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将 Hansen–Jagannathan 界用于资产定价模型的经典检验AI 解读

In this article, tests of the implications of consumption-based asset-pricing models are developed. Four of these tests are based on variance bounds for intertemporal marginal rates of substitution introduced by L. P. Hansen and R. Jagannathan. The tests provide one means of quantifying the effects of sampling error when the bounds are used as a diagnostic device. The tests are used to construct confidence regions for the parameters of an asset-pricing model using U.S. data.…

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使用目标区间模型对欧洲货币体系汇率进行单变量分析AI 解读

Abstract The models in the literature on exchange‐rate target zones imply a non‐linear time series model for the exchange rate. We show how the parameters of such models can be estimated and develop Maximum Likelihood and Method of Simulated Moments estimators for the target zone model of Krugman (1991). The Maximum Likelihood estimator is based on a computationally attractive approximation to the exact predictive density of the continuous time model. Monte Carlo experiments…

拟合良好的均衡资产定价模型能否产生均值回归？AI 解读

Abstract In recent papers, Cecchetti et al . (1990) and Kandel and Stambaugh (1990) showed that negative serial correlation in long horizon returns was consistent with an equilibrium model of asset pricing. In this paper, we show that their results rely on misspecified Markov switching models for the endowment process. Once the proper Markov specification is chosen for the endowment process, the model does not produce mean reversion of the magnitude detected in the data.…

加速高斯重要性抽样及其在动态潜变量模型中的应用AI 解读

We propose a new generic and highly efficient Accelerated Gaussian Importance Sampler (AGIS) for the numerical evaluation of (very) high-dimensional density functions. A specific case of interest to us is the evaluation of likelihood functions for a broad class of dynamic latent variable models. The feasibility of our method is strikingly illustrated by means of an application to a first-order dynamic stochastic volatility model for daily stock returns, whose likelihood for…

非线性时间序列模型的拟合及随机方差模型应用AI 解读

New strategies for the implementation of maximum likelihood estimation of nonlinear time series models are suggested. They make use of recent work on the EM algorithm and iterative simulation techniques. The estimation procedures are applied to the problem of fitting stochastic variance models to exchange rate data.

GARCH 模型的非平稳性：贝叶斯分析AI 解读

First, the non-stationarity properties of the conditional variances in the GARCH(1, 1) model are analysed using the concept of infinite persistence of shocks. Given a time sequence of probabilities for increasing/decreasing conditional variances, a theoretical formula for quasi-strict non-stationarity is defined. The resulting conditions for the GARCH(1,1) model are shown to differ from the weak stationarity conditions mainly used in the literature. Bayesian statistical…

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近似因子模型中因子个数的检验AI 解读

ABSTRACT An important issue in applications of multifactor models of asset returns is the appropriate number of factors. Most extant tests for the number of factors are valid only for strict factor models, in which diversifiable returns are uncorrelated across assets. In this paper we develop a test statistic to determine the number of factors in an approximate factor model of asset returns, which does not require that diversifiable components of returns be uncorrelated…

基于资产定价模型数值解的矩估计量一致性AI 解读

This paper considers the properties of estimators based on numerical solutions to a class of economic models. In particular, the numerical methods discussed are those applied in the solution of linear integral equations, specifically Fredholm equations of the second kind. These integral equations arise out of economic models in which endogenous variables appear linearly in the Euler equations, but for which easily characterized solutions do not exist. Tauchen and Hussey [24]…

ARCH 模型中的自适应估计AI 解读

We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH( P ) process. We do not assume a functional form for the conditional density of the errors, but do require that it be symmetric about zero. The estimators of the mean parameters are adaptive in the sense of Bickel [2]. The ARCH parameters are not jointly identifiable with the error density. We consider a reparameterization of the variance…

资产价格马尔可夫模型的模拟矩估计AI 解读

This paper provides a simulated moments estimator of the parameters of dynamic models in which the state vector follows a time-homogeneous Markov process. Conditions are provided for both weak and strong consistency as well as asymptotic normality. Various trade-offs among the regularity conditions underlying the large sample properties of the simulated moments estimator are discussed in the context of an asset-pricing model. Geometric ergodicity of the underlying Markov…

GARCH 过程的时间聚合AI 解读

The authors derive low frequency, say weekly, models implied by high frequency, say daily, ARMA models with symmetric GARCH errors. They show that low frequency models exhibit conditional heteroskedasticity of the GARCH form as well. The parameters in the conditional variance equation of the low frequency model depend upon mean, variance, and kurtosis parameters of the corresponding high frequency model. Moreover, strongly consistent estimators of the parameters in the high…

