EconPapers    
Economics at your fingertips  
 

Significance of log-periodic precursors to financial crashes

D. Sornette and A. Johansen

Quantitative Finance, 2001, vol. 1, issue 4, 452-471

Abstract: We clarify the status of log-periodicity associated with speculative bubbles preceding financial crashes. In particular, we address Feigenbaum's criticism ([A article="1469-7688/1/3/306"] Feigenbaum J A 2001 Quantitative Finance1 346-60 [/A]) and show how it can be refuted. Feigenbaum's main result is as follows: 'the hypothesis that the log-periodic component is present in the data cannot be rejected at the 95% confidence level when using all the data prior to the 1987 crash; however, it can be rejected by removing the last year of data' (e.g. by removing 15% of the data closest to the critical point). We stress that it is naive to analyse a critical point phenomenon, i.e., a power-law divergence, reliably by removing the most important part of the data closest to the critical point. We also present the history of log-periodicity in the present context explaining its essential features and why it may be important. We offer an extension of the rational expectation bubble model for general and arbitrary risk-aversion within the general stochastic discount factor theory. We suggest guidelines for the use of log-periodicity and explain how to develop and interpret statistical tests of log-periodicity. We discuss the issue of prediction based on our results and the evidence of outliers in the distribution of drawdowns. New statistical tests demonstrate that the 1% to 10% quantile of the largest events of the population of drawdowns of the NASDAQ composite index and of the Dow Jones Industrial Average index belong to a distribution significantly different from the rest of the population. This suggests that very large drawdowns may result from an amplification mechanism that may make them more predictable.

Date: 2001
References: Add references at CitEc
Citations View citations in EconPapers (62) Track citations by RSS feed

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1088/1469-7688/1/4/305 (text/html)
Access to full text is restricted to subscribers.

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:taf:quantf:v:1:y:2001:i:4:p:452-471

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Series data maintained by Chris Longhurst ().

 
Page updated 2017-10-21
Handle: RePEc:taf:quantf:v:1:y:2001:i:4:p:452-471