Investor Sentiment in an Artificial Limit Order Market
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-30
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper examines the under/overreaction effect driven by sentiment belief in an artificial limit order market when agents are risk averse and arrive in the market with different time horizons.
We employ agent-based modeling to build up an artificial stock market with order book and model a type of sentiment belief display over/underreaction by following a Bayesian learning scheme with a Markov regime switching between conservative bias and representative bias.
Simulations show that when compared with classic noise belief without learning, sentiment belief gives rise to short-term intraday return predictability.
In particular, under/overreaction trading strategies are profitable under sentiment beliefs, but not under noise belief.
Moreover, we find that sentiment belief leads to significantly lower volatility, lower bid-ask spread, and larger order book depth near the best quotes but lower trading volume when compared with noise belief.
American Psychological Association (APA)
Wei, Lijian& Shi, Lei. 2020. Investor Sentiment in an Artificial Limit Order Market. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1144453
Modern Language Association (MLA)
Wei, Lijian& Shi, Lei. Investor Sentiment in an Artificial Limit Order Market. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1144453
American Medical Association (AMA)
Wei, Lijian& Shi, Lei. Investor Sentiment in an Artificial Limit Order Market. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1144453
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1144453