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两种长期方差估计量：超越短记忆AI 解读

This paper deals with the estimation of the long-run variance of a stationary sequence. We extend the usual Bartlett-kernel heteroskedasticity and autocorrelation consistent (HAC) estimator to deal with long memory and antipersistence. We then derive asymptotic expansions for this estimator and the memory and autocorrelation consistent (MAC) estimator introduced by Robinson [Robinson, P. M., 2005. Robust covariance matrix estimation: HAC estimates with long…

状态价格密度的动态变化AI 解读

State price densities (SPDs) are an important element in applied quantitative finance. In a Black-Scholes world they are lognormal distributions, but in practice volatility changes and the distribution deviates from log-normality. In order to study the degree of this deviation, we estimate SPDs using EUREX option data on the DAX index via a nonparametric estimator of the second derivative of the (European) call pricing function. The estimator is constrained so as to satisfy…

追随德国：利用国际货币联系估计货币政策的经济效应AI 解读

Forward-looking behavior on the part of the monetary authority makes it difficult to estimate the effect of monetary policy interventions on output. We present instrumental variables estimates of the impact of interest rates on quarterly real output for several European countries, using German interest rates as the instrument. These estimates confirm a strong forward-looking bias in least squares estimates that persists even conditional on standard controls for the history…

半参数整数值 AR(p) 模型的自回归参数与创新分布有效估计AI 解读

Summary Integer-valued auto-regressive (INAR) processes have been introduced to model non-negative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of auto-regression coefficients and a probability distribution on the non-negative integers, called an immigration or innovation distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to…

未知方差下的高斯模型选择AI 解读

Let Y be a Gaussian vector whose components are independent with a common unknown variance. We consider the problem of estimating the mean μ of Y by model selection. More precisely, we start with a collection $\mathcal{S}=\{S_{m},m\in\mathcal{M}\}$ of linear subspaces of ℝn and associate to each of these the least-squares estimator of μ on Sm. Then, we use a data driven penalized criterion in order to select one estimator among these. Our first objective is to analyze the…

未知噪声下遍历动力系统预测的支持向量机一致性AI 解读

We consider the problem of forecasting the next (observable) state of an unknown ergodic dynamical system from a noisy observation of the present state. Our main result shows, for example, that support vector machines (SVMs) using Gaussian RBF kernels can learn the best forecaster from a sequence of noisy observations if (a) the unknown observational noise process is bounded and has a summable α-mixing rate and (b) the unknown ergodic dynamical system is defined by a…

ARMA 模型的稳健估计AI 解读

This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard…

多元时间序列回归模型序贯程序的检测延迟AI 解读

We consider a multiple regression model in which the explanatory variables are specified by time series. To sequentially test for the stability of the regression parameters in time, we introduce a detector which is based on the first excess time of a CUSUM-type statistic over a suitably constructed threshold function. The aim of this paper is to study the delay time associated with this detector. As our main result, we derive the limit distribution of the delay time and…

序列相关误差下协整回归有效估计量的渐近性质AI 解读

In this paper, we analytically investigate three efficient estimators for cointegrating regression models: Phillips and Hansen's [Phillips, P.C.B., Hansen, B.E., 1990. Statistical inference in instrumental variables regression with I(1) processes. Review of Economic Studies 57, 99-125] fully modified OLS estimator, Park's [Park, J.Y., 1992. Canonical cointegrating regressions. Econometrica 60, 119-143] canonical cointegrating regression estimator, and Saikkonen's [Saikkonen,…

含全球随机趋势的面板协整AI 解读

This paper studies estimation of panel cointegration models with cross-sectional dependence generated by unobserved global stochastic trends. The standard least squares estimator is, in general, inconsistent owing to the spuriousness induced by the unobservable I(1) trends. We propose two iterative procedures that jointly estimate the slope parameters and the stochastic trends. The resulting estimators are referred to respectively as CupBC (continuously-updated and…

基于近似 Bahadur 斜率比较结构突变检验的相对功效AI 解读

We compare the asymptotic relative efficiency of the Exp, Mean, and Sup functionals of the Wald, LM and LR tests for structural change analyzed by Andrews [Andrews, D.W.K., 1993. Tests for parameter instability and structural change with unknown change point. Econometrica 61, 821-856.] and Andrews and Ploberger [Andrews, D.W.K., Ploberger, W., 1994. Optimal tests when a nuisance parameter is present only under the alternative. Econometrica 62, 1383-1414.]. We derive the…

检验重要性抽样背后的假设AI 解读

Importance sampling is used in many areas of modern econometrics to approximate unsolvable integrals. Its reliable use requires the sampler to possess a variance, for this guarantees a square root speed of convergence and asymptotic normality of the estimator of the integral. However, this assumption is seldom checked. In this paper we use extreme value theory to empirically assess the appropriateness of this assumption. Our main application is the stochastic volatility…

