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随机时间下收益波动率度量中的因果效应AI 解读

We provide a structural approach to identify instantaneous causality effects between durations and stock price volatility. So far, in the literature, instantaneous causality effects have either been excluded or cannot be identified separately from Granger type causality effects. By giving explicit moment conditions for observed returns over (random) duration intervals, we are able to identify an instantaneous causality effect. The documented causality effect has significant…

已实现波动率及相关估计量的 Edgeworth 展开AI 解读

This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to Cornish-Fisher inversion and help setting intervals more accurately than those relying on normal distribution.

已实现波动率的 Box–Cox 变换AI 解读

The log transformation of realized volatility is often preferred to the raw version of realized volatility because of its superior finite sample properties. One of the possible explanations for this finding is the fact the skewness of the log transformed statistic is smaller than that of the raw statistic. Simulation evidence presented here shows that this is the case. It also shows that the log transform does not completely eliminate skewness in finite samples. This…

带跳跃马尔可夫模型的阈值估计与利率建模AI 解读

We reconstruct the level-dependent diffusion coefficient of a univariate semimartingale with jumps which is observed discretely. The consistency and asymptotic normality of our estimator are provided in the presence of both finite and infinite activity (finite variation) jumps. Our results rely on kernel estimation, using the properties of the local time of the data generating process, and the fact that it is possible to disentangle the discontinuous part of the state…

非同步交易与市场微观结构噪声下的协方差测量AI 解读

This paper studies the problem of covariance estimation when prices are observed non-synchronously and contaminated by i.i.d. microstructure noise. We derive closed form expressions for the bias and variance of three popular covariance estimators, namely realised covariance, realised covariance plus lead and lag adjustments, and the Hayashi and Yoshida estimator, and present a comprehensive investigation into their properties and relative efficiency. Our main finding is that…

报价按固定最小价位变动时的二次变差估计AI 解读

For financial assets whose best quotes almost always change by jumping by the market's price tick size (one cent, five cents, etc.), this paper proposes an estimator of Quadratic Variation which controls for microstructure effects. It measures the prevalence of alternations, where quotes jump back to their just-previous price. It defines a simple property called "uncorrelated alternation", which under conditions implies that the estimator is consistent in an asymptotic limit…

When estimating finance panel regressions, it is common practice to adjust standard errors for correlation either across firms or across time. These procedures are valid only if the residuals are correlated either across time or across firms, but not across both. This paper shows that it is very easy to calculate standard errors that are robust to simultaneous correlation along two dimensions, such as firms and time. The covariance estimator is equal to the estimator that…

通过分位数回归评估风险价值模型AI 解读

This article is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such as Christoffersen (1998) and Engle and Manganelli (2004) are based on such variables. In this article we propose a new backtest that does not rely solely on binary variables. It is…

利用倾向得分的自适应实验设计AI 解读

Many social experiments are run in multiple waves or replicate earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for estimating an average treatment effect when covariate information is available for experimental subjects. We use data from the first stage to choose a conditional treatment assignment rule for…

协变量依赖删失下的异方差变换模型AI 解读

In this article we propose an inferential procedure for transformation models with conditional heteroscedasticity in the error terms. The proposed method is robust to covariate dependent censoring of arbitrary form. We provide sufficient conditions for point identification. We then propose an estimator and show that it is √n-consistent and asymptotically normal. We conduct a simulation study that reveals adequate finite sample performance. We also use the estimator in an…

自轮廓（Autocontours）：动态设定检验AI 解读

We propose a new battery of dynamic specification tests for the joint hypothesis of iid-ness and density function based on the fundamental properties of independent random variables with identical distributions. We introduce a device—the autocontour—whose shape is very sensitive to departures from the null in either direction, thus providing superior power. The tests are parametric with asymptotic t and chi-squared limiting distributions and standard convergence rates. They…

动态条件协方差的估计与预测：半参数多变量模型AI 解读

We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare…

名次减去二分之一：改进尾部指数 OLS 估计的简便方法AI 解读

Despite the availability of more sophisticated methods, a popular way to estimate a Pareto exponent is still to run an OLS regression: log(Rank) = a − b log(Size), and take b as an estimate of the Pareto exponent. The reason for this popularity is arguably the simplicity and robustness of this method. Unfortunately, this procedure is strongly biased in small samples. We provide a simple practical remedy for this bias, and propose that, if one wants to use an OLS regression,…

协整面板的参数可合并性新检验AI 解读

This paper proposes a new test of the null hypothesis that the parameters in a cointegrated panel data regression are equal across the cross-section. The asymptotic distribution of the new test statistic is derived and simulation results are provided to suggest that it performs very well in small samples. An empirical application to the monetary exchange rate model is also provided. Copyright (C) 2009 John Wiley & Sons, Ltd.

