Bollinger bands stop loss

Tales From The Trenches: A Simple Bollinger Band® Strategy.

Bollinger Bands® were created by John Bollinger in the '80s, and they have quickly become one of the most commonly used tools in technical analysis. Bollinger Bands® consist of three bands - an upper, middle and lower band - that are used to spotlight extreme short-term prices in a security. The upper band represents overbought territory, while the lower band can show you when a security is oversold. Most technicians will use Bollinger Bands® in conjunction with other analysis tools to get a better picture of the current state of a market or security. (To learn more about how Bollinger Bands® are constructed see, The Basics of Bollinger Bands® .)

Most technicians will use Bollinger Bands® in conjunction with other indicators, but we wanted to take a look at a simple strategy that uses only the bands to make trading decisions. It has been found that buying the breaks of the lower Bollinger Band® is a way to take advantage of oversold conditions. Usually, once a lower band has been broken due to heavy selling, the price of the stock will revert back above the lower band and head toward the middle band. This is the exact scenario this strategy attempts to profit from. The strategy calls for a close below the lower band, which is then used as an immediate signal to buy the stock the next day.

Example 1: Intel Corp. (INTC)

Below is an example of how this strategy works under ideal conditions.

Figure 1 shows that Intel breaks the lower Bollinger Band® and closes below it on December 22. This presented a clear signal that the stock was in oversold territory.

Our simple Bollinger Band® strategy calls for a close below the lower band followed by an immediate buy the next day. The next trading day was not until December 26, which is the time when traders would enter their positions. This turned out to be an excellent trade. December 26 marked the last time Intel would trade below the lower band. From that day forward, Intel soared all the way past the upper Bollinger Band®. This is a textbook example of what the strategy is looking for.

While the price move was not major, this example serves to highlight the conditions that the strategy is looking to profit from. (For related reading, see Profiting From The Squeeze .)

Another example of a successful attempt using this strategy is found on the chart of the New York Stock Exchange when it broke the lower Bollinger Band® on June 12, 2006.

NYX was clearly in oversold territory. Following the strategy, technical traders would enter their buy orders for NYX on June 13. NYX closed below the lower Bollinger Band® for the second day, which may have caused some concern among market participants, but this would be the last time it closed below the lower band for the remainder of the month.

This is the ideal scenario that the strategy is looking to capture. In Figure 2, the selling pressure was extreme and while the Bollinger Bands® adjust for this, June 12 marked the heaviest selling. Opening a position on June 13 allowed traders to enter right before the turnaround.

Example 3: Yahoo Inc. (YHOO)

In a different example, Yahoo broke the lower band on December 20, 2006. The strategy called for an immediate buy of the stock the next trading day.

Just like in the previous example, there was still selling pressure on the stock. While everyone else was selling, the strategy calls for a buy. The break of the lower Bollinger Band® signaled an oversold condition. That proved correct, as Yahoo soon turned around. On December 26, Yahoo again tested the lower band, but did not close below it. This would be the last time that Yahoo tested the lower band as it marched upward toward the upper band.

Riding the Band Downward.

As we all know, every strategy has its drawbacks and this one is definitely no exception. In the following examples, we'll demonstrate the limitations of this strategy and what can happen when things do not work out as planned.

When the strategy is incorrect, the bands are still broken and you'll find that the price continues its decline as it rides the band downward. Unfortunately, the price does not rebound as quickly, which can result in significant losses. In the long run, the strategy is often correct, but most traders will not be able to withstand the declines that can occur before the correction.

Example 4: International Business Machines (IBM)

For example, IBM closed below the lower Bollinger Band® on February 26, 2007. The selling pressure was clearly in oversold territory. The strategy called for a buy on the stock the next trading day. Like the previous examples, the next trading day was a down day; this one was a bit unusual in that the selling pressure caused the stock to go down heavily. The selling continued well past the day the stock was purchased and the stock continued to close below the lower band for the next four trading days. Finally, on March 5, the selling pressure was over and the stock turned around and headed back toward the middle band. Unfortunately, by this time the damage was done.

