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The Timing of the Popping: Using the Log-Periodic Power Law Model to Predict the Bursting of Bubbles on Financial Markets
Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences. (Nationalekonomi)
Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
2016 (English)In: Financial History Review, ISSN 0968-5650, E-ISSN 1474-0052, Vol. 23, no 2, p. 193-217Article in journal (Refereed) Published
Abstract [en]

The occurrence and unpredictability of speculative bubbles on financial markets, and their accompanying crashes, have confounded economists and economic historians worldwide. We examine the ability of the log-periodic power law model (LPPL-model) to accurately predict the end dates of speculative bubbles on financial markets through modeling of asset price dynamics on a selection of historical bubbles. The method is based on a nonlinear least squares estimation which yields predictions of when the bubble will change regime. Previous studies have only presented results where the predictions turn out to be successful. This study is the first to highlight both the potential and the limitations of the LPPL-model.

We find evidence which support the characteristic patterns as proposed by the LPPL-framework leading up to the change in regime; asset prices during bubble periods seem to oscillate around a faster-than-exponential growth. In most cases the estimation yields accurate predictions, although we conclude that the predictions are quite dependent on the point in time at which the prediction is conducted. We also find that the end of a speculative bubble seems to be influenced by both endogenous speculative growth and exogenous factors. For this reason we propose a new way of interpreting the predictions of the model, where the end dates should be interpreted as the start of a time period where the asset prices are especially sensitive to exogenous events. We propose that negative news during this time period results in a regime shift and the bursting of the bubble. Thus, the model has the ability to predict sensitivity to exogenous events ex-ante. 

Place, publisher, year, edition, pages
2016. Vol. 23, no 2, p. 193-217
Keyword [en]
bubble forecasting, financial crisis, stock market crash, log-periodic power law model (LPPL-model), asset price dynamics.
National Category
Economic History
Identifiers
URN: urn:nbn:se:liu:diva-132917DOI: 10.1017/S0968565016000123OAI: oai:DiVA.org:liu-132917DiVA, id: diva2:1051304
Available from: 2016-12-01 Created: 2016-12-01 Last updated: 2018-03-26Bibliographically approved

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CiteExportLink to record
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  • apa
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