setting

In this note we consider a quadratic growth backward stochastic differential equation (BSDE) driven by a continuous martingale M. We prove (in Theorem 3.2) that if M is a strong Markov process and if the BSDE has the form (2.2) with regular data then the unique solution (Y,Z,N) of the BSDE is reduced to (Y,Z), i.e. the orthogonal martingale N is equal to zero, showing that in a Markovian setting the “usual” solution (Y,Z) (of a BSDE with regular data) has not to be completed by a strongly orthogonal component even if M does not enjoy the martingale representation property.     

Optimal investment,consumption and proportional reinsurance for an insurer with option type payoff

This paper is devoted to the study of optimization of investment, consumption and proportional reinsurance for an insurer with option type payoff at the terminal time under the criterion of exponential utility maximization. The surplus process of the insurer and the financial risky asset process are assumed to be diffusion processes driven by Brownian motions which are non-Markovian in general. Very general constraints are imposed on the investment and the proportional reinsurance processes. Based on the martingale optimization principle, we use BSDE and BMO martingale techniques to derive the optimal strategy and the optimal value function. Some interesting particular cases are studied in which the explicit expressions for the optimal strategy are given by using the Malliavin calculus.     

Backward stochastic differential equations with Azéma's martingale

The aim of this paper is to study backward stochastic differential equations (BSDE) driven by Azéma's martingale and the associated deterministic functional equations. More precisely, we introduce BSDE's vs. Azéma's martingale in a general frame, then we prove that the existence of a solution to a Markovian BSDE implies the existence of a solution to a deterministic functional equation of a new type. Uniqueness for the functional equation is proved in a particular case. Then we discuss BSDE's vs. an asymmetric martingale: half Brownian motion/half Azéma's martingale, which leads to an asymmetric deterministic functional equation.     

Optimal investment-consumption and life insurance selection problem under inflation. A BSDE approach

We discuss an optimal investment, consumption and insurance problem of a wage earner under inflation. Assume a wage earner investing in a real money account and three asset prices, namely: a real zero-coupon bond, the inflation-linked real money account and a risky share described by jump-diffusion processes. Using the theory of quadratic-exponential backward stochastic differential equation (BSDE) with jumps approach, we derive the optimal strategy for the two typical utilities (exponential and power) and the value function is characterized as a solution of BSDE with jumps. Finally, we derive the explicit solutions for the optimal investment in both cases of exponential and power utility functions for a diffusion case.     

A BSDE-based approach for the optimal reinsurance problem under partial information

We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival intensity and claim sizes distribution affected by an unobservable environmental stochastic factor. By filtering techniques (with marked point process observations), we reduce the original problem to an equivalent stochastic control problem under full information. Since the classical Hamilton–Jacobi–Bellman approach does not apply, due to the infinite dimensionality of the filter, we choose an alternative approach based on Backward Stochastic Differential Equations (BSDEs). Precisely, we characterize the value process and the optimal reinsurance strategy in terms of the unique solution to a BSDE driven by a marked point process.     

Backward SDEs with superquadratic growth

In this paper, we discuss the solvability of backward stochastic differential equations (BSDEs) with superquadratic generators. We first prove that given a superquadratic generator, there exists a bounded terminal value, such that the associated BSDE does not admit any bounded solution. On the other hand, we prove that if the superquadratic BSDE admits a bounded solution, then there exist infinitely many bounded solutions for this BSDE. Finally, we prove the existence of a solution for Markovian BSDEs where the terminal value is a bounded continuous function of a forward stochastic differential equation.     

Power utility maximization under partial information: Some convergence results

In this paper we consider the power utility maximization problem under partial information in a continuous semimartingale setting. Investors construct their strategies using the available information, which possibly may not even include the observation of the asset prices. Resorting to stochastic filtering, the problem is transformed into an equivalent one, which is formulated in terms of observable processes. The value process, related to the equivalent optimization problem, is then characterized as the unique bounded solution of a semimartingale backward stochastic differential equation (BSDE). This yields a unified characterization for the value process related to the power and exponential utility maximization problems, the latter arising as a particular case. The convergence of the corresponding optimal strategies is obtained by means of BSDEs. Finally, we study some particular cases where the value process admits an explicit expression.     

Market Viability and Martingale Measures under Partial Information

We consider a financial market model with a single risky asset whose price process evolves according to a general jump-diffusion with locally bounded coefficients and where market participants have only access to a partial information flow. For any utility function, we prove that the partial information financial market is locally viable, in the sense that the optimal portfolio problem has a solution up to a stopping time, if and only if the (normalised) marginal utility of the terminal wealth generates a partial information equivalent martingale measure (PIEMM). This equivalence result is proved in a constructive way by relying on maximum principles for stochastic control problems under partial information. We then characterize a global notion of market viability in terms of partial information local martingale deflators (PILMDs). We illustrate our results by means of a simple example.