论文检索

基于 GARCH 创新密度的拟合优度检验AI 解读

Testing goodness (or lack) of fit for distributions of observable and nonobservable random variables is one of the main topics in statistics. When they exist, the corresponding density functions and their shapes allow researchers to easily recognize the underlying distribution functions. The present paper is concerned with the densities of (unobservable) generalized autoregressive conditional heteroskedasticity (GARCH) innovations and also with developing goodness-of-fit…

利率期限结构与宏观经济的联合模型AI 解读

Abstract We present and estimate a continuous time term structure model that incorporates observable macroeconomic variables and latent variables with a clear macroeconomic interpretation. Our model is able to accurately describe the joint dynamics for US macroeconomic variables and the yield curve. However, the observable variables do not explain the long end of the term structure. Central tendencies of these macroeconomic variables do a much better job in this respect.…

若干异方差时间序列模型中的误差分布拟合AI 解读

This paper addresses the problem of fitting a known distribution to the innovation distribution in a class of stationary and ergodic time series models. The asymptotic null distribution of the usual Kolmogorov–Smirnov test based on the residuals generally depends on the underlying model parameters and the error distribution. To overcome the dependence on the underlying model parameters, we propose that tests be based on a vector of certain weighted residual empirical…

不同抽样方案下已实现方差的性质AI 解读

This article investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise. Different from the existing literature, the analysis relies on a pure jump process for high-frequency security prices and explicitly distinguishes among alternative sampling schemes, including calendar time sampling, business time sampling, and transaction time sampling. The main finding in this article is that transaction time sampling is…

资产配置中动态相关性的检验与价值评估AI 解读

We evaluate alternative models of variances and correlations with an economic loss function. We construct portfolios to minimize predicted variance subject to a required return. It is shown that the realized volatility is smallest for the correctly specified covariance matrix for any vector of expected returns. A test of relative performance of two covariance matrices is based on work of Diebold and Mariano. The method is applied to stocks and bonds and then to highly…

已实现方差与市场微观结构噪声AI 解读

We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure…

GARCH(1,1) 模型的闭式估计量AI 解读

We propose a closed-form estimator for the linear GARCH(1,1) model. The estimator has the advantage over the often used quasi-maximum likelihood estimator (QMLE) that it can be easily implemented and does not require the use of any numerical optimization procedures or the choice of initial values of the conditional variance process. We derive the asymptotic properties of the estimator, showing T(κ−1)/κ-consistency for some κ ∈ (1,2) when the fourth moment exists and…

正态混合 GARCH(1,1)：汇率建模应用AI 解读

Abstract Some recent specifications for GARCH error processes explicitly assume a conditional variance that is generated by a mixture of normal components, albeit with some parameter restrictions. This paper analyses the general normal mixture GARCH(1,1) model which can capture time variation in both conditional skewness and kurtosis. A main focus of the paper is to provide evidence that, for modelling exchange rates, generalized two‐component normal mixture GARCH(1,1)…

全球股票市场多变量波动率门限的估计与预测AI 解读

Abstract We propose a general double tree structured AR‐GARCH model for the analysis of global equity index returns. The model extends previous approaches by incorporating (i) several multivariate thresholds in conditional means and volatilities of index returns and (ii) a richer specification for the impact of lagged foreign (US) index returns in each threshold. We evaluate the out‐of‐sample forecasting power of our model for eight major equity indices in comparison to some…

金融因子、宏观信息与利率期限结构的预期理论AI 解读

In this paper we develop on the VAR framework, originally proposed by Campbell and Shiller (J. Political Econom 95 (1987) 1062) to evaluate the Expectations Theory, along three dimensions: the use of a testing method based on a real-time procedure, the measurement of the risk premium, the specification of the implicit monetary policy maker’s reaction function. We use financial factors and macroeconomic information to construct a test of the theory based on simulating…

不同计量设定下风险的期限结构AI 解读

This paper characterizes the term structure of risk measures such as value at risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with Student-t errors, two-component GARCH models and a nonparametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting…

