2012/02/01 by João Pires da Cruz, da Cruz, João P., Pedro G. Lind +1
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #Computational Finance (q-fin.CP) #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Economics and business #FOS: Physical sciences #Financial Risk and Volatility Modeling #Market Dynamics and Volatility
paper · pdf · doi:10.48550/arxiv.1202.0142
openalex publication_date 2012/02/01 · openalex created_date 2022/09/05 · openalex updated_date 2026/07/28
The study of heavy-tailed distributions in economic and financial systems has\nbeen widely addressed since financial time series has become a research\nsubject.After the eighties, several "highly improbable" market drops were\nobserved (e.g. the 1987 stock market drop known as "Black Monday" and on even\nmore recent ones, already in the 21st century) that produce heavy losses that\nwere unexplainable in a GN environment. The losses incurred in these large\nmarket drop events did not change significantly the market practices or the way\nregulation is done but drove some attention back to the study of heavy-tails\nand their underlying mechanisms. Some recent findings in these context is the\nscope of this manuscript.\n