论国际商事仲裁裁决承认与执行中的公共政策

公共政策在国际商事仲裁中主要和仲裁裁决的承认与执行有关,即当事人请求一国法院承认与执行外国法院的仲裁裁决过程中,如果一国法院认为,承认与执行该仲裁裁决有悖于执行地所在国家的公共政策,则可以此为理由拒绝承认与执行该外国仲裁裁决,起到的是"兜底防线"的角色。由于各国社会背景和文化因素等条件的影响,很难对其作出明确的定义。以Parsons & Whittemore v. RAKTA案为出发点,对公共政策的特点和发展趋势作进一步探讨。     

完善我国承认与执行外国商事仲裁裁决制度

国际商事仲裁是解决国际经济贸易纠纷的重要手段,仲裁裁决的承认与执行是仲裁制度得以实施的重要保障。我国承认与执行外国商事仲裁裁决制度的框架已基本形成,但细节尚需完善。为此我国应该明确外国仲裁机构在我国内地作出的仲裁裁决的国籍,对社会公共利益作出限定解释,删去人民法院报告制度,以使我国承认与执行外国商事仲裁裁决制度更为完善。     

美国承认执行ICSID仲裁裁决的立法与实践评析

美国承认执行ICSID仲裁裁决的国内法依据包括《解决投资争端公约法案》和《外国主权豁免法案》。依据美国目前的相关司法实践,ICSID仲裁裁决胜诉方应向哥伦比亚特区联邦地区法院提出承认执行申请,向被告送达传票和诉状是必经程序。美国在ICSID仲裁裁决的执行问题上是适用限制豁免原则的。用于商业活动的他国财产在一定情形下不得享受豁免。我国投资者去美国寻求ICSID仲裁裁决的承认执行应确保符合上述要求。作为《解决国家与他国国民间投资争议公约》缔约国,我国政府应明确表明履行公约项下义务的立场,尽快指定承认执行ICSID仲裁裁决的主管法院或机构,明确相关程序规则,完善有关国家豁免的规定。     

未来国际商事仲裁的发展趋势

随着世界经济一体化进程的加快,国际交流及经济活动日趋频繁,跨国纠纷也逐渐增多。国际商事仲裁作为解决跨国经济纠纷的有效手段之一,将越来越受重视。笔者认为未来的国际商事仲裁将呈现以下发展趋势:一、对国际商事仲裁司法监督的弱化趋势联合国在1958年通过的关于《承认和执行外国仲裁裁决的公约》(简称《纽约公约》),为各国承认及执行外国仲裁裁决确立了可操作的标准,但《纽约公约》所规定的许多条款的内涵仍可以作出诸多不同的解释,这给各国承认和执行他国仲裁裁决仍然留下了不少灵活性,使国际商事仲裁裁决的执行受到一定程度的影响。近…     

纽约公约与中国仲裁裁决在外国的承认和执行

仲裁的作用在很大程度上依赖于对裁决公正和有效的执行，近年来我国有关仲裁的论述不少，但涉及中国仲裁裁决在外国承认和执行的研究不多，本文通过对外国法院典型案例分析，揭示了我国仲裁裁决在外国执行时遇到的实际法律问题，重点分析了外国法院对《纽约公约》的解释和适用。     

浅析无涉外因素纠纷的外国仲裁——由“北京朝来新生体育休闲有限公司申请承认和执行外国仲裁裁决案”引入

本文以北京朝来新生体育休闲有限公司申请承认和执行外国仲裁裁决案为切入点,分析无涉外因素纠纷在外国仲裁机构仲裁的相关问题。国内当事人将无涉外因素的纠纷约定提请外国仲裁机构仲裁的,仲裁协议不应因无涉外因素即认定为无效,如无其他阻碍事由,只要符合仲裁协议有效要件就应认定为有效。相应的仲裁裁决,如果不存在《纽约公约》第五条规定的无效情形的,应得到我国法院的承认与执行。     

