Fragmentation and inefficiencies in US equity markets: Evidence from the Dow 30

no code implementations • 13 Feb 2019 • Brian F. Tivnan, David Rushing Dewhurst, Colin M. Van Oort, John H. Ring IV, Tyler J. Gray, Brendan F. Tivnan, Matthew T. K. Koehler, Matthew T. McMahon, David Slater, Jason Veneman, Christopher M. Danforth

Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a single and fixed frame of reference.

Human language reveals a universal positivity bias

no code implementations • 15 Jun 2014 • Peter Sheridan Dodds, Eric M. Clark, Suma Desu, Morgan R. Frank, Andrew J. Reagan, Jake Ryland Williams, Lewis Mitchell, Kameron Decker Harris, Isabel M. Kloumann, James P. Bagrow, Karine Megerdoomian, Matthew T. McMahon, Brian F. Tivnan, Christopher M. Danforth

Using human evaluation of 100, 000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage.

Cultural Vocal Bursts Intensity Prediction Translation