Help Center Blog Open An Account

How do you adjust your targets and stops when volatility changes? How do you think you should?

On this week’s weekly webinar, we want to know: How do you adjust your targets and stops when you trade?

Let us know in the comment section below for a chance to win the following:

  • THREE months of the Optimus Flow trading platform (Professional License)
  • THREE months of FREE Live CME Data from dxFeed
  • 30 minutes of my time for a personal one-on-one consultation
3 Likes

Hi everyone, I’m Cesar I’m here coming from the webinar. If I go with the trend one I see the trigger I set a 2:1 target. Against the trend I go for a 1:1.

4 Likes

I use Fib tools to establish a potential target and stop areas, adjustments are made as past equal moves are honored or broken. I’m learning to use order flow (Bookmap) to make a target and stop decisions/adjustments. For larger targets and timeframes I believe knowing where the highest open option interest is in a trading instrument to be very valuable in determining potential target or stop area. Knowing if the day is expected to be high vs low volatility also is an important role in achieving larger vs smaller trading ranges and targets and of course wider or tighter stop areas. Most importantly, does the instrument have momentum, and is it in your favor.

3 Likes

My simple answer, I don’t. Not if I am in the trade… not anymore.

There are days that I study the market for an hour before my criteria is met. The majority of that criteria is finding an entry with a reward that is a multiple of the risk I am willing lose, ex. 2:1, 3:1. When I execute that trade, I need to see it’s outcome. I want to gain experience and learn from it. I learned this the hard way.
My adjustments were always based on emotion. Moving the stop because of fear or hope and moving the limit for more profit or greed. I didn’t move them because it was part of my criteria or method.
Perhaps one day I can be “flexible” with my trades. I don’t feel I have the experience, or capital, for a robust strategy at this time.

I hope this is helpful.

3 Likes

Good answer and I agree with the sentiment. If you have predetermined targets they should not (in my opinion) be changed once you are in a trade.

I changed the topic question a bit to ask what traders do when market conditions change.
So if volatility rises will you change your targets or just wait for market conditions to return to those that you are comfortable with(?). Thank you for all your feedback and posting.

Matt Z
Optimus Futures

1 Like

Thank you for the reply.

My answer to the new question is the same as the previous.

Because, outside of an options discussion, volatility (in my view) is simply the measurement of what we already know to be unpredictable, which is price movement. With that being said, I will make adjustments to the size of the trade based on volatility, but only as a means to manage my risk. Also learned this the hard way. I also avoid having an open position in the market before high volatility events, such as economic announcements and the like.

John

1 Like

Nice job sticking to your plan and waiting patiently for your targets to be reached @JDFtrader. I prefer being more active in my approach because I think every bit of information that we see has an impact on the potential risk, reward, and probability of the trade. That being said, sometimes that leads me to exit good trades too soon rather than letting them run, so it’s possible that in the long run using an active approach and sticking to the original plan probably even out somewhat.

Have you considered using certain predefined criteria to exit trades early? For example, if you’re trading price action and you have a second entry against your position that triggers, potentially using that as a reason to get out of the trade and reassess. Managing in that sort of manner could make it so that the small losses (trades you take off before your hard stop) and small wins (trades that don’t reach the target) approximately even each other out and some trades get to your 2R or 3R targets while some reach the full stop. This depends on the entries you take so test it in SIM to see if it would have a positive expectancy for you, but it may be worth experimenting with.

In terms of adjusting targets and stops, I pay attention to the average size of bars to help decide minimum target sizes. Generally I aim to have a minimum scalp size of at least half the size of an average bar. For the ES and MES I also won’t take a trade unless I think the profit potential is at least 1 point. If the volatility picks up, I’ll also look to increase my minimum target size. I learned from Al Brooks to use a minimum scalp size of 5-10% of the daily range. So if the volatility expands to 100 points, then the scalp size would be 5 to 10 points. With more volatility I also decrease my position size. Basically I want to make sure that since my stops will have to be further away I’m using a wide enough target that I’m not going to need to have a drastic change in my win rate to accommodate.

Every trade is a balance of risk, reward, and probability. Dr. Brooks writes this out as something he calls the trader’s equation:
probability of reward x size of the reward > probability of loss x size of loss
Essentially with each trade that’s taken, aim to structure it in a manner that this equation is positive. Even if volatility expands or contracts, keeping this idea in mind is helpful for trade management. Generally speaking, the better the risk/reward profile, the lower the probability and vice versa - I’d argue that this isn’t always the case though, particularly if the trade location and the behavior at the location is advantageous.