跳跃尾部的估计AI 解读

We propose a new and flexible nonparametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple-to-implement set of estimating equations associated with the compensator for the jump measure, or its intensity, that only utilizes the weak assumption of regular variation in the jump tails, along with in-fill asymptotic arguments for directly estimating the “large” jumps. The procedure assumes that the large-sized…

含逆向选择与道德风险的合同模型：非参数识别AI 解读

This paper studies the nonparametric identification of a contract model with adverse selection and moral hazard. Specifically, we consider the false moral hazard model developed by Laffont and Tirole (1986). We first extend this model to allow for general random demand and cost functions. We establish the nonparametric identification of the demand, cost, deterministic transfer, and effort disutility functions as well as the joint distribution of the random elements of the…

基于扩展矩方法的有效衍生品定价AI 解读

In this paper, we introduce the extended method of moments (XMM) estimator. This estimator accommodates a more general set of moment restrictions than the standard generalized method of moments (GMM) estimator. More specifically, the XMM differs from the GMM in that it can handle not only uniform conditional moment restrictions (i.e., valid for any value of the conditioning variable), but also local conditional moment restrictions valid for a given fixed value of the…

应用非参数工具变量估计AI 解读

Instrumental variables are widely used in applied econometrics to achieve identification and carry out estimation and inference in models that contain endogenous explanatory variables. In most applications, the function of interest (e.g., an Engel curve or demand function) is assumed to be known up to finitely many parameters (e.g., a linear model), and instrumental variables are used identify and estimate these parameters. However, linear and other finite-dimensional…

弱收敛假设下的检验效率AI 解读

The asymptotic validity of tests is usually established by making appropriate primitive assumptions, which imply the weak convergence of a specific function of the data, and an appeal to the continuous mapping theorem. This paper, instead, takes the weak convergence of some function of the data to a limiting random element as the starting point and studies efficiency in the class of tests that remain asymptotically valid for all models that induce the same weak limit. It is…

模型置信集合AI 解读

This paper introduces the model confidence set (MCS) and applies it to the selection of models. A MCS is a set of models that is constructed such that it will contain the best model with a given level of confidence. The MCS is in this sense analogous to a confidence interval for a parameter. The MCS acknowledges the limitations of the data, such that uninformative data yield a MCS with many models, whereas informative data yield a MCS with only a few models. The MCS…

实验设计中的加权最优性AI 解读

An optimality framework is developed for designing experiments in which not all treatments are of equal interest, such as those including an established control. Differential interest in treatments is formalized by assignment of weights, incorporated into optimality measures through a weighted version of the information matrix. All conventional measures of design efficacy are shown to have weighted analogs. The properties of weighted measures are explored, some general…

结合非参数预测与最优线性时间序列预测AI 解读

We introduce a semiparametric procedure for more efficient prediction of a strictly stationary process admitting an ARMA representation. The procedure is based on the estimation of the ARMA representation, followed by a nonparametric regression where the ARMA residuals are used as explanatory variables. Compared to standard nonparametric regression methods, the number of explanatory variables can be reduced because our approach exploits the linear dependence of the process.…

聚类数据稳健估计的自助推断AI 解读

In mixed models, the use of robust estimates raises several interesting inferential challenges. One of these challenges arises from the realization that the effect of contamination is to increase the variability in the data, but robust estimates of variance components are usually smaller than their nonrobust counterparts. The robust estimates reflect the variability of the bulk of the data, which is not the same as the variability in the data-generating process. This means…

多抽样框调查的伪经验似然推断AI 解读

This article presents a pseudo–empirical likelihood approach to inference for multiple-frame surveys. We establish a unified framework for point and interval estimation of finite population parameters, and show that inferences on the parameters of interest making effective use of different types of auxiliary population information can be conveniently carried out through the constrained maximization of the pseudo–empirical likelihood function. Confidence intervals are…