突破交易策略的附加限制条件

Cristian Păuna
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引用次数: 2

摘要

金融市场中最流行的交易方法之一是海龟策略。1983年中期,理查德•丹尼斯(Richard Dennis)和比尔•埃克哈特(Bill Eckhardt)争论伟大的交易员是天生的还是后天养成的,此后很久就过去了。为了决定这个问题,他们招募并培训了一些交易员(海龟),给他们真实的账户和完整的交易策略,看看哪个想法是正确的。这是一种突破交易策略,意味着他们在价格超过20天或50天的最高价时买入,在价格低于同一区间的最低价时卖出。从那时起,金融市场发生了许多变化。电子交易被广泛发布,金融交易已成为人人都能接触到的。算法交易成为交易决策系统的重要组成部分,高频交易将当今金融市场的波动性推向了新的难以置信的极限。智能电脑使用先进的数学算法,几乎可以即时生成并发送订单。随着所有这些变化,今天有许多关于突破策略的问题。Turtle规则仍然有效吗?海龟策略如何在算法交易中实现自动化?其结果是否可与其他现代交易策略相比较?本文将通过对这一制度的历史和规则的简要介绍,为这些问题找到一些答案。我们将揭示一种自动化突围策略的方法。更多不同的交易策略源自海龟规则将被提出。建立交易信号的数学模型将被描述,以使交易过程自动化。当与现代极限条件相结合时,发现所有这些规则都具有正期望。本文还将包括用所提出的方法获得的交易结果,以便比较和分析这种特别适用于算法交易的资本投资方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Additional Limit Conditions for Breakout Trading Strategies
One of the most popular trading methods used in financial markets is the Turtle strategy. Long time passed since the middle of 1983 when Richard Dennis and Bill Eckhardt disputed about whether great traders were born or made. To decide the matter, they recruited and trained some traders (the Turtles) and give them real accounts and a complete trading strategy to see which idea is right. That was a breakout trading strategy, meaning they bought when the price exceeded the maximum 20 or 50 days value, and sold when the price fell below the minimum of the same interval. Since then many changes have occurred in financial markets. Electronic trading was widespread released and financial trading has become accessible to everyone. Algorithmic trading became the significant part of the trading decision systems and highfrequency trading pushed the volatility of the financial markets to new and incredible limits nowadays. The orders are built and sent almost instantly by smart computers using advanced mathematical algorithms. With all these changes there are many questions today regarding the breakouts strategies. Are the Turtle rules still functional? How can the Turtle strategy be automated for algorithmic trading? Are the results comparable with other modern trading strategies? After a short display of the history and the system’s rules, this paper will find some answers to all these questions. We will reveal a method to automate a breakout strategy. More different trading strategies originating from the Turtle rules will be presented. A mathematical model to build the trading signals will be described in order to automate the trading process. It was found that all of these rules have a positive expectancy when they are combined with modern limit conditions. The paper will also include trading results obtained with the methods presented in order to compare and to analyze this capital investment methodology adapted especially for algorithmic trading.
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