How To Manage Your Trades Part 1: Basic Notions

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Most retail traders are focued on finding the “right strategy” which usually boils down to “the best entry”. However, the entry is just one component of a trading model and it sits between more important components such as identifying the proper market conditions and managing the trade once it’s live. The truth is that most traders study their entries for hundreds of hours, yet have no idea what to do once the trade is live.

Without structuring proper trade management decisions, you will be left at the mercy of your emotions and typically commit some (or all) of the following mistakes:

  • moving your stop loss to breakeven “ASAP”;
  • holding a losing trade and taking profit as soon as it turns around in your favour;
  • getting stopped out prematurely, only to see the market continue in your intended direction;
  • closing bits & pieces of your position as the market moves in your favour (scaling out);
  • not really knowing what kind of market behaviour would suggest a need to interveine;
  • etc…

If you find yourself suffering from any of the following symptoms, then read on. This is the first installment in a series called “How to Manage Your Trades”. In this series we will attempt to build a knowledge base that will help you build your trade management vehicle from the ground up.

Why You Need to Manage Your Trades

In the largest study of retail trader habits that I’ve found on the web, the guys at DailyFX used 1 year of data (over 40Mln trades) from FXCM retail trader accounts to uncover common retail trader issues. Their results clearly highlight the fact that most retail traders have no idea how to manage their trades and are in fact prone to emotional decisions.

First things first: we all like to win. However, trading is not about winning; it’s about making sure your wins are much bigger than your losses, on average. Trading is about thinking in bets as Sam Elhelou pointed out on our recent webinar. Without knowing what to do once a trade is live, we are all at the mercy of our emotions.

Hence, most retail traders want to obtain a high win rate which caters to the natural human tendency to be uncertainty-adverse and loss-adverse. The typical example that illustrates this tendency is the following question:

Which situation would you prefer?

  • A 50% chance to win $100 and a 50% chance of winning $0.
  • A 100% chance to win $45.

Most people select the second situation: the certainty of winning $45, despite the fact that the expectancy of the first situation is advantageous over time ($50).

Again, which situation would you prefer?

  • A 50% chance of losing $100 and a 50% chance of losing $0.
  • A 100% chance of losing $45.

Here instead, people tend to choose the first option, despite having a lower expectancy over time (-$50).

Human nature tends to make us risk-adverse when taking profit, but we become risk-seeking if there is a chance of avoiding a loss. 

This is how our natural tendencies are displayed in practice.

Retail traders tend to have high win rates on their trades (which is psychologically pleasing) but the average loss is much larger than the average gain.

So we need to have a fail-safe in place, that can protect us from our own tendencies. The most evident fail-safe is a positive risk:reward ratio. It’s also one basic component of trade management, which essentially says:

don’t fiddle with the trade unless you get a profit which is at least as large as your risk on any given trade.

In the same study on FXCM clients, the data shows that 53% of traders which used at least a 1:1 risk:reward ratio were profitable over the observation period. On the contrary, only 17% of the traders that had unfavourable risk:reward ratios   were profitable over the same period.

The message is clear: we need to have clear rules to manage our trades, else we will be overcome by our natural tendency to take quick profits and hang onto losses hoping that they will reverse.

In this screenshot, Oanda’s Open Order Indicator allows us to see current client positions. 60% of clients are long into the decline and most are holding long positions (without a hard stop loss) from 200-300 pips higher up.

Bottom line: we have a need for solid trade management practices!

Set and Forget?

The evidence we have up till now is clear:

  • without having a clear plan, we will make emotionally-driven decisions;
  • without obtaining at least a 1:1 Risk:Reward ratio, we will probably lose money over time.

The first thing most traders do to overcome these issues is simply adopt a passive approach to trade management: the set & forget stance. Once the trade is live, the trader walks away from the screen and the trade either hits the profit target or it hits the stop loss.  The math would support this stance:

Minimum Win Rate = 1/(1 + Avg.Reward-to-Risk)

  • An average return of 1R requires the win rate to be higher than 50%.
  • An average return of 1.5R requires the win rate to be higher than 40%.
  • An average return of 2R requires the win rate to be higher than 33%.
  • An average return of 3R requires the win rate to be higher than 25%.

In theory this approach is like hitting 2 birds with one stone. You’re no longer hanging your hat on the win rate, you’re using positive risk:reward ratios AND you’re not making emotional decisions.

However, there are at least three drawbacks to the set & forget stance:

  • Risk:Reward is not static and it changes during the course of a trade.

Notice in the chart below the initial logical intraday risk:reward for this EurAud trade (shaded orange vs. intraday objective). Entry = 1.5600, Stop Loss = 1.5635, Intraday Objective = 1.5550, Weekly Objective = 1.5500. That’s approximately 1.4 R to the intraday objective and 2.85 R to the Weekly Objective. But during the day the market pushes almost to a 2:1 Risk:Reward and then retraces all the way back to entry. Then the market pushes again to a 2:1 Risk:Reward reaching the Weekly Objective before pulling back again almost to entry.

The thing to notice is this: what happens if your trade gets within 5 pips of your intraday objective and then pulls back and stops you out? Your are not just losing your initial risk! You’re losing 1R + unrealized profit of 1.4 R = 2.4 R! That’s the potential cost of setting and forgetting your trade.

  • Set & Forget does not allow you to “let your winners run”.  This is quite obvious, especially for trend-following models. With fixed targets, you don’t give the trade any room to breathe. This may be a decent stance within defined ranges, but within a trending market it’s definitely putting a cap on the magnitude of your winning trades. If you had taken all profits at 1.4R (intraday objective) you would not have seen the full potential of your trade at nearly double that (2.85R) into the week’s close.
  • Set & Forget does not work well with all trading strategies. Set & Forget may be useful with some strategies but as noted above, it sets a cap on winners and goes against the recommendation of “letting your profits run”.

Bottom Line: Set & Forget is a serious improvement over “not having any trade management rules”. But it’s not a panacea and it has drawbacks. However, if you are finding yourself fiddling with trades too often, perhaps take a step back and analyze what would have happened if you had not fiddled with it at all.

Over to You

In this brief introduction to trade management, we highlighted why it’s necessary to think about trade management in the first place, and what the most passive way to manage trades is. For those of you that wish to dig deeper into the subject, we have a discussion on the subject here.

Our work in this series will go beyond common sense trade management as we will proceed methodically in order to analyze and illustrate pro’s and con’s of various trade management strategies:

  • all-in/all-out;
  • scale-in/all-out;
  • scale-in/scale-out;
  • active to passive (for example working a core position off smaller timeframes and then gradually zooming out as the trade gets under way);
  • trailing stop & variations on the theme;
  • scratching non-performing trades.

We will show various permutations on some systematic strategies, and then we will take some real-life examples from FXRenew traders.

To be continued…

About the Author

Justin is a Forex trader and Coach. He is co-owner of, 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.

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