英文标题：
《How to Evaluate Trading Strategies: Single Agent Market Replay or
  Multiple Agent Interactive Simulation?》
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作者：
Tucker Hybinette Balch, Mahmoud Mahfouz, Joshua Lockhart, Maria
  Hybinette, David Byrd
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最新提交年份：
2019
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英文摘要：
  We show how a multi-agent simulator can support two important but distinct methods for assessing a trading strategy: Market Replay and Interactive Agent-Based Simulation (IABS). Our solution is important because each method offers strengths and weaknesses that expose or conceal flaws in the subject strategy. A key weakness of Market Replay is that the simulated market does not substantially adapt to or respond to the presence of the experimental strategy. IABS methods provide an artificial market for the experimental strategy using a population of background trading agents. Because the background agents attend to market conditions and current price as part of their strategy, the overall market is responsive to the presence of the experimental strategy. Even so, IABS methods have their own weaknesses, primarily that it is unclear if the market environment they provide is realistic. We describe our approach in detail, and illustrate its use in an example application: The evaluation of market impact for various size orders.
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中文摘要：
我们展示了多代理模拟器如何支持评估交易策略的两种重要但不同的方法：市场重播和交互式基于代理的模拟（IABS）。我们的解决方案很重要，因为每种方法都提供了暴露或隐藏主题策略缺陷的优缺点。市场重播的一个关键弱点是，模拟市场没有实质性地适应或响应实验策略的存在。IABS方法使用背景交易代理群体为实验策略提供了一个人工市场。由于背景代理商将市场条件和当前价格作为其策略的一部分，因此整个市场对实验策略的存在作出响应。即便如此，IABS方法也有其自身的弱点，主要是不清楚它们提供的市场环境是否现实。我们详细描述了我们的方法，并在一个示例应用程序中说明了它的使用：评估各种规模订单的市场影响。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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一级分类：Computer Science        计算机科学
二级分类：Computer Science and Game Theory        计算机科学与博弈论
分类描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵盖计算机科学和博弈论交叉的所有理论和应用方面，包括机制设计的工作，游戏中的学习（可能与学习重叠），游戏中的agent建模的基础（可能与多agent系统重叠），非合作计算环境的协调、规范和形式化方法。该领域还涉及博弈论在电子商务等领域的应用。
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