Quantilograms under Strong Dependence

Ji Hyung Lee, Oliver B. Linton, Yoon-Jae Whang

Research output: Working paper

Abstract

This paper studies the limit theory of the quantilogram and cross-quantilogram under long memory. We establish the sub-root-n central limit theorems for quantilograms that depend on nuisance parameters. A moving block bootstrap (MBB) procedure is proposed and its consistency is proved, thereby enabling a consistent confidence interval construction for the quantilograms. The newly developed uniform reduction principles (URPs) for the quantilograms serve as the main technical devices used to derive asymptotics and MBB validity. Confirmatory simulation results are reported. Some empirical practices on quantile predictive relations between financial returns and long memory predictors are performed using the new methods.
Original languageEnglish (US)
Number of pages31
DOIs
StatePublished - Mar 27 2017

Fingerprint

Moving Block Bootstrap
Long Memory
Reduction Principle
Nuisance Parameter
Quantile
Central limit theorem
Confidence interval
Predictors
Roots
Simulation

Keywords

  • Long Memory
  • Moving Block Bootstrap
  • Nonlinear Dependence
  • Quantilogram and Cross-Quantilgoram
  • Uniform Reduction Principle

Cite this

Quantilograms under Strong Dependence. / Lee, Ji Hyung; Linton, Oliver B.; Whang, Yoon-Jae.

2017.

Research output: Working paper

Lee, Ji Hyung ; Linton, Oliver B. ; Whang, Yoon-Jae. / Quantilograms under Strong Dependence. 2017.
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