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Research: trading pullbacks in CL
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Research: trading pullbacks in CL

  #101 (permalink)
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Analysis of Results

Clearly, based on our sample and our chosen rule set for entries and trade management, this first test shows us we don't have a profitable pullback system. After making some good money in January it becomes a net loser in February and March, taking back all profits and then some.

The culprit could be:

* Poor trade selection, need to refine entry rules.
* Not taking second entries when provided.
* Poor trade management rules.
* Bad luck due to small sample size.

We also notice a few other things:

* The winners appear larger, overall, than the losers.
* This exit strategy allowed all 13 "immediate win" trades to reach their profit target unimpeded.
* There can be as many as 8 losers in a row (late January - early February).
* Our initial profit targets are skewed above 1.0 R, which gives them a positive skew.

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  #102 (permalink)
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System analysis continued: Was it bad luck?

Let's first address the issue of 'bad luck', that is the system as it stands with its current rules is actually good but our sample was poor, we stumbled into a bad period (indeed, had we just looked at February and March, this system would be a total dog).

Here we have a printout of a histogram and our 'descriptive statistics' from Excel.

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The histogram (trades on the y axis, %R on the x axis) shows that we do have a positive skew to the distribution. The statistically inclined will have already have noted that in the skewness measure in the table on the right.

Taking a look at our descriptive statistics box on the right, there are two things of note (outlined in red). First, the standard distribution is very high - a total of 0.91R! That's a pretty violent swing in either direction.

What should be our target average %R? I would argue that I'd like a trading system with an expectancy of 0.2R net all trading frictions (slippage and commission). This would amount to a 60% probability of being correct if we normalized things for a 1:1 risk reward ratio net frictions. That's not a small achievement for day trading where the spread and commissions can eat a significant percent of that %R (sometimes up to half of it).

Can we based on our data already understand that our trading system is no good, or is it just a bad patch in what is in fact a 0.2x %R system?

The second circled item, confidence level, tells us that with our current mean and standard deviation we have a 95% chance of being sure that the actual real expectancy of this system with its current rule set is in between +0.21x and -0.31x %R. Hardly a comforting thought, but this is how the numbers play out with this given sample size and standard deviation.

How can we increase our level of confidence in our system?

First of all, increasing the sample size. However, this may cause another issue - while large sample sizes are good in that they provide us more comfort, they will likely stretch over different market "regimes" (a mode of behavior, what people usually mean when they say 'a different market'). We can try to minimize this problem by defining these different modes of behavior, e.g. we can take a read on the trendiness of the market or the overall levels of volatility (ATR, etc). Indeed, a pullback system should work well when markets are trending, and poorly when they are rangebound. This would require altering our entry and/or exit rules to adapt to these regimes, a task that requires quite a bit more thought and research that we haven't gotten down to yet.

Second, reducing the variance of the system's performance (its %R returns). Perhaps by adopting another set of trade management rules we can accomplish this (one possible way is to manage it on a smaller time frame chart such as the 512 tick). We may miss out on some of the bigger wins, but we will more importantly minimize the losses. The lesser the variance in returns (which directly translates into a lower standard deviation), the less samples we need to ascertain if a system if working or not.

However, it's important to be careful not to get too cute with reducing variance. The system may perform better over the long run if we allow it to have greater variance, or it may not. This is something we'll have to figure out.

Bet at least a few people reading this thought initially it wouldn't be so complicated, right?

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  #103 (permalink)
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Exit Strategy: Thoughts


We've analyzed our first iteration of a pullback trading system, which includes a simple, somewhat primitive exit strategy (trailing the stop under/over the latest candle). This exit strategy was just a random choice, as a starting point. The results of our system did not live up to our expectations - the system had a lot of variance and we couldn't tell after 48 samples if we had a profitable system or not when we take into account the confidence interval that we're dealing with.

Before we go into addressing the other possible causes of our ill performance (not the least of which could be poor trade selection), I want to see if we can possibly give our exit strategy some more thought.

If we think back conceptually to what our pullback trade is, it is a failure of a counter-trend trend. It is a counter-counter-trend trend, if you will

We've entered at the point at which we believe a new trend has begun, which simply resumes the original trend.

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If we're mistaken, we've likely entered when the counter-trend trend was retracing as opposed to reversing (in other words we've entered in a miniature pullback in the wrong direction). In such a case we'll likely get stopped out pretty fast, within the first bar or two. The next possibility is that we've entered when the counter-trend trend was retracing in a more complex manner (a mini complex pullback). Here we might see a little more initial follow through before we're stopped out. Then we might enter into a situation where neither happens, when the market enters into a directionless consolidation which reduces the directionality and thus the probability of follow through (it may even increase the chances of a reversal, which is what some reversal traders look for).

