This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly...This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly correlated with returns.To this end,we propose a robust test which can capture empirical phenomena such as heavy tails,stationary,and local to unity.Moreover,we develop related asymptotic results without the second-moment assumption between the predictive variable and returns.To make the proposed test reasonable,we propose a generalized correlation and provide theoretical support.To illustrate the applicability of the test,we perform a simulation study for the impact of heavy-tailed innovations on predictability,as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon.Finally,we provide an empirical study for further illustration,to which the proposed test is applied to a U.S.equity data set.展开更多
Let variables in the {X, Xn, n ≥ 1} be a sequence of strictly stationary φ-mixing positive random domain of attraction of the normal law. Under some suitable conditions the principle for self-normalized products of ...Let variables in the {X, Xn, n ≥ 1} be a sequence of strictly stationary φ-mixing positive random domain of attraction of the normal law. Under some suitable conditions the principle for self-normalized products of partial sums is obtained.展开更多
The paper discusses the statistical inference problem of the compound Poisson vector process(CPVP)in the domain of attraction of normal law but with infinite covariance matrix.The empirical likelihood(EL)method to con...The paper discusses the statistical inference problem of the compound Poisson vector process(CPVP)in the domain of attraction of normal law but with infinite covariance matrix.The empirical likelihood(EL)method to construct confidence regions for the mean vector has been proposed.It is a generalization from the finite second-order moments to the infinite second-order moments in the domain of attraction of normal law.The log-empirical likelihood ratio statistic for the average number of the CPVP converges to F distribution in distribution when the population is in the domain of attraction of normal law but has infinite covariance matrix.Some simulation results are proposed to illustrate the method of the paper.展开更多
Removal of foreign bodies from seed mixtures, or their calibration for use as planting material, as well as fraction classification of granular materials requires screening surfaces with vibratory motion. This paper p...Removal of foreign bodies from seed mixtures, or their calibration for use as planting material, as well as fraction classification of granular materials requires screening surfaces with vibratory motion. This paper presents some aspects on the working process of a sieve, made of perforated sheet and having an outer conical surface with oscillatory circular motion （alternative） on the horizontal. Results are presented for some experimental researches on the movement of material on the sieve, for various kinematical parameters of the sieve （amplitude and oscillation frequency）. A conical sieve, suspended at the upper and lower in three points, was tested for screening of rapeseeds in order to estimate the influence of oscillation frequency on the screening process. Curves were drawn for separation intensity on the sieve generating line, and by regression analysis with normal distribution law were determined the equation coefficients and the correlation with experimental data. Movement of material on the sieve and its working process, in general, was appreciated by means of the peak position of distribution curve depending on the oscillation frequency of the sieve, considering that the normal distribution law correlates very well the data obtained by experiments.展开更多
Let {X, Xn; n ≥ 0} be a sequence of independent and identically distributed random variables with EX=0, and assume that EX^2I（｜X｜ ≤ x） is slowly varying as x →∞, i.e., X is in the domain of attraction of the n...Let {X, Xn; n ≥ 0} be a sequence of independent and identically distributed random variables with EX=0, and assume that EX^2I（｜X｜ ≤ x） is slowly varying as x →∞, i.e., X is in the domain of attraction of the normal law. In this paper, a self-normalized law of the iterated logarithm for the geometrically weighted random series Σ~∞（n=0）β~nXn（0 〈 β 〈 1） is obtained, under some minimal conditions.展开更多
Using suitable self-normalization for partial sums of i.i.d.random variables,Griffin and Kuelbs established the law of the iterated logarithm for all distributions in the domain of attraction of a normal law.We obtain...Using suitable self-normalization for partial sums of i.i.d.random variables,Griffin and Kuelbs established the law of the iterated logarithm for all distributions in the domain of attraction of a normal law.We obtain the corresponding results for Studentized increments of partial sums under thesame condition.展开更多
Let {X,Xn,n1} be a sequence of independent identically distributed random variables with EX=0 and assume that EX2I(|X|≤x) is slowly varying as x→∞,i.e.,X is in the domain of attraction of the normal law.In this pap...Let {X,Xn,n1} be a sequence of independent identically distributed random variables with EX=0 and assume that EX2I(|X|≤x) is slowly varying as x→∞,i.e.,X is in the domain of attraction of the normal law.In this paper a Strassen-type strong approximation is established for self-normalized sums of such random variables.展开更多
基金The research of WONG Hsin-Chieh is partially supported by the NSTC(111-2118-M-305-004-MY2)the research of PANG Tian-xiao is partially supported by the National Social Science Foundation of China(21BTJ067)。
文摘This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly correlated with returns.To this end,we propose a robust test which can capture empirical phenomena such as heavy tails,stationary,and local to unity.Moreover,we develop related asymptotic results without the second-moment assumption between the predictive variable and returns.To make the proposed test reasonable,we propose a generalized correlation and provide theoretical support.To illustrate the applicability of the test,we perform a simulation study for the impact of heavy-tailed innovations on predictability,as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon.Finally,we provide an empirical study for further illustration,to which the proposed test is applied to a U.S.equity data set.