3 Likes

I find it helpful to set a fixed price scale for each chart, regardless of volatility. This way, it is easier to fully appreciate the size of moves. It is tempting to keep readjusting the Y scale to zoom in and see the detail during quiet periods, or zoom out to accommodate large candles during volatile periods, but this can make it difficult to fully grasp and the size of a move.

For example, if price is flat-lining and moving sideways in a very tight range, it is tempting to zoom in, but I find this encourages me to look for trades when there are none. Similarly, when price breaks out and the range of each bar is great, it is tempting to reduce the scale. But this can trick the brain into thinking the move isn’t so great, which can lead to staying in a losing trade longer than planned.

Once the brain is subconsciously aware of volatility, I find it is more natural to set targets and stops accordingly.

I plot the tick size of each candle (High-Low) and a moving average. I trade the Globex sessions so I find this easier to keep track of than a daily ATR, but the principle is the same. It shows me at a glance the average size of the last X bars on the timeframe I’m trading, which makes it a good ball-park for setting stops and profit targets.

4 Likes

Thank you for your kind words, they are greatly appreciated.

That is a great question, and suggestion. I have attempted to include that in my system (method), but in the interest of simplicity and consistency I no longer do.

When I first started to build my system, outside of the live market environment, my goal was to maximize profitability while decreasing loses. I found it difficult to avoid, what I believe is called, “curve fitting”. The idea of layering rules or criteria on top of a more, relatively, simple entry and exit criteria in an attempt to optimize the results. This “curve fitting” left me with a very complex system, and as a beginner I don’t feel is ideal for me.

Thank you for sharing your thoughts,

John

2 Likes

Isn’t a shorter version better? size of the reward > size of loss
how do you assign a probability to risk/reward before each trade when at ANY point it’s 50/50? At times, this is hard for some to grasp because if the NASDAQ (for example) went up 300 points, some believe it “should” come down. So they assign an intuitive probability that it must “must correct.” It does not.

If the Dow (for example) is down 1500 points, then “it should correct.” No, it does not. We can’t call tops, bottoms, or the next 5 minutes.

However, when you have a reasonable size sample of figures for your trading. You can resort to the “Positive Expectancy” formula:
Expectancy = (Average Winner X Win Rate) – (Average Loser X Loss Rate)

As you see, these are averages wins and losses, and on top of that, you have the percent number of wins and losses. That gives you an idea of a larger number of trades you take instead of assigning percent to each trade before taking (that, in my opinion, are based on intuitive bias confirmation, therefore, in my opinion, worthless).

If your average win is $500 and it occurs 60% of the time, while your average loss is $200 and it occurs 40% of the time, now you have ($500 X 0.6) X (-$200X0.4) = $300-80=$220.
Now your Expectancy per trade is $220.

Now you have a statistic you can use. You can go back to the charts, look at your past trades, decide if you are getting too early, too late, stay too long, etc. Again, you want to max out your positive Expectancy. If you look at the formula variables, you could see that you could have more losses than wins yet come out positive when you max out your successes.

The expectancy formula should be applied when the number of contracts does not change, and ideally, you are doing it for each individual Futures contract you are trading(Indicies, Bonds, Gold, Oil, etc.). While you may have the same method for all the Futures contracts, you need to look individually at each contract and its performance. You may decide to drop or increase activity on some Futures contracts.

Matt Z
Optimus Futures

There is a substantial risk of loss in futures contracts. Past performance is not indicative of future results.

3 Likes

I promised to mention the volatility indicators that we discussed in the webinar:

VIX:
You can think of the VIX as a gauge for day traders. It measures the amount of risk they feel when there is high volatility in the market, more traders are scared out of long positions and take short positions instead. They are buying protection in case things turn out badly. THUS, the VIX rises when a lot of investors’ confidence is shaken, and it falls again when they get over their fears.
VIX could be Googled daily when volatility increases or decreases.

ATR:
Average True Range:
To discover the True Range on the chart, (ideally), you should do three calculations and take the one that gives the highest value:
(High of the Current Period) – (Low of the Current Period)
(Current Period High Absolute Value) – (Close of Previous Period)
(Current Period Low Absolute Value) – (Close of Previous Period)

However, even if you choose one formula and stick with it, it will give you a gauge as to the volatility. Start with the first one.
Optimus Flow has ATR build into it.

