Monitoring the intraday volatility pattern

R. Gabrys, Siegfried Hörmann, P. Kokoszka

Research output: Contribution to journalArticle

Abstract

A functional time series consists of curves, typically one curve per day. The most important parameter of such a series is the mean curve. We propose two methods of detecting a change in the mean function of a functional time series. The change is detected on line, as new functional observations arrive. The general methodology is motivated by, and applied to, the detection of a change in the mean intraday volatility pattern. The methodology is asymptotically justified by applying a new notion of weak dependence for functional time series. It is calibrated and validated by simulations based on real intraday volatility curves
Original languageEnglish
Pages (from-to)87-116
Number of pages30
JournalJournal of Time Series Econometrics
Volume5
Publication statusPublished - 2013

Fingerprint Dive into the research topics of 'Monitoring the intraday volatility pattern'. Together they form a unique fingerprint.

Cite this