Name
Abstract | ||
|---|---|---|
Limit order book simulations based on “zero-intelligence” or “entropy-maximizing” agents address two difficult issues in financial economics. First, the models address the significance of trading mechanisms by explicitly accounting for the logic of those mechanisms. Second, they avoid the difficulty of modeling human decision-making by generating orders stochastically. This paper reports on a computational experiment in which a strategic agent trading on endogenous market signals is embedded in an otherwise stochastic order book simulation. Under certain parameterizations of the model the agent is profitable despite the fact that the agent only employs market orders. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CIFEr.2014.6924086 | Computational Intelligence for Financial Engineering & Economics |
Keywords | Field | DocType |
decision making,economics,entropy,marketing,multi-agent systems,pricing,profitability,stochastic processes,endogenous market signals,entropy-maximizing agents,financial economics,human decision-making modeling,limit order book simulations,microprice trading mechanism,order-driven market,stochastic order book simulation,strategic agent trading,zero-intelligence agents | Economics,Numerical models,Microeconomics,Stochastic process,Multi-agent system,Alternative trading system,Profitability index,Industrial organization,Algorithmic trading,Stochastic ordering,Order (exchange) | Conference |
ISSN | Citations | PageRank |
2380-8454 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew Todd | 1 | 0 | 0.34 |
| Hayes, R. | 2 | 0 | 0.34 |
| Peter A. Beling | 3 | 0 | 0.34 |
| William T. Scherer | 4 | 0 | 0.34 |