The diagram below displays our several options when exiting (this is not meant to be comprehensive, but these are the parameters I'm used to):

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The first responds to market structure, in this case it trails stops (the red line) above swing highs in a bearish trend.

The second moves the stop in relation to how much the market has moved (in this case, going in 10 point increments, but it can also be in percentage risk or percent ATR) regardless of what patterns price displays.

The third is what we used to test this system with, it simply trails to each candle extreme, which is sort of similar to the first idea but it treats every candle extreme as a swing which is not exactly the same.

The fourth idea is a time stop which can either trail a fixed distance based on how much time has passed (e.g. every bar or second bar), or it can simply exit after a number of bars have passed (e.g. exit after 7 bars) without trailing our stop (obviously leaving the original stop in place), or it can combine the two.

With methods two and four, we can trail the stop in a linear fashion (moving it a fixed amount of points or risk units each time) or logarithmically (beginning less aggressively and then becoming more aggressive, or beginning aggressively and then trailing less aggressively).

In fact, we can easily combine several of these ideas into one (for example the market structure method with the time stop). The trick here is to see what works best with the market and our personalities as well.


Last edited by Georgii; September 17th, 2014 at 06:02 PM.
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  #104 (permalink)
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Failed Pullbacks: An analysis

Let's take a look at these failures and see if we can draw any healthy conclusions from them.

Our first category of failures are failures that happen on the same bar we enter the trade on. I've found three of these, and we display them below (5 min above, 512 tick below). The purple line is the entry, the red line beneath is the initial stop.

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These appear to be DOA trades, in other words they just take us out within five minutes of being in them. Not a pleasant situation for those who've been in it. You feel like you never even had a chance, dammit!

Now, we do notice that only in one case did the market immediately reverse and go against us after triggering our tipping point entry (purple line), that is trade 14 026 (the middle one). The other two did advance somewhat - not much perhaps, but enough to possibly take some action, at least in the case of 14 006 (left most trade). If you look at the 512 tick version of the chart, we see there is a pink line just above the initial stop line drawn in. There is also an encircled level to the left of the entry, which the market broke through. We could hvae trailed our stop under the last bullish tick bar where the pink line is drawn once the trade broke the level on the left, which would have saved us maybe 3-4 points when the stopout happened. Not a treasure by any measure, but I'll pick up $30 off the street any day. It's small stuff like this that can sometimes make a big difference in how a strategy performs.

Granted, there may be cases where such management may take us out of what otherwise would have been a good trade, so we have to see if over the long term this pays off or not.

Let's also note that all three of these did have triggers that could have allowed us to enter a complex pullback. Going from left to right we see in the first trade (14 006), entering this complex pullback would have given us maybe a small profit or a medium one depending on how we trail our stops, in the second case (14 026) the complex pullback would have completed beautifully, and in the third case (14 018) we would have triggered, but with a tight stop management policy would have ended up either slightly negative or near breakeven as the strong negative excursion shook us out before the trade completed.

Theoretically it would have been possible to flip short during the stop out and possibly grab enough points to break even, but this would require a very modest take profit and very aggressive management.


Last edited by Georgii; September 18th, 2014 at 12:25 AM.
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  #105 (permalink)
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Before I go into analyzing more failures, I want to bring two categories to the fore, the "ragged successes" and the "not quites".

What I did here was I outlined the swing highs/lows of these trades, so that it would be possible to theorize about how the stop could be trailed based on price structure.

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What we do notice is that the market should theoretically take off pretty fast if we have something that has a chance of getting anywhere near our initial profit objective. It should not 'revisit' the area from where it took off from. There should be theoretically no 'double bottom/double top' action. So the first hypothesis is that we want to perhaps start trailing right after the entry candle, by at least a bit. We should take just a little risk off the table as soon as the market shows it has intention to move our way.

The next thing we notice is that we do get some situations where the market nearly touches our profit target. It should stand to reason that whatever methodology we use, it should be absolutely unacceptable for us to sustain a loss or to even come out with a break even trade if the market is within a few points of our profit target. Our primitive candle trailing rule could, theoretically, allow such an unwelcome scenario. Consequently, some sort of rule that dictates once we are perhaps 75% on our way to our profit target, we should at the least be at a break even stop.

Now, I know that break even is not a condition the market sees or cares about. However, if we are in a 1:1 risk reward trade, which is our minimum criteria, we shouldn't be in a situation where the market moves 0.75 R and then retreats into the negative column. Unless you're trying to grab a very long move of many R multiples, which we're not, we don't want to assume that risk anymore, we simply won't see the payoff that would make it worthwhile. Sure, once in a while it might cost us, but we need to see what happens over a large sample of trades (and once again, let's not mislead ourselves into thinking that these 48 samples are giving us a good picture of the CL 5 minute pullback universe!).

