Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/194743 
Authors: 
Year of Publication: 
2017
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 5 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2017 [Pages:] 1-24
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
This study develops an agent-based computational stock market model in which each trader's buying and selling decisions are endogenously determined by multiple factors: namely, firm profitability, past stock price movement, and imitation of other traders. Each trader can switch from being a buyer to a seller, and vice versa, depending on market conditions. Simulation findings imply liquidity in the stock market decreases as more traders try to behave in a similar way to other traders. Stock return volatility is increasing in memory length when the information set of a trader includes only the fundamental of stock. On the other hand, when all traders consider only the past stock price movement, stock prices undergo boom and bust cycles with the occasional no-trade states. Furthermore, when traders consider three factors equally, the stock return is characterized by more pronounced fat-tail property and lower volatility.
Subjects: 
heterogeneous trader
memory length
asset pricing
agent-based stock market
JEL: 
G11
G12
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.