Example 5: Apple Computer Inc. (AAPL)

In a different example, Apple closed below the lower Bollinger Bands® on December 21,2006.

The strategy calls for buying Apple shares on December 22. The next day, the stock made a move to the downside. The selling pressure continued to take the stock down where it hit an intraday low of $76.77 (more than 6% below the entry) after only two days from when the position was entered. Finally, the oversold condition was corrected on December 27, but for most traders who were unable to withstand a short-term drawdown of 6% in two days, this correction was of little comfort. This is case where the selling continued in the face of clear oversold territory. During the selloff there was no way to know when it would end.

The strategy was correct in using the lower Bollinger Band® to highlight oversold market conditions. These conditions were quickly corrected as the stocks headed back toward the middle Bollinger Band®.

There are times, however, when the strategy is correct, but the selling pressure continues. During these conditions, there is no way of knowing when the selling pressure will end. Therefore, a protection needs to be in place once the decision to buy has been made. In the NYX example, the stock climbed undaunted after it closed below the lower Bollinger Band® a second time. The strategy correctly got us into that trade.

Both Apple and IBM were different because they did not break the lower band and rebound. Instead, they succumbed to further selling pressure and rode the lower band down. This can often be very costly. In the end, both Apple and IBM did turn around and this proved that the strategy is correct. The best strategy to protect us from a trade that will continue to ride the band lower is to use stop-loss orders. In researching these trades, it has become clear that a five-point stop would have gotten you out of the bad trades but would have still not gotten you out of the ones that worked. (To learn more, see The Stop-Loss Order - Make Sure You Use It .)

Buying on the break of the lower Bollinger Band® is a simple strategy that often works. In every scenario, the break of the lower band was in oversold territory. The timing of the trades seems to be the biggest issue. Stocks that break the lower Bollinger Band® and enter oversold territory face heavy selling pressure. This selling pressure is usually corrected quickly. When this pressure is not corrected, the stocks continued to make new lows and continue into oversold territory. To effectively use this strategy, a good exit strategy is in order. Stop-loss orders are the best way to protect you from a stock that will continue to ride the lower band down and make new lows.

6 Ways To Place Stop Losses In The Most Effective Way – Pros And Cons.

Contents in this article.

Following a consistent stop loss approach is very important because it takes out the emotional and impulsive aspect of taking losses that so many traders struggle with. If you don’t really know where your stop goes, and you just put it at a random level, you are much more likely to mess with your stop – widening the stop that is in most cases – when price moves against you.

On the other hand, when you know where your stop goes (and why you place it there), because you use the same approach every single time, you will feel less tempted to break your stop loss rules and adhere to the initial plan.

We show you 6 ways, tools and concepts that can be used for stop placement and we explain the benefits and disadvantages of every single one.

Bollinger Bands.

Especially for trend following traders, the Bollinger Bands are a great tool for stop placement and for trailing your stop. In an uptrend you typically see that price moves higher close to the outer Bollinger Bands. A trend that is losing momentum will start pulling away from the outer band and gravitate towards the middle band. Keep in mind that the middle band is a moving average so it makes sense that during a trend price pulls away from the average and once price loses momentum, it comes back to its average.

Thus, trend following traders would place their stop above/below the middle band and trail it along with it as the trend moves on. A trader who prefers a more conservative strategy would place his stop outside the opposite outer Bollinger Band.

Trendline and Support and Resistance.

Trendlines are a famous tool when it comes to stop placement. As a natural support and resistance level, trendlines are used by many traders and the self-fulfilling prophecy plays into this equation. A trendline-break often signals the end or the weakening of a trend and it makes only sense to have your stop on the other side of a trendline so that you exit your trade when clear price signals are given.

The downside is that drawing trendlines can be subjective sometimes as it’s not always clear if you should go for wicks or candle bodies. Hence, we suggest to draw trendlines connecting the extremes (price wicks) so that you are on the safer side when it comes to stop placement and avoid false signals during premature volatility spikes.

