Comparison of the Behavior of Human and Robot Traders in a Computerized Double Auction Market

计算机化双重拍卖市场中人类和机器人交易者的行为比较

• 批准号: 9010046
• 负责人: John Rust
• 金额: $ 5.2万
• 依托单位: Santa Fe Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-07-01 至 1992-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9010046&HistoricalAwards=false
• 关键词: Comparison; Behavior; Human; Robot; Traders

This project conducts a series of human double auction market experiments to generate a matching data set for a tournament of "robot traders" who compete in an artificial double auction market. The double auction market is a simplified version of the AURORA electronic double auction market recently developed by the Chicago Board of Trade. Precise comparisons will be made of the behavior of human and robot traders. Existing experimental data on human double auction markets are not directly comparable to the computerized market because the latter divides time into discrete bid-offer and buy-sell steps, and adopts a new institutional design, Chicago Rules, that allows only holders of the highest outstanding bid or lowest outstanding offer to execute transactions. The project uses the experiments to study the impact of Chicago rules, the effects of variations in period length in a market with discrete trading intervals, and the consequences of restrictions on the messages that can be transmitted and received by traders. The results of this research will improve experimental methods and our understanding of widely used market institutions. By matching human experimental data with the results from the tournament of computerized robot traders, the project will be able to provide strong tests of the ability of "artificially intelligent" agents to mimic the behavior of human traders in Double-Auction markets. If computer simulations could complement human experiments, this would dramatically increase the number and type of experiments that investigators could use to study the effects of institutional changes. The results of the experiments should also provide new insights into the performance of double auctions. This is important because the double auction is the type of trading institution used by the Chicago Board of Trade, the New York Stock Exchange, and many other securities and commodities exchanges throughout the world.

该项目进行了一系列人类的双拍卖市场实验，以为在人造双拍卖市场中竞争的“机器人交易者”锦标赛生成匹配的数据集。 双重拍卖市场是芝加哥贸易委员会最近开发的Aurora电子双重拍卖市场的简化版本。 将与人类和机器人交易者的行为进行精确的比较。 现有关于人类双重拍卖市场的实验数据与计算机市场无法直接相提并论，因为后者将时间分为离散的竞标和购买台阶，并采用了新的机构设计，芝加哥规则，该规则只允许最高出色的出价或最低未偿还的持有人来执行交易。 该项目使用实验来研究芝加哥规则的影响，具有离散交易间隔的市场中周期长度变化的影响，以及对交易者可以传输和接收的消息的限制后果。 这项研究的结果将改善实验方法和我们对广泛使用的市场机构的理解。 通过将人类的实验数据与计算机化机器人交易员锦标赛的结果相匹配，该项目将能够对“人为智能”代理模仿人类商人在双重拍卖市场中的行为的能力进行强有力的测试。 如果计算机模拟可以补充人类实验，这将大大增加研究人员可以用来研究制度变化影响的实验数量和类型。 实验的结果还应为双重拍卖的性能提供新的见解。 这很重要，因为双重拍卖是芝加哥贸易委员会，纽约证券交易所以及世界上许多其他证券和商品交易所使用的交易机构的类型。