| Title | Investigation on effect of excess buy orders using agent-based model |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Noritake, Yoshito, Mizuta, Takanobu, Hemmi, Ryuta, Nagumo, Shota, Izumi, Kiyoshi |
| Conference Name | 2022 9th International Conference on Behavioural and Social Computing (BESC) |
| Keywords | Agent-Based Model, Artificial Market, Computational modeling, Human Behavior, Impediments to Short-Selling of Stock, Order Imbalance, pubcrawl, Scalability, security, simulation, Social Agents, social computing, stock markets |
| Abstract | In financial markets such as stock markets, securities are traded at a price where supply equals demand. Behind the impediments to the short-selling of stock, most participants in the stock market are buyers, so trades are more probable at higher prices than in situations without such restrictions. However, the order imbalance that occurs when buy orders exceed sell orders can change due to many factors. Hence, it is insufficient to discuss the effects of order imbalance caused by impediments to short-selling on the stock price only through empirical studies. Our study used an artificial market to investigate the effects on traded price and quantity of limit orders. The simulation results revealed that the order imbalance when buy orders exceed sell orders increases the traded price and results in fewer quantities of limit sell orders than limit buy orders. In particular, when the sell/buy ratio of the order imbalance model is less than or equal to 0.9, the limit sell/buy ratio becomes lower than that. Lastly, we investigated the mechanisms of the effects on traded price and quantity of limit orders. |
| DOI | 10.1109/BESC57393.2022.9994930 |
| Citation Key | noritake_investigation_2022 |
Investigation on effect of excess buy orders using agent-based model