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	1. Mean-variance portfolio selection for an insurer in theMarkov-modulated market
	LI Jin-Zhu
	Mathematics 04 December 2015
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	Abstract:This paper studies the optimal investment strategy foran insurer under Markowitz's mean-variance criterion. The insurercan invest in a bond and multiple stocks in a financial market. Themarket parameters, including the interest rate of the bond and theappreciation and volatility rates of the stocks, are modulated by aMarkov chain with finite states. The risk process is described by aclassical compound Poisson model. Using techniques of stochasticlinear-quadratic (LQ) control, the paper obtains the optimalinvestment strategy and efficient frontier.
	TO cite this article:LI Jin-Zhu. Mean-variance portfolio selection for an insurer in theMarkov-modulated market[OL].[ 4 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4669068


	2. Asymptotic ruin probabilities for a kind of delayed-claims risk modelunder heavy tailed conditions
	LI Jin-Zhu
	Mathematics 04 December 2015
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	Abstract:This paper investigates a kind of risk model in whicheach main claim induces a delayed claim called by-claim. The paperassumes that both main claims and by-claims are heavy tailed, morespecifically, are regularly varying at infinity. Under theassumption that the delay times are bounded, the paper obtains theasymptotic ruin probabilities for both risk models without and withthe constant force of interest. It is worth saying that thetreatment in this paper allows a special dependent structure on eachmain claim and its by-claim.
	TO cite this article:LI Jin-Zhu. Asymptotic ruin probabilities for a kind of delayed-claims risk modelunder heavy tailed conditions[OL].[ 4 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4668924

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	3. On the comparison theorem for $1$-dimensional generalized anticipated BSDEs
	XU Xiao-Ming
	Mathematics 19 November 2014
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	Abstract:In this paper, we will establish a general comparison theoremfor the following $1$-dimensional generalized anticipated backward stochastic differential equation(GABSDE):egin{equation}left{egin{tabular}{rlll}$-dY_t$ &=& $f(t, {Y_r}_{rin [t, T+C]}, {Z_r}_{rin [t,T+C]})dt-Z_tdB_t, $ & $tin[0, T];$\$Y_t$ &=& $xi_t, $ & $tin[T, T+C];$\$Z_t$ &=& $eta_t, $ & $tin[T, T+C].$end{tabular} ight.end{equation}
	TO cite this article:XU Xiao-Ming. On the comparison theorem for $1$-dimensional generalized anticipated BSDEs[OL].[19 November 2014] http://en.paper.edu.cn/en_releasepaper/content/4619509


	4. Probabilistic representation for solution of some coupled system of quasilinear parabolic PDEs
	XU Xiao-Ming
	Mathematics 11 November 2014
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	Abstract:In this paper, we obtain a probabilistic representation for thesolution of the following coupled system of quasilinear parabolicPDEs:egin{equation}left{egin{tabular}{ll}$partial_t u^0+ b u_x^0+rac{1}{2}sigma^2 u_{xx}^0+(Deltau-delta u_x^0)gamma_t+f(t, x, u^0, u_x^0 sigma, Delta u)=0,$\$partial_t u^1+ b u_x^1+rac{1}{2}sigma^2 u_{xx}^1+f(t, x, u^1,u_x^1sigma, Delta u)=0,$\$u^0(T, x)=arphi(0, x)in mathbb{R},$\$u^1(T,x)=arphi(1, x)in mathbb{R},$end{tabular} ight.end{equation}where $Delta u(t, x)=u^1(t, x+delta(t, x))-u^0(t, x)$ and $b$,$sigma$, $delta$ are $mathbb{R}$-valued functions defined on $[0,T] imes mathbb{R}$, by introducing a new kind of backwardstochastic differential equation, called BSDE with random defaulttime.
	TO cite this article:XU Xiao-Ming. Probabilistic representation for solution of some coupled system of quasilinear parabolic PDEs[OL].[11 November 2014] http://en.paper.edu.cn/en_releasepaper/content/4618172


	5. A novel method for decoding any high-order hidden Markov model
	YE Fei, WANG Yi-Fei
	Mathematics 26 May 2014
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	Abstract:This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar's transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model.
	TO cite this article:YE Fei, WANG Yi-Fei. A novel method for decoding any high-order hidden Markov model[OL].[26 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4598699


