AN LPPL ALGORITHM FOR ESTIMATING THE CRITICAL TIME OF A STOCK MARKET BUBBLE

Daniel Traian Pele ()

Journal of Social and Economic Statistics, 2012, vol. 1, issue 2, 14-22

Abstract: LPPL models have been widely used to describe the behaviour of stock prices during an endogenous bubble and to predict the most probable time of the regime switching. Although their utility has been proved in many papers, there is still a lack of consensus on the statistical robustness, as the estimators are obtained through a nonlinear optimization algorithm and they are sensitive to the initial values. In this paper we propose an extension of the approach from Liberatore (2011), using a time series peak detection algorithm.

Keywords: LPPL; stock market crash; speculative bubble (search for similar items in EconPapers)
JEL-codes: G G01 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://jses.ase.ro/downloads/current_issue/122.pele.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aes:jsesro:v:1:y:2012:i:2:p:14-22

Access Statistics for this article

Journal of Social and Economic Statistics is currently edited by Zizi Goschin

More articles in Journal of Social and Economic Statistics from Bucharest University of Economic Studies Contact information at EDIRC.
Bibliographic data for series maintained by Bogdan-Vasile Ileanu ().