'Human swarming' amplifies accuracy and roi when forecasting financial markets

Hans Schumann, Gregg Willcox, Louis Rosenberg, Niccolo Pescetelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Many social species amplify their decision-making accuracy by deliberating in real-time closed-loop systems. Known as Swarm Intelligence (SI), this natural process has been studied extensively in schools of fish, flocks of birds, and swarms of bees. The present research looks at human groups and tests their ability to make financial forecasts by working together in systems modeled after natural swarms. Specifically, groups of financial traders were tasked with forecasting the weekly trends of four common market indices (SPX, GLD, GDX, and Crude Oil) over a period of 19 consecutive weeks. Results showed that individual forecasters, who averaged 56.6% accuracy when predicting weekly trends on their own, amplified their accuracy to 77.0% when predicting together as real-time swarms. This reflects a 36% increase in forecasting accuracy and shows high statistical significance (p<0.001). Further, if investments had been made according to these swarm-based forecasts, the group would have netted a 13.3% return on investment (ROI) over the 19 weeks, compared to the individual's 0.7% ROI. This suggests that enabling groups of traders to form real-time systems online, governed by swarm intelligence algorithms, has the potential to significantly increase the accuracy and ROI of financial forecasts.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Humanized Computing and Communication, HCC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-82
Number of pages6
ISBN (Electronic)9781728141251
DOIs
StatePublished - Sep 2019
Externally publishedYes
Event1st IEEE International Conference on Humanized Computing and Communication, HCC 2019 - Laguna Hills, United States
Duration: Sep 25 2019Sep 27 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Humanized Computing and Communication, HCC 2019

Conference

Conference1st IEEE International Conference on Humanized Computing and Communication, HCC 2019
Country/TerritoryUnited States
CityLaguna Hills
Period9/25/199/27/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Social Psychology
  • Communication

Keywords

  • Artificial Intelligence
  • Artificial Swarm Intelligence
  • Collective Intelligence
  • Financial Forecasting
  • Human Forecasting
  • Human Swarming
  • Swarm Intelligence
  • Wisdom of Crowds

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