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Stop Losses: Help or Hindrance? [Part 2 of 3]

  • Written by Syndicated Publisher No Comments Comments
    April 26, 2011

    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.

    By Dr. Bruce Vanstone

    BackgroundBruce Vanstone is Assistant Professor at Bond University in Australia. He completed his PhD in Computational Finance in 2006 and is a regular presenter and publisher of academic work on stockmarket trading systems. He teaches stockmarket trading courses, and consults to Porter Capital Management on the design of mechanical, rules-based trading systems. More information on Bruce’s research and methods can be found athttp://trading.it.bond.edu.au.

    Bruce has a controversial view on the effectiveness of stop losses and I have asked him to write a series of articles based on his research.

    ~ Colin Twiggs

    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).

    AMP With 5% Trailing Stop

    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

    Trailing Percentage Stop 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

    Trailing Percentage Stop 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).

    ANZ With 2xATR Stop

    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

    ATR Stop 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

    ATR Stop 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.

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