	6. Pruning L'evy trees via an admissible family of branching mechanisms
	HE Hui
	Mathematics 01 April 2014
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	Abstract: By studying an admissible family of branching mechanisms introduced in Li (2014), a pruning procedure on L'evy trees is obtained. Then a decreasing L'evy-CRT-valued process ${T_t}$ by pruning L'evy trees and an analogous process ${T^_t}$ are constructed by pruning a critical L'evy tree conditioned to be infinite. Under a regular condition on the admissible family of branching mechanisms, it is shown that the law of ${T_t}$ at the ascension time can be represented by ${T^_t}$. The results generalize those studied in Abraham and Delmas (2012).
	TO cite this article:HE Hui. Pruning L'evy trees via an admissible family of branching mechanisms[OL].[ 1 April 2014] http://en.paper.edu.cn/en_releasepaper/content/4591607


	7. The quasi-sure existence of solutions for integral equations with vector fields of low regularity
	Xu Si-yan, Zhang Hua
	Mathematics 03 March 2014
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	Abstract:This paper consideres the existence of flows associated with vector fields under low regularity. Using the finite dimensional approximations of vector fields and a capacity version of Kolmogorov’s criterion for path continuity, and the existence of almost-sure flows of vector fields, the authors construct (1,p)-quasi-sure flows for integral equations with vector fields of low regularity.
	TO cite this article:Xu Si-yan, Zhang Hua. The quasi-sure existence of solutions for integral equations with vector fields of low regularity[OL].[ 3 March 2014] http://en.paper.edu.cn/en_releasepaper/content/4588634


	8. Simulation of two-phase shear flows with the one dimensional turbulence model
	Wu Yuxin,Philip J. Smith,Alan R. Kerstein,Lv Junfu
	Mathematics 28 February 2014
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	Abstract:The One Dimensional Turbulence (ODT) method is used to study spatially developing particle laden shear flows based on a novel proposed particle-eddy interaction model. The instantaneous and average flow fields of the gas phase are simulated with ODT model. The particle motions are tracked with a Lagrangian scheme. When a particle enters an eddy that is given by the ODT simulation, an instantaneous particle-eddy interaction model is used to represent turbulence-induced particle dispersion. The model is validated by comparisons between numerical results and measured data of a two-phase shear flow. Particle-size dependence of particle dispersion is studied. Although turbulent mixing process strengthens the particle dispersion in shear layers, those intermediate particles whose Stokes number are close to unity tend to concentrate in a regular pattern.
	TO cite this article:Wu Yuxin,Philip J. Smith,Alan R. Kerstein, et al. Simulation of two-phase shear flows with the one dimensional turbulence model[OL].[28 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4587931


	9. A note on the scaling limits of contour functions of Galton-Watson trees
	HE Hui,LUAN Na-Na
	Mathematics 11 October 2013
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	Abstract:Recently, Abraham and Delmas constructed the distributions of super-critical L'evy trees truncated at a fixed height by connecting super-critical L'evy trees to (sub)critical L'evy trees via a martingale transformation. A similar relationship also holds for discrete Galton-Watson trees. In this paper, by the existing works on the convergence of contour functions of (sub)critical trees, the contour functions of truncated super-critical Galton-Watson trees are shown to converge weakly to the distributions constructed by Abraham and Delmas.
	TO cite this article:HE Hui,LUAN Na-Na. A note on the scaling limits of contour functions of Galton-Watson trees[J].


	10. Precise large deviations for sums of two-dimensional random vectors with dependent components with extended regularly varying tails
	TIAN Hai-Lan,SHEN Xin-Mei
	Mathematics 02 July 2013
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	Abstract:Let ${ec{X}_{k}, k geq 1}$ be a sequence ofindependent identically distributed non-negative random vectors withcommon marginal distributions $F_{1}$, $F_{2}$ having extendedregularly varying tails, joint distribution function $F_{1,2}$ andfinite mean $ec{mu}=epec{X}_{1}$. The two components of$ec{X}_{1}$ are allowed to be dependent. Under some mildassumptions, precise large deviations for both the partial sums$ec{S}_{n}=sum_{k=1}^{n}ec{X}_{k}$ and the random sums$ec{S}_{N(t)}=sum_{k=1}^{N(t)}ec{X}_{k}$ are investigated,where $N(t)$ is a counting process independent of the sequence${ec{X}_{k}, k geq 1}$.
	TO cite this article:TIAN Hai-Lan,SHEN Xin-Mei. Precise large deviations for sums of two-dimensional random vectors with dependent components with extended regularly varying tails[OL].[ 2 July 2013] http://en.paper.edu.cn/en_releasepaper/content/4549936

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