Algorithmic Decision-Making Framework

R. Kissell, R. Malamut
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引用次数: 28

Abstract

The emergence of algorithmic trading as a viable and often preferred execution mechanism has created a need for new suites of trading analytics to assist investors compare, evaluate, and select appropriate algorithms. Unfortunately, many of the existing algorithms do not provide necessary transparency to make informed trading decisions. In this paper we provide a dynamic algorithmic decision making framework to assist investors determine the most appropriate algorithm given overall trading goals and investment objectives. The approach is based on a three step process where investors choose their price benchmark, select trading style (risk aversion), and specify adaptation tactic. The framework makes extensive use of the Almgren & Chriss (1999, 2000) efficient trading frontier.
算法决策框架
算法交易作为一种可行的、通常是首选的执行机制的出现,创造了对新的交易分析套件的需求,以帮助投资者比较、评估和选择合适的算法。不幸的是,许多现有的算法不能提供必要的透明度来做出明智的交易决策。在本文中,我们提供了一个动态的算法决策框架,以帮助投资者在给定的总体交易目标和投资目标下确定最合适的算法。该方法基于投资者选择价格基准、选择交易风格(风险规避)和指定适应策略的三步过程。该框架广泛使用了Almgren & Chriss(1999,2000)的有效贸易边界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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