Stochastic L2-Integration with a Locally Compact Time-Region

This paper contains some results about the theory of stochastic L²-Integration with a general time-region. The starting point of our theory is not a family of σ-algebras but, more generally, a family of projection operators in the Hilbert space of all square integrable random functions. To do this we use some Hilbert space analysis as well as the methods of Metivier and Pellaumail.     

A central limit theorem for generalized multilinear forms

Let X₁, …, X_n be independent random variables and define for each finite subset I {1, …, n} the σ-algebra = σ{X_i : i ε I}. In this paper -measurable random variables W_I are considered, subject to the centering condition E(W_I ) = 0 a.s. unless I J. A central limit theorem is proven for d-homogeneous sums W(n) = Σ_{I = d}W_I, with var W(n) = 1, where the summation extends over all (_n^d) subsets I {1, …, n} of size I = d, under the condition that the normed fourth moment of W(n) tends to 3. Under some extra conditions the condition is also necessary.     

On representation and regularity of continuous parameter multivalued martingales

In this paper we study multivalued martingales in continuous time. First we show that every multivalued martingale in continuous time can be represented as the closure of a sequence of martingale selections. Then we prove two results concerning the cadlag modifications of continuous time multivalued martingales, in Kuratowski-Mosco convergence and in convergence in the Hausdorff metric respectively.

     

Duality results and inequalities with respect to Hardy spaces containing function sequences

With the help of two-parameter martingales and strong martingales Hardy spaces consisting of adapted function sequences are considered. The Hardy spaces generated by the square and by the conditional square functions and their dual spaces are investigated. An inequality due to Stein and Lepingle is extended to two parameters.This research was supported by the Hungarian Scientific Research Funds No. 2085 and No. 74189 as well as by DAAD, the lattest with a stay at the Ludwig-Maximilians-Universität in München.     

两指标随机积分方程解的唯一性

在正交增量的随机积分基础上，利用Ｌｉｐｓｃｈｉｔｚ条件，讨论了下面一类两参数随机积分方程解的唯一性。Ｘ（ｓ，ｔ）＝Ｚ（ｓ，０）＋Ｚ（０，ｔ）－Ｚ（０，０）＋∫Ｒｓｔα（ｕ，ｖ，Ｘ）ｄＭｕｖ＋∫Ｒｓｔβ（ｕ，ｖ，Ｘ）ｄｍｕｖ＋∫Ｒ＾ｓｔγ１（ｕ，ｖ，ｕ＇，ｖ＇，Ｘ）ｄＭｕｖｄＭｕ＇ｖ＇＋∫Ｒ＾２ｓｔγ２（ｕ，ｖ，ｕ＇，ｖ＇，Ｘ）ｄＭｕｖｄｍｕ＇ｖ＇＋∫Ｒ＾２ｓｔγ３（ｕ，ｖ，ｕ＇，ｖ＇，Ｘ）ｄｍｕｖ     

Another view on martingale central limit theorems

Based on the martingale version of the Skorokhod embedding Heyde and Brown (1970) established a bound on the rate of convergence in the central limit theorem (CLT) for discrete time martingales having finite moments of order 2+2δ with 0<δ1. An extension for all δ>0 was proved in Haeusler (1988). This paper presents a rather quick access based solely on truncation, optional stopping, and prolongation techniques for martingale difference arrays to obtain other upper bounds for sup

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(φbeing the standard normal d.f.) yielding weak sufficient conditions for the asymptotic normality of . It is shown that our approach also yields two types of martingale central limit theorems with random norming.     

Stochastic regression model with heteroscedastic disturbance

This paper discusses some properties of stochastic regression model with continuous form of heteroscedastic disturbance. The strong consistency and asymptotic normality of a generalized weighted least squares estimate will be investigated under certain conditions on the stochastic regressors and errors. More, the linear hypothesis testing problem also be discussed and an example to be demonstrated to reestablish the results of Cheng and Chang (1990, Tech. Report, National Tsing Hua University).Supported by the National Science Council Grant No. 810208M763 at National Tsing Hua University.     

停止变换的不变性

利用条件期望的表达式给出了两指标过程在停线处的停止定义,研究了停止变换下的若干不变性．给出了这种停止意义下的局部平方可积强鞅的定义,进一步研究了局部平方可积强鞅二次变差的存在性及其停止性质，得到了重要的Burkholder-Davis-Gundy型不等式及平方可积强鞅的一个充要条件。     

Estimation of IIR Systems with Binary-Valued Observations*

Estimation and control problems with binary-valued observations exist widely in practical systems. However, most of the related works are devoted to finite impulse response (FIR for short) systems, and the theoretical problem of infinite impulse response (IIR for short) systems has been less explored. To study the estimation problems of IIR systems with binary-valued observations, the authors introduce a projected recursive estimation algorithm and analyse its global convergence properties, by using the stochastic Lyapunov function methods and the limit theory on double array martingales. It is shown that the estimation algorithm has similar convergence results as those for FIR systems under a weakest possible non-persistent excitation condition. Moreover, the upper bound for the accumulated regret of adaptive prediction is also established without resorting to any excitation condition.     

The fundamental theorem of mutual insurance

The essence of mutual insurance is the notion that re-distributing risk in a pool of risks is more beneficial than taking the risk alone. Interpreting ‘more beneficial’ as an increase in utility and considering sequences of exchangeable risks, we are able to formalize this notion from the policyholder’s perspective and demonstrate its validity for various alternative preference functionals (e.g., expected utility, Choquet expected utility, and distortion risk measures). To obtain this result, we exploit that for a sequence of exchangeable risks the corresponding sequence of arithmetical averages is a reversed martingale.We conclude that pooling risks is fundamental for understanding the mechanisms of insurance because it favourably affects the utility of policyholders, and we refer to this phenomenon as the ‘utility-improving effect of risk pooling’. Moreover, we demonstrate that the utility of the policyholder is (strictly) increasing with the size of the risk pool.