摘要暂缺

跳跃对收益与已实现方差的影响：时间变换 Lévy 过程的计量分析AI 解读

In order to assess the effect of jumps on realised variance calculations, we study some of the econometric properties of time-changed Lévy processes. We show that in general realised variance is an inconsistent estimator of the time-change, however we can derive the second order properties of realised variances and use these to estimate the parameters of such models. Our analytic results give a first indication of the degrees of inconsistency of realised variance as an…

摘要暂缺

基于排序的依赖 Dirichlet 过程AI 解读

In this article we propose a new framework for Bayesian nonparametric modeling with continuous covariates. In particular, we allow the nonparametric distribution to depend on covariates through ordering the random variables building the weights in the stick-breaking representation. We focus mostly on the class of random distributions that induces a Dirichlet process at each covariate value. We derive the correlation between distributions at different covariate values and use…

截断帕累托分布的参数估计AI 解读

The Pareto distribution is a simple model for nonnegative data with a power law probability tail. In many practical applications, there is a natural upper bound that truncates the probability tail. This article derives estimators for the truncated Pareto distribution, investigates their properties, and illustrates a way to check for fit. These methods are illustrated with applications from finance, hydrology, and atmospheric science.

不同长度时间序列的多变量模型估计AI 解读

Abstract We consider the problem of estimating parametric multivariate density models when unequal amounts of data are available on each variable. We focus in particular on the case that the unknown parameter vector may be partitioned into elements relating only to a marginal distribution and elements relating to the copula. In such a case we propose using a multi‐stage maximum likelihood estimator (MSMLE) based on all available data rather than the usual one‐stage maximum…

鞅变换的稳定极限及其在 GARCH 参数估计中的应用AI 解读

In this paper we study the asymptotic behavior of the Gaussian quasi maximum likelihood estimator of a stationary GARCH process with heavy-tailed innovations. This means that the innovations are regularly varying with index α∈(2,4). Then, in particular, the marginal distribution of the GARCH process has infinite fourth moment and standard asymptotic theory with normal limits and $\sqrt{n}$-rates breaks down. This was recently observed by Hall and Yao [Econometrica 71 (2003)…

政府债券收益率期限结构预测AI 解读

Despite powerful advances in yield curve modeling in the last twenty years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the no-arbitrage approach, which focuses on accurately fitting the cross section of interest rates at any given time but neglects time-series dynamics, nor the equilibrium approach, which focuses on time-series dynamics (primarily those of the instantaneous…

基于 Copula 的半参数时间序列模型估计AI 解读

This paper studies the estimation of a class of copula-based semiparametric stationary Markov models. These models are characterized by nonparametric invariant (or marginal) distributions and parametric copula functions that capture the temporal dependence of the processes; the implied transition distributions are all semiparametric, and a member in this class can be expressed as a generalized semiparametric regression transformation model. One advantage of this copula…

摘要暂缺

自回归条件持续期模型的评价AI 解读

This article contains two novelties. First, a unified framework for testing and evaluating the adequacy of an estimated autoregressive conditional duration (ACD) model is presented. Second, two new classes of ACD models, the smooth transition ACD model and the time-varying ACD model, are introduced and their properties discussed. New misspecification tests for the ACD class of models are introduced. These are Lagrange multiplier and Lagrange multiplier–type tests against…

特质波动率、股票市场波动率与预期股票收益AI 解读

We find that the value-weighted idiosyncratic stock volatility and aggregate stock market volatility jointly exhibit strong predictive power for excess stock market returns. The stock market risk–return relation is found to be positive, as stipulated by the capital asset pricing model; however, idiosyncratic volatility is negatively related to future stock market returns. Also, idiosyncratic volatility appears to be a pervasive macrovariable, and its forecasting abilities…

多变量 GARCH 模型综述AI 解读

Abstract This paper surveys the most important developments in multivariate ARCH‐type modelling. It reviews the model specifications and inference methods, and identifies likely directions of future research. Copyright © 2006 John Wiley & Sons, Ltd.