Black Swan events in the financial market: A network approach

Published: 25 March 2024| Version 1 | DOI: 10.17632/z8phkgphm9.1


The data set consists of 483 stocks that were continuously traded on the S&P 500 Index in the period from June 28, 2016 to August 9, 2023, and each stock has 1,791 data points of the daily closing price adjusted for splits and dividends. Sample data are separated into two subsets: the stabilization period before the market crash and the market disruption period during the COVID-19 pandemic and the Russian-Ukrainian war. The cut-off point for the separation of the two sub-periods was set on January 20, 2020. Therefore, the stabilization period is defined between June 29, 2016 and January 17, 2020; the market disruption period is set between January 21, 2020 and August 09, 2023. The split between the two periods is equal, with 895 time series in each period (approximately 3.5 years). Companies are classified into 11 economic sectors according to the classification of Yahoo Finance. These historical data were collected from Yahoo Finance (; accessed on 10.09.2023). The data set contains two matrices of cross-correlation networks of stock returns, based on the minimal spanning tree approach for the aforementioned time periods.


Steps to reproduce

The network was constructed using the minimal spanning tree approach.


Politechnika Lodzka


Financial Market, Unsupervised Learning, Complex System, COVID-19