如何使用 Williams %R 交易期货

在本文中,我们将评估交易领域最著名的指标之一的使用:“威廉姆斯百分比范围”,也就是众所周知的“%R”。...

在本文中,我们将评估交易领域最著名的指标之一的使用:“威廉姆斯百分比范围”,也就是众所周知的“%R”。

Larry Williams 基于随机指标开发了 Williams %R。虽然随机指标使用收盘价与 n 个周期的最低低点之间的差值,但收盘价与 n 个周期的最高高点之间的差值(其中 n=14 被认为是理想值)用于计算威廉姆斯 % R。然后 %R 会在 0 到 100 的范围内波动(但在某些情况下,它会在 -100 到 0 的负范围内计算)。

一些交易者使用该指标来确定市场何时处于超卖或超买状态,当然还有趋势反转。作者将超买条件的阈值设置为 80(负比例时为 -20),将超卖条件的阈值设置为 20(-80)。

然而,在振荡器的日常使用中,会出现许多错误信号。在本文中,我们将研究是否可以针对高度多样化的期货投资组合优化 Williams %R 参数,以用作自动化策略(交易系统)的启动脚本。

图1

战略

我们将使用的策略是基于“均值回归”方法的传统系统,即我们将利用 %R 的两个阈值作为市场的反转点。我们将等到价格超过超卖阈值 (20),然后在震荡指标再次从下行到上行穿过该水平时做多。相反,如果震荡指标再次从上行到下行穿过该水平,我们将在价格超过超买阈值 (80) 后做空。

由于这是一种“均值回归”策略,因此从一开始就使用止损是有利的,这可以在一定程度上保护我们免受过度的资本损失。止损计算为最后 5 个柱的平均波动率除以 1.5(通过初步优化获得的值),以便获得的参数对于相关投资组合的所有基础资产尽可能一致。

在此示例中,我们将在 1440(分钟)的时间范围内测试该策略,代表调整到最后市场价格的每日柱形图,以了解以下期货在 2010 年至 2022 年期间的表现:



  • 原油 (CL)

  • 标准普尔 500 (ES)

  • 纳斯达克 (NQ)

  • 达克斯 (FDAX)

  • 黄金 (GC)

  • 活牛 (LC)

  • 饲养牛 (FC)

  • 大豆 (S)

  • 30 年美国国库券(美国)

  • 小麦 (W)

  • 英镑 (BP)

  • 外滩 (FGBL)

  • 铜 (HG)

  • 取暖油 (H2O)

  • Natural Gas (NG)

  • RBOB Gasoline (RB)

  • EuroFX (EC)

In Figures 2 and 3, we can estimate the metrics obtained with the reversal strategy in terms of %R. The results are quite encouraging with a rising equity line, which is a good starting point, but we can see that this hasn’t been consistent over the years either. For example, the significant drawdown from 2020 onwards shows that the strategy needs to be refined.

Figure 2

Figure 3

Looking at the results for the individual markets, we see that only 6 of 17 markets suffered losses.

A downer, however, is the average total trade, which only reaches $23. This isn’t enough to make the system usable for live trading, as commission costs and slippage would completely consume it. It’s, therefore, necessary to at least tweak the indicator’s parameters to see if there’s room for improvement.

优化

因此,让我们尝试通过干预指标来改善策略的平均交易量。具体来说,我们将优化超买和超卖水平,以查看作者建议的值(80 和 20)是否是寻找趋势反转区域的最佳值(因为我们选择了均值回归策略)。

从图 4 所示的优化结果中,我们看到 25-85 组合持续提高了净利润(371,483 美元)和平均交易量(超过 50 美元),同时降低了最大投资组合回撤。

图 4

系统的公平性有所提升,但如果不做进一步的调整,系统仍然不能说是可交易的。

当尝试输入止盈时,它也是根据最后 5 根柱线的平均波动率乘以乘法因子计算得出的,该因子的最佳值通过优化为 1.5 找到(巧合地与止损相同)。

图 5

此时,净值线更加稳定(见图 5),净利润升至 40.7228 美元,平均交易额升至 57 美元,而最大回撤降至更可接受的值,尽管该策略在实时可用时仍然很高贸易。

结论

In summary, %R, optimized in its parameters for this specific portfolio and time frame, has shown that it can be a valuable tool for systematic trading. However, the strategy presented here needs further refinement. For example, the average trade value is still relatively low. However, the large number of trades would make it possible to use additional filters for the entries and try to eliminate the less profitable ones.

Generally, achieving a very high average trade value with such a diverse and diversified portfolio is still challenging. However, one could try to isolate trades only on days when a particular price pattern occurred, thus avoiding taking a position when the conditions are unfavorable for the trend reversal that the strategy seeks to achieve.

Finally, it should be noted that the %R value is excellent for identifying bullish and bearish divergences. A bearish divergence occurs when prices reach new highs while the oscillator indicates falling highs. Conversely, we see a bullish divergence when prices mark new lows while the oscillator shows rising lows. Tracking divergences could be another idea to work on to filter trades and improve the system.

I hope you have gained some interesting insights from the above. I recommend you always to be curious and open to testing new ideas.

© 2022 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

然而,在振荡器的日常使用中,会出现许多错误信号。在本文中,我们将研究是否可以针对高度多样化的期货投资组合优化 Williams %R 参数,以用作自动化策略(交易系统)的启动脚本。

Source: https://www.benzinga.com/news/22/09/28823363/how-to-trade-futures-using-williams-r

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