In today’s blog post we continue our exploration of trade management techniques and their impact on your bottom line. You can find the basic notions of trade management here, and a discussion regarding style and objectives here.
In today’s post we are bringing fourth some cold hard data generated by using a simple setup (Low-Volatility Breakouts) on a combination of FX Majors, Crude Oil and Dow and applying 5 different management techniques on the same trades.
If you were wondering just how influential trade management techniques can be, then read on. You just might be surprized.
The Low Volatility Breakout
Before digging into the discussion on trade management, we still need to be reminded how all components of the trading process are important:
- instrument selection (what you’re trading and why)
- low-risk/high potential reward setup
- your trade management vehicle
When thinking about trading, we do need to remember that we are essentially “timing” the market and as such, we’re either good with our timing, or we should do something better with our time. Being good with your timing means that you have studied, and are exploiting some kind of behaviour that gives you an advantage. The market should move in your favour more often than not, before it starts to move against you. Setups and triggers should be low-risk/high potential reward opportunities that make your efforts “efficient”. But this is not the time to digress on the concept of setup efficiency. We have illustrated this in-depth in Lesson #9 of the Advanced Course for Smart Traders (Damn Good Forex Setups).
In our simulation we’re using a simple dynamic: the fact that price volatility is cyclical, and periods of high volatility are followed by periods of relative calm. These periods of calm tend to forewarn of future higher volatility and strong moves, which is what we are trying to leg into as soon as the market “breaks out” of the consolidation phase.
Test #1 – Does the Low-Volatility Breakout Provide an Edge
I need to emphasize that all the subsequent data was produced by the hard work of our programmer, Tony Shacklock. If you ever have any questions or want any ad-hoc tests done in MT4 or Ninjatrader environments, please feel free to write him at [email protected]
The results above are derived from a brutal “systematic” application of the Low-Volatility Breakout filter on:
on Daily Charts from 2007 to 2018 with an initial stop loss of 0.8x7Day ATR. You may ask how we chose this precise stop loss value. The answer is simple and comes from an investigation of the MAE/MFE conditions of the trigger day.
There are outliers that appear arond the 0.8 ATR mark so that’s where we drew the line.
The dark blue line is the basic test to see whether the low-volatility breakout has an edge or not, if applied systematically across the selected assets. The dark blue line is simply closing the trade at 1R. Evidently the Low-Volatility Breakout is a concept that works, although without any filters, it’s performance is not great, if adjusted for risk.
From this basic no-filter test, we can see a few things:
- Taking profit at 2R, despite being advantageous on paper, isn’t feasible in real life without additional filters. This gives more substance to our argument from the first article in this series: set & forget might help overcome psychological biases that usually work against us, but we cannot count on the mathematics of risk:reward alone if we want to profit in the markets. In reality, positive results over time are a product of market type + risk:reward + win rate.
- The best management techniques for the low-volatility breakout seem to be trailing stops and not fixed targets. And this dynamic is evident even without filtering for market type! So the low-volatility breakout does in-fact allow traders to leg into fresh trending markets.
- Without filtering for market type, the risk-adjusted return of all management methods is quite low, because drawdowns are high and the volatility of the equity curve is simply too high.
Test #2- Do Trending Markets Provide an Ideal Environment
This is where we started to discover some dynamics that are curious:
- Yes, trend filters do enhance the risk-adjusted performance of the Low-Volatility Breakout model
- There is a “sweet spot” for defining a trend that compliments the Low-Volatility Breakout.
We tried using a Monthly Market Type Filter down to a 30Day Simple Moving Average Filter and some other iterations in between. What we found is that anything above a Weekly Market Type and anything below 30 Days don’t really help the model.
The chart above shows the results when applying the Low-Volatility Breakout only when the Weekly Market Type is bullish or bearish. The results are imemdiately visible: the 1R target as well as short-term trailing stops and momentum measures start to lag the performance of a 2R target and the Supertrend Trailing Stop (2,7) which is the most conservative of our management methods.
The even more interesting “sweet spot” was the CTA-style 3-month lookback. By using the slope of a 60 Simple Moving Average, all management models produce decent risk-adjusted results and the more aggressive trailing stop (2-bar) actually performs just as well as the more conservative SuperTrend Trailing Stop (2,7).
