介绍
本文我将引进蒙特•卡罗方法，并展示我们将如何利用它加强我们关于不同类型止损的认识。
蒙特•卡罗分析法
根据定义，投资组合是根据信号下单的交易集合。投资组合中交易数量通常小于最大可交易数量，这通常和交易者如何管理资金有关。因此，一个投资组合具有特定的资金量对于检测投资组合效益很有必要。资金量和资金管理方式细微差异所对应的投资组合都有所不同。
假设一位交易者的资金为$10,000，有时两只股票同时给出买卖信号，这中情况下将会如何呢？很明显，只有一只股票的信号会被成功执行。但会是哪一只呢？随着时间的推移，这两只股票可能有两种不同的结果：比如，一只上升，另一只下降。
当运行投资组合的时候，同时出现多个交易信号的情况很常见，尤其是在趋势交易中。同样，当交易信号发出而交易者没有资金去支持该交易，结果将会怎样？当然是跳过该信号。为了便于充分认识交易信号被跳过和成功执行的含义，定量分析师会借助蒙特•卡罗分析法。它可以得出所有互相独立的投资组合的结果概率。
比如上文中所举的例子，我们想知道在资金只支持一次交易的情况下，要如何模拟两种交易信号下投资组合的可能结果？根据数学计算方法，理论上我们这时面对着两种投资组合，每种投资组合只有一只股票。从这一逻辑来看，经过一段时间之后，实际上已经产生了大量的投资组合（基于交易者的不同选择），所有的这些组合都有可能是最终的结果。
为了充分的评估止损的作用，我们不仅要模拟一种投资组合的结果（正如我们之前做的那样），而是要把所有的理论结果都展现出来。这里，我们可以利用蒙特•卡罗方法反映不同投资组合的回报概率。
下面图片分别显示原始交易收益的概率分布和1000种无止损情况下投资组合的最大亏损。1000种投资组合的最小、平均和最大收益显示在相应的图表下方。
最小收益 =-17.32%, 平均收益 = 11.66%, 最大收益 = 43.82%
最小亏损率 = -30.00%, 平均亏损率 = -44.44%, 最大亏损率 = -53.21%
结果
下图是1000种可能的投资组合结合25种止损后的平均收益和最大亏损率。
启示
上面的图表显示，1000种可能的投资组合中，无止损的收益是最大的。同时，基于平均真实波幅(ATR)止损的投资组合收益低于所有百分比止损的投资组合收益。因此，无止损情况下的投资组合可以提高收益。
结论
一些交易者似乎在利用止损为自己提供心理安慰。如果在你测试过自己的交易系统之后仍然觉得自己无法离开止损，那么你必须继续使用止损。也许，你可以考虑一下将止损的范围设置得大一些。然而，许多交易者认为止损是万能药。事实证明，止损会加速投资者交易的失败，同时是导致交易组合表现不理想的原因所在。
止损不利于交易的原因之一可能是许多止损都是同时被触发。这通常是由于整体市场的影响，而不是股票所在公司的变化。
Stop-Loss Orders: Help or Hindrance? [Part 3 of 3]
Monte-Carlo Analysis
By definition a portfolio is a subset of the raw trades signalled by the entry and exit rules. The most common reason that a portfolio usually has less trades than the total possible relates to the way the trader/investor manages money, and that is why it is important to test a portfolio with a specific amount of capital. Different amounts of capital (and money management approaches) can give rise to different possible portfolios.
Consider a trader/investor who invests his/her money in multiples of $10,000 according to the above buy/sell rules. What will the trader/investor do if 2 stocks are signalled on the same day, yet the trader/investor only has $10,000 left? Clearly, only 1 trade can be taken, but which one?
It may well be that over time the two trades have very different outcomes. For example, one goes up, and one goes down!
When running a portfolio, the issue of having more trading opportunities than money can occur reasonably frequently, particularly in a trend-trading approach. Again, in the above example, what will the trader/investor do on the next day, when yet another trade is signalled, and there is no money left to take it. Of course, it must be skipped from the portfolio.
To fully understand the implications of taking and skipping certain trades, quantitative analysts may resort to Monte-Carlo modeling, which allows us to build a probability outcome of all the possible portfolios which could have been built dependent on the decisions the trader/investor took.
As an example, in an earlier paragraph we wondered how to model the portfolio outcome when there were two possible trading candidates but only enough money to take 1 trade. The solution using computational mathematical methods is that from this point forward, there are now two theoretical portfolios � one with each possible stock in it. Following on from this logic, you can see that over a period of time, there could actually be a great number of possible portfolios, all dependent on the decisions taken by the individual trader/investor. All of these portfolios would be real possible outcomes, totally dependent on the choices made by the trader/investor on a day to day basis!
To assess the impact of stops completely, we need to consider not just one simulated portfolio outcome (as we did earlier), but a large number of the possible theoretical outcomes. We can approach this using the Monte-Carlo methodology, and determine the probability of various return and drawdown outcomes.
The following figures show the probability distributions for the Raw Return (aka Net Profit) and the Maximum Drawdown metrics for 1000 of the possible 'NO STOP LOSS' portfolios. These provide the benchmark for this final piece of analysis. Under each figure, I have also included the smallest, average and largest values obtained from the 1000 simulations.
Smallest =-17.32%, Average = 11.66%, Largest = 43.82%
Smallest = -30.00%, Average = -44.44%, Largest = -53.21%
Outcomes
The following table shows the average values for both the Net Profit % (not the APR%), and the Maximum Drawdown % for 1000 possible portfolios for each of the 25 stop combinations tested.
Implications
From inspection of this table, we can see that there was no set of 1000 possible portfolios more profitable than the 'NO STOP LOSS' combinations. We can also see the ATR based stop methods have performed quite poorly compared to nearly all of the simple percentage based stop methods. In summary, no combination of stops was able to improve on the basic strategy without stops.
Conclusion
Some traders appear to use stops to provide a level of comfort about the risk they take with their trading. If you feel you absolutely cannot live without stops, even after performing similar tests to these on your own system, you must, of course, continue using them. Perhaps you could even consider simply making them wider.
However, many traders and investors appear to view the stop loss order as a panacea. These empirical results show that the stop loss order may actually be contributing to the poor performance of some traders, and may even be the cause of their lower than expected returns.
One of the reasons that this behavior may be occurring is that many stops are being hit at the same time. This is more likely due to changes in the overall market rather than having any specific relationship to changes in some particular company share price.
I have seen similar results in the past when testing stop orders against long-only, equity based, trend-following types of systems.
If your trading style is best described by phrases like "long-only", "equity based", and "trend-following", and you use stop-loss orders, then you may wish to consider testing your trading rules to see if the stops are actually helping or hindering your performance. You can follow the procedure outlined in this series of articles, and in my book, Designing Stockmarket Trading Systems (with and without soft computing), to help you do this.
Forum Discussion
We hope you find this series of articles interesting. There is a thread on the forum where readers can contribute their views: Do Stop Losses Really Work?
Regards,
Colin Twiggs
本文翻译由兄弟财经提供
文章来源：http://www.incrediblecharts.com/trading/stoploss-trading-3.php