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未知形式条件异方差下时间序列条件均值模型的广义谱检验AI 解读

Economic theories in time series contexts usually have implications on and only on the conditional mean dynamics of underlying economic variables. We propose a new class of specification tests for time series conditional mean models, where the dimension of the conditioning information set may be infinite. Both linear and nonlinear conditional mean specifications are covered. The tests can detect a wide range of model misspecifications in mean while being robust to…

股权溢价的结构突变AI 解读

This article uses Bayesian marginal likelihood analysis to compare univariate models of the stock return behavior and test for structural breaks in the equity premium. The analysis favors a model that relates the equity premium to Markov-switching changes in the level of market volatility and accommodates volatility feedback. For this model, there is evidence of a one-time structural break in the equity premium in the 1940s, with no evidence of additional breaks in the…

协变量调整回归AI 解读

We introduce covariate-adjusted regression for situations where both predictors and response in a regression model are not directly observable, but are contaminated with a multiplicative factor that is determined by the value of an unknown function of an observable covariate. We demonstrate how the regression coefficients can be estimated by establishing a connection to varying-coefficient regression. The proposed covariate-adjustment method is illustrated with an analysis…

两样本生存数据中短期与长期风险比的半参数分析AI 解读

Standard approaches to semiparametric modelling of two-sample survival data are not appropriate when the two survival curves cross. We introduce a two-sample model that accommodates crossing survival curves. The two scalar parameters of the model have the interpretations of being the short-term and long-term hazard ratios respectively. The time-varying hazard ratio is expressed semiparametrically by the two scalar parameters and an unspecified baseline distribution. The new…

多变量生存过程的函数型关联模型AI 解读

We consider multivariate temporal processes that are continuously observed within overlapping time windows. The intended application is in censored multistate and multivariate survival settings, where point processes are continuously observed. These data differ from other functional data, like longitudinal data, which are discretely observed at irregular times. Existing functional approaches to survival processes use intensity models, which require smoothing and depend…

具有时变回归系数的Cox模型AI 解读

In the analysis of censored failure time observations, the standard Cox proportional hazards model assumes that the regression coefficients are time invariant. Often, these parameters vary over time, and the temporal covariate effects on the failure time are of great interest. In this article, following previous work of Cai and Sun, we propose a simple estimation procedure for the Cox model with time-varying coefficients based on a kernel-weighted partial likelihood…

股票收益建模与预测：利用期货信息、区制转换和国际溢出AI 解读

Abstract This paper proposes a vector equilibrium correction model of stock returns that exploits the information in the futures market, while allowing for both regime‐switching behaviour and international spillovers across stock market indices. Using data for three major stock market indices since 1989, we find that: (i) in sample, our model outperforms several alternative models on the basis of standard statistical criteria; (ii) in out‐of‐sample forecasting, our model…

时间安排不平衡的纵向数据分析AI 解读

Summary The paper considers modelling, estimating and diagnostically verifying the response process generating longitudinal data, with emphasis on association between repeated meas-ures from unbalanced longitudinal designs. Our model is based on separate specifications of the moments for the mean, standard deviation and correlation, with different components possibly sharing common parameters. We propose a general class of correlation structures that comprise random effects,…

半参数部分线性变系数模型的有效估计AI 解读

In this paper we propose a general series method to estimate a semiparametric partially linear varying coefficient model. We establish the consistency and $\sqrt{n}$-normality property of the estimator of the finite-dimensional parameters of the model. We further show that, when the error is conditionally homoskedastic, this estimator is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator of the finite-dimensional parameter…

金融波动率建模中的自动推断与学习AI 解读

This paper uses the specific-to-general methodological approach that is widely used in science, in which problems with existing theories are resolved as the need arises, to illustrate a number of important developments in the modeling of univariate and multivariate financial volatility. Some of the difficulties in analyzing time-varying univariate and multivariate conditional volatility and stochastic volatility include the number of parameters to be estimated and the…

摘要暂缺

汇率的长期摆动AI 解读

Several authors have reported evidence of long swings in U.S. dollar exchange rates by rejecting the random walk in favor of a Markov regime-switching model. We show that this evidence is not robust to an extension of the sample period. One should, however, not conclude that long swings are thus absent, because the tests may have insufficient power. A possible reason for this is the low data frequency, because existing tests are based on quarterly data, and we find that the…

