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There's The Exit

05/18/06 03:33:36 PM PST
by Austin Passamonte

What type of stops and profit targets do you use for emini trades?

Traders using one-minute charts who look for 10 to 20 trades per session will have an entirely different scale for stop-loss and profit objective management than another trader playing five-minute charts. That is just common sense, with the understanding that each of those traders may be working the same symbol but in different sequences of entry and exit.

In addition, different markets or symbols require different stop-loss and profit objective sizes. For example, using a -$100 initial stop in the emini Standard & Poor's 500 (ES) is wide enough for recent volatility levels, but the same -$100 initial stop in the emini Russell 2000 (ER) would be tight. The same stop will work for both symbols, but ES trades will not get stopped out nearly as often as ER trades do. This is because of the pure dynamics of each symbol. The ER has nearly twice an average value range intraday compared to the ES. That makes the normal range of volatility or "noise" in ER, currently double that of the ES.

So in order to have the same percent of range stop-loss order in each symbol, the ES -$100 per contract level would equal ER -$200 per contract level. The former example easily handles normal intraday volatility, while the latter keeps the same dollar per contract risk inside the normal volatility of that symbol.


For reasons too numerous to mention, emini traders seem anxious to get out of a trade the very moment an entry fills. This is due to several reasons all based on human emotions. The mere fact that traders spend endless hours figuring ways to bail out at the first sign of trouble, whatever that is, or devise intricate, complex methods for scaling out of trades demonstrates a fear-based focus on managing trades.

Both behaviors are based on fear of loss. Fear of loss is based solely on a partial or complete lack of understanding. Bailing out of trades and scaling out of trades are both positions of weakness: They actually reduce the trader's profit to loss ratio leverage. Did you know that? It's true.


Assuming you have a profitable method of trading, what if you examined 100 average trades backward in time to see how far price action actually went from each entry to maximum distance before the next trade signal and/or end of session? What could you glean from that type of data? Everything you needed to know about proper trade management for your specific method or approach is in that data!

For the sake of this exercise, assume we are trading the S&P 500 emini futures using the following hypothetical scale. Although the scale is optimistic, the process will be similar for any scenario.

Maximum potential profit of 100 average ES trades:
A. 30 trades immediately reach -2 points from entry
B. 20 trades reach +2 points from entry
C. 20 trades exceed +4 points from entry
D. 20 trades exceed +6pts from entry
E. 10 trades exceed +8 points from entry

If you place 100 trades, regardless of the distribution, it'll result in the cumulative table above. In essence, there's no point in being fixated on each individual trade and the outcome of each trade. In order to manage your trades with utmost efficiency, you must focus on results of the law of large numbers over time.


Trade series A and E are the tails of the data curve; 30% of all trades are immediate failures at maximum loss, and 10% of the trades go further in potential profit than you would normally expect. That takes care of 40% all trades from the study.

Another 20% of trades work for at least +2 points from entry before reversing back into your entry. If you followed a rule that trailed your initial stop-loss from -2 points to entry or par when each trade went at least +2 points in favor, that simple act would convert 20% of all trades to zero net results. From this, 30% would result in -2 points, but the average total net loss for both groups would then be roughly -1.25 points.

Thirty trades at -2 points equal -60 points. Twenty trades at zero points equal zero. With that in mind, 50 trades at -60 points net equal -1.25 ES points. There is our ratio of true risk per trade in this scenario, averaged over a long period of time.


Of the remaining 50% ES trades in the study, each trade moves at least +4 points in favor of entry. Using a trailed-stop scale to lock in +3 points each time a trade goes +4 points in favor on the full position is similar to taking a half position off at +4 points and trailing the remaining half position at +2 points.

In the first scenario, you have +3 points locked in with full position leverage to keep adding gains. Considering 30% of every individual ES trade you take goes +6 points to 10+ points in favor, the probability of averaging 4+ points profit against -1.25 points controlled loss is a profit-to-loss ratio you could probably live with.