欧洲货币体系周度汇率的信息：均值回归、条件异方差与跳跃AI 解读

Weekly rates of the European Monetary System (EMS) vis-a-vis the Deutsche mark from April 1979 to March 1991 are modeled as a combined MA (1)-GARCH (1, 1)-jump process. The moving average (MA) part accounts for mean reversion required for the rates to stay inside the target zone. The generalized autoregressive conditional heteroscedasticity (GARCH) part accounts for changing volatility, whereas the jump process models parity changes and other erratic movements. Using an…

利用后验赔率检测多个方差变点AI 解读

This article uses a Bayesian procedure based on obtaining posterior odds to assess the evidence about the existence of multiple changes of variance in a time series. The approach is developed for sequences of independent observations. An extension to consider autoregressive models is also discussed. The information on the data about the location of the change points and the magnitude of the variances at the different pieces of the series is summarized through posterior…

作为不可观测成分的远期外汇溢价：札记AI 解读

We reconsider the signal-extraction approach to measuring premia in the pricing of forward foreign exchange, put forward by Wolff, in which the difference between the forward rate and the associated future spot rate is modeled as an autoregressive moving average (ARMA) model for the risk premium buried in a white-noise forecast error. We point out that an ARMA model for the risk premium is not always identifiable from information on the difference between the forward rate…

费雪效应与利率期限结构：协整检验AI 解读

The literature on the Fisher effect has ignored the potential relationship between inflation and long-term interest rates. Using an expectations model of the term structure of interest rates, the authors establish the conditions under which innovations in short-term inflation will be transmitted to long-term as well as short-term interest rates. Cointegration tests find support for both the Fisher effect and the expectations theory of the term structure. Copyright 1993 by…

条件方差中的共同持久性AI 解读

A common finding in many of the recent empirical studies with the ARCH class of models applied to high frequency financial data concerns the apparent persistence of shocks for forecast of the future conditional variances. It is likely that several different variables share this same implied long-run component, however. In that situation, the variables are defined to be copersistent in variance. Conditions for copersistence to occur in the linear multivariate GARCH model are…

ARCH 与 GARCH 回归扰动的局部最大平均功效得分检验AI 解读

This paper considers testing for autoregressive conditional heteroskedasticity and generalized autoregressive conditional heteroskedasticity disturbances in the linear regression model. These testing problems are one-sided in nature; a fact ignored by the Lagrange multiplier test. A test that exploits this one-sided aspect is constructed based on the sum of the scores. The size and power properties of two versions of this test under normal and leptokurtic disturbances are…

门限 ARCH 模型与波动率非对称性AI 解读

Abstract This paper attempts to enlarge the class of Threshold Heteroscedastic Models (TARCH) introduced by Zakoían (1991a). We show that it is possible to relax the positivity constraints on the parameters of the conditional variance. Unconstrained models provide a greater generality of the paths allowing for nonlinearities in the volatility. Cyclical behaviour is permitted as well as different relative impacts of positive and negative shocks on volatility, depending on…

英镑兑美元汇率高频模型中的新闻效应AI 解读

Abstract This paper uses an extremely high frequency data set on the dollar‐sterllng exchange rate to investigate the impact of news events on the very short‐term movements in exchange rates. The data set is a continuous record of the quoted price for the exchange rate on the Reuters screen. As such it records some 130,000 observations over an 8‐week period. The paper investigates the time‐series properties of the data using orthodox regression models, and then by making…

欧洲货币体系汇率的多变量最近邻预测AI 解读

Exchange rate modelling has been a persistent puzzle for international economists. Forecasts from popular models for the exchange rate generally fail to improve upon the random walk out-of-sample. While a multivariate nonparametric approach provides useful information about exchange rates, the model produces forecasts superior to the random walk for only one of the three EMS currencies examined. Using a statistic developed in Mizrach (1991), I find that the forecast…

利用波动率指标改善预测AI 解读

This paper explores the possibility of improved out of sample forecasting for stock returns and foreign exchange rates using observed nonlinearities in the two series. Forecasting is done using nonparametric techniques where important information is obtained from the current level of volatility in the series. For both series forecast improvements are observed, but for stock returns the improvements are only marginal. These results indicate the usefulness and stability of…

股票波动率的非线性时间序列分析AI 解读

The absolute value of the mean-corrected excess return is used in this paper to measure the volatility of stock returns. We apply various nonlinearity tests available in the literature to show that such volatility series are strongly nonlinear. We then explore the use of threshold autoregressive (TAR) models in describing monthly volatility series. The models built suggest that the volatility series exhibit significant lower-order serial correlations when the volatility is…