基金National Natural Science Foundation of China(1067117610771192).
文摘Let variables in the {X, Xn, n ≥ 1} be a sequence of strictly stationary φ-mixing positive random domain of attraction of the normal law. Under some suitable conditions the principle for self-normalized products of partial sums is obtained.
基金Characteristic Innovation Projects of Ordinary Universities of Guangdong Province,China(No.2022KTSCX150)Zhaoqing Education Development Institute Project,China(No.ZQJYY2021144)Zhaoqing College Quality Project and Teaching Reform Project,China(Nos.zlgc202003 and zlgc202112)。
文摘The paper discusses the statistical inference problem of the compound Poisson vector process(CPVP)in the domain of attraction of normal law but with infinite covariance matrix.The empirical likelihood(EL)method to construct confidence regions for the mean vector has been proposed.It is a generalization from the finite second-order moments to the infinite second-order moments in the domain of attraction of normal law.The log-empirical likelihood ratio statistic for the average number of the CPVP converges to F distribution in distribution when the population is in the domain of attraction of normal law but has infinite covariance matrix.Some simulation results are proposed to illustrate the method of the paper.
文摘Removal of foreign bodies from seed mixtures, or their calibration for use as planting material, as well as fraction classification of granular materials requires screening surfaces with vibratory motion. This paper presents some aspects on the working process of a sieve, made of perforated sheet and having an outer conical surface with oscillatory circular motion （alternative） on the horizontal. Results are presented for some experimental researches on the movement of material on the sieve, for various kinematical parameters of the sieve （amplitude and oscillation frequency）. A conical sieve, suspended at the upper and lower in three points, was tested for screening of rapeseeds in order to estimate the influence of oscillation frequency on the screening process. Curves were drawn for separation intensity on the sieve generating line, and by regression analysis with normal distribution law were determined the equation coefficients and the correlation with experimental data. Movement of material on the sieve and its working process, in general, was appreciated by means of the peak position of distribution curve depending on the oscillation frequency of the sieve, considering that the normal distribution law correlates very well the data obtained by experiments.
基金Supported by National Natural Science Foundation of China(Grant Nos.11301481,11371321 and 10901138)National Statistical Science Research Project of China(Grant No.2012LY174)+1 种基金Zhejiang Provincial Natural Science Foundation of China(Grant No.LQ12A01018)the Fundamental Research Funds for the Central Universities and Zhejiang Provincial Key Research Base for Humanities and Social Science Research(Statistics)
文摘Let {X, Xn; n ≥ 0} be a sequence of independent and identically distributed random variables with EX=0, and assume that EX^2I（｜X｜ ≤ x） is slowly varying as x →∞, i.e., X is in the domain of attraction of the normal law. In this paper, a self-normalized law of the iterated logarithm for the geometrically weighted random series Σ~∞（n=0）β~nXn（0 〈 β 〈 1） is obtained, under some minimal conditions.
基金Project supported by the National Natural Science Foundation of Chinaan NSERC Canada grant of M.Csorgo at Carletoa University of Canada+1 种基金the Fok Yingtung Education Foundationan NSERC Canada Scientific Exchange Award at Carleton University
文摘Using suitable self-normalization for partial sums of i.i.d.random variables,Griffin and Kuelbs established the law of the iterated logarithm for all distributions in the domain of attraction of a normal law.We obtain the corresponding results for Studentized increments of partial sums under thesame condition.
基金supported by an NSERC Canada Discovery Grant of M.Csrgo at Carleton UniversityNational Natural Science Foundation of China(Grant No.10801122)+1 种基金Research Fund for the Doctoral Program of Higher Education of China(Grant No.200803581009)the Fundamental Research Funds for the Central Universities
文摘Let {X,Xn,n1} be a sequence of independent identically distributed random variables with EX=0 and assume that EX2I(|X|≤x) is slowly varying as x→∞,i.e.,X is in the domain of attraction of the normal law.In this paper a Strassen-type strong approximation is established for self-normalized sums of such random variables.