论外国仲裁裁决在韩国的承认与执行

国际商事仲裁因具有异国执行、平等中立、一裁终局等特点,在解决国际商事纠纷中所起的作用备受瞩目,随着中韩贸易的不断发展,相互承认和执行仲裁裁决尤为重要。为顺应《国际商事仲裁示范法》修订内容,符合国际仲裁制度标准,2016年韩国新《仲裁法》正式实施。据此,正确理解与适用韩国对于外国仲裁裁决的承认与执行的规定有助于尽快解决双方涉及的国际商事纠纷,提高"一带一路"建设争端解决效率。     

美国法院对外国两种不同“裁决”的承认与执行

<正> 美国法院在承认和执行外国两种不同的“裁决”——由外国法院作出的司法判决(以下简称外国判决)和由1958年《纽约公约》的参加国的仲裁机构作出的仲裁裁决(以下简称仲裁裁决)     

澳门与内地仲裁裁决制度之比较分析

内地与澳门之间相互承认与执行仲裁裁决经过多年的司法实践和总结，已有一定的经验积累，并在此基础上不断的完善和修订相关法律，澳门关于涉外仲裁裁决法律规定的内容制定出台的时间虽然比较晚，但对商事仲裁裁决制定的修订与完善仍有一定的借鉴意义，本文从分析二地间仲裁裁决制度设定的不同，探讨因区级法律冲突所造成的裁决执行难的问题。     

论强制性规则与公共政策对国际商事仲裁的影响

<正> 公共政策作为一个国际私法的概念,经常被用于拒绝有违法院地法律基本原则的外国法的适用或某些判决的执行。在国际商事仲裁中,公共政策与强制性规则对仲裁协议的效力、仲裁程序的合法性、仲裁裁决的有效性等,均有不同程度的影响。国家虽然赋予当事人广泛的仲裁自治权,但法院仍然通过外国仲裁裁决的承认与执行制度,对国际商事仲裁保有最终的审查控制权。     

时差型卫星定位系统目标位置标校算法的误差分析

针对时差型卫星定位系统位置标校算法中标校源选择的问题,首先建立了基于单个标校源的标校方法的误差分析模型,分析了参数的系统性误差和随机测量误差对标校效果的影响;其次,定义了两类定位误差改善因子,用来定量描述标校算法对定位精度的改善能力,并可以通过理论计算评价标校源的标校效果,从而为标校源的选择提供了依据。最后,仿真分析验证了误差分析模型及定位误差改善因子的有效性。     

基于平均循环周期图方法的Frank编码信号循环谱特征参数估计

针对Frank编码信号非合作条件下参数估计问题,提出了基于平均循环周期图的循环 谱特征参数估计算法。该算法利用信号参数与循环谱特征的联系,通过提取信号的循环谱特 征,实现对其关键参数的估计。分析了算法的计算量,给出了该算法的具体实现步骤,并通 过对信号参数归一化均方根估计误差的仿真计算,分析了噪声环境对参数估计的影响,表明 该算法对Frank编码信号循环谱特征参数估计的有效性。     

A marginal-predictive approach to identifying household parameters

Estimation of household parameters in scanner panel data requires the introduction of prior information. Traditionally, prior information is incorporated by restricting parameters to be constant across households or by specifying a random coefficient distribution. An alternative solution is to incorporate stochastic prior information in a formal Bayesian approach. In standard Bayesian analysis, a prior distribution over the model parameters is specified and combined with the household likelihood to obtain the Bayes estimates. The construction of the prior distribution over model parameters may be difficult, especially when working with new models whose parameters are difficult to interpret. In this paper, we propose a solution which specifies prior information through the marginal distribution of the data, i.e., the outcomes. We evaluate this marginal-predictive approach, using both actual and simulated panel data, and show it to be highly accurate relative to other available alternatives.     

雷达杂波谱参量估计及其在自适应滤波中的应用

本文结合自适应滤波技术在地面监视雷达信号处理中的工程应用,提出一种利用自相关法实时估计杂波谱参量,并根据统计参量自适应控制滤波器的方法.采用门限判决法,改善了杂波空域分布不均匀和目标引入对杂波谱参量估计带来的误差.文中特别对自适应滤波技术的实际工程应用问题进行分析讨论.经理论分析和计算模拟论证了该方法的正确性和可行性.最后结合工程实践,给出采用TMS32020数字信号处理器实现杂波谱参量估计和自适应控制滤波器的方案设想.     

