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DIAGNOSTIC CHECKING FOR THE ADEQUACY OF NONLINEAR TIME SERIES MODELS

非线性时间序列模型充分性的诊断检验

We propose a new diagnostic test for linear and nonlinear time series models, using a generalized spectral approach. Under a wide class of time series models that includes autoregressive conditional heteroskedasticity (ARCH) and autoregressive conditional duration (ACD) models, the proposed test enjoys the appealing “nuisance-parameter-free” property in the sense that model parameter estimation uncertainty has no impact on the limit distribution of the test statistic. It is…

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SEMIPARAMETRIC ESTIMATION OF A HETEROSKEDASTIC SAMPLE SELECTION MODEL

异方差样本选择模型的半参数估计

This paper considers estimation of a sample selection model subject to conditional heteroskedasticity in both the selection and outcome equations. The form of heteroskedasticity allowed for in each equation is multiplicative, and each of the two scale functions is left unspecified. A three-step estimator for the parameters of interest in the outcome equation is proposed. The first two stages involve nonparametric estimation of the “propensity score” and the conditional…

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HIGHER ORDER ASYMPTOTIC THEORY FOR MINIMUM CONTRAST ESTIMATORS OF SPECTRAL PARAMETERS OF STATIONARY PROCESSES

平稳过程谱参数最小对比估计量的高阶渐近理论

Let g(λ) be the spectral density of a stationary process and let fθ(λ), θ ∈ Θ, be a fitted spectral model for g(λ). A minimum contrast estimator of θ is defined that minimizes a distance between , where is a nonparametric spectral density estimator based on n observations. It is known that is asymptotically Gaussian efficient if g(λ) = fθ(λ). Because there are infinitely many candidates for the distance function , this paper discusses higher order asymptotic theory for in…

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COVARIANCE MATRIX ESTIMATION AND THE LIMITING BEHAVIOR OF THE OVERIDENTIFYING RESTRICTIONS TEST IN THE PRESENCE OF NEGLECTED STRUCTURAL INSTABILITY

遗漏结构不稳定时协方差估计与过度识别检验的极限行为

We consider the limiting behavior of the overidentifying restrictions test in the presence of neglected structural instability at a single “break point.” It is shown that the test need not be consistent against this type of misspecification. If it is consistent then it emerges that the limiting behavior of this test statistic depends on the covariance matrix estimator employed. In this paper we consider the case in which a heteroskedasticity autocorrelation covariance (HAC)…

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THE CONTINUITY OF THE LIMIT DISTRIBUTION IN THE PARAMETER OF INTEREST IS NOT ESSENTIAL FOR THE VALIDITY OF THE BOOTSTRAP

极限分布对目标参数连续并非 Bootstrap 有效性的必要条件

It is well known that the unrestricted bootstrap estimator of the slope parameter in the random walk model without drift converges to a random distribution. This bootstrap failure is commonly attributed to the discontinuity of the limit distribution of the least-squares estimator in the parameter of interest. We demonstrate by counterexample that this type of continuity is not essential for the validity of the bootstrap nor is it essential that the rate of convergence of the…

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AR(1) MODELS, UNIT ROOTS, AND ADJUSTED PROFILE LIKELIHOOD

AR(1) 模型、单位根与调整剖面似然

An unobserved components and a conventional first-order autoregressive (AR) model with constant are analyzed with the adjusted profile likelihood of Cox and Reid (1987, Journal of the Royal Statistical Society, Series B 49, 1–39; 1993, Journal of the Royal Statistical Society, Series B 55, 467–71). Both the unobserved components model and the Cox–Reid adjustment can provide more accurate estimates of an AR coefficient of unity. The unobserved components model yields more…

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A full-factor multivariate GARCH model

全因子多元 GARCH 模型

A new multivariate time series model with time varying conditional variances and covariances is presented and analysed. A complete analysis of the proposed model is presented consisting of parameter estimation, model selection and volatility prediction. Classical and Bayesian techniques are used for the estimation of the model parameters. It turns out that the construction of our proposed model allows easy maximum likelihood estimation and construction of well-mixing Markov…

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Nonparametric Methods for Deconvolving Multiperiodic Functions

多周期函数解卷积的非参数方法

Summary Multiperiodic functions, or functions that can be represented as finite additive mixtures of periodic functions, arise in problems related to stellar radiation. There they represent the overall variation in radiation intensity with time. The individual periodic components generally correspond to different sources of radiation and have intrinsic physical meaning provided that they can be ‘deconvolved’ from the mixture. We suggest a combination of kernel and orthogonal…

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On-Line Inference for Hidden Markov Models via Particle Filters

利用粒子滤波进行隐马尔可夫模型的在线推断

Summary We consider the on-line Bayesian analysis of data by using a hidden Markov model, where inference is tractable conditional on the history of the state of the hidden component. A new particle filter algorithm is introduced and shown to produce promising results when analysing data of this type. The algorithm is similar to the mixture Kalman filter but uses a different resampling algorithm. We prove that this resampling algorithm is computationally efficient and…

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Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models

利用广义谱与非线性时间序列模型推断汇率可预测性

It is often documented, based on autocorrelation, variance ratio, and power spectrum, that exchange rates approximately follow a martingale process. Because these data check serial uncorrelatedness rather than martingale difference, they may deliver misleading conclusions in favor of the martingale hypothesis when the test statistics are insignificant. In this paper, we explore whether there exists a gap between serial uncorrelatedness and martingale difference for exchange…

