Analysis of the Lehman Brothers collapse and the flash crash event by applying wavelets methodologies

DOI10.1016/j.physa.2017.01.064zbMath1400.91672OpenAlexW2571794480MaRDI QIDQ1620593

Maria P. Beccar-Varela, Osei K. Tweneboah, Ionut Florescu, Maria Christina Mariani

Publication date: 13 November 2018

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

Full work available at URL: https://doi.org/10.1016/j.physa.2017.01.064

zbMATH Keywords

high frequency financial dataflash crash eventLehman Brothers collapsewavelets methodology

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Economic time series analysis (91B84) Financial applications of other theories (91G80)

Related Items (3)

Analysis of stock market data by using dynamic Fourier and wavelets techniques ⋮ Modeling high frequency stock market data by using stochastic models ⋮ Geometric analysis of nonlinear dynamics in application to financial time series

Uses Software

• astsa

Cites Work

• Stochastic differential equations applied to the study of geophysical and financial time series
• Use of wavelets techniques to discriminate between explosions and natural earthquakes
• Detecting market crashes by analysing long-memory effects using high-frequency data
• Unnamed Item

This page was built for publication: Analysis of the Lehman Brothers collapse and the flash crash event by applying wavelets methodologies