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持久时间序列中随机周期的估计AI 解读

A number of economic, financial, and climatic time series exhibit persistent cycles which are characterized by time-dependence patterns and peaks in the spectrum. In this article, we introduce a class of semiparametric cyclical–memory processes which enable the modeling of random cyclical patterns in stationary and non-stationary time series. We develop a theoretical background and asymptotic estimation theory for the frequency of a cycle represented by the location of a…

无需预检跳跃的跳跃溢出检验AI 解读

This article develops statistical tools for testing conditional independence among the jump components of the daily quadratic variation, which we estimate using intraday data. To avoid sequential bias distortion, we do not pretest for the presence of jumps. If the null is true, our test statistic based on daily integrated jumps weakly converges to a Gaussian random variable if both assets have jumps. If instead at least one asset has no jumps, then the statistic approaches…

方差矩阵的无结构设定估计AI 解读

This paper introduces a new method for estimating variance matrices. Starting from the orthogonal decomposition of the sample variance matrix, we exploit the fact that orthogonal matrices are never ill-conditioned and therefore focus on improving the estimation of the eigenvalues. We estimate the eigenvectors from just a fraction of the data, then use them to transform the data into approximately orthogonal series that deliver a well-conditioned estimator (by construction),…

线性过程加权和的渐近正态性AI 解读

We establish asymptotic normality of weighted sums of linear processes with general triangular array weights and when the innovations in the linear process are martingale differences. The results are obtained under minimal conditions on the weights and innovations. We also obtain weak convergence of weighted partial sum processes. The results are applicable to linear processes that have short or long memory or exhibit seasonal long memory behavior. In particular, they are…

国际市场联系与波动率传递AI 解读

This paper gauges volatility transmission between stock markets by testing conditional independence of their volatility measures. In particular, we check whether the conditional density of the volatility changes if we further condition on the volatility of another market. We employ nonparametric methods to estimate the conditional densities and model-free realized measures of volatility, allowing for both microstructure noise and jumps. We establish the asymptotic normality…

积分波动率的预测推断AI 解读

Numerous volatility-based derivative products have been engineered in recent years. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this article we propose nonparametric estimators of the aforementioned quantities, based on model-free volatility estimators. We establish consistency and asymptotic normality for the feasible estimators and study their finite-sample properties through a Monte Carlo…

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基于已实现测度的日波动率预测密度估计AI 解读

The main objective of this paper is to propose a feasible, model free estimator of the predictive density of integrated volatility. In this sense, we extend recent papers by Andersen et al. [Andersen, T.G., Bollerslev, T., Diebold, F.X., Labys, P., 2003. Modelling and forecasting realized volatility. Econometrica 71, 579-626], and by Andersen et al. [Andersen, T.G., Bollerslev, T., Meddahi, N., 2004. Analytic evaluation of volatility forecasts. International Economic…

两种长期方差估计量：超越短记忆AI 解读

This paper deals with the estimation of the long-run variance of a stationary sequence. We extend the usual Bartlett-kernel heteroskedasticity and autocorrelation consistent (HAC) estimator to deal with long memory and antipersistence. We then derive asymptotic expansions for this estimator and the memory and autocorrelation consistent (MAC) estimator introduced by Robinson [Robinson, P. M., 2005. Robust covariance matrix estimation: HAC estimates with long…

通过已实现波动率度量评估市场微观结构效应：道琼斯工业平均指数成分股应用AI 解读

Transaction prices of financial assets are contaminated by market microstructure effects. This is particularly relevant when estimating volatility using high frequency data. In this article, we assess statistically the effect of microstructure noise on volatility estimators, and test the hypothesis that its variance is independent of the sampling frequency. We provide evidence based on the Dow Jones Industrial Average stocks. We find that noise has a statistically…

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利用已实现测度对随机波动率模型进行半参数比较AI 解读

This paper proposes a procedure to test for the correct specification of the functional form of the volatility process within the class of eigenfunction stochastic volatility models. The procedure is based on the comparison of the moments of realized volatility measures with the corresponding ones of integrated volatility implied by the model under the null hypothesis.We first provide primitive conditions on the measurement error associated with the realized measure, which…

ARMA representation of squared Markov switching heteroskedastic models—solution.

GRETL：面向 GNU 一代的计量经济学软件AI 解读

There is also an obvious reference to the classic fairy tale 'Hansel and Gretel' in which Gretel is the mature and resourceful girl whose ingenuity saves her sibling's life from an evil witch who, after kidnapping them by means of gingerbread and candies, intends to fatten and eventually eat him.2 We mainly used version 0.997, the Windows release available at the time most of the review was written.The hardware was a 600 MHz Pentium III with 256 MB of RAM running on Windows…

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