Matt Z
Optimus Futures

3 Likes

Good discussion everyone! Good points @Mod-MattZ, in some ways we mean the same thing, but I’ll try to clarify my perspectives:

Risk and reward are things that we have control over based on where the target and stop are set. However, probability is an important variable that has to be taken into account, even though we can never know it with certainty; it is based on market tendencies. You’re making an assumption that the probability “at ANY point is 50/50” however this is arguably incorrect (I’ll expand on this below). It is more accurate to say that the outcome of an individual trade cannot be known ahead of time, but that is not the same as saying that there’s a 50/50 probability at any given moment. If that were true, then why bother looking at charts, order flow, Profile, or anything else? Trade location matters because it is tied to probability. I’d argue that a lack of exactness, in the way that risk/reward can be exactly assigned, does not make it less objective. An assessment of probability doesn’t necessarily rely on intuition or subjectivity (though we are always trading our beliefs of the market in some way or another so I don’t think there’s a reason to dislike those softer attributes). There are objective and subjective aspects to any trade that is taken.

We’re actually talking about the same exact thing, we’re just using different words to describe it. This equation, if rearranged is the same as the trader’s equation that I talked about in a prior post. The terms “probability” and “win rate” are interchangeable. The key thing to note is that this equation takes risk, reward, and probability into account. All three variables are important.

I want to expand on the idea that “at ANY point it’s 50/50” because I think that is at the heart of where we disagree (we both agree on the use of the expectancy formula which Brooks calls the trader’s equation). I think you’re using 50/50 to describe the fact that we can’t know whether or not the current trade will be profitable. It is true that we can’t know the outcome of a trade ahead of time, but that does not make the trade itself a 50/50 proposition. The approximation of probability is based on the likelihood of one thing happening over another and in many instances that is not 50/50. Probability, as I view it, is approximately assigned based on the behavioral tendencies of the market. If a certain behavior tends to play out in a particular manner, for instance, 70% of the time, just because this current trade may result in a win or a loss does not mean that the trade itself has a 50% probability or that somehow a series of 50/50 trades becomes a behavioral pattern that holds in 70% of cases. “Win” or “lose” are two different potential outcomes, but they don’t necessarily have equal probabilities. To put it another way, I’ll use an extreme example of the lottery: I could win or I could lose, those are two possible outcomes, however the likelihood of those two outcomes is certainly not 50/50 (and if it were I’d be playing the lottery not trading the market lol).

As a more specific example of what I mean by behavior tendencies consider this: in a bracketed market why do traders tend to buy near the lower portion of the range and sell in the upper portion of the range? It’s because at those locations there is a greater likelihood of the prices reverting to the mean than breaking out. The market is facilitating trade around a range that it finds to be fair so unless the perception of value has changed it has a greater likelihood of rotating around that area than becoming imbalanced. I may short in the upper portion and this may be the time when the market breaks out against my position, so it is true that I may win or lose on the trade, but that doesn’t mean that there’s an equal probability of winning or losing in that location. If the same trade were to be taken hundreds or thousands of times, then it is more likely to be a profitable method than a losing one (assuming the risk and reward is also reasonable) because the behavioral tendency in that market context is to revert to the mean.

I’m not buying just because the market sold off or selling just because the market moved up a certain amount. As another example, in a strong trend, there is a strong degree of directional conviction and so it is likely that the trend will continue, however it isn’t guaranteed to continue (i.e. I don’t know for certainty whether I’m buying the top tick or selling the bottom tick). So even in a market context that has a high degree of directional conviction, the outcome is still probabilistic but it is unlikely to be 50/50. Let’s say the market is trending up, as it ticks back down it is becoming a more attractive price to buy at and a less attractive price to sell at. As long as there hasn’t been a significant change in the behavior of the participants, buying at these temporary lower prices has a higher probability of leading to a profitable trade than shorting at the same location. If we can say something along the lines of “most of the time ‘x’ happens, ‘y’ tends to follow” then the probability is likely greater than 50/50.

We don’t even need to use my examples, let’s use the long trade that you talked about a couple of weeks ago in the webinar. Why did you buy where you did? I don’t know with certainty, but it’s likely because you thought that higher prices were more likely to follow the market activity that was being seen than lower prices. If that weren’t the case, you would’ve either waited for lower prices to buy or potentially even considered shorting if you believed that the likelihood that the market would sell off further was higher than it being bought back up. That is an assessment of probability and directional conviction.

Something else to consider is the fact that not all prices are traded equally. Some trade a lot and some trade very little, which means that there is a difference in the quality of various opportunities in the market. Knowing that means that certain opportunities intrinsically have a better probability of success than 50/50.

