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改善多项Logit有限混合模型个体估计与预测的经验贝叶斯方法AI 解读

with by specifying either a multinomial or a normal distribution of the coefficients, leading to finite mixture logit and mixed logit models. Focusing on the former, we show that individual-level estimates and predictions of finite mixtures estimated by maximizing the likelihood function can be improved through integration over the estimation error of the hyperparameters, using an empirical Bayes approach. We investigate the conjecture that this approach is more robust…

波动减弱的美国经济AI 解读

Using a Bayesian model comparison strategy, we search for a volatility reduction in U.S. real gross domestic product (GDP) growth within the postwar sample. We find that aggregate real GDP growth has been less volatile since the early 1980s, and that this volatility reduction is concentrated in the cyclical component of real GDP.Sales and production growth in many of the components of real GDP display similar reductions in volatility, suggesting the aggregate volatility…

半参数持续时间模型AI 解读

estimation of the parameters in a non-iid environment. In contrast to classical time series models where innovations are assumed to be iid we show that in, for example, the often-used autoregressive conditional duration (ACD) model, the assumption of independent innovations is too restrictive to describe financial durations accurately. Therefore, we consider semiparametric extensions of the standard specification that allow for arbitrary kinds of dependencies between the…

用于比较随机波动率模型的偏差信息准则AI 解读

stochastic volatility models for analyzing financial time series. Recent advances made it possible to fit stochastic volatility models of increasing complexity, including covariates, leverage effects, jump components, and heavy-tailed distributions. However, a formal model comparison via Bayes factors remains difficult. The main objective of this article is to demonstrate that model selection is more easily performed using the deviance information criterion (DIC). It…

线性条件异方差模型的矩与记忆性质及一种新模型AI 解读

conditional heteroscedasticity models in which the conditional variance is a linear function of squared lags of the process. GARCH, IGARCH, FIGARCH, and a newly proposed generalization, the HYGARCH model, belong to this class. Conditions are derived for the existence of second and fourth moments, and for the limited memory condition of near-epoch dependence. The HYGARCH model is applied to 10 daily dollar exchange rates, and also to data for Asian exchange rates over the…

协整检验之间的混合信号AI 解读

Abstract This paper illustrates that, under the null hypothesis of no cointegration, the correlation of p ‐values from a single‐equation residual‐based test (i.e., ADF or $\widehat{Z}_{\alpha}$ ) with a system‐based test (trace or maximum eigenvalue) is very low even as the sample size gets large. With data‐generating processes under the null or ‘near’ it, the two types of tests can yield virtually any combination of p ‐values regardless of sample size. As a practical…

租金最大化的随机含义：不列颠哥伦比亚木材立木费率的应用AI 解读

Abstract We construct a model of rent‐maximizing behaviour by a single seller of timber in the absence of a formal market, deriving the stochastic implications of rent maximization for timber prices (stumpage rates) when other input and output (lumber) prices are random. Subsequently, we examine the model's ability to describe monthly, time‐series, stumpage‐rate data from British Columbia, Canada between January 1979 and October 1999. Deviations of stumpage rates from their…

马尔可夫误差修正模型：股票价格与股息应用AI 解读

Abstract This paper considers Markov error‐correction (MEC) models in which deviations from the long‐run equilibrium are characterized by different rates of adjustment. To motivate our analysis and illustrate the various issues involved, our discussion is structured around the analysis of the long‐run properties of US stock prices and dividends. It is shown that the MEC model is flexible enough to account for situations where deviations from the long‐run equilibrium are…

ARCH 与 GARCH 模型的最小绝对偏差估计AI 解读

Hall & Yao (2003) showed that, for ARCH/GARCH, i.e. autoregressive conditional heteroscedastic/generalised autoregressive conditional heteroscedastic, models with heavy‐tailed errors, the conventional maximum quasilikelihood estimator suffers from complex limit distributions and slow convergence rates. In this paper three types of absolute deviations estimator have been examined, and the one based on logarithmic transformation turns out to be particularly appealing. We have…

纵向数据大规模协方差矩阵的非参数估计AI 解读

Estimation of an unstructured covariance matrix is difficult because of its positive‐definiteness constraint. This obstacle is removed by regressing each variable on its predecessors, so that estimation of a covariance matrix is shown to be equivalent to that of estimating a sequence of varying‐coefficient and varying‐order regression models. Our framework is similar to the use of increasing‐order autoregressive models in approximating the covariance matrix or the spectrum…

