eurusd Archives - Algorithmic and Mechanical Forex Strategies

Trading with the Aroon Indicator

January 2, 2017 by Lior Alkalay Leave a Comment

Through this column we have covered many oscillators which are generally very effective in analyzing momentum; they include the Average True Range, MACD and the VIDYA. Some oscillators are better at predicting short term momentum, while some are lagging indicators and tend to shine brighter when it comes to long term momentum. Yet, in this article, I will be focusing on one oscillator—the Aroon Indicator—that has a very different benefit. As a backstory, the Aroon Indicator was developed by Dr. Tushar Chande a little more than 20 years ago. What makes the Aroon indicator special is that it provides in-depth insight as to how the buyers and the sellers are behaving within each price level. I will explain how that understanding of the buyers’ and the sellers’ behavior is very useful information.

Aroon Indicator: The Basics

The Aroon indicator, as seen in the chart below, has two separate curves, in this case marked with green and red. The green curve, called the Aroon Up, measures the buying momentum over time and the red curve, called the Aroon Down, measures the selling momentum. How does the Aroon measure momentum? In the Aroon Up it measures how much time it takes a pair to reach the highest level from the opening price at a given period. Conversely, in the Aroon Down, it measures how much time it takes the pair to reach a new low from the opening price.

In both the Aroon Up and the Aroon Down, the higher the indicator the stronger the momentum. So if the Aroon Up is high, it means buying activity is strong, and if the Aroon Down is high it means selling activity is strong. If both are high, then buying and selling activity is high, and if both are low, vice versa.

Aroon Indicator: Down to Practice

Now that we have established how to read the Aroon Up and the Aroon Down, it’s time to move into practice—how comparing the Aroon Up and the Aroon Down within the Aroon Indicator can help us understand the trend.

In the sample below we can see two zones, which I will call Zone A and Zone B. Each chart variation captures a different layer in the Aroon analysis and therefore each could provide a practical example on how to use the Aroon Indicator.

Zone A.

In Zone A, we can see that, around July(Point X) the EURUSD had just started a very strong bearish trend that subsided only in April 2015. Before the Bearish trend began, the Aroon Up was high and the Aroon Down was low. This indicates that buying activity was elevated while selling activity was low. Then in April, the Aroon Up was starting to fall and the Aroon Down jumped shortly after. What does it mean? It means a quick change of momentum because as soon as the buyers became exhausted the sellers immediately began piling in. Selling activity was high through to April 2015 while buying activity continued to fall.

Insights-

The sellers are substantially more dominant around Point X. The sellers were very quick to react, showing overwhelming conviction over the buyers around this point. Hence, it should be recognized by the trader as a substantial pivot.
Once the Aroon Down jumped it stayed at an elevated level and held almost a straight line, suggesting the selling momentum was especially strong and this means a trader could expect a strong bearish move.

Zone B.

In Zone B, we can see something interesting; while the Aroon Down fell until October 16^th, the Aroon Up was still staying low. So, while the sellers were out of the market, the buyers were not coming in, suggesting very weak buying appetite. Moreover, after October 16^th, the Aroon Up jumped and so did the Aroon Down; later, both fell and then both jumped again. That suggests that even after the nose dive the pair took, and even after some buyers came back, the buyers were hesitant to buy. Nevertheless, because the Aroon Down is also unstable it means that, at that level, the sellers were also somewhat hesitant.

Insights-

In the immediate time frame, the trader might expect the pair to trade with some sort of sideways momentum, with both the buyers and the sellers undecided.
When we look at the bigger picture and in the context of what happened before October 16^th it is clear that the sellers had the upper hand. And, even when the sellers were sitting on the fence, the buyers did not come in and even when they did they were still hesitant. This means that there is a rather high likelihood that the sellers will gradually comeback for more and that signals a high likelihood of another bearish wave once the sideways movement is over.

The Bottom Line

Of course, I always like to stress that no single indicator is perfect and the Aroon Indicator is no different in that respect. If the Aroon Indicator is not calibrated to the right duration or at other times during very high volatility the reliability of it might be lower. But, this is a very powerful Indicator, and the fact that it adds another layer to our analysis by letting us understand the behavior of both the buyers and the seller around each time frame and price zone makes it a powerful tool for those traders that focus on the long term.

