止损: 帮助还是阻碍？ [2 / 3]

简介

在本文中，我将继续以60日指数移动平均数指标为基准，并与其引入百分比止损、基于ATR（真实波动幅度均值）追踪止损之后的结果相比较。

百分比跟踪止损

许多交易者和经纪商使用最初的百分比止损和百分比跟踪止损来管理自己的仓位。比如，一个交易者或许会说，“我将在开仓价位下方5%处设置止损，并把跟踪止损设置为前一日收盘价下方的5%处”。这里，我们将会把1%-10%的止损百分比引入60日指数移动平均数指标来测试这一方法。下图中绿色的点表示百分比跟踪止损，粉红色线为EMA（60）的值。

                                                                                                利用 5%跟踪控制止损价
1%~10%跟追止损对于单子的获利和风险的影响如下：
原始交易

 
上面图表很清楚的显示，跟踪止损没有提高无止损情况下的日均收益。这符合我们的预期，因为根据定义，止损包括亏损平仓。为了确认止损是否可以减小投资组合中的风险，我们做了下面测试。

投资组合

 
百分比跟踪止损同样没有提高无止损情况下的年收益率。同时，无止损可以提高夏普比率。所有加入追踪止损的60日指数移动平均数指标所得收益都降低，并且有较大风险性。

启示

为了便于对比投资组合结果，我们使用方差分析法。这样我们就可以同时比较无止损情况下的交易结果与结合百分比止损之后的交易结果。这将有助于确定我们统计数据的重要性。结果显示，结合1%~10%止损之后的60日指数移动平均数指标并没有好的表现。本文我特地省略了使用方差分析法的具体细节。感兴趣的读者可以参阅我的书籍《股票交易系统设计（有无软计算）》并从中找到别的有效分析方法。

基于ATR指标的止损

许多交易者仅仅根据ATR指标（平均真实波幅）来确定止损价位。比如，一个交易者或许会说，“我会根据5日ATR指标的2倍来设置止损”。为了论证这种方法的实用性，我将其设置为跟踪止损以锁定盈利。这也是许多交易者使用的典型方法。下图中绿色点表示基于ATR指标的跟踪止损，粉色线显示了EMA（60）的值。

 
                                                                                              Figure 3: 根据2 x ATR(5)设置止损
原始止损对于交易发收益和风险的影响如下所示：

原始交易

上图中数据很清楚的显示，无止损的日均回报是最高的。这符合我们的预期，因为根据定义，止损包括亏损平仓。为了确认止损是否可以减小投资组合中的风险，我们做了下面测试。

投资组合

上图显示，止损不仅没有提高交易的年收益率，而且也没有提高夏普比率。一些较高止损百分百的最大亏损与无止损情况相似。实质上，结合止损之后的交易的回报率都有所降低，并且风险较高。

启示

同样，我们也可以使用方差分析法来确认我们统计数据的重要性。结果显示，止损百分比并没有让我们提高盈利。

结论

本文中，我将60日指数移动平均数指标与不同的止损方法（百分比跟踪止损和基于ATR跟踪止损）相结合的结果进行测试。结果显示，所有测试的止损都增加了原始交易的风险性并减少了投资回报。

Stop-Loss Orders: Help or Hindrance? [Part 2 of 3]
By Dr. Bruce Vanstone
Introduction
This article is part 2 of a 3 part-series on stops. In this article, I continue testing and benchmarking the original EMA crossover strategy by adding in percentage-based and ATR-based trailing stops.
Trailing Percentage Stops
Many traders and brokers use an initial percentage stop and a trailing percentage stop to manage their positions. As an example, a trader might say, "I will set a stop loss 5% below my entry price, and then trail it 5% below the previous days closing price as the trade progresses". Here, we test this method using percentage thresholds from 1% - 10% in steps of 1, for all the trades generated by the ema crossover rules.
An example is shown in Figure 2. The green dots show the position of the percentage-based trailing stop, and the pink line shows the value of the EMA(60).
Figure 2: Percentage trailing stop (5%) used for controlling the stop loss price
The impact that these percentage trailing stops have on both return and risk is presented next.
Raw Trades
From the table presented, it is clear that none of the stop methods tested improved the 'NO STOP LOSS' portfolio's daily mean return. This is as expected, given that, by definition, an initial stop loss rule entails selling at a loss. To determine whether this approach has decreased our risk, we next test within a portfolio setting.
Portfolio
From this table, we can see that none of the stop methods have improved the 'NO STOP LOSS' portfolio's APR. Further, none of the stop loss settings was able to improve the Sharpe Ratio. Again, all combinations of stop loss tested achieved less return, and were riskier.
Implications
To statistically compare the portfolio results, we can use the ANOVA procedure, which allows us to simultaneously compare all the trades generated under the 'NO STOP LOSS' condition, with all the sets of trade possibilities from the 10 stop loss combinations. This allows us to determine whether there is any statistical significance in our findings.
The results indicate that no benefit has been obtained from any of the stop combinations. I have purposefully omitted a detailed explanation of using the ANOVA procedure in this article, to allow us to keep focused on the effects of stop losses. As mentioned earlier, those readers interested in pursuing the benchmarking of trading systems using statistical methods can find all the details in my book, Designing Stockmarket Trading Systems (with and without soft computing).
ATR-based Stops
Many traders simply use a multiple of the ATR (Average True Range) to determine their stop level price. As an example, a trader might say, "I will set a stop loss 2 times the 5-day ATR below my entry price". To demonstrate the versatility of this technique, I have implemented this as both an initial ATR stop, and then allowed it to become a trailing stop as the trade moves into profit. This is typical of the way many retail traders manage their ATR based stops.
An example is shown in Figure 3. The green dots show the position of the ATR-based trailing stop, and the pink line shows the value of the EMA(60).
Figure 3: ATR stop (2 x ATR(5)) used for controlling the stop loss price
The impact that these initial stops have on both return and risk is presented next.
Raw Trades
From the table presented, it is clear that none of the stop methods tested improved the portfolio's return. This is as expected, given that, by definition, an initial stop loss rule entails selling at a loss. To determine whether this approach has decreased our risk, we next test within a portfolio setting.
Portfolio
From this table, we can see that none of the stop methods have improved the 'NO STOP LOSS' portfolio's APR. Further, none of the stop loss settings was able to improve the Sharpe Ratio. Again, all combinations of stop loss tested achieved less return, and were riskier.
Implications
Again we can use the ANOVA procedure to determine the statistical significance of these results. The results indicate that no benefit has been obtained from any of the stop combinations tested.
Summary
In this article, I have continued testing different types of stops to see if they can improve the original EMA crossover strategy. This time I have tested percentage-based trailing stops, and ATR-based trailing stops. It was found that all stops tested increased the risk and reduced the return of the original strategy.
In the next article, I will demonstrate the Monte-Carlo technique and show how it can provide additional insights into the use of stops.

文章翻译由兄弟财经提供

文章来源：http://www.incrediblecharts.com/trading/stoploss-trading-