Capital market based warning indicators of bank runs

Elena Vakhtina and Jan Henrik Wosnitza

Physica A: Statistical Mechanics and its Applications, 2015, vol. 417, issue C, 304-320

Abstract: In this investigation, we examine the univariate as well as the multivariate capabilities of the log-periodic [super-exponential] power law (LPPL) for the prediction of bank runs. The research is built upon daily CDS spreads of 40 international banks for the period from June 2007 to March 2010, i.e. at the heart of the global financial crisis. For this time period, 20 of the financial institutions received federal bailouts and are labeled as defaults while the remaining institutions are categorized as non-defaults. The employed multivariate pattern recognition approach represents a modification of the CORA3 algorithm. The approach is found to be robust regardless of reasonable changes of its inputs. Despite the fact that distinct alarm indices for banks do not clearly demonstrate predictive capabilities of the LPPL, the synchronized alarm indices confirm the multivariate discriminative power of LPPL patterns in CDS spread developments acknowledged by bootstrap intervals with 70% confidence level.

Keywords: Bank run prediction; CORA3 algorithm; Credit default swap spreads; Econophysics; Log-periodic [super-exponential] power law; Phase transition (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:417:y:2015:i:c:p:304-320

DOI: 10.1016/j.physa.2014.07.024

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