Correction vs Change in Trend

May 3, 2016 by Lior Alkalay 4 Comments

How many times you have seen an FX pair, or any other instrument for that matter, start moving opposite to the trend? Did you wonder was it a mere correction or were you perhaps witnessing a change in trend? Your conclusion will have an acute impact on how you choose your next trade and thus your profit or loss.

Of course, it’s impossible to be 100% certain. But here are three simple methods that could help you decide which could dramatically improve your odds of being right.

Correction zone

The first method to identify a correction or a change in trend is one I like to call the “zone method.” The idea behind it is rather simple.

When a support line has also been a resistance line it’s no longer just support and resistance. Rather, it is a border trimming between two separate zones. One is a zone where the pair is bullish and likely to move higher. The other is a zone where the pair is bearish and likely to move lower.

If that zone hasn’t changed, then it’s a temporary correction. If the zone has changed, then it’s a change in trend. From the EURUSD chart below you can see when the 1.168 was broken back in 2014, the pair moved into a bearish zone. If the EURUSD had rebounded back to the bullish zone, then that would mean the trend had changed to bullish.

The Trend Average

The second method that is useful in gauging a correction or trend change is done by running a moving average. The trick here is to play with the average period until it captures nearly all the trend. You can also switch between an exponential moving average and a simple moving average. Sometimes, an exponential captures the trend better and other times, a simple moving average is all you need. The idea here is to tweak, or fine tune, if you will. In our case, the trend has to be below the average.

Once you have done that, you need to see how the current correction stakes up against the rest. If the latest correction is below the average then it’s a mere correction. If the average is broken, the trend has changed, just as can be seen in the chart below.

Notice that this method is usually effective where the trend is on a rather linear path. It might work on more volatile trends but it will not always be effective.

Failed Record

The last of the simple signals is actually more a matter of probability than a proper signal. And it’s actually the simplest to identify. Simply put it is when a pair fails to break a record and it doesn’t matter if it’s a record high or record low.

Usually, three is the lucky charm. Say the pair fails to break a record on the third attempt, as in the examples below. Then, there’s a higher likelihood that this is more than a mere correction. When a record high or record low is involved, there’s a much higher likelihood that this is not a mere correction but a change in trend.

In Conclusion

As you may expect, there are many more methods to differentiate between a correction and a change in trend. Some are more advanced and complicated. Others, like Fibonacci retracement which often times is used incorrectly, tend to be misleading.

While the methods above are far from perfect, the average trader might find that they are simple and easy to implement. They could, therefore, serve him well as he tries to determine if the pair is in correction mode or an actual change in trend.

Ground Rules for Day Trading

January 28, 2016 by Lior Alkalay 19 Comments

Day trading is challenging. Don’t let anyone tell you otherwise. The odds are stacked against you and the risks of loss seemingly lurks at every turn. That’s why it’s important to understand some ground rules about day trading. The rules are there so that you can safely swim with the sharks.

Range is Key for Day Trading

One of the most common mistakes with day trading is failing to identify the daily range. Say you’re planning to take a long on the EUR/USD. However, the pair’s already moved above its average daily range. What might be the result? Your trade could be doomed as the market tends to gravitate into its average range.

When you trade for a few hours most of the signals you count on are a few hours old. This means, essentially, that the signals are naturally soft and fluid. Markets, especially on an intraday interval, tend to gravitate towards its range. Thus fluid signals tend to be much less reliable.

Knowing the range of the interlay trade can lower your risk of loss. Moreover, used in your favor, it could also improve your gains.

How to identify the range?

There are many techniques to identify the true range, including the Moving Standard Deviation or Bollinger Bands. However, those techniques tend to be more effective on swing trading. When day trading, I always recommend starting with what I call the top to bottom approach.

That is a method to identify your support and resistance levels in higher intervals, say, daily. Daily is actually ideal because it’s two levels up, compared to just hourly. Then you apply those levels on an hourly trade. What you get are solid levels you can count on rather than the fluid hourly support levels.

Down to Practice

This is a chart we used to identify the daily range. Now, we drill down into our desired interval. In this chart it’s the hourly interval, where we can get reliable resistance and support levels for either shorts or longs.

Source: esignal

Be in and Out Quickly

You should never stay in a trade longer than you have to; that’s clear and common sense. This method can be more forgiving in longer duration trades, e.g., multi days to several weeks. However, in day trading, when trades are counted by the minute, then every minute counts.

