Assessment of Uncertainty in High Frequency Data: The Observed Asymptotic Variance

The availability of high frequency financial data has generated a series of estimators based on intra‐day data, improving the quality of large areas of financial econometrics. However, estimating the standard error of these estimators is often challenging. The root of the problem is that traditionally, standard errors rely on estimating a theoretically derived asymptotic variance, and often this asymptotic variance involves substantially more complex quantities than the original parameter to be estimated. Standard errors are important: they are used to assess the precision of estimators in the form of confidence intervals, to create “feasible statistics” for testing, to build forecasting models based on, say, daily estimates, and also to optimize the tuning parameters. The contribution of this paper is to provide an alternative and general solution to this problem, which we call Observed Asymptotic Variance. It is a general nonparametric method for assessing asymptotic variance (AVAR). It provides consistent estimators of AVAR for a broad class of integrated parameters Θ = ∫ θ_t dt, where the spot parameter process θ can be a general semimartingale, with continuous and jump components. The observed AVAR is implemented with the help of a two‐scales method. Its construction works well in the presence of microstructure noise, and when the observation times are irregular or asynchronous in the multivariate case. The methodology is valid for a wide variety of estimators, including the standard ones for variance and covariance, and also for more complex estimators, such as, of leverage effects, high frequency betas, and semivariance.     

自我表露及其作用

有关自我表露的研究是心理学关于自我研究的一个重要领域,心理学家发现,展示个人信息的行为有重要的心理学意义.自我表露是个人成长和自我实现的必要环节,是个体印象管理和应对压力的有效方式,也是心理治疗的重要途径.     

跨国公司对华投资国民待遇问题研究

跨国投资企业对东道国发挥的经济效应 ,与东道国对跨国投资企业给予的待遇密切相关。介绍外国对其外资企业所采取的待遇标准 ,论述我国对来华投资企业的待遇安排及其产生的效果 ,认为我国当前对来华投资企业实行国民待遇不切实际 ,只能逐步向有限制的国民待遇方向发展。     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

突发公共事件应对中的行政权威及其尺度

我国继SARS、禽流感之后又遭受了较为严重的狂犬病疫情袭击。在这些事件的应对中,政府权力行使所暴露的缺陷依然如故,引起人们的广泛关注。笔者分析了突发公共事件应对中行政权力行使的必要性,认为在应对突发公共事件中,必须树立民主与权威相结合的指导原则;同时,必须根据权力法定、权益保护、公共评价、比例原则和制度体系这五个因素来综合制定评判标准以明确行政权力行使的界限。     

感官欣赏与理性欣赏的重要环节——音乐欣赏课的教学与实践

本文认为，要提高音乐欣赏能力，使审美意识达到更高的境界，就必须掌握音乐理论基础知识，了解各种不同形式、不同体裁的音乐理作品的风格与特点，从而在理论上为独立分析音乐作品打下一个基础。这是音乐欣赏课的出发点     

概述我国古代先贤对职业病的认识及其防治

以我国古代典籍所载的史料为依据 ,汇集了先贤们对职业病的认识及其相应采取的行之有效的防治之法 ,说明在职业病领域 ,我国传统医学亦取得了一定的历史性成果。这必将为我们今天发掘职业病防治的精粹 ,开拓中医药防治职业病的新局面提供有益的启迪     

非定常控制系统的绝对稳定性

从研究中间变量σ情况和判断控制系统解的界及k类函数法来讨论控制系统零解的绝对稳定,并给出了判断非线性非定常系统零解绝对稳定的一种新方法.     

用VB实现PC机与GPIB通讯卡的通讯

主要研究波形测试及分析数据传递问题，测量模块采用GPIB总线标准，模块与计算机间的通讯用VB编程实现。