In this paper, we propose a method for evaluating autonomous trading strategies that provides realistic expectations, regarding the strategy's long-term performance. This method addresses This method addresses many pitfalls that currently fool even experienced software developers and researchers, not to mention the customers that purchase these products. We present the results of applying our method to several famous autonomous trading strategies, which are used to manage a diverse selection of financial assets. The results show that many of these published strategies are far from being reliable vehicles for financial investment. Our method exposes the difficulties involved in building a reliable, long-term strategy and provides a means to compare potential strategies and select the most promising one by establishing minimal periods and requirements for the test executions. There are many developers that create software to buy and sell financial assets autonomously and some of them present great performance when simulating with historical price series (commonly called backtests). Nevertheless, when these strategies are used in real markets (or data not used in their training or evaluation), quite often they perform very poorly. The proposed method can be used to evaluate potential strategies. In this way, the method helps to tell if you really have a great trading strategy or you are just fooling yourself.
翻译:在本文中,我们提出了一个评估自主贸易战略的方法,该方法为该战略的长期业绩提供了现实的预期。该方法针对的是目前愚昧的、甚至有经验的软件开发者和研究人员的很多陷阱,更不用说购买这些产品的客户了。我们介绍了将我们的方法应用于几个著名的自主贸易战略的结果,这些战略用于管理多种多样的金融资产选择。结果显示,这些公布的战略中有许多远非金融投资的可靠工具。我们的方法暴露了制定可靠、长期战略的困难,并提供了比较潜在战略并选择最有希望的战略的手段,为测试处决规定了最短的期限和要求。许多开发者创建了自动买卖金融资产的软件,其中一些在模拟历史价格序列(通常称为背数)时表现很好。然而,当这些战略在实际市场(或培训或评估中未使用的数据)使用时,这些战略往往表现很差。拟议的方法可用于评估潜在战略。这样,这种方法有助于说明你是否真的拥有伟大的贸易战略或只是愚弄自己。