Spend too long at a trade and there can be dire consequences. The market that is already less reliable at such low intervals could turn against you. And the chances this could occur continue to grow the longer your trade is open. Hence, you should always concentrate on minimizing the time your trade is open while maintaining a worthwhile profit.

Down to Practice

How do you implement this rule in real day trading? You make sure your limit per trade is much smaller than the daily range. Why? As you approach the daily resistance/support level, the odds start to turn against you. There is a greater likelihood that the market will turn around before your position has reached its “full potential.”

Trade small and target prices that are well within the daily range. That way, you improve your chance of hitting that “home run” and profiting from your position.

Beware the Trend

Of course, we’re all familiar with the old adage “the trend is your friend.” Well, to that I say if the trend’s a friend then who needs enemies? There’s a rule of thumb for day trading. If there’s a bullish long term trend (i.e. several weeks) and you’re trading a short then beware. The market will have a tendency to unexpectedly surge higher and move against you.

Implementation

Now, some day traders may simply avoid taking shorts in just such a scenario. Yet that doesn’t have to be the case. Instead, you might just take trades with significantly lower leverage. By doing so you balance out the risk associated with trading against the long term trend.

Autocorrelation

July 5, 2015 by Shaun Overton 11 Comments

It’s the 4th of July weekend. My wife is running errands this afternoon and my youngest son is napping. I can’t go outside for a run – it’s July in Texas (i.e., incredibly hot) and, what if the baby wakes up? The only ways to spend my holiday afternoon was either to a) watch TV or 2) dive into Michael Halls-Moore’s recent article, “Series Correlation in Time Series“.

I’m going to skip the math and keep this very layman friendly. There are some key take aways that even the most mathematically challenged traders can learn.

The Layman’s Guide to Correlation

Let’s go easy on the mathiness and remind ourselves what correlation is. Correlation is directly related to the angle between two points.

It’s easiest to understand in two dimensions because that’s what fits on a piece of paper or computer screen. The points (1,0) and (2,0) share an angle of 0°. Basically, the points lie on the same line.

Correlation is directly related to the angle between two points. These points lay on the same line, so the angles between each other are 0°. The fact that they are on the same line makes them 100% correlated.

Correlation is the cosine of the angle between two points. Get out a calculator and try it. The cosine of 0° is 1.

cos(0) = 1.0, which is 100% correlation.

Look at the image above. The points (1,0) and (2,0) share the same line. Doesn’t it make sense that points on the same line are 100% correlated? Points that are less than 100% correlated lie on different lines.

To keep this intuitive, you probably know from trading that a 60% correlation is worth paying attention to, but it’s not very predictive. What does that mean geometrically?

We want to get the angle where cos⁻¹(θ) = 0.6. Please don’t get caught up on the cosine stuff. I just want you to realize how this relates to angles.

The angle with a 60% correlation is 53°. They’re kind of close together, but not too close.

Those lines are pretty far apart. A 60% correlation between two forex pairs puts you in the same ballpark, but you’re hardly tracking pip for pip.

Forex prices are like points on the graphs above. 1 bar ago, 2 bars ago… 16,000 bars ago the prices of EURUSD were 1.11342, 1.11297…. 1.31974. The historical data on EURUSD forms a point in space. It’s 16,000 dimensional space, which is completely incomprehensible mentally, but it’s still a point. That means you can draw a line to it!

We usually talk about correlations in forex by comparing two currency pairs. Most traders know that EUR/JPY and GBP/JPY are correlated. You’re drawing a line between 0 and the EURJPY point, then drawing a line between 0 and the GBPJPY point, then calculating the angle to determine the correlation.

The EURUSD example only lets us draw one line. What if we compare the EURUSD against itself with a lag? That would let us draw two EURUSD lines!

The memory function

Using the EURUSD example, you naturally expect a 100% correlation if you drew the same line twice. It’s the same series of prices. That on its own doesn’t tell us too much.

The idea of autocorrelation is to lag the prices. Right now is 15:00. I can take the prices from 15:00, 14:00 and 13:00 and compare it with a one hour delay. The new delayed series are the prices from 14:00, 13:00 and 12:00. A one hour gap is 99.9% correlated with the original price series.

Michael’s article encouraged me to look at bigger and bigger time lags.

The correlation of EURUSD decreases against itself as the time lag increases.

The number on the horizontal axis is the time lag, done in groups of 100. The vertical axis shows the correlation.

EURUSD loses all its information after around 3,000 hours of data. That’s about the point where the correlation function reaches 0%.

