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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…

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多个误设条件区间模型的比较检验AI 解读

This paper introduces a test for the comparison of multiple misspecified conditional interval models, for the case of dependent observations. Model accuracy is measured using a distributional analog of mean square error, in which the approximation error associated with a given model, say, model i, for a given interval, is measured by the expected squared difference between the conditional confidence interval under model i and the “true” one.When comparing more than two…

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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…

仅在备择假设下存在干扰参数时的推断界AI 解读

In hypothesis testing with nuisance parameters present only under the alternative two issues typically arise: (i) critical values are data dependent and so cannot be tabulated; (ii) we need to choose a functional over the nuisance parameter space. We address the first issue by providing easily computable bounds for the case of dependent and heterogeneous observations. We tackle the second issue by suggesting a weighted average statistic with weights given by the (quasi)…

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利用函数迭代对数律界限区分 I(0) 与 I(1)AI 解读

We construct properly scaled functions of R p -valued partial sums of demeaned data and derive bounds via the functional law of the iterated logarithm for strong mixing processes. If we obtain a value below or equal to the bound we decide in favor of I (0); otherwise we decide in favor of I (1). This provides a consistent rule for classifying time series as being I (1) or I (0). The nice feature of the procedure lies in the almost sure nature of the bound, guaranteeing a lim…

扩散过程之间的长期共动AI 解读

The aim of this paper is to characterize and analyze long-run comovements among diffusion processes. Broadly speaking, if X = ( X 1 ,, X 2 ,;t ≥ 0) is a nonergodic diffusion in R 2 , but there exists a linear combination, say, γ′ X , that is instead ergodic in R, then we say there exists a linear stochastic comovement between the components of X . Linear diffusions exhibiting stochastic comovements admit an error correction representation. Estimation of γ and hypothesis…