Physica A: Statistical Mechanics and its Applications

Chinese RMB/US$ exchange rates in Mainland and Hong Kong market (CNY and CNH) daily values

Density of risk drinkers for Brazil, during the window of time 2009 to 2019.

Brazilian welfare program payments dataset files provided by Transparency Portal. These data were submited to a Newcomb-Benford Law (NBL)-based method for fraud detection.

These data accompany the publication "Trends, Reversion, and Critical Phenomena in Financial Markets". They contain daily data from Jan 1992 to Dec 2019 on 24 financial markets, namely - 6 equity indices: S&P 500, TSE 60, DAX 30, FTSE 100, Nikkei 225, Hang Seng - 6 Interest rates for government bonds: US 10-year, Canada 10-year, Germany 10-year, UK 10-year, Japan 10-year, Australia 3-year - 6 FX rates: CAD/USD, EUR/USD, GBP/USD, JPY/USD, AUD/USD, NZD/USD - 6 Commodities: Crude Oil, Natural Gas, Gold, Copper, Soybeans, Live Cattle The data are provided in 13 columns: - Column 1: date - Column 2: market - Column 3: daily log return of futures on that market, normalized to have mean 0 and standard deviation 1 over the 28-year time period - Columns 4-13: trend strengths in that market over 10 different time horizons of (2,4,8,16,32,64,128,256,512,1024) business days. The trend strengths are defined in the accompanying paper. They are cut off at plus/minus 2.5. The daily log returns were computed from daily futures prices, rolled 5 days prior to first notice, which were taken from Bloomberg. The following mean returns and volatilites were used to normalize the daily log returns in column 3: Market Mean St. Dev. S&P 500 2.217% 1.100% TSE 60 2.416% 1.067% DAX 30 1.199% 1.366% FTSE 100 1.053% 1.103% Nikkei 225 -0.483% 1.486% Hang Seng 0.768% 1.674% US 10-year 3.734% 0.366% Can. 10-year 3.637% 0.376% Ger. 10-year 4.141% 0.337% UK 10-year 2.983% 0.419% Jap. 10-year 4.453% 0.249% Aus. 3-year 3.029% 0.074% CAD/USD 0.048% 0.479% EUR/USD -0.222% 0.619% GBP/USD 0.316% 0.597% JPY/USD -0.761% 0.667% AUD/USD 0.851% 0.725% NZD/USD 1.563% 0.724% Crude Oil 0.093% 2.243% Natural Gas -2.649% 2.985% Gold 0.580% 0.987% Copper 0.936% 1.586% Soybeans 0.631% 1.360% Live Cattle 0.483% 0.894%

The datasets contain many famous complex networks and generated benchmarks, as well as some datasets collected from real-world websites. The Adjnoun Network (adj.gml) is an undirected network of common nouns and adjective adjacencies in the novel “David Copperfield” by 19th century English writer Charles Dickens, seen in reference [13] in our paper. The Celegansneural data set (celegansneural.gexf) contains the graph of interconnections among the neurons in the C.elegans nematode [25]. The Bottleneck Dolphin Network (dolphins.gml) records the relationship and interactions between different dolphins in New Zealand [26] and is a famous data set for community detection. The football club network (football.gexf) includes the American club members in universities and their connections, seen in reference [1]. The lesmis network records relationships around Les Mis´erables, a French historical novel by Victor Hugo, first published in 1862, which is considered one of the greatest novels of the 19th century. The LFR2500 network (LFR2500_1.gexf) is the network generated by LFR. The Karate Club Network is a famous network for testing community detection [5]. The primary school network includes collected data of contacts between students and teachers in a primary school, seen in [28]. The file titled "primaryschool.gml" is complete data and the file titled "primaryschool120.gexf" is the network by removing the edge with contacts less than 120 seconds. The skill graph network (skillgraph.gexf) indicates how different skills are connected in the resume. The network in the file titled "t2.gexf" records a propagation tree in Microblog. And the file titled "user.gexf" contains the user relationship network of the users involved in the information propagation.

This is the supporting data for the article Urban Growth Tendency of Electrical Cables in the Costa Rican Metropolitan Area. It includes the pictures used in the measurements, as well as the Matlab scripts used to generate the results.

global migration 2006- 2010

Replication files for The exponential Pareto model with hidden income processes: evidence from Chile

The data enclosed was used in the study and include daily data for decile portfolios and industries.

A proof of concept of a method that improves reconstructing the network / graph structure from experimental data using entropy bias estimation.