Autocorrelation is often called the memory function. Traders can use this to ask themselves the question, “How far back in time can I go and still obtain useful information?” I can tell you with high confidence that if you’re trading one hour charts, it’s useless to consider anything beyond 3,000 hours.

My personal threshold for significance is a 75% correlation. EURUSD maintains that autocorrelation through 800 bars of data, which you can see on the chart if you zoom in closely.

The take-away for traders is that once you go past around 1,300 bars back, your information rapidly becomes less and less valuable.

Trading Lessons from 2008

May 13, 2015 by Lior Alkalay 2 Comments

2008 is remembered as the year of turbulence in the financial markets. It was a year when stock prices were in utter meltdown across the globe.

Metaphorically speaking, 2008 resulted in a good, old fashioned butt kicking. It was a painful, well-deserved lesson, but ultimately a useful one that would forever change the way I trade.

Let me lay it out for you…I was well entrenched in a Martingale strategy approaching an 85% loss. I was on the verge of imploding; every single moment – awake, asleep, didn’t matter – all I thought about was trading. I was obsessed with the next one – the one I believed would put me back in the black.

From Hero to Zero

I already had three years of lucrative trading under my belt; I considered myself a superstar. I was using the Martingale technique, a simple strategy using multiple orders on the EUR/USD. When the EUR/USD was bearish I placed one order after another, each set at the next resistance level.

It worked as follows; assuming a short position, every time you hit the stop loss (typically near resistance) it simultaneously triggered a new order. The new order, though, would be twice as large (2X) as the one before.

Back then, the strategy worked amazingly well because the Euro had moved, with nary a correction, in a single unwavering direction. The pair moved first lower then higher, allowing me to gain in both directions. With more than a thousand pips movement either way, it was a pretty sweet and very profitable “system.” Looking back (and clearly showing my naiveté), I believed I had cracked the “system;” that I alone had the “edge.” I foresaw very prosperous days ahead.

On December 8^th 2008, it all went haywire; a week earlier, the Federal Reserve Bank had announced the first round of stimulus. Within nine days, the EUR/USD surged a jaw dropping 2,000 pips.

The move on the EUR/USD was so quick and so aggressive that in a matter of days every order I had placed hit its stop loss. All of the profits I had made so “easily” over the previous months were completely wiped out, and then some. Everything I had built, all my “successes” and my dreams of prosperous days ahead, evaporated.

After days and days bouncing between self-flagellation and self-pity I did the only thing I could do. I took a deep breath and exhaled. I realized that that very awful event had all the earmarks of a positive learning experience, philosophically and practically. I vowed to learn, recover and prosper so that I would (fingers crossed) never have to live through it again.

Trading Lesson 1

With 20-20 hindsight, it’s obvious that a technique which raises risk as the market goes against you is a recipe for disaster. One day, the unexpected will occur and you will be unceremoniously thrown out of the game. So, lesson one: the amount (in Dollars, or Euro or Yen) you’re willing to risk in a trade should remain steady, even if you gain more and more.

What do I mean? Let’s say you have a portfolio of $100,000 and you risk $5,000 or 5%. If you gain over time and your account grows to $200,000 then $5,000 isn’t a 5% risk but a 2.5% risk. You’ve reduced your risk.

Why is this so important? Because the more successful you become, the greater the probability that your next trade could be a losing one. But if you reduce your risk as you gain then any potential damage can be minimized. Eventually, you may question whether or not you should you increase the amount you risk. Understand that it’s better to maintain a constant amount longer, as your risks will decline as you profit.

Trading Lesson 2

Always go up two intervals to check for support and resistance. Even if you only trade on a daily interval, you should check weekly and monthly intervals for resistance and support levels. Now, you’re probably asking yourself is that really necessary?

The answer is yes; because the higher you go on an interval, then the stronger the resistance/support. The resistance on a monthly level is certainly more significant than on a daily or hourly resistance. What you want to do is make sure that you’re not headed for a brick wall.

Trading Lesson 3

The longer the trading interval, i.e. monthly versus weekly versus daily, etc., the greater the impact fundamental and macro data will have on your trade. For example, if you trade on a weekly (or longer) interval then the decisions of a central bank or movements within an economy will determine your trade’s path.

On a long term trade, fundamentals rule and determine the direction. “Technicals,” meanwhile, let you time your entry and exit points and calibrate your risk. Given a trading style more aligned toward the longer term, this has been my most useful lesson. It has led me to specialize in macroeconomics so I can better predict how economics might affect my trade.

