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首页> 外文会议>IEEE Congress on Evolutionary Computation >Better trade exits for foreign exchange currency trading using FXGP
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Better trade exits for foreign exchange currency trading using FXGP

机译：使用FXGP进行外汇货币交易的更好的交易退出

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摘要

Retracement is the tendency of markets to move between upper `resistance' and lower `support' price levels. Human traders frequently make use of visual tools to help identify these resistance and support levels so that they can by used in their trading decisions. These decision can be put into trading strategies composed of rules designed to mitigate losses after a trade is started, often called `stop loss' orders, or to take profit at a near optimal time, often called `take profit' orders. However, identifying such resistance and support levels is notoriously difficult given market volatility. Indeed, the levels need recalculating on a continuous basis, and only hold to an approximate degree. In this work we describe an approach for evolving buy-stay-sell currency trading rules using genetic programming. These rules are explicitly linked to technical indicators that incorporate features characterizing retracement. Benchmarking is then performed using the most recent three years of data from the EURUSD foreign exchange market with three different methods of identifying retracement based on moving average, pivot points and Fibonacci ratios. Investment strategies employing Fibonacci ratios and found to provide superior performance among the strategies examined.
机译：回撤是市场在较高的“阻力位”和较低的“支撑位”价格水平之间移动的趋势。人类交易者经常使用视觉工具来帮助识别这些阻力和支撑位，以便他们可以在其交易决策中使用。可以将这些决定放到交易策略中，这些策略由旨在减轻交易开始后的损失（通常称为“止损”订单）或在接近最佳时间获利（通常称为“获利”订单）的规则组成。但是，鉴于市场动荡，要确定这样的阻力和支撑位是非常困难的。实际上，需要连续不断地重新计算级别，并且只能保持近似的程度。在这项工作中，我们描述了一种使用遗传程序制定不断发展的买卖货币交易规则的方法。这些规则明确链接到技术指标，这些指标包含表征回撤的特征。然后使用来自欧元兑美元外汇市场的最新三年数据，通过基于移动平均线，枢轴点和斐波那契比率的三种不同的回撤方法来进行基准测试。采用斐波那契比率的投资策略，在所考察的策略中表现出优异的表现。

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