JONES TYPE C^(*)-BASIC CONSTRUCTION IN NON-EQUILIBRIUM HOPF SPIN MODELS

Let H be a finite dimensional Hopf C^(*)-algebra,and let K be a Hopf^(*)-subalgebra of H.Considering that the field algebra■K of a non-equilibrium Hopf spin model carries a D(H,K)-invariant subalgebra ■K,this paper shows that the C^(*)-basic construction for the inclusion ■K×■K can be expressed as the crossed product C^(*)-algebra■KD(H,K).Here,D(H,K)is a bicrossed product of the opposite dual H^(op) and K.Furthermore,the natural action of D(H,K)on D(H,K)gives rise to the iterated crossed product■KD(H,K)×D(H,K),which coincides with the C^(*)-basic construction for the inclusion■K×■KD(H,K).In the end,the Jones type tower of field algebra■Kis obtained,and the new field algebra emerges exactly as the iterated crossed product.

The Survival Probability in Generalized Poisson Risk Model

In this paper we generalize the aggregated premium income process from a constant rate process to a poisson process for the classical compound Poinsson risk model,then for the generalized model and the classical compound poisson risk model ,we respectively get its survival probability in finite time period in case of exponential claim amounts.

Double Conditional Expectation

The concept of double conditional expectation is introduced. A series of properties for the double conditional expectation are obtained several convergence theorems and Jensen inequality are proved. Finally we discuss the special cases and application for double conditional expectation. Key words double conditional expectation - covergence theorem - Jensen inequality - branching chain in random environment CLC number O 211.6 Foundation item: Supported by the National Science Foundation of China (10371092) and the Foundation of Wuhan UniversityBiography: HU Di-he (1935-), male, Professor, research direction: stochastic processes and random fractals.

Stock market and macroeconomic variables:new evidence from India

Understanding the relationship between macroeconomic variables and the stock market is important because macroeconomic variables have a systematic effect on stock market returns.This study uses monthly data from India for the period from April 1994 to July 2018 to examine the long-run relationship between the stock market and macroeconomic variables.The empirical findings suggest that standard cointegration tests fail to identify any relationship among these variables.However,a transformation that extracts the actual functional relationship between these variables using the alternating conditional expectations algorithm of(J Am Stat Assoc 80:580–598,1985)identifies strong evidence of cointegration and indicates nonlinearity in the long-run relationship.Further,the continuous partial wavelet coherency model identifies strong coherency at a lower frequency for the transformed variables,establishing the fact that the long-run relationship between stock prices and macroeconomic variables in India is nonlinear and time-varying.This evidence has far-reaching implications for understanding the dynamic relationships between the stock market and macroeconomic variables.

L_p-CONTINUITY OF NONCOMMUTATIVE CONDITIONAL EXPECTATIONS

Let （M,τ） be a noncommutative probability space, （Mn）n≥l a sequence of von Neumann subalgebras of M and N a von Neumann subalgebra of M. We introduce the notions of It-approach and orthogonal approach for （Mn）n≥1 and prove that ε（x｜Mn）Lp→ε（x｜N） for any x ∈ Lp（M） （1 ≤ p 〈 ∞） if and only if （Mn）n≥1 τ-approaches and orthogonally approaches N.

OPTIONAL AND PREDICTABLE PROJECTIONS OF SET-VALUED MEASURABLE PROCESSES

In this paper,the optional and predictable projections of set-valued measurable processes are studied.The existence and uniqueness of optional and predictable projections of set-valued measurable processes are proved under proper circumstances.

VAR AND CTE BASED OPTIMAL REINSURANCE FROM A REINSURER'S PERSPECTIVE

In this article,we study optimal reinsurance design.By employing the increasing convex functions as the admissible ceded loss functions and the distortion premium principle,we study and obtain the optimal reinsurance treaty by minimizing the VaR(value at risk)of the reinsurer's total risk exposure.When the distortion premium principle is specified to be the expectation premium principle,we also obtain the optimal reinsurance treaty by minimizing the CTE(conditional tail expectation)of the reinsurer's total risk exposure.The present study can be considered as a complement of that of Cai et al.[5].

