Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law SingularitiesReportar como inadecuado




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We augment the existing literature using the Log-Periodic Power Law Singular LPPLS structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle at least partially the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the -SandP 500 1987- bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst-rally occurs.



Autor: Qun Zhang, Qunzhi Zhang, Didier Sornette

Fuente: http://plos.srce.hr/



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