3 Likes

Yes, very good discussion !
As I read through your post, which I really like, two topics came to mind that I would like to add to the discussion.
The first being the law of large numbers theorem. Which describes the mean ,or average, of a group of samples being revealed as the sample size increases. It is this theory that traders aim to lose less than they profit on a consistent basis.
The most simple example of this is the coin flip. All things being equal with the coin and toss, it’s 50/50 average is not seen until multiple tosses have occurred.
This leads me to the second topic, gambler’s fallacy. I like to think of it as a form of informational bias. Understanding that the average expectancy of the coin flip is 50%, one might “believe” after 2 or 3 outcomes in the same direction, say heads, that the opposite direction, tails, should occur. The expectancy should not to be used for each occurrence, for they are individual and have no effect on the others.
Coming back to the original subject, these two topics better explain my choice for not adjusting my trade once it is executed. Adjusting my take profit and stop loss is adjusting my risk to reward ratio. If I understand that my expectancy, over time, is ~50% then my risk:reward of each trade(samples) need to be as similar as possible. It could be argued that its possible to adjust my trade and maintain the same risk:reward but I am a beginner trader battling with ‘the emotions’ so I am focused on keeping things as simple as possible.

John

2 Likes

I trade ES and I NEVER change my stop, my stop is 8 ticks and my target(1) is 8 ticks, and target(2) is based off a level target (support / resistance), but I only do this once a certain profit target has been met either daily or weekly. My goal is to execute simple and winnable trades

2 Likes

@Trader, thank you for helping the Optimus community with such elaborate and helpful education. Many thanks for that! And much appreciated.

When I say a trade is 50/50 I do not refer to the fact of whether a trade will be profitable or not.
I refer to the fact that the market could go up or down at any point of entry to the market.
It is a binary state, and that is a fact.

Whether you use a sophisticated quant analysis, a statistical method, or a simple TA, there are only two states the minute you enter. Up or down. This is my 50/50 analogy.

I did not mean to imply that traders should randomly choose entries, but the real work starts when they enter. The market can go in your favor from the start, go against you, then go in our favor and against you again. There are many scenarios past the point of entry. However, it is the management of your trades after the entry that would determine one’s success. You could be right in terms of direction yet lose in the trade because you mismanaged it due to psychology (weak hands), over-leverage (too many contracts), or lack of precise methodology.

However, the “full picture” could only develop after a trader has gathered enough data to see exactly where his strength and weakness lie. Therefore, analyzing each trade as a mistake or declaring a victory is not appropriate in my opinion. That was the point. If it came any other way, it was not my intention.

As far as lottery tickets: They also have a binary state win/lose. But, there is no management of your number’s choice, which makes the gamer’s odds written on entry. In other words, odds are written against you from the beginning. The markets, on the other hand, give you a lot more flexibility after your original entry.

Great to exchange ideas with you!

Thank you,
Matt Z
Optimus Futures

There is a substantial risk of loss in futures trading. Past performance is not indicative of future results.

2 Likes

I have 3 stop classifications:

  1. Really tight - when joining a momentum move, I do not expect price to go against me at all. I look at my MAE stats to determine a suitable stop. Not affected by volatility
  2. Based on market structure - I do not expect price to exceed a particular point, beyond which I would consider the trade to be a failure. This could be a swing point, trend line, fib retracement, etc. Not affected by volatility
  3. Based on market character - if markets are generally undecided and choppy but with a slow underlying trend or mean reversion, then I will use some variation of ATR or Standard Deviation to determine a suitable stop distance. This is more to deal with unexpected news or system failure than to automatically exit if a trade has failed. Is affected by volatility
1 Like

@Mod-MattZ Thank you for your kind words! I’m just another student of the markets and I’m happy to be included in such an enthusiastic community of traders. I really appreciate what you guys have going here and enjoy being able to think collaboratively! It’s helpful for me to try and articulate these ideas as well.

Directional probability (the tendency for the market to move X ticks in one direction before it moves the same X ticks in the other direction) is an interesting topic to grapple with and I’m really enjoying this discussion. Like we’ve both said it is only a component of the overall management of a trade. If the risk and reward doesn’t make sense for the level of directional conviction then that poor management can still lead to losses over time. If more complex management styles are introduced like scaling in and out, altering position sizing, etc. then it makes matters even more complicated.

