局部平方可积鞅的比值不等式

本对局部平方可积鞅建立了几个比值不等式，推广了连续鞅的相应结果．     

集值局部平方可积鞅

介绍集值类（D）过程和集值局部鞅的概念和有关性质，进而讨论了集值局部平方可积鞅的概念和性质。     

关于局部平方可积鞅的重对数律

设(M_t,f_t,t≥0)为(Ω,f,P)上的局部平方可积鞅,(简记M ∈m_100~2),M_=0,{f_t}满足通常条件,f_0={Φ,Ω},为M~2的可料补偿,本文证明了如下结论: ⅰ)若存在可料过程k_t t≥0,k_t=0 a.s.,使得 |△M_t|≤k_t·_t~(1/2)/[2lg_2 k~2V_t)]~(1/2) a.s.,_∞=∞, 则 M_t/[2_t lg_2(e~2V_t)]~(1/2)=1 a.s. ⅱ)若存在可料过程K_t,t≥0和常数0_t~(1/2)/[21g_2(e~2V_t)]~(1/2) a.s. 则存在0<8(K)<1,↓8(K)=0,使在_∞=∞上, M_t/[2_t lg_2(e~2V_t)]~(1/2)≤1 8(K) a.s.     

平方可积鞅

讨论了集值平方可积鞅和实值平方可积鞅的性质.它对集值随机过程的进一步研究将起到很重要的作用.     

局部平方可积鞅Chung重对数律的下界

设Ｘ＝（Ｘｔ，ｔ≥０）为零初值的局部平方可积鞅〈Ｘ，Ｘ〉＝（〈Ｘ，Ｘ〉ｔ，ｔ≥０）为具可料二阶交差，在类似于Ｋｏｌｍｏｎｏｒｏｖ最初给出的条件下，证明了局部平方可积鞅的Ｃｈｕｎｇ重对数律的下界成立，即     

局部平方可积鞅的Chug重对数律

设Ｘ＝（Ｘｔ，ｔ≥０）为局部平方可积鞅，且Ｘ０＝０〈Ｘ，Ｘ〉ｔ为其二阶可料变差。利用继续半鞅的强逼近结果，我们证明了在较弱的条件下，Ｘ的Ｃｈｕｎｇ重对数律成立，即ｐ（＾ｌｉｍｉｎｆ ｔ→∞ ＾ｓｕｐ│Ｘｓ│ ｏ≤ｓ≤ｔ／（〈ｘ，ｘ〉ｔ／ｌｏｇｌｏｇ〈Ｘ，Ｘ〉 ｔ）＾１／２＝π／根号８）＝１。     

局部平方可积鞅的Chung重对数律(英文)

设X＝（Xt，t0）为局部平方可积鞅，且Xo＝0，＜X，X＞t为其二阶可料变差．利用连续半鞅的强逼近结果，我们证明了在较弱的条件下，X的Chung重对数律成立，即     

关于模糊集值平方可积鞅的随机积分

给出了模糊集值平方可积鞅的定义以及简单实值可料过程关于模糊集值平方可积鞅的随机积分的定义;证明了该积分仍具有模糊集值平方可积鞅的性质。     

有界可料过程关于集值平方可积鞅的集值随机积分

本文定义了一类有界可料过程关于集值平方可积鞅的集值随机积分,并研究了集植随机积分的性质。此为建立集值随机分析的理论奠定了基础。     

两指标局部鞅的停止变换及Wiener过程的鞅刻划

本文主要讨论两指标局部平方可积鞅的停止变换问题及Ｗｉｅｎｅｒ过程的鞅刻划和停止问题。     

A law of the iterated logarithm for processes with independent increments

ＡＬＡＷＯＦＴＨＥＩＴＥＲＡＴＥＤＬＯＧＡＲＩＴＨＭＦＯＲＰＲＯＣＥＳＳＥＳＷＩＴＨＩＮＤＥＰＥＮＤＥＮＴＩＮＣＲＥＭＥＮＴＳＷＡＮＧＪＩＡＧＡＮＧ（汪嘉冈）（ＥａｓｔＣｈｉｎａＵｎｉｖｅｒｓｉｔｙｏｆＳｃｉｅｎｃｅ＆Ｔｅｃｈｎｏｌｏｇｙ,Ｓｈａｎｇ...     

Laws of the iterated logarithm for locally square integrable martingales

Three types of laws of the iterated logarithm （LIL） for locally square integrable martingales with continuous parameter are considered by a discretization approach. By this approach, a lower bound of LIL and a number of FLIL are obtained, and Chung LIL is extended.     

人寿保险中随机Thiele微分方程的另一方法及应用

本文针对人寿保单被描述为时间非时齐的马氏链情形,较之文[7]更一般的假设条件下,给出了鞅M(t)=E[V0│Ft]的局部平方可积鞅的表示性,该方法不同于文[4]的方法。由此得到了随机Thiele微分方程,而且给出损失方差的一般表示。文章最后通过赔偿依赖于准备金的寡妇养老 金例子说明了随机Thiele微分方程的应用。     

Stochastic integral with respect to set-valued square integrable martingales

In this paper, we shall firstly illustrate why we should consider integral of a stochastic process with respect to a set-valued square integrable martingale. Secondly, we shall prove the representation theorem of set-valued square integrable martingale. Thirdly, we shall give the definition of stochastic integral of a stochastic process with respect to a set-valued square integrable martingale and the representation theorem of this kind of integrals. Finally, we shall prove that the stochastic integral is a set-valued sub-martingale.     

独立增量过程的一个强逼近定理

该文给出了独立增量过程的一种强逼近定理,由此得到相应的ｓｔｒａｓｓｅｎ重对数律．     

ON THE CONCAVE φ-INEQUALITIES FOR NONNEGATIVE SUBMARTINGALES

Let φ1, φ2 be nonnegative nondecreasing functions, and φl be concave. The authors prove the equivalence of the following two conditions:(i) Eφ1 (Mf) ≤ cEφ2(Zo+A∞) for every nonnegative submartingale f = (fn)n≥0 with it's Doob's Decomposition: f = Z + A, where Z is a martingale in L1 and A is a nonnegative incrasing and predictable process.(ii) There exists positive constants c, to such that ft∞φ1(s)/s2 ds ≤ c φ2(t)/t, t ＞ to.When φ1 = φ2 the condition (ii) above is equivalent to the classical condition -Pφ＜1. As a consequence, for a concave function φ, -Pφ＜ 1 if and only if Eφ1 (Mf) ≤ cEφ2 (Z0 + A∞)for every nonnegative submartingale f.     

Stochastic integration for operator valued processes on hilbert spaces and on nuclear spaces

The representation of a nuclear space valued square integrable martingale by means of another nuclear space valued square integrable martingale is given in terms of stochastic inegrals of operator valued processes. The construction of the stochastic integral goes through that of operator valued processes on Hilbert spaces. A new approach is given for the Hilbertian case, so that only the integration of Hilbert-Schmidt operator valued processes is needed to represent square integrable martingales