Ma

Sequential detection of structural changes in irregularly observed data

date
19.07.2018 
time
02:40 PM - 03:40 PM 
speaker
Tobias Kley  
affiliation
Humboldt-Universität Berlin 
part of series
TUD Mathematics AG Analysis & Stochastics 
language
en 
main topic
Mathematics: general
host
Prof. Dr. R. Schilling 
abstract


Online surveillance of time series is traditionally done with the aim to identify changes in the marginal distribution under the assumption that the data between change-points is stationary and that new data is observed at constant frequency. In many situations of interest to data analysts, the classical approach can be too restrictive to be used unmodified. We propose a unified system for the monitoring of structural changes in streams of data where we use generalised likelihood ratio-type statistics in the sequential testing problem, obtaining the flexibility to account for the various types of changes that are practically relevant (such as, for example, changes in the trend of the mean). Our method is applicable to sequences where new observations are allowed to arrive irregularly. Early identification of changes in the trend of financial data can assist to make trading more profitably. In an empirical illustration we apply the procedure to intra-day prices of components of the NASDAQ-100 stock market index. This is joint work with Piotr Fryzlewicz (London School of Economics).

 

Last update: 09.07.2018 10:46.

venue 

TUD Willers-Bau (WIL A 124) 
Zellescher Weg 12-14
01069 Dresden
homepage
https://navigator.tu-dresden.de/etplan/wil/00 

organizer 

TUD Mathematik
Willersbau, Zellescher Weg 12-14
01069 Dresden
telefon
49-351-463 33376 
homepage
http://tu-dresden.de/mathematik 
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