A stable and robust calibration scheme of the log-periodic power law model

DOI10.1016/j.physa.2013.04.012zbMath1402.91946arXiv1108.0099OpenAlexW2039947804MaRDI QIDQ1673119

Didier Sornette, Vladimir Filimonov

Publication date: 11 September 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1108.0099

zbMATH Keywords

optimizationfinancial bubblescrasheslog-periodic power lawfit methodJLS model

Mathematics Subject Classification ID

Financial applications of other theories (91G80)

Related Items (7)

Modified profile likelihood inference and interval forecast of the burst of financial bubbles ⋮ Comparing nested data sets and objectively determining financial bubbles' inceptions ⋮ New JLS-factor model versus the standard JLS model: a case study on Chinese stock bubbles ⋮ Liquidity crisis detection: an application of log-periodic power law structures to default prediction ⋮ Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data ⋮ On the predictability of stock market bubbles: evidence from LPPLS confidence multi-scale indicators ⋮ Limit theorems for nearly unstable Hawkes processes

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