Firm size distribution and mobility of the top 500 firms in China,the United States and the world

This paper considers the macroscopic and microscopic statistical features of the top 500 firms in China, the United States and the world, denoted as China 500 (CH500), Fortune 500 (US500) and Fortune Global 500 (FG500). From a macroscopic perspective, the firm size distribution of each category, when measured by revenue, is steadily distributed over the observed period, even during periods of financial crises. As is evidenced by the Gini coefficient, divergences between firm scales are most significant for the CH500. From a microscopic perspective, the underlying micro-dynamics are volatile and often turbulent due to the exit and entry of firms as well as shifts in their revenues and ranks. Such fluctuations, or mobility, are visualized in rank/revenue/share clocks. We also propose a revenue/rank/share mobility index that is a quantitative measurement of mobility. Among these, we find that the share mobility acts as an effective indicator of economic status; where there is a share mobility spike, there is an ailing economy. The share mobility indexes indicate that the 2008 Financial Crisis had little impact on the Chinese economy, while it triggered violent changes in the top 500 firms in the United States and the world.     

Valuation perspectives and decompositions for variable annuities with GMWB riders

The guaranteed minimum withdrawal benefit (GMWB) rider, as an add on to a variable annuity (VA), guarantees the return of premiums in the form of periodic withdrawals while allowing policyholders to participate fully in any market gains. GMWB riders represent an embedded option on the account value with a fee structure that is different from typical financial derivatives. We consider fair pricing of the GMWB rider from a financial economic perspective. Particular focus is placed on the distinct perspectives of the insurer and policyholder and the unifying relationship. We extend a decomposition of the VA contract into components that reflect term-certain payments and embedded derivatives to the case where the policyholder has the option to surrender, or lapse, the contract early.     

Wave mixing in coupled phononic crystals via a variable stiffness mechanism

We investigate wave mixing effects in a phononic crystal that couples the wave dynamics of two channels – primary and control ones – via a variable stiffness mechanism. We demonstrate analytically and numerically that the wave transmission in the primary channel can be manipulated by the control channel's signal. We show that the application of control waves allows the selection of a specific mode through the primary channel. We also demonstrate that the mixing of two wave modes is possible whereby a modulation effect is observed. A detailed study of the design parameters is also carried out to optimize the switching capabilities of the proposed system. Finally, we verify that the system can fulfill both switching and amplification functionalities, potentially enabling the realization of an acoustic transistor.     

Likelihood Inference under Generalized Hybrid Censoring Scheme with Comp eting Risks

Statistical inference is developed for the analysis of generalized type-II hybrid censoring data under exponential competing risks model. In order to solve the problem that approximate methods make unsatisfactory performances in the case of small sample size, we establish the exact conditional distributions of estimators for parameters by conditional moment generating function(CMGF). Furthermore, confidence intervals(CIs) are constructed by exact distributions, approximate distributions as well as bootstrap method respectively, and their performances are evaluated by Monte Carlo simulations. And finally, a real data set is analyzed to illustrate all the methods developed here.     

A class of random field memory models for mortality forecasting

This article proposes a parsimonious alternative approach for modeling the stochastic dynamics of mortality rates. Instead of the commonly used factor-based decomposition framework, we consider modeling mortality improvements using a random field specification with a given causal structure. Such a class of models introduces dependencies among adjacent cohorts aiming at capturing, among others, the cohort effects and cross generations correlations. It also describes the conditional heteroskedasticity of mortality. The proposed model is a generalization of the now widely used AR-ARCH models for random processes. For such a class of models, we propose an estimation procedure for the parameters. Formally, we use the quasi-maximum likelihood estimator (QMLE) and show its statistical consistency and the asymptotic normality of the estimated parameters. The framework being general, we investigate and illustrate a simple variant, called the three-level memory model, in order to fully understand and assess the effectiveness of the approach for modeling mortality dynamics.     

How the expanded crowd-funding mechanism of some southern rural areas in China affects cooperative behaviors in threshold public goods game

The pursuit of high cooperation rates in public goods games has attracted many researchers. However, few researchers attach much weight to the influence of emotions on decision-making, especially on public goods games. From ancient to modern times, publishing the list of cooperators to stimulate cooperation has been a common phenomenon in some southern rural areas in China. Actually, the published list can influence individuals’ behaviors by affecting their emotions. Here we extend the method of publishing the list and optimize it by adding a lobbyist mechanism. Through numerical simulations, we find that the role of lobbyists can not be ignored unless the synergy factor is larger than a certain value. Additionally, we find that publishing the list certainly has a great effect on individual’s cooperative behavior. But whether to publish the list or not and how to publish the list depend on the situation.     

Effective transfer entropy approach to information flow between exchange rates and stock markets

We investigate the strength and direction of information flow between exchange rates and stock prices in several emerging countries by the novel concept of effective transfer entropy (an alternative non-linear causality measure) with symbolic encoding methodology. Analysis shows that before the 2008 crisis, only low level interaction exists between these two variables and exchange rates dominate stock prices in general. During crisis, strong bidirectional interaction arises. In the post-crisis period, the strong interaction continues to exist and in general stock prices dominate exchange rates.     

Network-based naive Bayes model for social network

Naive Bayes (NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes (NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational effciency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance. A real data example is also analyzed for illustration purpose.     

Nonlinear FCS-MPC strategy of NPC/H-5 L inverter based on satisfactory optimization algorithm

In the design of the cost function in the nonlinear finite control set model predictive control (FCS-MPC) system, the traditional method based on weighting factors demonstrates some limitations, such as the weighting factors adjusting and heavy predictive calculation due to the increased number of voltage vectors applied in controlling multilevel converters. This paper proposes a simplified FCS-MPC method based on common mode voltage satisfactory optimization, which could considerably reduce the predictive calculation by the optimized switch combination and simplify the cost function design. Moreover, satisfactory optimization is adopted to achieve the accuracy control of common-mode voltage amplitude without adjusting process of weighting factors. The simulation and experimental results verify the feasibility of this control strategy.     

Equivalent Conditions for Local Error Bounds

In this paper we present two classes of equivalent conditions for local error bounds in finite dimensional spaces. We formulate conditions of the first class by using subderivatives, subdifferentials and strong slopes for nearby points outside the referenced set, and show that these conditions actually characterize a uniform version of the local error bound property. We demonstrate this uniformity for the max function of a finite collection of smooth functions, and as a consequence we show that quasinormality constraint qualifications guarantee the existence of local error bounds. We further present the second class of equivalent conditions for local error bounds by using the various limits defined on the boundary of the referenced set. In presenting these conditions, we exploit the variational geometry of the referenced set in a systematic way and unify some existing results in the literature.