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Burridge–Guerre 非参数单位根检验的推广AI 解读

In this note the nonparametric unit root test of Burridge and Guerre (1996, Econometric Theory, 12, 705–723), which is based on the standardized number of crossings of a level of a random walk, is extended in two ways, allowing for a deterministic trend in the process and more general innovations. The test has a well-known standard limit distribution. Monte Carlo experiments revealed the good finite-sample properties of the proposed test.The authors appreciate helpful…

内生解释变量单方程协整模型中的 fixed-b 渐近理论AI 解读

This note uses fixed bandwidth (fixed-b) asymptotic theory to suggest a new approach to testing cointegration parameters in a single-equation cointegration environment. It is shown that the standard tests still have asymptotic distributions that are free of serial correlation nuisance parameters regardless of the bandwidth or kernel used, even if the regressors in the cointegration relationship are endogenous.I thank Tim Vogelsang for his guidance, Pentti Saikkonen for the…

基于小波谱密度估计的多元时间序列序列相关检验AI 解读

A new one-sided test for serial correlation in multivariate time series models is proposed. The test is based on a comparison between a multivariate spectral density estimator and the spectral density under the null hypothesis of no serial correlation. Duchesne and Roy (2004, Journal of Multivariate Analysis 89, 148–180) considered a multivariate kernel-based spectral density estimator. However, when the spectral density exhibits irregular features (because of strong…

金融计量中双幂变差的极限定理AI 解读

In this paper we provide an asymptotic analysis of generalized bipower measures of the variation of price processes in financial economics. These measures encompass the usual quadratic variation, power variation, and bipower variations that have been highlighted in recent years in financial econometrics. The analysis is carried out under some rather general Brownian semimartingale assumptions, which allow for standard leverage effects.Ole E. Barndorff-Nielsen's work is…

动态回归模型的数据驱动非参数设定检验AI 解读

The paper introduces a new nonparametric specification test for dynamic regression models. The test combines chi-square statistics based on Fourier series regression. A data-driven choice of the regression order, which uses the square root of the number of Fourier coefficients, is proposed. The benefits of the new test are (1) the selection procedure produces explicit and chi-square critical values that give a finite-sample size close to the nominal size; (2) the test is…

气温序列趋势的半参数估计与检验AI 解读

The application of a partially linear model to global and hemispheric temperature series is proposed. Partially linear modelling allows the trend to take a very general form rather than imposing the restriction of linearity seen in existing studies. The removal of the linearity restriction is based on the fact that it is well accepted that a significant trend is present in global temperature series. The model will allow for the data to "speak for themselves" with regard to…

平稳与非平稳协整回归的工具变量估计AI 解读

Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least-squares estimation of cointegrating regressions between non-stationary and/or long memory stationary variables where the integration orders of regressor and disturbance sum to less than 1, as happens always for stationary regressors, and sometimes for mean-reverting non-stationary ones. Unlike in the classical…

三区制SETAR模型中的单位根检验AI 解读

This paper proposes a simple testing procedure to distinguish a unit root process from a globally stationary three-regime self-exciting threshold autoregressive process. Following the threshold cointegration literature we assume that the process follows the random walk in the corridor regime, and therefore we propose that the null of a unit root be tested by the Wald statistic for the joint significance of autoregressive parameters in both lower and upper regimes. We…

初始观测来自无条件分布时的单位根检验与结构变化AI 解读

Following Elliott (1999; International Economic Review 40, 767--83.) and Perron and Rodríguez (2003; Journal of Econometrics 115,1--27), we develop unit root tests in the context of structural change models using GLS detrended data ( Elliott, Rothenberg and Stock 1996; Econometrica 64, 813--39) when the initial observation is drawn from its unconditional distribution. We derive the limiting distributions of the M-tests ( Stock, 1999 cointegration, causality and forecasting;…

含结构突变的单位根检验：联合假设的设定AI 解读

Several tests based on a t-ratio have been proposed in the literature to decide the order of integration of a time series allowing for a structural break. However, another approach based on testing a joint hypothesis of unit root and the irrelevance of some nuisance parameters is also feasible. This paper proposes new unit root tests consistent with the presence of a structural break applying this second perspective. Our approach deals both with the case where the break is…

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基于奇异值分解的广义降秩检验AI 解读

We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the LDU rank statistic of Cragg and Donald (1996) and Gill and Lewbel (1992), a limiting distribution that is not a standard chi-squared distribution for the rank statistic of Robin and…

扩散指数预测的置信区间与因子增强回归推断AI 解读

We consider the situation when there is a large number of series, N, each with T observations, and each series has some predictive ability for some variable of interest. A methodology of growing interest is first to estimate common factors from the panel of data by the method of principal components and then to augment an otherwise standard regression with the estimated factors. In this paper, we show that the least squares estimates obtained from these factor-augmented…

利用已实现测度对随机波动率模型进行半参数比较AI 解读

This paper proposes a procedure to test for the correct specification of the functional form of the volatility process within the class of eigenfunction stochastic volatility models. The procedure is based on the comparison of the moments of realized volatility measures with the corresponding ones of integrated volatility implied by the model under the null hypothesis.We first provide primitive conditions on the measurement error associated with the realized measure, which…

利率的树结构多状态模型AI 解读

This article develops a generalized tree-structured (GTS) model of the short-term interest rate that accommodates regime-dependent mean reversion and regime-dependent volatility clustering and level effects in the conditional variance. The model is constructed using the idea of multivariate tree-structured thresholds and nests the popular generalized autoregressive conditional heteroscedasticity and square root processes as simple special cases. It allows us to estimate the…

基于 Wishart 过程的多变量随机波动率模型AI 解读

Financial models for asset and derivatives pricing, risk management, portfolio optimization, and asset allocation rely on volatility forecasts. Time-varying volatility models, such as generalized autoregressive conditional heteroscedasticity and stochastic volatility (SVOL), have been successful in improving forecasts over constant volatility models. We develop a new multivariate SVOL framework for modeling financial data that assumes covariance matrices stochastically…

追踪欧元区商业周期AI 解读

This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties. Furthermore, cycle shifts for individual time series are incorporated as part of the multivariate model and estimated simultaneously with the remaining parameters. The inclusion of…

美国实际产出状态切换时间序列模型的有效性评估AI 解读

Two types of state-switching models for U.S. real output have been proposed: models that switch randomly between states and models that switch states deterministically, as in the threshold autoregressive model of Potter. These models have been justified primarily on how well they fit the sample data, yielding statistically significant estimates of the model coefficients. Here we propose a new approach to the evaluation of an estimated nonlinear time series model that…

含极端异常值金融时间序列的二阶滤波分布近似AI 解读

Particle filters are regularly used to obtain the filter distributions associated with state–space financial time series. The most common use today is the auxiliary particle filter (APF) method in conjunction with a first-order Taylor expansion of the log-likelihood. We argue that for series such as stock returns, which exhibit fairly frequent and extreme outliers, filters based on this first-order approximation can easily break down. However, an APF based on the much more…