Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model

We describe the development and calibration of a hybrid agent-based dynamical systems model of the stock market that is capable of reproducing empirical market behavior. The model consists of two types of trader agents, fundamentalists and noise traders, as well as an opinion dynamic for the latter...

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Main Authors: Daniel A. Cline, Grant T. Aguinaldo, Christian Lemp
Format: Article
Language:English
Published: Binghamton University Library 2022-05-01
Series:Northeast Journal of Complex Systems
Online Access:https://orb.binghamton.edu/nejcs/vol4/iss2/1
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author Daniel A. Cline
Grant T. Aguinaldo
Christian Lemp
author_facet Daniel A. Cline
Grant T. Aguinaldo
Christian Lemp
author_sort Daniel A. Cline
collection DOAJ
description We describe the development and calibration of a hybrid agent-based dynamical systems model of the stock market that is capable of reproducing empirical market behavior. The model consists of two types of trader agents, fundamentalists and noise traders, as well as an opinion dynamic for the latter (optimistic vs. pessimistic). The trader agents switch types stochastically over time based on simple behavioral rules. A system of ordinary differential equations is used to model the stock price as a function of the states of the trader agents. We show that the model can reproduce key stylized facts (e.g., volatility clustering and fat tails) while providing a behavioral interpretation of how the stock market itself can cause periods of high volatility and large price movements, even when the economic value of the stock grows at a constant rate.
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spelling doaj.art-5f9142ff18074126a823289da453b7c52023-11-13T21:42:05ZengBinghamton University LibraryNortheast Journal of Complex Systems2577-84392022-05-014210.22191/nejcs/vol4/iss2/1Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems ModelDaniel A. Cline0https://orcid.org/0000-0003-1085-0757Grant T. Aguinaldo1https://orcid.org/0000-0003-1676-6169Christian Lemp2https://orcid.org/0000-0002-7970-9324Binghamton UniversityBinghamton UniversityBinghamton UniversityWe describe the development and calibration of a hybrid agent-based dynamical systems model of the stock market that is capable of reproducing empirical market behavior. The model consists of two types of trader agents, fundamentalists and noise traders, as well as an opinion dynamic for the latter (optimistic vs. pessimistic). The trader agents switch types stochastically over time based on simple behavioral rules. A system of ordinary differential equations is used to model the stock price as a function of the states of the trader agents. We show that the model can reproduce key stylized facts (e.g., volatility clustering and fat tails) while providing a behavioral interpretation of how the stock market itself can cause periods of high volatility and large price movements, even when the economic value of the stock grows at a constant rate.https://orb.binghamton.edu/nejcs/vol4/iss2/1
spellingShingle Daniel A. Cline
Grant T. Aguinaldo
Christian Lemp
Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
Northeast Journal of Complex Systems
title Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
title_full Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
title_fullStr Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
title_full_unstemmed Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
title_short Modeling Empirical Stock Market Behavior Using a Hybrid Agent-Based Dynamical Systems Model
title_sort modeling empirical stock market behavior using a hybrid agent based dynamical systems model
url https://orb.binghamton.edu/nejcs/vol4/iss2/1
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AT granttaguinaldo modelingempiricalstockmarketbehaviorusingahybridagentbaseddynamicalsystemsmodel
AT christianlemp modelingempiricalstockmarketbehaviorusingahybridagentbaseddynamicalsystemsmodel