Another point to think about is being careful not to choke the trade as it gets to the profit target. Clearly the profit target is a magnet. It is also a place where some traders are exiting early, and some counter-trend traders are scaling in. We want to give them a little room to dance, and those who've traded crude know how crude can do a pretty intense dance as it approaches a level.

So perhaps we can look at our stop trailing methodology as starting off aggressively, then giving some room for the market to do its thing, watching the technical levels as they emerge and making decisions off of those. We need to be sure the market will have enough room to get to its target and hit it without letting it get away from us and cause problems.

We haven't thought yet about when we might want to exit at market without waiting for our stop to get hit, or when we should perhaps pull in our take profit order.

This is all very general and its a discretionary process. It would be difficult to code and test this, but we can at least try to outline the parameters so we can figure out how we might test it.

Lastly, I want to indicate that I'm particularly happy we started with this kind of sample size. Yes, it's not enough to draw proper statistical inferences from, but it gives us some clues as to the variance we're likely to encounter and guides us toward asking the right questions, while remaining manageable. I can't imagine what it'd be like if we had 250 samples on our hands right now.

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  #106 (permalink)
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Test Results: A new trade management system (B)


I've done a bit of thinking and came up with a new trade management system based on our current sample set (January - March 2014 pullback trades, no re-entries).

The entry criteria (stop entry at the break of the candle extreme) and initial stop criteria (stop is under the extreme of the signal bar) are the same.

If you remember the original trade management criteria was simply trailing the stop behind each candle extreme as the trade progressed (we'll call this trade management system "A")

The rules for this new trade management system "B" (which also operates off of five minute candles) are as follows:

1. When triggered into the trade, trail the stop one tick behind the extreme of the 'entry bar' (the bar that triggered us into the trade) once the entry bar closes.
2. Do not trail the stop until a significant pullback happens. It is not easy to define a 'significant pullback', but we can define it as a retracement in the trend we are trading that retreats at least 50% from its peak, and then moves back into our direction, leaving behind a point which we could trail our stop to. It is important that price leaves that point before we trail our stop. How much is 'leaving'? Till it clears through the extreme of the retracement candle back into the direction of the trend.
3. If the market returns to test the last significant retracement a second time, the initial take profit is shortened to the extreme of the retracement.
4. When the market reaches 75% of the take profit target and the candle closes, the stop must be trailed to break even. It is important that the candle closes before we make our assessment. If after the candle closes the market has retraced into negative territory, the stop is trailed just behind the candle.

What this exit system does is it begins by trailing the stop immediately to the extreme of the entry bar. This is exactly how our more primitive system A begins as well. This has the effect of cutting a little pain off of the losers that fail quickly. Unfortunately we can't save the ones that fail in the first bar, but both system A and B shave a little off those losers that fail shortly after that.

Then, unlike system A, system B gives the market significant slack to move to the profit target. The main condition we have is to watch for significant retracements, and respect them. We also have to watch if the market is giving us more than one retracement, at that point we have reason to consider an earlier exit to acknowledge that we may be running out of directionality. Lastly, we want to be sure we don't go into the negative column if we have already gotten 75% into our take profit zone.

There are no time stops in this system, though we could add one (e.g. exit at market or tighten stop and take profit after the trade has gone on for 7 bars).

Let's take a look at the results and see how they compare to our more primitive system A:

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While our system is still not performing well in February and March, we are definitely more in the plus column with system B overall, being ahead by 4.18x %R or 61 CL pts ($610 for one contract). I'll take that.

Some things worth noting: point 1 shows a less hostile PnL dip in system B. System B also manages to have twice the peak PnL over system A at point 2 (8X R versus 4X R on system A). Pretty interesting.

Let's see some more detail from the underperforming periods:

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As we can see, the under performing periods are both very similar, and both end up going down by the same amount in this segment (approx -4.3X %R). So the main contribution to PnL of the new trade management system appears to have been made in January when we were doing very well in both cases, the remainder of the time we seem to have been getting smacked a lot no matter how we managed our trades.

Next, let's see what our trade by trade situation looks like:

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More good news. System B offers fewer consecutive losers over system A (a total of 5 versus 8). That is a pretty good thing to see, because consecutive losers can be a real emotional burden.

Next, we look at trade distribution:

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System A is on the left, system B on the right. System B significantly reduces variance in the losses as you can see, while the winners get a little boost. There is still a visible positive skew.

Now finally, the stuff nobody likes to look at, STATISTICS:

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As we compare numbers, we see that the average per trade performance of system B is better though if we look at the median, overall we see a number that's unpleasant - a negative one (which is smaller thank goodness than system A's number). Ideally we'd like to see both a positive mean AND median.

Interestingly enough the standard deviation of system B is in fact higher than system A, not by terribly much though.