The Power of Pi

April 26, 2015 by Shaun Overton 53 Comments

One of my favorite TV shows is Nova on PBS, which recently showed an hour long feature on the history of math. Now I know that would put most of you to sleep, but my initial reaction was, “Sweet!”.

Not two minutes into the show, the moderator starts discussing the number pi (π) and all the unusual places where it shows up. It’s not just the ratio of a circumference to the diameter of a circle. It shows up in statistics and, oddly enough, in the distance between a river’s path and its distance as the crow flies.

Look at the map of the Brisbane River above. The blue line is the river while the red line is the direct distance. If you take the distance that the blue line travels with all the wiggles and bends in the river, then divide it by the distance of the red line, you should get a ratio approximating π.

Will the ratio of the river exactly equal pi? No. But if you take the ratio of all rivers in the world, then average them together, you should get something pretty close to π.

Does this apply to forex?

The alarm bell immediately goes off in my head. “Whoa, maybe I can use that for trading!”

So, I made a mad dash for the office. I mean seriously, like a full on sprint 30 feet racing to get a pen and paper.

The idea for forex is a little different. It’s possible for the price not to go anywhere in 50 bars. It might move 0 pips.

If I used the river formula of walk/distance and the distance equals 0, bad things happen mathematically. I made a minor adjustment and decided to compare the distance/walk, the inverse. The expected outcome is now 1/π.

Analyze the Power of Pi in R

R is one of my favorite analysis platforms. If you’d like to the code that, you can download it.

Getting the price data is easy. Just go to MT4 and click File, Save. The currently selected chart can then save it’s data. The R code opens up the csv and does the analysis. Each list will look like this after processing the MT4 data.

The last step is to take the mean of the ratio column on the far right.

I started doing that for different currency pairs on H1 charts and found something odd

Currency	Time Frame	Mean Ratio
EURUSD	H1	0.1614123
AUDNZD	H1	0.145748
GBPJPY	H1	0.1587237
USDSEK	Daily	0.182126

1/π = 0.318
The average of the values in the table is 0.162.
1/2π = 0.159

Now we’re on to something interesting! The ratio of distance to movement or any given currency looks like it might be 1/2π. I’ve only analyzed a handful of charts so far. This isn’t conclusive, but it’s an interesting early observation.

Graphs

The this is for those of you more analytically inclined. The probability distribution frequency histograms of these very different currency pairs appear to have equal slopes, if you normalize the frequency values.

Digital Signal Processing

The more that I’ve thought about this idea, the more that I realize it’s a pure concept from digital signal processing (DSP).

Engineers analyze signals like this and call it the signal to noise ratio. The idea is simple – how much real information is contained within the observed data?

Using 1/2π as our assumed barrier, we now have a convenient way to categorize market conditions.

Ranging markets – the signal to noise ratio (SNR) <= 1/2π

Trending markets – SNR > 1/2π

I did a quick check in R using the code

range<- audnzd$ratio[audnzd$ratio <= limit]
length(range)/length(audnzd$ratio)
[1] 0.6083298

According to this rough guideline, the market ranges 60% of the time and trends 40% of the time. If I use 1/π as the barrier for a strong trend, the relative frequency drops to only 8%-12%, depending on the instrument.

Conclusion: If you wait for the SNR to reach the weak trend zone above 1/2π before accepting any trend trades, then approximately 1 in 5 trades should experience a significant trend.

The logic runs as follows:

40% of the time is spent in a trend
8-12% of the time is spent in a strong trend
8/40 = 0.2, which is 20%. Strongly trending pairs may experience up to 30% significant trends.

How do you think we should use the SNR in a trading strategy? Share your ideas in the comments section below.

Want a Faster Entry Signal? Try MACD Histogram Bars

April 19, 2015 by Richard Krivo Leave a Comment

Traders who use the MACD indicator often are critical of the fact that it will signal an entry after the initial move has begun and, therefore, pips are left on the table. As such, many traders wanting to enter a trade sooner dismiss it as a “lagging” indicator.

In the case of the MACD indicator, the most widely used entry signal is when the MACD line crosses over the Signal Line in the direction of the Daily trend. Since these two lines are simply two moving averages, by their very nature the crossover will not occur until the move itself is under way. And, since that crossover is the entry signal, this will put the trader in the trade after the initial move has begun. Some traders prefer this method of entry as it offers more confirmation that the move is more likely to continue in that direction.

