• Title/Summary/Keyword: Stationary process

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Stationary bootstrap test for jumps in high-frequency financial asset data

  • Hwang, Eunju;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.163-177
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    • 2016
  • We consider a jump diffusion process for high-frequency financial asset data. We apply the stationary bootstrapping to construct a bootstrap test for jumps. First-order asymptotic validity is established for the stationary bootstrapping of the jump ratio test under the null hypothesis of no jump. Consistency of the stationary bootstrap test is proved under the alternative of jumps. A Monte-Carlo experiment shows the advantage of a stationary bootstrapping test over the test based on the normal asymptotic theory. The proposed bootstrap test is applied to construct continuous-jump decomposition of the daily realized variance of the KOSPI for the year 2008 of the world-wide financial crisis.

Block Bootstrapped Empirical Process for Dependent Sequences

  • Kim, Tae-Yoon
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.253-264
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    • 1999
  • Conditinal weakly convergence of the blockwise bootstrapped empirical process for stationary sequences to the appropriate Gaussian process is reestablished particularly for severely dependent $\alpha$-mixing sequences. Issue of block size is discussed from the point of validity of bootstrap method.

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Discrimination between trend and difference stationary processes based on adaptive lasso (Adaptive lasso를 이용하여 추세-정상시계열과 차분-정상시계열을 판별하는 방법에 대한 연구)

  • Na, Okyoung
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.723-738
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    • 2020
  • In this paper, we study a method to discriminate between trend stationary and difference stationary processes. Since a crucial ingredient of this discrimination is to determine the existence of unit root, we can use a unit root testing strategy. So, we introduce a discrimination based on unit root testing and propose the method using the adaptive lasso. Our Monte Carlo simulation experiments show that the adaptive lasso improves the discrimination accuracy when the process is trend stationary, but has lower accuracy than unit root strategy where the process is difference stationary.

STATIONARY SOLUTIONS FOR ITERATED FUNCTION SYSTEMS CONTROLLED BY STATIONARY PROCESSES

  • Lee, O.;Shin, D.W.
    • Journal of the Korean Mathematical Society
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    • v.36 no.4
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    • pp.737-746
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    • 1999
  • We consider a class of discrete parameter processes on a locally compact Banach space S arising from successive compositions of strictly stationary random maps with state space C(S,S), where C(S,S) is the collection of continuous functions on S into itself. Sufficient conditions for stationary solutions are found. Existence of pth moments and convergence of empirical distributions for trajectories are proved.

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A CENTRAL LIMIT THEOREM FOR THE STATIONARY MULTIVARIATE LINEAR PROCESS GENERATED BY ASSOCIATED RANDOM VICTORS

  • Kim, Tae-Sung;Ko, Mi-Hwa;Chung, Sung-Mo
    • Communications of the Korean Mathematical Society
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    • v.17 no.1
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    • pp.95-102
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    • 2002
  • A central limit theorem is obtained for a stationary multivariate linear process of the form (equation omitted), where { $Z_{t}$} is a sequence of strictly stationary m-dimensional associated random vectors with E $Z_{t}$ = O and E∥ $Z_{t}$$^2$ < $\infty$ and { $A_{u}$} is a sequence of coefficient matrices with (equation omitted) and (equation omitted).ted)..ted).).

M/PH/1 QUEUE WITH DETERMINISTIC IMPATIENCE TIME

  • Kim, Jerim;Kim, Jeongsim
    • Communications of the Korean Mathematical Society
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    • v.28 no.2
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    • pp.383-396
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    • 2013
  • We consider an M/PH/1 queue with deterministic impatience time. An exact analytical expression for the stationary distribution of the workload is derived. By modifying the workload process and using Markovian structure of the phase-type distribution for service times, we are able to construct a new Markov process. The stationary distribution of the new Markov process allows us to find the stationary distribution of the workload. By using the stationary distribution of the workload, we obtain performance measures such as the loss probability, the waiting time distribution and the queue size distribution.

Generation of Artificial Earthquake Ground Motions considering Design Response Spectrum (설계응답스펙트럼을 고려한 인공지진파의 발생에 관한 연구)

  • 정재경;한상환;이리형
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1999.04a
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    • pp.145-150
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    • 1999
  • In the nonlinear dynamic structural analysis, the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea, it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary stochastic process model which can be modeled as components with an intensity function, a frequency modulation function and a power spectral density function to describe such non-stationary characteristics. This paper shows the process to generate nonstationary artificial earthquake ground motions considering target design response spectrum chosen by ATC14.

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Characteristics, mathematical modeling and conditional simulation of cross-wind layer forces on square section high-rise buildings

  • Ailin, Zhang;Shi, Zhang;Xiaoda, Xu;Yi, Hui;Giuseppe, Piccardo
    • Wind and Structures
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    • v.35 no.6
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    • pp.369-383
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    • 2022
  • Wind tunnel experiment was carried out to study the cross-wind layer forces on a square cross-section building model using a synchronous multi-pressure sensing system. The stationarity of measured wind loadings are firstly examined, revealing the non-stationary feature of cross-wind forces. By converting the measured non-stationary wind forces into an energetically equivalent stationary process, the characteristics of local wind forces are studied, such as power spectrum density and spanwise coherence function. Mathematical models to describe properties of cross-wind forces at different layers are thus established. Then, a conditional simulation method, which is able to ex-tend pressure measurements starting from experimentally measured points, is proposed for the cross-wind loading. The method can reproduce the non-stationary cross-wind force by simulating a stationary process and the corresponding time varying amplitudes independently; in this way the non-stationary wind forces can finally be obtained by combining the two parts together. The feasibility and reliability of the proposed method is highlighted by an ex-ample of across wind loading simulation, based on the experimental results analyzed in the first part of the paper.

Parameter Estimation in a Complex Non-Stationary and Nonlinear Diffusion Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.29 no.4
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    • pp.489-499
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    • 2000
  • We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

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