Herding as a consensus problem

Herding as a consensus problem In this paper, we show that herding phenomena in financial markets can be interpreted using the theoretical tools of pinning control. This is accomplished by viewing herding as a diffusion of a certain opinion in a network of financial agents, whose trading strategies dynamically depend on that of their neighbors according to a nonlinear state-dependent law. The interaction among the agents is modeled through a directed weighted graph, and following the logic of pinning control, we model the generic exogenous information triggering herding behavior as a control signal fed by an external entity to a subset of agents that, by virtue of the received information, can play the correct trading action. The topological conditions of partial pinning control theory enable us to predict the number of agents reaching consensus, i.e., the diffusion of information through the network, and thus the magnitude of the herding phenomenon triggered by the informed/pinned nodes. By testing our model of opinion dynamics in an artificial agent-based financial market, we prove that it is capable of replicating herding phenomena of different and predictable intensities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nonlinear Dynamics Springer Journals

Herding as a consensus problem

Loading next page...
 
/lp/springer_journal/herding-as-a-consensus-problem-qnsbC3QI01
Publisher
Springer Netherlands
Copyright
Copyright © 2018 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Engineering; Vibration, Dynamical Systems, Control; Classical Mechanics; Mechanical Engineering; Automotive Engineering
ISSN
0924-090X
eISSN
1573-269X
D.O.I.
10.1007/s11071-018-4094-4
Publisher site
See Article on Publisher Site

Abstract

In this paper, we show that herding phenomena in financial markets can be interpreted using the theoretical tools of pinning control. This is accomplished by viewing herding as a diffusion of a certain opinion in a network of financial agents, whose trading strategies dynamically depend on that of their neighbors according to a nonlinear state-dependent law. The interaction among the agents is modeled through a directed weighted graph, and following the logic of pinning control, we model the generic exogenous information triggering herding behavior as a control signal fed by an external entity to a subset of agents that, by virtue of the received information, can play the correct trading action. The topological conditions of partial pinning control theory enable us to predict the number of agents reaching consensus, i.e., the diffusion of information through the network, and thus the magnitude of the herding phenomenon triggered by the informed/pinned nodes. By testing our model of opinion dynamics in an artificial agent-based financial market, we prove that it is capable of replicating herding phenomena of different and predictable intensities.

Journal

Nonlinear DynamicsSpringer Journals

Published: Feb 12, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial