Conditional Likelihood Estimators for Hidden Markov Models and Stochastic Volatility Models

ABSTRACT.  This paper develops a new contrast process for parametric inference of general hidden Markov models, when the hidden chain has a non-compact state space. This contrast is based on the conditional likelihood approach, often used for ARCH-type models. We prove the strong consistency of the conditional likelihood estimators under appropriate conditions. The method is applied to the Kalman filter (for which this contrast and the exact likelihood lead to asymptotically equivalent estimators) and to the discretely observed stochastic volatility models.     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

基于二阶段随机规划的城市医疗废弃物回收网络设计

城市医疗废弃物日益增加,且回收需求量受诸多因素的影响,难以准确预测,假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下,医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题,建立了以选址成本、运输成本最小为目标,设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点,设计了基于Benders decomposition的求解算法,同时,设计了一系列加速技术用于提高算法的求解效率。最后,以国内某城市医疗回收网络为背景设计算例,检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划,随机规划的解能够节约总成本,结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。     

股市联动中的“涟漪效应”

本文提出"涟漪效应"来解释国际股市联动性的大幅波动。所谓涟漪效应就是中心市场特有波动对其它市场间联动性产生影响的现象。本文采用滚动窗口和DCC-GARCH的方法计算了市场特有波动和收益相关系数,以9个主要市场指数为样本对国际股票市场中涟漪效应进行实证检验。研究结果显示,2007年后国际股市联动性变化与美国市场的涟漪效应有关,美国市场特有波动升高（降低）会导致全球股市联动性升高（降低）,而其他市场特有波动并没有类似影响。美国市场与其他市场间联动性基本不受第三方市场特有波动的影响,A股与美股联动性的增强是造成A股与其它股市联动性变化的主要原因。此外,研究特有波动与相关系数的关系能帮助我们识别国际股市中风险传递方向,本文结果显示欧洲市场对其他市场的影响非常有限,以往研究可能高估了欧洲市场的影响力。本文丰富了股市联动性影响因素的研究,对理解市场联动性变化、评估市场影响力等问题有重要意义。     

金融市场多标度分形现象及与风险管理的关系

已有研究通过对汇率、股票收益率、黄金价格等金融市场实证数据的分析,发现这些数据 具有多标度分形(multifractal) 特征. 通过对中国金融市场的代表数据之一———上海证券交易 所综合股价指数(SSECI) 的研究得出了相似的结论,并且初步提出了运用多标度分形理论所 提供的信息来进行金融风险管理的风险管理思路.     

金融工程中资产收益的连续时间模型评述

总结了在过去30年中金融资产收益连续时间模型的发展及主要成果,讨论了迄今连续时间模型参数估计的主要方法,其中特别讨论了MCMC方法;最后指出了现在和未来该领域研究所面临的主要课题。     

基于GARCH族模型的深证成指波动特征实证分析

采用GARCH族模型对深证成指总体及分阶段收益率的波动性进行统计拟合分析,指出深证成指的波动具有集聚性、持久性、显著的非对称性效应及阶段性特征。以深证成指价格达到最高点的时间点为分界,将整个样本分成两个阶段:在第一阶段,“利好消息”对深证成指的冲击比同等程度的“利空消息”大;在第二阶段,“利空消息”的冲击比同等程度的“利好消息”大。这说明深证市场具有杠杆效应。     

On a system of nonhomogeneous components sharing a common frailty

The components of a reliability system subjected to a common random environment usually have dependent lifetimes. This paper studies the stochastic properties of such a system with lifetimes of the components following multivariate frailty models and multivariate mixed proportional reversed hazard rate (PRHR) models, respectively. Through doing stochastic comparison, we devote to throwing a new light on how the random environment affects the number of working components of a reliability system and on assessing the performance of a k-out-of-n system.     

New calibration estimator based on two auxiliary variables in stratified sampling

In recent years, calibration estimation has become an important field of research in survey sampling. This paper proposes a new calibration estimator for the population mean in the presence of two auxiliary variables in stratified sampling. The theory of new calibration estimator is given and optimum calibration weights are derived. A simulation study is carried out to performance of the proposed calibration estimator over other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than other existing calibration estimators in stratified sampling.     

Why Frequency is Not Well Defined for Engineering Systems with Nonexponential Failure Times

Dr. Yellman proposes to define frequency as “a time‐rate of events of a specified type over a particular time interval.” We review why no definition of frequency, including this one, can satisfy both of two conditions: (1) the definition should agree with the ordinary meaning of frequency, such as that less frequent events are less likely to occur than more frequent events, over any particular time interval for which the frequencies of both are defined; and (2) the definition should be applicable not only to exponentially distributed times between (or until) events, but also to some nonexponential (e.g., uniformly distributed) times. We make the simple point that no definition can satisfy (1) and (2) by showing that any definition that determines which of any two uniformly distributed times has the higher “frequency” (or that determines that they have the same “frequency,” if neither is higher) must assign a higher frequency number to the distribution with the lower probability of occurrence over some time intervals. Dr. Yellman's proposed phrase, “time‐rate of events … over a particular time interval” is profoundly ambiguous in such cases, as the instantaneous failure rates vary over an infinitely wide range (e.g., from one to infinity), making it unclear which value is denoted by the phrase “time‐rate of events.”