Monotone Iterative Technique for Duffie-Epstein Type Backward Stochastic Differential Equations

For Duffle-Epstein type Backward Stochastic Differential Equations, the comparison theorem is proved. Based on the comparison theorem, by monotone iterative technique, the existence of the minimal and maximal solutions of the equations are proved.

Strong Limit Theorems for Arbitrary Fuzzy Stochastic Sequences

Based on fuzzy random variables, the concept of fuzzy stochastic sequences is defined. Strong limit theorems for fuzzy stochastic sequences are established. Some known results in non-fuzzy stochastic sequences are extended. In order to prove results of this paper, the notion of fuzzy martingale difference sequences is also introduced.

Pricing American Options using the Malliavin Calculus

In this paper we elaborate a general expression of the conditional expectation related to pricing problem of the American options using the Malliavin derivative （without localization）. This work is a generalization of paper of Bally et al. （2005） [ 1 ] for the one dimensional case. Basing on the density function of the asset price, Bally and al. used the Malliavin calculus to evaluate the conditional expectation related to pricing American option problem, but in our work we use the Malliavin derivative to resolve the previous problem.

Dual representation of expectile-based expected shortfall and its properties

An expectile can be considered a generalization of a quantile.While expected shortfall is a quantile-based risk measure,we study its counterpart-the expectile-based expected shortfall-where expectile takes the place of a quantile.We provide its dual representation in terms of a Bochner integral.Among other properties,we show that it is bounded from below in terms of the convex combination of expected shortfalls,and also from above by the smallest law invariant,coherent,and comonotonic risk measures,for which we give the explicit formulation of the corresponding distortion function.As a benchmark to the industry standard expected shortfall,we further provide its comparative asymptotic behavior in terms of extreme value distributions.Based on these results,we finally explicitly compute the expectile-based expected shortfall for selected classes of distributions.

Doob's Stopping Theorems for Set-Valued (Super, Sub) Martingales with Continuous Time

In this paper the regularity of set-valued martingales in the sense of JL is given first. Then we show some kinds of Doob's stopping theorems for set-valued (super, sub) martingales with continuous time.

Age-dependent branching processes in random environments

We consider an age-dependent branching process in random environments. The environments are represented by a stationary and ergodic sequence ξ = (ξ 0, ξ 1,…) of random variables. Given an environment ξ, the process is a non-homogenous Galton-Watson process, whose particles in n-th generation have a life length distribution G(ξ n ) on ?+, and reproduce independently new particles according to a probability law p(ξ n ) on ?. Let Z(t) be the number of particles alive at time t. We first find a characterization of the conditional probability generating function of Z(t) (given the environment ξ) via a functional equation, and obtain a criterion for almost certain extinction of the process by comparing it with an embedded Galton-Watson process. We then get expressions of the conditional mean E ξ Z(t) and the global mean EZ(t), and show their exponential growth rates by studying a renewal equation in random environments.

Probability representations of fuzzy systems

In this paper, the probability significance of fuzzy systems is revealed. It is pointed out that COG method, a defuzzification technique used commonly in fuzzy systems, is reasonable and is the optimal method in the sense of mean square. Based on different fuzzy implication operators, several typical probability distributions such as Zadeh distribution, Mamdani distribution, Lukasiewicz distribution, etc, are given. Those distributions act as ＂inner kernels＂ of fuzzy systems. Furthermore, by some properties of probability distributions of fuzzy systems, it is also demonstrated that CRI method, proposed by Zadeh, for constructing fuzzy systems is basically reasonable and effective. Besides, the special action of uniform probability distributions in fuzzy systems is characterized. Finally, the relationship between CRI method and triple I method is discussed. In the sense of construction of fuzzy systems, when restricting three fuzzy implication operators in triple I method to the same operator, CRI method and triple I method may be related in the following three basic ways： 1） Two methods are equivalent; 2） the latter is a degeneration of the former; 3） the latter is trivial whereas the former is not. When three fuzzy implication operators in triple I method are not restricted to the same operator, CRI method is a special case of triple I method; that is, triple I method is a more comprehensive algorithm. Since triple I method has a good logical foundation and comprises an idea of optimization of reasoning, triple I method will possess a beautiful vista of application.

