Investor Sentiment and IPOs Anomalies: An Agent-Based Computational Finance

This study builds an agent-based computational finance platform that can reproduce the basic characteristics of China’s initial public offering (IPO) market and explain its anomalies. The results of our computational experiments show that along with the increasing proportion of sentiment strategy investors (i.e., those with an information advantage) entering the market, the IPO underpricing rate also rises correspondingly. Sentiment investors usually suffer losses because of their irrational investment decisions, while sentiment strategy investors profit by preying on sentiment investors.

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Agent-based economic models and econometrics

The Knowledge Engineering Review ◽

10.1017/s0269888912000136 ◽

2012 ◽

Vol 27 (2) ◽

pp. 187-219 ◽

Cited By ~ 131

Author(s):

Shu-Heng Chen ◽

Chia-Ling Chang ◽

Ye-Rong Du

Keyword(s):

Financial Markets ◽

Agent Based Modeling ◽

Computational Finance ◽

Agent Based ◽

Second Stage ◽

The Past ◽

Stage Development ◽

Three Stages ◽

The One ◽

Two Stages

AbstractThis paper reviews the development of agent-based (computational) economics (ACE) from an econometrics viewpoint. The review comprises three stages, characterizing the past, the present, and the future of this development. The first two stages can be interpreted as an attempt to build the econometric foundation of ACE, and, through that, enrich its empirical content. The second stage may then invoke a reverse reflection on the possible agent-based foundation of econometrics. While ACE modeling has been applied to different branches of economics, the one, and probably the only one, which is able to provide evidence of this three-stage development is finance or financial economics. We will, therefore, focus our review only on the literature of agent-based computational finance, or, more specifically, the agent-based modeling of financial markets.

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Investor Sentiment in an Artificial Limit Order Market

Complexity ◽

10.1155/2020/8581793 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Lijian Wei ◽

Lei Shi

Keyword(s):

Regime Switching ◽

Trading Volume ◽

Bayesian Learning ◽

Investor Sentiment ◽

Agent Based Modeling ◽

Order Book ◽

Limit Order ◽

Agent Based ◽

Bid Ask Spread ◽

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 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.

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Agent-based computational finance: Suggested readings and early research

Journal of Economic Dynamics and Control ◽

10.1016/s0165-1889(99)00022-6 ◽

2000 ◽

Vol 24 (5-7) ◽

pp. 679-702 ◽

Cited By ~ 285

Author(s):

Blake LeBaron

Keyword(s):

Early Research ◽

Computational Finance ◽

Agent Based

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From the simplest price formation models to paradigm of agent-based computational finance: a first step

Agent-Based Social Systems - Agent-Based Approaches in Economic and Social Complex Systems V ◽

10.1007/978-4-431-87435-5_18 ◽

2009 ◽

pp. 219-230

Author(s):

Takashi Yamada ◽

Takao Terano

Keyword(s):

Price Formation ◽

Computational Finance ◽

Agent Based

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QUEUING, SOCIAL INTERACTIONS, AND THE MICROSTRUCTURE OF FINANCIAL MARKETS

Macroeconomic Dynamics ◽

10.1017/s1365100507070010 ◽

2008 ◽

Vol 12 (2) ◽

pp. 211-233 ◽

Cited By ~ 21

Author(s):

ULRICH HORST ◽

CHRISTIAN ROTHE

Keyword(s):

Financial Markets ◽

Social Interactions ◽

Continuous Time ◽

Order Approximation ◽

Investor Sentiment ◽

Agent Based ◽

First Order ◽

First Order Approximation ◽

Delay Differential ◽

Over Time

We consider an agent-based model of financial markets with asynchronous order arrival in continuous time. Buying and selling orders arrive in accordance with a Poisson dynamics where the order rates depend both on past prices and on the mood of the market. The agents form their demand for an asset on the basis of their forecasts of future prices and their forecasting rules may change over time as a result of the influence of other traders. Among the possible rules are “chartist” or extrapolatory rules. We prove that when chartists are in the market, and with choice of scaling, the dynamics of asset prices can be approximated by an ordinary delay differential equation. The fluctuations around the first-order approximation follow an Ornstein–Uhlenbeck dynamics with delay in a random environment of investor sentiment.

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