强边着色猜想问题的最优图

著名图论专家Erds和Nesetǐil对图的强边色数上界提出了一个猜想:当最大度Δ为偶数时,χ's(G)≤5/4Δ~2;当最大度Δ为奇数时,χ's(G)≤1/4(5Δ~2-2Δ+1);并且给出了当Δ=4时的最优图.此处构造了一族图,并证明了当最大度为奇数时,如果Erd9s和Ne2etǐil提出的强边着色猜想成立,则猜想中的上界是最优的.     

Geopolitical risk and global financial cycle: Some forecasting experiments

In this study, we investigate the connection between geopolitical risk (GPR) and global financial cycle (GFCy) as well as whether the former has predictive value for the out-of-sample predictability of the latter. We utilize both the historical and recent GPR data and their variants, namely, GPR act covering all “acts” that constitute GPR such as war, nuclear invasion and terrorism, and GPR threat, which represents threats of these acts. We construct a predictive model that accommodates the salient features of the predicted and predictor series while the forecast evaluation is conducted for both in-sample and out-of-sample periods. Our findings reveal that a rise in GPR discourages investments in risky assets and by implication worsens GFCy. The impact is more severe after the global financial crisis (gfc), and the GPR threat exerts more adverse effect on GFCy compared with GPR act regardless of whether historical GPR or recent GPR is used. Meanwhile, the predictive model of GFCy that accommodates the GPR data outperforms the benchmark model that ignores it both in the in-sample and out-of-sample estimates albeit with improved forecast performance during the post-gfc period and at a longer forecast horizon. However, the recent GPR data, which are broader in scope, offer better forecast accuracy than the historical GPR data. Additional analyses involving the vulnerability of global economic conditions reveal similar outcomes as GFCy.     

基于风险最小化的多粒度三支决策模型

为减小传统的二支决策中直接接受或拒绝决策带来的决策风险,分析问题决策的多粒度空间,研究了基于风险最小化的多粒度三支决策模型.在三支决策风险代价分析基础上,为寻求最优的粒度空间,结合不同属性特征在粒度空间中具有不同决策权重的特点,以粒化重要度和粒化决策权重为启发式信息,从多个不同的粒度层次出发,寻求风险最小的决策行动.最后针对不承诺选项中一些急需决策的现实问题,给出了基于风险控制的二支决策转化方法,并进行了具体的实例应用.     

Forecasting with Micro Panels: The Case of Health Care Costs

Micro panels characterized by large numbers of individuals observed over a short time period provide a rich source of information, but as yet there is only limited experience in using such data for forecasting. Existing simulation evidence supports the use of a fixed‐effects approach when forecasting but it is not based on a truly micro panel set‐up. In this study, we exploit the linkage of a representative survey of more than 250,000 Australians aged 45 and over to 4 years of hospital, medical and pharmaceutical records. The availability of panel health cost data allows the use of predictors based on fixed‐effects estimates designed to guard against possible omitted variable biases associated with unobservable individual specific effects. We demonstrate the preference towards fixed‐effects‐based predictors is unlikely to hold in many practical situations, including our models of health care costs. Simulation evidence with a micro panel set‐up adds support and additional insights to the results obtained in the application. These results are supportive of the use of the ordinary least squares predictor in a wide range of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.     

一类三圈图关于Merrifield-Simmons指标的排序

研究了一类三圈图瓦的Merrifield-Simmons指标，根据Cq上三种不同的连接方式，给出了该类三圈图关于Merrifield-Simmons指标的排序．     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

旅居者旅游感知风险探究

该文主要运用SPSS软件对旅居者感知到的旅游风险进行分析,研究旅居者旅游感知风险构面,找出旅居者旅游感知风险因子.最终得出6个风险构面,分别为身体安全风险、交通风险、财务风险、功能风险、文化风险、社会-心理风险.其中旅居者最为顾忌身体安全风险,同时并不在意社会-心理风险.     

Forecasting VaR models under Different Volatility Processes and Distributions of Return Innovations

This paper provides clear‐cut evidence that the out‐of‐sample VaR (value‐at‐risk) forecasting performance of alternative parametric volatility models, like EGARCH (exponential general autoregressive conditional heteroskedasticity) or GARCH, and Markov regime‐switching models, can be considerably improved if they are combined with skewed distributions of asset return innovations. The performance of these models is found to be similar to that of the EVT (extreme value theory) approach. The performance of the latter approach can also be improved if asset return innovations are assumed to be skewed distributed. The performance of the Markov regime‐switching model is considerably improved if this model allows for EGARCH effects, for all different volatility regimes considered. Copyright © 2014 John Wiley & Sons, Ltd.     

技术和价格不确定下企业研发投资决策研究

随着科学技术的迅速发展,研发(RD)活动对企业的生存与发展日益重要.本文将企业研发投资项目所承受的风险分为两种:研发前期不可对冲的技术风险,以及研发产品投入市场时因价格和需求的不确定性所承受的价格风险,而后者是可以部分对冲的.本文考虑一个以创新研发投资为主的企业,如何进行相应的投资消费问题.通过建立效用最大化模型,运用随机最优控制理论与方法得到关于指数效用函数的最优策略,同时阐述了研发投资价值及其投资/中止阈值.数值结果表明:较大的技术风险,会产生更大的信息生成价值,使得研发的总价值不减反增;风险厌恶态度对企业的研发价值以及研发/中止阈值都有较明显的影响;因研发信息生成价值的存在,使得研发/中止阈值不同于传统净现值(NPV)降为零的阈值.     

An Overview of Kernelization Algorithms for Graph Modification Problems

Kernelization algorithms for graph modification problems are important ingredients in parameterized computation theory. In this paper, we survey the kernelization algorithms for four types of graph modification problems, which include vertex deletion problems, edge editing problems, edge deletion problems, and edge completion problems. For each type of problem, we outline typical examples together with recent results, analyze the main techniques, and provide some suggestions for future research in this field.