Likewise, if you decided to exit all trades at +2 points ES, that offers roughly a 70% win ratio if you manage entries correctly. A total of 100 trades would result in loss of -60 points on 30 trades, with a gain of +140 points on the remaining 70 trades. That averages out to a net gain of +80 index points' potential profit per 100 trades.


Armed with such data, you now have some basis for expected performance. The greatest predictor of future behavior is prior behavior. If you know your trading approach offers roughly $200 per contract gains against -$62.50 loss on each trade over the course of 100 trades, that is a +$137.50 potential average profit per trade.

Likewise, simply taking +2 points profit on each ES trade with no further trade management would offer a +$100 gain 70% of the time with -$100 loss the remaining 30% of the time. Net result over 100 trades would be +$40 per ES contract average profit. That's less than a third the potential of using trailed stops in the example given to catch some bigger wins and ratchet up the equity curve, a fact that savvy veteran traders already realize.


In reality, is there any valid, logical, unemotional reason to bail or scale out of any single trade? After all, each is valid in the series regardless of individual outcome. Building this type of faith and trust using your own math applied to your own individual trading approach is precisely how robust trade management methods are designed. Profitable trading is at the core level built upon a balanced scale of small losses and larger profits. What exactly the numbers are inside that ratio depends on price action in harmony with the method or system.

An emotionally designed exit strategy based on fear or ignorance could involve picking numbers out of thin air to make you feel good. The fear comes partly from the ignorance factor. Most traders have absolutely no idea what the average loss and maximum profit distance ratios are for their trading approach. All system designers know these two factors backward and forward: that's how systematic trade management is mathematically possible.

Too many traders simply have no idea if they are operating efficiently or inefficiently. Heck, isn't it enough to just get in the trade, pray that it goes anywhere in favor, and whack a few ticks' profit when possible?

If a given time frame chart and method approach utilized to enter trade signals averages +2.5 points maximum distance beyond entry, choosing a +2.0 point profit objective makes perfect sense. That is very efficient trading. On the other hand, if a selected method or approach commonly offers +5 points average profit potential while a trader scalps for +2 points purely out of fear, that emotional decision leads to inefficient trading.

It's highly probable that most traders have no idea what the average maximum per-trade profit potential is for their given approach. All research time is spent on entry methods that try to catch exact tops and bottoms of a move. A better use of study time might be figuring out how to glean the most net profit overall from those same trades in the first place.

One constant is the initial stop-loss size that is able to hold normal price action. Using the scale of trade performance mentioned previously, say a trader arbitrarily chooses a profit target of +1 point just because the trader cannot stand the uncertainty (fear) of holding for bigger gains.

The decision to exit each trade at +1 point or +2 points (while knowing that 50 out of 100 trades go beyond +4 points from entry) does not mean an initial stop of -0.5 point to -1.00 point is feasible. It is certainly not the market's fault that our knee-jerk trader doesn't have the right emotional balance to trade a selected approach profitably. The market is offering this trader a +4/-1.25 point average ratio to work with. If said trader chooses to sabotage a handsomely profitable approach by cutting profits short, who is at fault?

The market will not support an initial risk-stop setting chosen purely out of fear. The market will accept some type of reasonable risk-stop based on price action volatility and dynamics. Likewise, the market will offer average potential profits some degree greater than that. Successful traders do not randomly pick stop-loss and profit target size; they work with the harmonic balance of their method or approach. Don't know what that is? Better find out...managing trades correctly is far more important than entering them in the first place. Mismanaging trades is the difference between enjoying net profits and suffering losses over time.


As you may have heard, correct mental/emotional attitude is absolutely the core of success in trading and in life itself. That includes trading 100% mechanical systems as well. There is no circumventing or escaping the need for self-management in our trading profession, period.

We must focus most of our time and attention on the mental side of trading. If you get that right, everything falls into place for you. The good news is, profitable trading is simpler than you might think but far from easy.

Austin Passamonte

Austin Passamonte is a full-time professional trader who specializes in emini stock index futures, forex, and commodity markets. His trading approach uses proprietary chart patterns found on an intraday basis. To find out more about Passamonte's work, visit

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