Investor Sentiment in an Artificial Limit Order Market
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 o...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/8581793 |
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| _version_ | 1850175829400616960 |
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| author | Lijian Wei Lei Shi |
| author_facet | Lijian Wei Lei Shi |
| author_sort | Lijian Wei |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c0bcdd25a3024c659754f47edfebd257 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-c0bcdd25a3024c659754f47edfebd2572025-08-20T02:19:22ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/85817938581793Investor Sentiment in an Artificial Limit Order MarketLijian Wei0Lei Shi1Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou 510275, ChinaMacquarie Business School, Department of Applied Finance, Macquarie University, Sydney, NSW 2109, AustraliaThis 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.http://dx.doi.org/10.1155/2020/8581793 |
| spellingShingle | Lijian Wei Lei Shi Investor Sentiment in an Artificial Limit Order Market Complexity |
| title | Investor Sentiment in an Artificial Limit Order Market |
| title_full | Investor Sentiment in an Artificial Limit Order Market |
| title_fullStr | Investor Sentiment in an Artificial Limit Order Market |
| title_full_unstemmed | Investor Sentiment in an Artificial Limit Order Market |
| title_short | Investor Sentiment in an Artificial Limit Order Market |
| title_sort | investor sentiment in an artificial limit order market |
| url | http://dx.doi.org/10.1155/2020/8581793 |
| work_keys_str_mv | AT lijianwei investorsentimentinanartificiallimitordermarket AT leishi investorsentimentinanartificiallimitordermarket |