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Bootstrap Unit Root Tests

Bootstrap 单位根检验

We consider the bootstrap unit root tests based on finite order autoregressive integrated models driven by iid innovations, with or without deterministic time trends. A general methodology is developed to approximate asymptotic distributions for the models driven by integrated time series, and used to obtain asymptotic expansions for the Dickey–Fuller unit root tests. The second-order terms in their expansions are of stochastic orders Op(n−1/4) and Op(n−1/2), and involve…

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Stationary Equilibria in Asset-Pricing Models with Incomplete Markets and Collateral

不完全市场与抵押约束资产定价模型中的平稳均衡

We consider an infinite-horizon exchange economy with incomplete markets and collateral constraints. As in the two-period model of Geanakoplos and Zame (2002), households can default on their liabilities at any time, and financial securities are only traded if the promises associated with these securities are backed by collateral. We examine an economy with a single perishable consumption good, where the only collateral available consists of productive assets. In this model,…

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Cointegration in Fractional Systems with Unknown Integration Orders

积分阶数未知的分数系统中的协整

Cointegrated bivariate nonstationary time series are considered in a fractional context, without allowance for deterministic trends. Both the observable series and the cointegrating error can be fractional processes. The familiar situation in which the respective integration orders are 1 and 0 is nested, but these values have typically been assumed known. We allow one or more of them to be unknown real values, in which case Robinson and Marinucci (2001, 2003) have justified…

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End-of-Sample Instability Tests

样本末端不稳定性检验

This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small—possibly as small as one. The well-known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations,…

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Multivariate GARCH models: software choice and estimation issues

多变量 GARCH 模型:软件选择与估计问题

The model acronym arises from the first letters of the surnames of the authors, with Bollerslev and Krafts being co-authors on the original version of the paper.2 Since Brooks et al. (2002) estimated only BEKK models, and this review uses the diagonal VECH representation, our results are not directly comparable with theirs.3 Since these contracts expire four times per year-March, June, September and December-to obtain a continuous time series we use the closest to maturity…

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A practical log‐linear aggregation method with examples: heterogeneous income growth in the USA

实用的对数线性加总方法:美国异质性收入增长示例

Abstract A practical aggregation method for heterogeneous log‐linear functions is presented. Inequality measures are employed in the construction of a simple but exact aggregate representation of an economy. Three macroeconomic applications are discussed: the aggregation of the Lucas supply function, the time‐inconsistent behaviour of an egalitarian social planner facing heterogeneous discount rates, and the case of a simple heterogeneous growth model. In the latter…

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Value‐at‐risk for long and short trading positions

多头与空头交易头寸的风险价值

Abstract In this paper we model Value‐at‐Risk (VaR) for daily asset returns using a collection of parametric univariate and multivariate models of the ARCH class based on the skewed Student distribution. We show that models that rely on a symmetric density distribution for the error term underperform with respect to skewed density models when the left and right tails of the distribution of returns must be modelled. Thus, VaR for traders having both long and short positions…

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Financial options and statistical prediction intervals

金融期权与统计预测区间

The paper shows how to convert statistical prediction sets into worst case hedging strategies for derivative securities. The prediction sets can, in particular, be ones for volatilities and correlations of the underlying securities, and for interest rates. This permits a transfer of statistical conclusions into prices for options and similar financial instruments. A prime feature of our results is that one can construct the trading strategy as if the prediction set had a 100…

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An Empirical Analysis of Analysts' Target Prices: Short‐term Informativeness and Long‐term Dynamics

分析师目标价的实证分析:短期信息含量与长期动态

Abstract Using a large database of analysts' target prices issued over the period 1997–1999, we examine short‐term market reactions to target price revisions and long‐term comovement of target and stock prices. We find a significant market reaction to the information contained in analysts' target prices, both unconditionally and conditional on contemporaneously issued stock recommendation and earnings forecast revisions. Using a cointegration approach, we analyze the…

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Bayes Estimates of Markov Trends in Possibly Cointegrated Series

可能协整序列中马尔可夫趋势的贝叶斯估计

Stylized facts show that average growth rates of U.S. per capita consumption and income differ in recession and expansion periods. Because a linear combination of such series does not have to be a constant mean process, standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid. To model the changing growth rates in both series, we introduce a multivariate Markov trend model that accounts for different growth rates in…

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Estimation of Dynamic Bivariate Mixture Models

动态二元混合模型的估计

This note compares a Bayesian Markov chain Monte Carlo approach implemented by Watanabe with a maximum likelihood ML approach based on an efficient importance sampling procedure to estimate dynamic bivariate mixture models. In these models, stock price volatility and trading volume are jointly directed by the unobservable number of price-relevant information arrivals, which is specified as a serially correlated random variable. It is shown that the efficient importance…

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Variance Shifts, Structural Breaks, and Stationarity Tests

方差突变、结构断裂与平稳性检验

stochastic stationarity in time series characterized by variance shifts at some (known or unknown) point in the sample. It is shown that existing stationarity tests can be severely biased in the presence of such shifts, either oversized or undersized, with associated spurious power gains or losses, depending on the values of the breakpoint parameter and on the ratio of the prebreak to postbreak variance. Under the assumption of a serially independent Gaussian error term with…

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