The results are clear:
- When using a Trend Filter, a trailing stop is the more logical approach and outperforms 1R take profits.
- The sweet spot seems to be anywhere between 50 and 100 days worth of history in order to gauge a “trend context”.
- The risk-adjusted returns are already viable and robust.
Discussion on the Different Management Techniques
Fortunately our logic and testing produced viable results – something we didn’t know beforehand as we went on this scientific exploration! (Once again thank you Tony for the hard work!).
Now we can explain the management styles we selected for the Low-Volatility Breakout. In following the logic outlined in the previous blog post, we attempted to use methods that would maximize momentum runs and trending runs, beyond the normal default 1R and 2R take profit levels.
Examples of Low Volatility Breakouts with 1R Targets
The default test was done with a 1R take profit. And unsurprizingly, the results are positive but underwhelming. The results are positive most likely because the low-volatility setup is strong, but without any further filters the setup could happen in rangebound markets and thus, the results show that it’s best to capture 1R and get out.
Examples of Low Volatility Breakouts with 2R Targets
Going for 2R also doesn’t need much of an explanation. We’re trying to see whether the “set & forget” style, with an advantageous risk:reward ratio will get the job done. It doesn’t, unless you also filter for market type. But if you filter for market type, there are even smarter ways to go about your management.
Examples of Low Volatility Breakouts with Momentum 2 Management
The first experiment we did was aimed at capturing the initial boost of momentum that the low-volatility breakout provides. We told the system to exit any trades when the day showed slowing momentum. To us that means ATR < 80% of it’s 7-day average value and/or a neutral close.
As it turned out, we were simply too clever for our own good. The management style is simply too quick and exits trades prematurely, most of the time.
Examples of Low Volatility Breakouts with 2-Bar high/low Management
The second method turned out to be a bit smarter. It’s a variation of a trailing stop which follows momentum along with market structure. We trail the stop below 2-bar highs (if selling) or 2-bar lows (if buying) and the stop is trailed ONLY if we make new highs. Essentially we’re trailing the stop but at the same time trying not to give too much back when the market starts to run out of steam.
This turned out to be quite a decent management technique that gave some of the best risk-adjusted returns of all models.
Examples of Low Volatility Breakouts with the Supertrend Trailing Stop (2,7).
We have spoken extensively about the benefits of a trailing stop here and here and here
Essentially the trailing stop is the go-to indicator for milking trends but it does tend to give a decent amount of profit back to the market when the trends only last for short periods of time.
Without out a doubt, trade management makes a huge difference. It can transform a volatile equity curve into a viable risk-adjusted curve. However, it takes experience to know where to look and what venues to explore, and this is the “art” of trading. There are always trade-offs to consider and without a tad of experience, it is difficult to not get blinded by rogue results.
One thing is clear: you cannot just take a setup and apply it everywhere. Through diversification, you might get lucky and stay afloat – but the odds are stacked against you.
We have found out that there are “sweet spots”…there are some combinations of market type, setup and management that go hand-in-hand and this means that if you are trading your own setups, it’s up to YOU to find out what feels right and what compliments your model the most. At a very basic level, fixed targets will work more for range-bound models and trailing stops will work better for trend-following models but those are only principles – it’s up to YOU as a trader and as the developer of your system, to know where to look.
In the matter of Low-Volatility Breakouts on a Daily chart, we seem to have found a combination that, at least at a first glance, is robust:
- Filter a trending market either by using a weekly momentum market type indicator or the slope of a 60 SMA.
- Deploy the Low Volatility Breakout on markets that tend to trend.
- Manage the trades with either a SuperTrend Trailing Stop (2,7) or via a 2-bar high/low.
About the Author
Justin is a Forex trader and Coach. He is co-owner of www.fxrenew.com, a provider of Forex signals from ex-bank and hedge fund traders (get a free trial), or get FREE access to the Advanced Forex Course for Smart Traders. If you like his writing you can subscribe to the newsletter for free.
The post How to Manage Your Trades Part 3: Managing Low Volatility Breakouts appeared first on FX Renew.