Intraday order placement and execution in a limit order market: Evidence from the Indonesia stock market

2019 ◽  
Author(s):  
Irwan A. Ekaputra ◽  
Chunlin Liu ◽  
S. Ghon Rhee ◽  
Hongchao Zeng
Keyword(s):  
Stock Market ◽  
Limit Order ◽  
Limit Order Market

scholarly journals Investor Sentiment in an Artificial Limit Order Market

Complexity ◽  
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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