Search Results for author: Brian F. Tivnan

Found 5 papers, 0 papers with code

Adaptive Agents and Data Quality in Agent-Based Financial Markets

no code implementations27 Nov 2023 Colin M. Van Oort, Ethan Ratliff-Crain, Brian F. Tivnan, Safwan Wshah

As a baseline, we populate ABMMS with simple trading agents and investigate properties of the generated data.

Meta Reinforcement Learning

Revisiting Stylized Facts for Modern Stock Markets

no code implementations13 Nov 2023 Ethan Ratliff-Crain, Colin M. Van Oort, James Bagrow, Matthew T. K. Koehler, Brian F. Tivnan

In 2001, Rama Cont introduced a now-widely used set of 'stylized facts' to synthesize empirical studies of financial time series, resulting in 11 qualitative properties presumed to be universal to all financial markets.

Time Series

Scaling of inefficiencies in the U.S. equity markets: Evidence from three market indices and more than 2900 securities

no code implementations13 Feb 2019 John H. Ring IV, Colin M. Van Oort, David R. Dewhurst, Tyler J. Gray, Christopher M. Danforth, Brian F. Tivnan

Using the most comprehensive, commercially-available dataset of trading activity in U. S. equity markets, we catalog and analyze quote dislocations between the SIP National Best Bid and Offer (NBBO) and a synthetic BBO constructed from direct feeds.

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

no code implementations13 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 implementations15 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

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