非线性与衰退的永久影响AI 解读

Abstract This paper presents a new nonlinear time series model that captures a post‐recession ‘bounce‐back’ in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession‐based dummy variables and threshold models, we relate the ‘bounce‐back’ effect to an endogenously estimated unobservable Markov‐switching state variable. When the model is applied to US real GDP, we find that the Markov‐switching regimes are…

动态计量模型中的结构变化监测AI 解读

Abstract The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation‐type tests in a monitoring situation—given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. Procedures based on estimates of the regression coefficients are extended in three…

一种半参数变点模型AI 解读

A semiparametric changepoint model is considered and the empirical likelihood method is applied to detect the change from a distribution to a weighted distribution in a sequence of independent random variables. The maximum likelihood changepoint estimator is shown to be consistent. The empirical likelihood ratio test statistic is proved to have the same limit null distribution as that with parametric models. A data-based test for the validity of the models is also proposed.…

非规则问题中的模型选择：数量性状基因座定位应用AI 解读

Two methods of model selection are discussed for changepoint-like problems, especially those arising in genetic linkage analysis. The first is a method that selects the model with the smallest p-value, while the second is a modification of the Bayes information criterion. The methods are compared theoretically and on examples from the literature. For these examples, they are roughly comparable although the p-value-based method is somewhat more liberal in selecting a…

低频结构突变下 ARFIMA 模型的预测能力AI 解读

Recent research has focused on the links between long memory and structural breaks, stressing the memory properties that may arise in models with parameter changes. In this paper, we question the implications of this result for forecasting. We contribute to this research by comparing the forecasting abilities of long memory and Markov switching models. Two approaches are employed: the Monte Carlo study and an empirical comparison, using the quarterly Consumer Price inflation…

空气污染与死亡率的改进半参数时间序列模型AI 解读

In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U. S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S–PLUS implementation of generalized additive…

存在辅助模型时的结构变化检验AI 解读

Several estimation procedures such as the efficient method of moments (EMM) of Gallant and Tauchen (1996, Econometric Theory 12, 657–681) and indirect inference procedure of Gouriéroux, Monfort, and Renault (1993, Journal of Applied Econometrics 8, S85–S118) involve two models, an auxiliary one and a model of interest. The role played by both models poses challenges and provides new opportunities for hypothesis testing beyond the usual Wald-, Lagrange multiplier–, and…

GARCH(p,q) 模型的序贯变点检测AI 解读

We suggest a sequential monitoring scheme to detect changes in the parameters of a GARCH(p,q) sequence. The procedure is based on quasi-likelihood scores and does not use model residuals. Unlike for linear regression models, the squared residuals of nonlinear time series models such as generalized autoregressive conditional heteroskedasticity (GARCH) do not satisfy a functional central limit theorem with a Wiener process as a limit, so its boundary crossing probabilities…

随机时间间隔采样下连续时间马尔可夫过程的估计AI 解读

We introduce a family of generalized-method-of-moments estimators of the parameters of a continuous-time Markov process observed at random time intervals. The results include strong consistency, asymptotic normality, and a characterization of standard errors. Sampling is at an arrival intensity that is allowed to depend on the underlying Markov process and on the parameter vector to be estimated. We focus on financial applications, including tick-based sampling, allowing for…

参数时间依赖的一般检验AI 解读

Abstract A new test for time‐dependent parameters is proposed. The Trig ‐test is based on a trigonometric expansion to approximate the unknown functional form of the variation in the parameters concerned. It is shown to have the correct empirical size and excellent power to detect structural breaks and stochastic parameter variation. The appropriate use of the Trig ‐test is demonstrated by testing for structural breaks in the US inflation rate. The test detects a…

隐马尔可夫模型中最优变点检测的渐近运行特性AI 解读

Let ξ0,ξ1,…,ξω−1 be observations from the hidden Markov model with probability distribution Pθ0, and let ξω,ξω+1,… be observations from the hidden Markov model with probability distribution Pθ1. The parameters θ0 and θ1 are given, while the change point ω is unknown. The problem is to raise an alarm as soon as possible after the distribution changes from Pθ0 to Pθ1, but to avoid false alarms. Specifically, we seek a stopping rule N which allows us to observe the ξ's…

离散时间即期利率模型的样本外表现AI 解读

We provide a comprehensive analysis of the out-of-sample performance of a wide variety of spot rate models in forecasting the probability density of future interest rates. Although the most parsimonious models perform best in forecasting the conditional mean of many financial time series, we find that the spot rate models that incorporate conditional heteroscedasticity and excess kurtosis or heavy tails have better density forecasts. Generalized autoregressive conditional…