For more aggressive traders…

…who are not interested in the additional confirmation and are simply looking for an early entry, they may prefer a less widely used entry signal based on the histogram bars.

As seen on the historical 1 hour chart of the EURUSD below, as soon as price action begins to move to the downside, the green histogram bars will begin to shorten. As soon as a bar does not close above the previous bar, that means that the upside movement by price has subsided for that moment in time. An aggressive trader can use that as a signal to short the pair at that point.

For greater confirmation of the histogram entry…

Traders who are a little less aggressive may prefer to wait until a few histogram bars – perhaps 3 to 5 – in a row close continually lower in a downtrend or continually higher in an uptrend. This will provide greater confirmation than just one histogram bar but generally will be a quicker entry than waiting for the MACD line to crossover the Signal Line. As can be seen on the chart below, although the bearish move has begun, the crossover entry signal has not yet taken place.

Note how a trader entering based on the histogram bars would have entered the trade ahead of a trader who entered based on a MACD/Signal Line crossover.

Each of the above entries based on the MACD is a valid entry. As usual, it is up to each individual trader to decide which one is right for them.

Keep in mind however that entering a trade sooner means entering with less confirmation. That is not always a good thing.

All the best and good trading…

Regards,

Richard

RKrivoFX@gmail.com

@RKrivoFX

The Dumbest Money in the Market (Retail Forex Traders)

December 8, 2014 by Shaun Overton 7 Comments

I’m an FX industry insider. That’s what happens when you work in a business for nearly a decade. I know senior executives across a dozen major FX brokerages. And yes, that does come with major perks.

Today’s big score is extremely proprietary data on the positions of all retail forex traders in the EURUSD over 10 months. You may have watched my talk on sentiment trading and how retail forex traders are the dumbest money in the market.

That’s not an indictment of you personally. But, it is an indictment of the average Joe trading at home. He’s making all the classic mistakes to ensure he’s eaten by the sharks:

He doesn’t know anything about financial markets
He doesn’t have a trading strategy
He overleverages
When he does trade, he doesn’t like to use stop losses

That last one in particular really strikes me. Maybe he uses a stop sometimes. Other times, maybe he knows the risk of losing big on this trade so, just this once, he’s not going to use a stop. That probably rings true to everyone reading this post.

Example

What happens if we compare traders holding a long trade that use a stop loss against those with short trades. Here’s an example from live data to make things more concrete.

On July 25, 2014 at 17:00, there were 2,902 individual trades open in the EURUSD on this broker. Of them, 2,419 of them were long and 483 were short.

Only 110 tickets of the 2,419 longs had a stop loss attached, which is 4.5% of the total long orders. 44 tickets of the 483 shorts had a stop loss, which is 9.2%

My formula is pretty simple. Take the percentage of long orders with a stop loss and subtract the percentage of short orders with a stop. 4.5%-9.2% = -4.7%

What happens if you do that all the time?

The real question here is does this predict anything? Take a look at this chart. You won’t understand the numbers behind it right away, but you can see it’s the closest thing you’ll ever get to a straight line when analyzing financial data.

The average return on the next bar is strongly predicted by the percentage difference between long and short traders using stop losses.

Click on the image so you can see the numbers on the horizontal axis. When I calculated a number between -5% and +5%, such as in the example, that goes in the 0% bin. A number between 5% and 15% goes in the 10% bin, and so on.

Having calculated the bins, the next step is to ask “What is the average return on the next bar for each bin?” The 0% bin has an average return of roughly 0. The 30% has a hugely positive return and the -30% bin has a hugely negative return. It’s pretty simple, really.

The next step is to turn this into a trading strategy. I’m getting a bit ahead of myself, but I wanted to share this with my readers because it’s so clearly predictive.

If you work for an algorithmic trading fund and would like to get your hands on this data, then send an email to info@onestepremoved.com.

The SuperTrend Trading Strategy: Getting To The Root of Trend Following

December 6, 2013 by Andrew Selby 10 Comments

The root of any good trend following system is always the same: identify the direction a market is trending and ride that trend.

Anyone who has traded a trend following system already knows that this concept can be much more difficult than it appears. Trending markets are filled with reversals, pullbacks, and false breakouts. Periods where markets aren’t trending will often leave traders wondering whether their indicators are still working.

