An Agent-Based Model of a Pricing Process with Power Law, Volatility Clustering, and Jumps
Authored by Yu Shi, Qixuan Luo, Handong Li
Date Published: 2019
DOI: 10.1155/2019/3429412
Sponsors:
Chinese National Natural Science Foundation
Platforms:
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Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
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Abstract
In this paper, we propose a new model of security price dynamics in
order to explain the stylized facts of the pricing process such as power
law distribution, volatility clustering, jumps, and structural changes.
We assume that there are two types of agents in the financial market:
speculators and fundamental investors. Speculators use past prices to
predict future prices and only buy assets whose prices are expected to
rise. Fundamental investors attach a certain value to each asset and buy
when the asset is undervalued by the market. When the expectations of
agents are exogenously driven, that is, entirely shaped by exogenous
news, then they can be modeled as following a random walk. We assume
that the information related to the two types of agents in the model
will arrive randomly with a certain probability distribution and change
the viewpoint of the agents according to a certain percentage. Our
simulated results show that this model can simulate well the random walk
of asset prices and explain the power-law tail distribution of returns,
volatility clustering, jumps, and structural changes of asset prices.
Tags
Dynamics
Financial-markets