Biblio
Filters: Author is Mizuta, Takanobu [Clear All Filters]
Investigation on effect of excess buy orders using agent-based model. 2022 9th International Conference on Behavioural and Social Computing (BESC). :1–5.
.
2022. 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.
How Many Orders Does a Spoofer Need? - Investigation by Agent-Based Model - 2020 7th International Conference on Behavioural and Social Computing (BESC). :1–4.
.
2020. Most financial markets prohibit unfair trades as they reduce efficiency and diminish the integrity of the market. Spoofers place orders they have no intention of trading in order to manipulate market prices and profit illegally. Most financial markets prohibit such spoofing orders; however, further clarification is still needed regarding how many orders a spoofer needs to place in order to manipulate market prices and profit. In this study I built an artificial market model (an agent-based model for financial markets) to show how unbalanced buy and sell orders affect the expected returns, and I implemented the spoofer agent in the model. I then investigated how many orders the spoofer needs to place in order to manipulate market prices and profit illegally. The results indicate that showing more spoofing orders than waiting orders in the order book enables the spoofer to earn illegally, amplifies price fluctuation, and reduces the efficiency of the market.