Kendall's tau for serial dependence

By Thomas S. Ferguson, Christian Genest, Marc Hallin. 2000

95 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b321eb13cdc6d8c3c7295a233f320a32f6632f12

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

In Statistics and Probability

Citations in the corpus

Order Patterns in Time Series (2007, methodology): “They do not use the actual values xt but only the information whether xs xt: M. Hallin and co-authors used rank correlation for statistical tests of autoregressive processes ( 8 ; 10; 12).”
Quantile Spectral Processes: Asymptotic Analysis and Inference (2014, unknown): “Marc Hallin was supported by the Belgian Science Policy Office (2012– 2017) Interuniversity Attraction Poles and a Humboldt-Forschungspreis of the Alexander von Humboldt-Stiftung.”
Peaks Over Threshold (POT): A methodology for automatic threshold estimation using goodness of fit p‐value (2017, methodology): “To this end, we follow Claps and Laio [2003] and use Kendall’s s test to verify the independence of the POT series [Ferguson et al., 2000] and the test proposed by Cunnane [1979] to verify the Poisson hypothesis.”
The stochastic conditional duration model: a latent variable model for the analysis of financial durations (2004, background): “16 Another possible measure is Kendall’s ( statistic, see Ferguson et al. (2000). As it is asymptotically equivalent to 1.”
Bayesian Inference for Kendall’s Rank Correlation Coefficient (2018, methodology): “By considering all possible permutations of the data, deriving the exact cumulative density of T ∗, and comparing the densities to those of a standard normal distribution, Ferguson et al. (2000) concluded that the normal approximation holds under H0 when n ≥ 10.”
Test of independence and randomness based on the empirical copula process (2004, background): “Other recent contributions are those of Kulperger and Lockhart (1998), Hong (1998), Hong (2000), Ferguson et al. (2000), and Genest et al. (2002) .”
A review of copula models for economic time series (2012, background): “[54] and Genest and Rémillard [70] consider rank-based tests of independence for serially dependent data.”
Statistical Dependence: Beyond Pearson’s ρ (2018, background): “It can be viewed as special cases of much more general results obtained by Hallin, Ingenbleek, and Puri (1985) and Ferguson, Genest, and Hallin (2000).”
Ordinal time series analysis (2005, background): “, T −1, was introduced by Ferguson et al. (2000) for testing linear autoregression coefficients.”