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Logistic model for stock market bubbles and anti-bubbles

Lynch, Christopher and Mestel, Benjamin (2017). Logistic model for stock market bubbles and anti-bubbles. International Journal of Theoretical and Applied Finance, 20(6), article no. 1750038.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1142/S0219024917500388
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Abstract

Log-periodic power laws often occur as signatures of impending criticality of hierarchical systems in the physical sciences. It has been proposed that similar signatures may be apparent in the price evolution of financial markets as bubbles and the associated crashes develop. The features of such market bubbles have been extensively studied over the past 20 years, and models derived from an initial discrete scale invariance assumption have been developed and tested against the wealth of financial data with varying degrees of success. In this paper, the equations that form the basis for the standard log-periodic power law model and its higher extensions are compared to a logistic model derived from the solution of the Schroder equation for the renormalization group with nonlinear scaling function. Results for the S&P 500 and Nikkei 225 indices studied previously in the literature are presented and compared to established models, including a discussion of the apparent frequency shifting observed in the S&P 500 index in the 1980s. In the particular case of the Nikkei 225 anti-bubble between 1990 and 2003, the logistic model appears to provide a better description of the large-scale observed features over the whole 13-year period, particularly near the end of the anti-bubble.

Item Type: Journal Item
ISSN: 0219-0249
Keywords: Log-periodic power laws; renormalization group; financial bubbles; discrete scale invariance; criticality.
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Item ID: 50905
Depositing User: Benjamin Mestel
Date Deposited: 12 Sep 2017 13:11
Last Modified: 02 May 2019 01:36
URI: http://oro.open.ac.uk/id/eprint/50905
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