• Corpus ID: 10838445

The quantile spectral density and comparison based tests for nonlinear time series

@article{Lee2011TheQS,
  title={The quantile spectral density and comparison based tests for nonlinear time series},
  author={Junbum Lee and Suhasini Subba Rao},
  journal={arXiv: Statistics Theory},
  year={2011}
}
In this paper we consider tests for nonlinear time series, which are motivated by the notion of serial dependence. The proposed tests are based on comparisons with the quantile spectral density, which can be considered as a quantile version of the usual spectral density function. The quantile spectral density 'measures' sequential dependence structure of a time series, and is well defined under relatively weak mixing conditions. We propose an estimator for the quantile spectral density and… 
Quantile‐frequency analysis and spectral measures for diagnostic checks of time series with nonlinear dynamics
  • Ta‐Hsin Li
  • Mathematics
    Journal of the Royal Statistical Society: Series C (Applied Statistics)
  • 2020
Nonlinear dynamic volatility has been observed in many financial time series. The recently proposed quantile periodogram offers an alternative way to examine this phenomena in the frequency domain.
Quantile-Frequency Analysis and Spectral Divergence Metrics for Diagnostic Checks of Time Series With Nonlinear Dynamics
Nonlinear dynamic volatility has been observed in many financial time series. The recently proposed quantile periodogram offers an alternative way to examine this phenomena in the frequency domain.
Robust Spectral Analysis
In this paper I introduce quantile spectral densities that summarize the cyclical behavior of time series across their whole distribution by analyzing periodicities in quantile crossings. This
SFB 823 Quantile spectral analysis for locally stationary time series D iscussion P aper
Classical spectral methods are subject to two fundamental limitations: they only can account for covariance-related serial dependencies, and they require second-order stationarity. Much attention has
Bayesian copula spectral analysis for stationary time series
Quantile spectral analysis for locally stationary time series
Classical spectral methods are subject to two fundamental limitations: they can account only for covariance‐related serial dependences, and they require second‐order stationarity. Much attention has
Quantile and Copula Spectrum: A New Approach to Investigate Cyclical Dependence in Economic Time Series
This chapter presents a survey of some recent methods used in economics and finance to account for cyclical dependence and account for their multifaced dynamics: nonlinearities, extreme events,
Clustering of time series using quantile autocovariances
TLDR
Results from an extensive simulation study show that the proposed metric outperforms or is highly competitive with a range of dissimilarities reported in the literature, particularly exhibiting high capability to cluster time series generated from a broad range of dependence models.
QUANTILE PERIODOGRAM AND TIME‐DEPENDENT VARIANCE
This article investigates the statistical properties of the recently introduced quantile periodogram for time series with time‐dependent variance. The asymptotic distribution of the quantile
Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables
In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and argue that this type of dependence is natural
...
...

References

SHOWING 1-10 OF 18 REFERENCES
Robust Spectral Analysis
In this paper I introduce quantile spectral densities that summarize the cyclical behavior of time series across their whole distribution by analyzing periodicities in quantile crossings. This
Bootstrapping frequency domain tests in multivariate time series with an application to comparing spectral densities
Summary.  We propose a general bootstrap procedure to approximate the null distribution of non‐parametric frequency domain tests about the spectral density matrix of a multivariate time series. Under
Generalized spectral tests for serial dependence
Two tests for serial dependence are proposed using a generalized spectral theory in combination with the empirical distribution function. The tests are generalizations of the Cramér‐von Mises and
Goodness of Fit Tests for Spectral Distributions
Abstract : The spectral distribution function of a stationary stochastic process standardized by dividing by the variance of the process is a linear function of the autocorrelations. The integral of
A nonparametric test of serial independence based on the empirical distribution function
The Blum, Kiefer & Rosenblatt (1961) statistic for testing independence is considered in a time series setting. This test is, under mild conditions, shown to be consistent against lag one dependent
Consistent Testing for Serial Correlation of Unknown Form
This paper proposes three classes of consistent tests for serial correlation of the residuals from a linear dynamic regression model. The tests are obtained by comparing a kernel-based spectral
DIAGNOSTIC CHECKING FOR THE ADEQUACY OF NONLINEAR TIME SERIES MODELS
We propose a new diagnostic test for linear and nonlinear time series models, using a generalized spectral approach. Under a wide class of time series models that includes autoregressive conditional
Testing for pairwise serial independence via the empirical distribution function
Built on Skaug and Tjøstheim's approach, this paper proposes a new test for serial independence by comparing the pairwise empirical distribution functions of a time series with the products of its
A GENERALIZED PORTMANTEAU GOODNESS-OF-FIT TEST FOR TIME SERIES MODELS
We present a goodness-of-fit test for time series models based on the discrete spectral average estimator. Unlike current tests of goodness of fit, the asymptotic distribution of our test statistic
Laplace Periodogram for Time Series Analysis
A new type of periodogram, called the Laplace periodogram, is derived by replacing least squares with least absolute deviations in the harmonic regression procedure that produces the ordinary
...
...