I think something that has to be emphasized is the idea of 50/50 on this current trade vs. a series of trades. We both touched on it, but it’s worth distinguishing since it is central to the idea of probabilistic thinking. It’s the reason why something like betting on weak reversal attempts in a strong trend, for example, tend to be bad bets in the long run even though the potential risk on each individual trade is small. The market may wind up reversing on this trade, but over a series of trades the odds are likely better to go with the trend, particularly because it is psychologically difficult to hold onto the relatively infrequent winning reversal trade for long enough for it to make up for the losses on prior trades.

My view does differ from yours in that I believe there are instances when the odds are not 50/50 even on a trade by trade basis (strong breakouts in the right context tend to have directional probability that is very likely to be higher than 50/50 for example). That being said, I don’t have statistics to back up what I say and I could be wrong, I’m basing my view on many hours of trading and direct observation, but it’s possible that a quant or statistician may have findings that would invalidate my view. A way that I’ve heard things put is that 80-90% of the time the directional probability is between 40-60%, with the remaining 10-20% accounting for the greater probability during strong breakouts. I tend to think that’s more accurate than viewing the market as having 50/50 odds in all cases.

This depends on a trader’s level of experience in my view. If a trader is experienced enough to distinguish between whether a trade failed due to poor execution or normal variance, then it is worth spending the time learning from it. We can’t know the “why” with certainty, but having a mental catalogue of typical behaviors is useful so that there’s at least some benchmark to measure one’s own performance against. By trading the repetition in behavior a trader can better understand the quality of his or her own execution. For instance, let’s say the offer is easily lifting and so a long trade is placed under the assumption that the market will soon be trading higher since sellers are observably unwilling to transact at lower prices. If a seller suddenly starts holding down the offer and pushing the market lower, then this is a change in behavior and a loss that is taken is due to this change. In that case, it’s an appropriately managed trade due to a change in the premise even though the trade was a loss. On the other hand, if the behavior hasn’t changed but the trade is exited for a small loss simply because it moves against the entry point, then that is an executional error. In this way, the market itself is being used a teacher and practice is being done in a more deliberate manner.

2 Likes

I agree with you. It would help if you based your decision on the current market condition and the risk/reward.
Nothing you said here contradicts what I believe in. I will elaborate on where we can (maybe) agree with each other. Your approach and explanation help me explain my process better as well.

Let’s touch on the 50/50 point Per single trade versus a series of decision-making. Don’t think trade; think decision-making.

Let’s use an example outside of trading: Let’s say we have two soccer teams and betting.
One team has terrific players, and one has weak players. Could you say with certainty that the strong players will win? No.
Yet, betting on the weak team would not be the right way to go.
Let’s assume that the weak team wins. Would you change your bet? You should not.
Let’s say the weak team wins again? Would you change your bet?
Let’s say the weak team wins the third time? Should you change your bet then?

My point is this: The win/loss outcome of a game is not the right way to determine how well a team actually played. So while betting on the right team is still the right thing to do, every single event boils down to 50/50.

You can definitely judge a soccer team after an entire season.

Bringing it back to trading: The win/loss outcome of a game (single trade) is not an accurate representation of a team’s performance (trader’s performance) and, therefore, its players’ intrinsic value (trader’s skills and method).

This also brings me to the main point: Beginner traders struggle with understanding each trade could be 50/50 (for the reasons above) and that you could have a series of losses even as a skilled trader. They change methods and question their skills when their system could prove proper in the long run. Again, I think that traders should be “obsessed” with statistics of one trade.

I am not a statistician, but stats, gaming, crowd behavior, and other topics related to trading are ones that I have read about for many years. I realized that there is a difference between what I want to believe in versus universal math and stats that apply in trading.

I respect your experience and observation, and if it led you down the right path, stick to it. I saw many cases where I see different approaches from different traders, yet good results for both.
However, what I try to run away from (and that applies to me specifically) is the word “intuition.”
I think that our brain is so selective as far as what we want to see and what we remember that it leads us to the wrong conclusions.

Matt Z
Optimus Futures

2 Likes

This is not an accurate conclusion based on the premise of the scenario. If you’re labeling one team as “strong team” and the other as “weak team” then that implies that one team has a higher probability of winning than the other. If they were two equal teams, then the probability could be said to be 50/50 since neither team has a higher probability of winning than the other (i.e. “equal” implies same probability in the same way that “strong” vs. “weak” implies a difference in probability). If one team is objectively stronger than the other, then the probability favors the stronger team and so the probability cannot be 50/50. This difference in probability is why you’re correctly choosing to keep betting on the stronger team since the odds favor them in the long run. Just because the weaker team wins multiple times in a row does not mean that there was a 50/50 chance of that happening from the get go, it just means that the lower probability outcome happened several times in a row. Therefore, it is inaccurate to say that “every single event boils down to 50/50” to describe wins and losses.