At the root of any good trend following strategy is the ability to identify the direction of a trend. That is exactly where the SuperTrend indicator excels.

Since identifying the trend direction is the root of a good trend following system, let’s take a look at a strategy that is based on identifying the trend.

Mark from Tradinformed recently published backtesting results of a basic Forex system that attempts to implement trend following in its purest form. The system uses the SuperTrend indicator combined with the 200-period simple moving average (SMA) to identify trends on the EUR/USD currency pair.

Here are the basic entry and exit rules for the SuperTrend Trading Strategy as Mark defined them:

Enter Long Position

When closing price is above 200 SMA and crosses from below to above SuperTrend
Or when closing price is above SuperTrend and crosses from below to above 200 SMA

Enter Short Position

When closing price is below 200 SMA and crosses from above to below SuperTrend
Or when closing price is below SuperTrend and crosses from above to below 200 SMA

Exit Long Position

When either Profit Target or Stop-Loss is hit
When trade is opened in the oppposite direction
When closing price crosses from above to below 25 EMA

Exit Short Position

When either Profit Target or Stop-Loss is hit
When trade is opened in the oppposite direction
When closing price crosses from below to above 25 EMA

Mark backtested this strategy over three separate 20,000 periods of 1-hour bars. He used a 5 ATR profit target and a 1 ATR stop loss.

The backtests started with an account value of $100,000 and ended with a value of over $1.3 million after a period of almost ten years. During that time, the system registered a profit factor of 1.15 with a winning percentage of 29% and a maximum drawdown of 38%.

Obviously, we would like to see a higher profit factor and winning percentage with a much lower maximum drawdown. The interesting thing about this SuperTrend strategy is that there is a lot of room to improve it. Because the strategy is so simple, there are dozens of options to add to it or tweak it in order to get different returns.

Simply adjusting the profit factor or stoploss could have a major impact on the returns. We could also try adding some sort of confirmation indicator to make the strategy more selective.

Cumulant Ratio Indicator

October 17, 2013 by Shaun Overton 2 Comments

Coursera is one of my favorite sites online. Two weeks ago, I finally had the opportunity to register for the course that I’ve been waiting for: Digital Signal Processing.

Digital Signal Processing is used in everything from music to communications to… predicting financial markets. Although it’s not the focus of the class, I already drummed up a few ideas worth exploring as indicators.

The first indicator idea that the course inspired, and the one that I’m the most excited about, looks for bars that are out of place with their peers. I arbitrarily chose a lookback period of 20 for my analysis.

Steps to calculate the cumulant ratio:

Calculate the average for periods 1-20
Calculate the sum of the absolute value of Close of the bar – average for bars 1-20
Calculate the sum of the Close of bar 0 (the last closed bar) – close of each bar, 1-20
Divide step 3 by step 2

The initial result looked as expected. I placed the absolute value bars on step 2 so that I wouldn’t have to worry about the average changing the sign of the output. The top function is only positive if the current price is “above” the sum of the last 20 bars. A negative position means that the current price is “below”.

Most markets are noise, which creates a natural noise band between ±1. Prices way out of line with the average show huge jumps like the one in the image.

Values around ±1 are expected. You wouldn’t, after all, expect a new bar to throw off the calculations very much.

That’s exactly the point. If something is near the ±1 window, then it’s probably worth ignoring. The price action is pure chop.

The real value is in the spikes. A spike of 20 isn’t any more important than a spike to 50. Above a certain threshold, the trader just needs to pay attention. It’s a black and white issue.

Strategy Ideas

My initial instinct was that the indicator would work well on emerging market currencies like TRY and ZAR. They’re so breakout prone that entering on the right side of the move, regardless of the reason, should do well.

It took about 20 minutes of chart gazing to come up with the strategy for the H4 chart. It was flat on most currencies, but USDZAR stood out. This equity curve used my initial settings without optimization. More importantly, the profit factor improved on a 1.5 year walk forward test.

The breakout strategy did great on USDZAR H4 charts

The majors showed exactly the opposite. They do trend, but hardly in the mega-monster manner of the emerging markets. I modified the strategy to do the opposite and let ranging conditions prevail. EURUSD, as seems to be usual with range trading strategies, stood out as the best performer.

The range trading approach works best on EURUSD H4

Nerd section

For the math nerds and programmers out there, the formula for the indicator is below.

The equation for the cumulant ratio