### Abstract

Language | English |
---|---|

Pages | 87-116 |

Number of pages | 30 |

Journal | Journal of Time Series Econometrics |

Volume | 5 |

Status | Published - 2013 |

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### Cite this

*Journal of Time Series Econometrics*,

*5*, 87-116.

**Monitoring the intraday volatility pattern.** / Gabrys, R.; Hörmann, Siegfried; Kokoszka, P.

Research output: Contribution to journal › Article

*Journal of Time Series Econometrics*, vol 5, pp. 87-116.

}

TY - JOUR

T1 - Monitoring the intraday volatility pattern

AU - Gabrys,R.

AU - Hörmann,Siegfried

AU - Kokoszka,P.

N1 - Language of publication: en

PY - 2013

Y1 - 2013

N2 - 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

AB - 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

M3 - Article

VL - 5

SP - 87

EP - 116

JO - Journal of Time Series Econometrics

T2 - Journal of Time Series Econometrics

JF - Journal of Time Series Econometrics

SN - 2194-6507

ER -