Think about it this way: if a weatherman says there’s a 70% chance of having a sunny day but it actually winds up raining (and for simplicity’s sake just consider two potential outcomes: sunny or rainy), that doesn’t mean that he was wrong, it means that the lower probability outcome occurred. However, just because the lower probability outcome occurred does not mean that the odds were 50/50 from the outset. In this example, the probability of a sunny day was 70% and the probability of a rainy day was 30%. The fact that it rained does not somehow change that starting probability to 50/50, it just means that the event that had a 30% likelihood of occurring did occur.

If we use math to describe the weatherman example with two possibles scenarios and say there were 3 trials:

  1. In case number 1 let’s say the high probability scenario (70%) happened 3 times in a row:
    (0.70 sunny) x (0.70 sunny) x (0.70 sunny) = 0.343 or a 34.3% chance of the high probability scenario occurring 3 times in a row

  2. In case number 2 let’s say the low probability scenario (30%) happened 3 times in a row:
    (0.30 rainy) x (0.30 rainy) x (0.30 rainy) = 0.027 or a 2.7% chance of the low probability scenario occurring 3 times in a row

Case number 2 can happen, however the probability of it occurring are lower than case number 1. The fact that case number 2 happens 3 times in a row does not make the starting probability 50/50, if that were true then the probability would have be calculated differently. This same sort of math is applicable when considering a scenario where one team is stronger than the other or in the case of a trade that has a directional probability greater than 50% or other similar probability problem.

For what it’s worth, one of the cardinal traits of expertise according to the Dreyfus model of skill acquisition is having an intuitive grasp of situations based on a deep understanding of various possibilities. Intuition allows transcending rigid rules and is arguably the most reliable way to adapt to a highly variable, fluid environment. It’s the difference between mechanically following a system and applying moment to moment discretion consistently accurately. I don’t think intuition is something to shy away from, but it’s something that can only be cultivated through a very long and thorough developmental process (one that I’m still undergoing). Jim Dalton incorporates discussion of the 5 stages of development as it relates to trading in his book *Mind Over Markets, 2nd ed.*and it may be of interest to you.

This is a great point. I agree that one of the fundamental challenges in trading is to be able to accept what is happening in an objective manner. There are so many cognitive biases and heuristics that can interfere with decision making, which is a large reason for why developing intuition and expertise is a very difficult process. I remember reading about the tendency for people to need more information to refute the conclusions that they already formed than what it took to form those conclusions in the first place (this was from The Psychology of Intelligence Analysis by Richards J Heuer which is freely available on the CIA.gov website for anyone who is interested). This points to how important it is to be able to weight information consistently and objectively and the inherent difficulty of being able to do so. Anyway, that’s a whole other conversation so I’ll stop writing here since this has become another very long post.

2 Likes

I find that one of the best and most accurate method to measure the most recent volatility in the market one trades is to use ATR (Average True Range).

It is self adaptive to any timeframe one uses and it gives a very accurate measure of the vol that can be used to effectively set stops and targets.

Depending on ones objectives, risk appetite and how aggressive are the Targets/Stops one can use 1.5x 2x 3x or even 4x ATR value to accurately avoid getting prematurely stopped out.

This is not to say that the market can’t just move against a trader at any time.

One must realize, and the faster that is truly comprehended the faster one can move up the ladder towards better trading, that STOPS are not guarantees but they allow one to setup a realistic expectation based on recent market volatility and not a price point from one’s head.

It’s always better to use current market statistics to set Stops & Targets then using made up numbers, no matter how convinced we might be about a certain price level, S/R on the chart etc…

ATR is my best friend. It’s relatively simple and always keeps me from trading too big.

Simply, Multiply current ATR x Your Desired Multiplier (example 2x) x Contracts Amount x Contract Tick Value = Your Stop Amount

If Your Stop Amount is at or below your Max Desired Risk, One can take the Trade but
if the amount is higher then One’s maximum desired Risk simple reduce the Contract Amount to adjust accordingly.

This simple Math could keep many traders from blowing their daily max stop by keeping their max stop to a logical and statistically sound and based on current market condition value.

Hope that helps,

Happy Trading,

  • Project 11
3 Likes