Poisson计数的观测驱动模型AI 解读

This paper is concerned with a general class of observation‐driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modelling a wide range of dependence structures. Conditions for stationarity and ergodicity of these processes are established from which the large‐sample properties of the maximum likelihood estimators can be derived.…

时间序列的自回归辅助周期图自助法AI 解读

A bootstrap methodology for the periodogram of a stationary process is proposed which is based on a combination of a time domain parametric and a frequency domain nonparametric bootstrap. The parametric fit is used to generate periodogram ordinates that imitate the essential features of the data and the weak dependence structure of the periodogram while a nonparametric (kernel-based) correction is applied in order to catch features not represented by the parametric fit. The…

平稳过程变形的估计AI 解读

This paper studies classes of nonstationary processes, such as warped processes and frequency-modulated processes, that result from the deformation of stationary processes. Estimating deformations can often provide important information about an underlying physical phenomenon. A computational harmonic analysis viewpoint shows that the deformed autocovariance satisfies a transport equation at small scales, with a velocity proportional to a deformation gradient. We derive an…

嵌套样本两阶段估计的标准误修正AI 解读

Data at different levels of aggregation are often used in two-stage estimation, with estimates obtained at the higher level of aggregation entering the estimation at the lower level of aggregation. An example is customers within markets: first-stage estimates on market data provide variables that enter the second-stage model on customers. We derive the asymptotic covariance matrix of the second-stage estimates for situations such as these. We implement the formulae in the…

以差分平稳为原假设的持久性变化检验AI 解读

Economists have recognized the possibility that a time series may change structure from trend-stationarity to difference-stationarity, or vice versa. Taking difference-stationarity as the null hypothesis, we develop tests for this possibility, where neither the location nor direction of any possible change under the alternative hypothesis need be specified. Copyright Royal Economic Society, 2003

风险价值的半参数估计AI 解读

Value at Risk (VaR) is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. Calculation of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this paper, several semiparametric techniques are introduced to estimate the volatilities of the market prices of a portfolio. In addition,…

检测时间序列结构突变数量的强一致规则AI 解读

This paper proposes a new approach for detecting the number of structural breaks in a time series when estimation of the breaks is performed one at the time. We consider the case of shifts in the mean of a possibly nonlinear process, allowing for dependent and heterogeneous observations. This is accomplished through a simple, sequential, almost sure rule ensuring that, in large samples, both the probabilities of overestimating and underestimating the number of breaks are…

摘要暂缺

平稳与非平稳短长记忆 ARFIMA–GARCH 模型的自适应估计与检验AI 解读

This article considers the fractionally autoregressive integrated moving average [ARFIMA(p,d,q)] models with GARCH errors. The process generated by this model is short memory, long memory, stationary, and nonstationary, respectively, when d ∈ (-1/2, 0), d ∈ (0, 1/2), d ∈ (-1/2, 1/2), and d ∈ (1/2, ∞). Using a unified approach, the local asymptotic normality of the model is established for d ∈ ∪∞j = 0(J - 1/2, J + 1/2). The adaptivity and efficiency of the estimating…

自相关误差下更高效的非参数局部多项式估计AI 解读

We propose a modification of local polynomial time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that must be estimated from the data. We establish the asymptotic distribution of our estimator under weak dependence conditions. We show that the proposed estimation procedure is more efficient than the conventional local polynomial method. We…

日内电力负荷的贝叶斯建模与预测AI 解读

The advent of wholesale electricity markets has brought renewed focus on intraday electricity load forecasting. This article proposes a multi-equation regression model with a diagonal first-order stationary vector autoregresson (VAR) for modeling and forecasting intraday electricity load. The correlation structure of the disturbances to the VAR and the appropriate subset of regressors are explored using Bayesian model selection methodology. The full spectrum of finite-sample…

宏观经济建模中的预测不确定性AI 解读

Weargue that probability forecasts convey information on the uncertainties that surround macroeconomic forecasts in a straightforward manner that is preferable to other alternatives, including the use of confidence intervals. Probability forecasts obtained using a small benchmark macroeconometric model and a number of other alternatives are presented and evaluated using recursive forecasts generated over the period 1999q1–2001q1. Out-of-sample probability forecasts of…

Autoregression and redundant instruments—solution.

贝塞尔过程分布的临界值与 p 值：计算及结构突变检验应用AI 解读

The p values of structural break tests, when the break date or dates are unknown, must be calculated in terms of the probability distributions of functions of Bessel processes. The literature so far has maintained that direct computation of these p values and of the corresponding critical values is too difficult and has relied on approximations based on simulations, asymptotic expansions, or curve fitting. This paper presents a fast simple method of calculating exact p…