OPTIMAL COMBINATIONAL OF QUOTA-SHARE AND STOP-LOSS REINSURANCE CONTRACTS UNDER VAR AND CTE WITH A CONSTRAINED REINSURANCE PREMIUM

This paper considers the problem of minimizing the VaR and CTE of an insurer＇s retained risk by controlling the combinational quota-share and stop-loss reinsurance strategy. With a constrained reinsurance premium, the authors give the explicit reinsurance forms and the minimal VaR and CTE of retained risk in the case of quota-share after stop-loss reinsurance and the case of stop-loss afterquota-share reinsurance respectively. Finally, the authors conclude that the quota-share after stop-loss is a better reinsurance strategy than stop-loss after quota-share to minimize the VaR and CTE with a same constrained reinsurance premium. And the pure stop-loss reinsurance is preferred for an insurer with a high level regulatory requirement.

Feature Screening for Nonparametric and Semiparametric Models with Ultrahigh-Dimensional Covariates

This paper considers the feature screening and variable selection for ultrahigh dimensional covariates. The new feature screening procedure base on conditional expectation which is used to differentiate whether an explanatory variable contributes to a response variable or not, without requiring a specific parametric form of the underlying data model. The authors estimate the marginal condi- tional expectation by kernel regression estimator. The proposed method is showed to have sure screen property. The authors propose an iterative kernel estimator algorithm to reduce the ultrahigh dimensionality to an appropriate scale. Simulation results and real data analysis demonstrate the proposed method works well and performs better than competing methods.

Asphaltene precipitation modeling through ACE reaping of scaling equations

Precipitation and deposition of asphaltene have undesirable effects on the petroleum industry by increasing operational costs due to reduction of well productivity as well as catalyst poisoning.Herein we propose a reliable model for quantitative estimation of asphaltene precipitation.Scaling equation is the most powerful and popular model for accurate prediction of asphaltene precipitated out of solution in crudes without regard to complex nature of asphaltene.We employed a new mathematical-based approach known as alternating conditional expectation(ACE)technique for combining results of different scaling models in order to increase the accuracy of final estimation.Outputs of three well-known scaling equations,including Rassamdana(RE),Hu(HU),and Ashoori(AS),are input to ACE and the final output is produced through a nonlinear combination of scaling equations.The proposed methodology is capable of significantly increasing the precision of final estimation via a divide-andconquer principle in which ACE functions as the combiner.Results indicate the superiority of the proposed method compared with other individual scaling equation models.

Some Properties of A Lack-of-Fit Test for a Linear Errors in Variables Model

The relationship between the linear errors-in-variables model and the corresponding ordinary linear model in statistical inference is studied. It is shown that normality of the distribution of covariate is a necessary and sufficient condition for the equivalence. Therefore, testing for lack-of-fit in linear errors-in-variables model can be converted into testing for it in the corresponding ordinary linear model under normality assumption. A test of score type is constructed and the limiting chi-squared distribution is derived under the null hypothesis. Furthermore, we discuss the power of the test and the choice of the weight function involved in the test statistic.

On Maximal Abelian Self-adjoint Subalgebras of Factors of Type II_1

In this note, we show that if N is a proper subfactor of a factor M of type Ⅱ1 with finite Jones index, then there is a maximal abelian self-adjoint subalgebra （masa） A of N that is not a masa in ,M. Popa showed that there is a proper subfactor R0 of the hyperfinite type Ⅱ1 factor R such that each masa in R0 is also a masa in R. We shall give a detailed proof of Popa＇s result.

NEW RESULTS ABOUT THE RELATIONSHIP BETWEEN OPTIMALLY WEIGHTED LEAST SQUARES ESTIMATE AND LINEAR MINIMUM VARIANCE ESTIMATE

The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about the relationship between the two estimates.Firstly,the authorsconsider the classical linear model in which the coefficient matrix of the linear model is deterministic,and the necessary and sufficient condition for equivalence of the two estimates is derived.Moreover,under certain conditions on variance matrix invertibility,the two estimates can be identical providedthat they use the same a priori information of the parameter being estimated.Secondly,the authorsconsider the linear model with random coefficient matrix which is called the extended linear model;under certain conditions on variance matrix invertibility,it is proved that the former outperforms thelatter when using the same a priori information of the parameter.