ON THE CONSISTENCY OF REGRESSION‐BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS

In many applications of regression‐based Monte Carlo methods for pricing, American options in discrete time parameters of the underlying financial model have to be estimated from observed data. In this paper suitably defined nonparametric regression‐based Monte Carlo methods are applied to paths of financial models where the parameters converge toward true values of the parameters. For various Black–Scholes, GARCH, and Levy models it is shown that in this case the price estimated from the approximate model converges to the true price.     

Link11系统的QualNet仿真

为了探索Link11系统中关键的网络参数与系统性能之间的关系,依据Link11相关标准,以QualNet为仿真平台,对Link 11系统进行建模和定义统计指标。以空中监视应用为例,通过仿真实验对系统典型参数与性能的制约关系进行深入分析,同时也提出数据链系统设计、仿真、使用时应注意的问题。     

Development of uncertainty-based work injury model using Bayesian structural equation modelling

This paper proposed a Bayesian method-based structural equation model (SEM) of miners’ work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts’ opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts’ opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.     

On the role of the utility function in the estimation of preference parameters

Modern economic theory summarizes the main characteristics of individual preferences through a definite set of parameters: risk aversion, prudence, and the elasticity of intertemporal substitution. Despite their importance, the results of the literature devoted to the parameters’ estimation are controversial. This paper highlights the neglected role that may have been played by the constraints that the quantitative definition of the parameters and the utility functions employed impose on the estimation. A number of simulation exercises are presented, which show that the same saving behaviour can be associated with quite different values of the parameters depending on the utility function adopted.     

On the unstable relationship between exchange rates and macroeconomic fundamentals

Survey evidence shows that the relationship between the exchange rate and macro fundamentals is perceived to be highly unstable. We argue that this unstable relationship naturally develops when structural parameters in the economy are unknown. We show that the reduced form relationship between exchange rates and fundamentals is then driven not by the structural parameters themselves, but rather by expectations of these parameters. These expectations can vary significantly over time as a result of perfectly rational “scapegoat” effects. These effects can be expected to hold more broadly in macro and finance beyond the application to exchange rates in this paper.     

Estimating time-varying parameters in brand choice models: A semiparametric approach

Nowadays, brand choice models are standard tools in quantitative marketing. In most applications, parameters representing brand intercepts and covariate effects are assumed to be constant over time. However, marketing theories, as well as the experience of marketing practitioners, suggest the existence of trends or short-term variations in particular parameters. Hence, having constant parameters over time is a highly restrictive assumption, which is not necessarily justified in a marketing context and may lead to biased inferences and misleading managerial insights.In this paper, we develop flexible, heterogeneous multinomial logit models based on penalized splines to estimate time-varying parameters. The estimation procedure is fully data-driven, determining the flexible function estimates and the corresponding degree of smoothness in a unified approach. The model flexibly accounts for parameter dynamics without any prior knowledge needed by the analyst or decision maker. Thus, we position our approach as an exploratory tool that can uncover interesting and managerially relevant parameter paths from the data without imposing assumptions on their shape and smoothness.Our approach further allows for heterogeneity in all parameters by additively decomposing parameter variation into time variation (at the population level) and cross-sectional heterogeneity (at the individual household level). It comprises models without time-varying parameters or heterogeneity, as well as random walk parameter evolutions used in recent state space models, as special cases. The results of our extensive model comparison suggest that models considering parameter dynamics and household heterogeneity outperform less complex models regarding fit and predictive validity. Although models with random walk dynamics for brand intercepts and covariate effects perform well, the proposed semiparametric approach still provides a higher predictive validity for two of the three data sets analyzed.For joint estimation of all regression coefficients and hyperparameters, we employ the publicly available software BayesX, making the proposed approach directly applicable.