股票收益与预期商业状况：半个世纪的直接证据AI 解读

Using survey data, we characterize directly the impact of expected business conditions on expected excess stock returns. Expected business conditions consistently affect expected excess returns in a counter-cyclical fashion. Moreover, inclusion of expected business conditions in otherwise-standard predictive return regressions substantially reduce the explanatory power of the conventional financial predictors, including the dividend yield, default premium, and term premium,…

通过已实现波动率度量评估市场微观结构效应：道琼斯工业平均指数成分股应用AI 解读

Transaction prices of financial assets are contaminated by market microstructure effects. This is particularly relevant when estimating volatility using high frequency data. In this article, we assess statistically the effect of microstructure noise on volatility estimators, and test the hypothesis that its variance is independent of the sampling frequency. We provide evidence based on the Dow Jones Industrial Average stocks. We find that noise has a statistically…

金融收益可预测性的非参数回溯检验与监测AI 解读

We develop and evaluate sequential testing tools for a class of nonparametric tests for predictability of financial returns that include, in particular, the directional accuracy and excess profitability tests. Our sequential methods consider in a unified framework both retrospection of a historical sample and monitoring newly arriving data. To this end, we focus on linear monitoring boundaries that are continuations of horizontal lines corresponding to retrospective critical…

利用时变Copula刻画非齐次依赖关系AI 解读

Measuring dependence in multivariate time series is tantamount to modeling its dynamic structure in space and time. In risk management, the nonnormal behavior of most financial time series calls for non-Gaussian dependences. The correct modeling of non-Gaussian dependences is, therefore, a key issue in the analysis of multivariate time series. In this article we use copula functions with adaptively estimated time-varying parameters for modeling the distribution of returns.…

半强 GARCH 模型的拟最大似然估计AI 解读

This note proves the consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the parameters of a generalized autoregressive conditional heteroskedastic (GARCH) model with martingale difference centered squared innovations. The results are obtained under mild conditions and generalize and improve those in Lee and Hansen (1994, Econometric Theory 10, 29–52) for the local QMLE in semistrong GARCH(1,1) models. In particular, no restrictions on…

GARCH 模型参数设定误检验的一阶渐近理论AI 解读

This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and Ng (1993, Journal…

含某些多频 I(1) 回归变量时 OLS 估计误差的几乎必然界AI 解读

Lai and Wei (1983, Annals of Statistics 10, 154–166) state in their Theorem 1 that the estimators of the regression coefficients in the regression $y_t = x_t^' \beta + \varepsilon _{\rm{t}} $ , t ∈ ℕ are almost surely (a.s.) consistent under the assumption that the minimum eigenvalue λ min ( T ) of $\sum\nolimits_{t = 1}^T {x_t } x'_t $ tends to infinity (a.s.) and log( λ max ( T ))/ λ min ( T ) → 0 (a.s.) where λ max ( T ) denotes the maximal eigenvalue.…

基于回归的季节性单位根检验AI 解读

The contribution of this paper is threefold. First, a characterization theorem of the subhypotheses comprising the seasonal unit root hypothesis is presented that provides a precise formulation of the alternative hypotheses associated with regression- based seasonal unit root tests. Second, it proposes regression-based tests for the seasonal unit root hypothesis that allow a general seasonal aspect for the data and are similar both exactly and asymptotically with respect to…

含中度整合与中度爆炸回归变量的协整系统极限理论AI 解读

An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form ρ ni = 1 + c i / n α , involving moderate deviations from unity when α ∈ (0, 1) and c i ∈ ℝ are constant parameters. When the data are moderately integrated in the stationary direction (with c i < 0), it is shown that least squares regression is consistent and…

时间序列面板的非参数加性模型AI 解读

This paper discusses nonparametric models for panels of time series. There is already a substantial literature on nonlinear models and nonparametric methods in a regression and time series setting. But almost without exception these developments have been limited to univariate and multivariate models of moderate dimensions. Very little has been done for panels, where the dimension, often corresponding to a number of individuals, typically is very large but where the number…

区分随机游走与均值变化备择AI 解读

We study test procedures that detect structural breaks in underlying data sequences. In particular, we wish to discriminate between different reasons for these changes, such as (1) shifting means, (2) random walk behavior, and (3) constant means but innovations switching from stationary to difference stationary behavior. Almost all procedures presently available in the literature are simultaneously sensitive to all three types of alternatives. The test statistics under…

因子 GARCH 模型的渐近理论AI 解读

This paper investigates the asymptotic theory for a factor GARCH (generalized autoregressive conditional heteroskedasticity) model. Sufficient conditions for asymptotic stability and existence of moments are established. These conditions allow for volatility spillover and integrated GARCH. We then show the strong consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the model parameters. The results are obtained under the finiteness of the…