Skewness here in fact decreases significantly, which is interesting. However, it is still a positive skew.

Lastly, the confidence level INCREASES, which is not really what we'd want to see from a standpoint of judging statistical significance. This means we have even less of a clue here if our system is really profitable or not, as compared to system A. True, the difference is not VERY big, but ideally we'd like to see it less so that we can be more sure of our results.


Last edited by Georgii; September 20th, 2014 at 05:22 PM.
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  #107 (permalink)
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Points of departure

We took a look at a sample of possible pullback trades based on three months worth of data. We tried two different stop trailing approaches, one that can be described as very aggressive, the other considerably less so. We've seen that for this sample the more laid back approach paid off, and it stands to reason: trailing indiscriminately behind each candle without regards to volatility of movement and price structure has little logic, while our second method had some kind of market logic.

However, in both cases the system was not truly profitable over a three month time span, experiencing a very similar peak to trough draw down of 8.6x %R or $1200 (one CL contract) for exit system A, and 8.4x %R or $1170 for exit system B. Not a comforting situation to say the least. That would suggest that our exit strategy is likely not the main culprit during this specific time period, unlike in January when it virtually doubled our earnings.

It also stands to imply that a lot of our trades are failing on us pretty quickly during this period as both method A and B begin by taking the same step - trailing the stop at the entry bar - and they both have almost identical draw down in this case.

There are several possible conclusions here:

1. We are simply having a string of 'bad luck' and need to look at a larger sample size.
2. We are doing a poor job of trade selection and need to become choosier, developing some filtering criteria.
3. We may still be able to further refine our exit strategy by looking at lower time frames (512 tick).
4. We may want to permit second entries.

Before we expand to another sample size or begin parsing the details of our failed trades (a time consuming endeavor), we should take a look at second entries as a possible remedy to our problem. This is effectively using a complex pullback if we get a valid setup for one, which can win back our profits in the event of a loss.

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  #108 (permalink)
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Correction

I wanted to note that I made one error in my testing, I exited one trade 12 points too favorably when testing system B. My actual result for system B should have been 12 CL points less and 0.8x %R less (beginning with trade 33 which is at the beginning of March).

This does not significantly impact our statistics (though now the performance of exit system A and B during the peak to trough draw down period puts system A ahead by 9%), but it underlines the importance of checking your work carefully. In my first run of the second system I noticed that I accidentally entered an exit price 100 points too favorably. Looking at the numbers and noticing outliers is very important to catch situations like this.


Last edited by Georgii; September 20th, 2014 at 06:47 PM.
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  #109 (permalink)
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Analyzing Second Entries

Let's try to see what life would be like if we allowed second entries.

The rules are as follows:

1. A second (complex) entry is an entry that occurs lower (if in a bullish pullback) or higher (if in a bearish pullback) than the previous swing. Below is an illustration in a bullish context:

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2. We enter the same exact way as with a simple pullback entry: stop entry after the counter-trend bar is broken, initial stop is at the last counter-trend bar, the initial take profit is one tick inside the last trend extreme.

3. We are not interested in third or fourth entries, just second entries.

Trade management we have not yet discussed here.

Below is our pool from the same sample period as before, 1/1-3/30/14:

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As we can see, this gives us 14 extra potential opportunities.

Using exit strategy B, eyeballing the trades I have come up with the following conclusions:

Successes (S): 3
Failures (F): 2
Small profit (+0): 4
Small loss (-0):6 (note, the second collection of complex entries includes one error, 14 030 should be -0, not +0)

As we can see, a situation that doesn't swing strong one way or another. Without a proper test, we won't know the answer, so let's dig into Excel and do it...


Last edited by Georgii; September 20th, 2014 at 07:44 PM.
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  #110 (permalink)
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Second Entry, Stats

The results please...

Using the rule set we've been adhering to, we are now separately analyzing just second entries (we didn't mix it with our simple pullback, no re-entries system), as if we were trading it as a system on its own.

We are using exit system B.

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As we can see, using second entries based on our criteria would have helped juice up our PnL by a whole 22 CL points. If we add this to our prior system using exit system B, we increase our PnL from 29 to 51 CL pts (a whole 75%).

This is encouraging, although it pays to note that this is a VERY small sample size at just 14 observations. We would need to see a bigger picture if we really wanted to get comfortable with whether re-entry is a good policy or not.

Also, this system would have eroded our general PnL during its initial iteration. This could be of course the classic 'portfolio approach', one zigs while the other one zags. As long as the zigs are greater than the zags in the long run, we're in business.

Note: An earlier version of this post had an incorrect diagram posted that stated the system had 8 consecutive losses. This was a mistake. This system has no more than 5 consecutive losses which is within expectations but again, this is a small sample size.

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