How Successful Are Wavelets in Detecting Jumps?

Autor: Burak Alparslan Eroğlu, Ramazan Gençay, M. Ege Yazgan
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Entropy, Vol 19, Iss 12, p 638 (2017)
Druh dokumentu: article
ISSN: 1099-4300
DOI: 10.3390/e19120638
Popis: We evaluate the performances of wavelet jump detection tests by using simulated high-frequency data, in which jumps and some other non-standard features are present. Wavelet-based jump detection tests have a clear advantage over the alternatives, as they are capable of stating the exact timing and number of jumps. The results indicate that, in addition to those advantages, these detection tests also preserve desirable power and size properties even in non-standard data environments, whereas their alternatives fail to sustain their desirable properties beyond standard data features.
Databáze: Directory of Open Access Journals