Furthermore, support and resistance levels are often more suited for range environments since some of the concepts, such as moving averages and Bollinger Bands often lose their validity during ranging markets.

Adding a few points as buffer between the trendline and your stop is recommended. It is well known that many traders use trendlines and horizontal lines for stop placement and they make an easy target during squeezes.

Fibonacci levels.

Fibonacci levels also act as support and resistance and, thus, the concepts of support/resistance stop placement also apply to the Fibonacci method. After you have identified a potential trade entry and also found a reasonable 1-2 sequence for your Fibonacci tool, you can use the retracement levels as stop loss levels.

The disadvantage is that you are not always able to find a 1-2 sequence, especially within ranges or early on in a trend, and thus, using the Fibonacci method won’t work 100% of the time.

Moving averages.

We have briefly touched on moving averages when talking about Bollinger Bands. When price is in a trend, price pulls away from its moving average which makes sense. When the trend slows and reverses, prices will revert back to the average. Just throw up any price chart and see how prices fluctuate around the long term moving average.

Furthermore, the “well known” moving averages, such as the 50, 100, 200 daily moving averages act as natural support and resistance. Thus, it can pay off to have them on your charts and place your stops outside of those moving averages.

The ATR stop loss approach is a so-called dynamic approach since the size of the stop varies based on market volatility. When the ATR is high, volatility is high and price moves and fluctuates more; this would lead to using a wider stop loss to avoid premature trade exits when volatility is high. On the other hand, when volatility is low, you’d use a smaller stop loss and counter the effect of smaller price moves without sacrificing your reward:risk ratio.

The benefit of the ATR approach is that it works well with almost all other stop methods. If, for example, you are using support and resistance for your stops, you would simply add a bit more padding when the ATR is high.

Tip: The Keltner Channel visualizes the ATR on your charts and makes it easy to use the concept of ATR for your stop placement.

Price patterns and price formations – the natural price method.

This last concept is probably among the most commonly used strategies for stops. When you are trading pin bars, you just place your stop above/below the high. When you trade a Head & Shoulders, you enter on a break of the neckline and place your stop on the other side of the line. And traders who enter trades during pullbacks will typically place their stop just above/below the high/low.

The downside is that such stop loss placement is well known and often easy to spot. We call this the “amateur squeeze” where you see an obvious price pattern followed by a clear signal, but the follow through makes it hard to trade.

In one of his tweets Trader Dante talked about this topic and we borrowed his idea, since he described it perfectly; the image on the left is the result of his idea. Adding the ATR concept to price stop placement is often the best idea.

right-click , save picture as.

The time stop.

The concept of the time-stop applies to all previously mentioned stop loss techniques. If you enter a buy trade at a certain price with the rationale that price should go up, but it doesn’t and price just keeps hovering around your entry price, your analysis was wrong and the trade does not work out as anticipated. Staying in a trade where your idea is proven wrong right after the start is a gamble and you are not in a high probability trade. If you have the chance to get out cheaply, get out and don’t hope for something to happen.

The worst stop loss concepts.

Using a fixed stop loss is typically done because traders are lazy and don’t see the importance of having a reasonable stop loss in the first place. Just placing a random stop 5, 10 or 20 points away from your entries violates all sound trading principles. It’s like a basketball player who shoots the ball every time after having made two steps, regardless of where he is on the court and whether he has opponents that can block him easily or whether a team member is positioned better. You always have to put things into perspective and analyze what is happening on your charts. Shortcuts don’t work.

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Blast Buy & Hold with this simple Bollinger Band strategy.

In Episode 4 of the Better System Trader podcast, Nick Radge discusses some trading ideas he’s used to create profitable systems. He mentions a Bollinger Band idea which is also published in his book Unholy Grails. Nick says:

the strategy that we did test and showed very promising results was an entry using a Bollinger band and an exit using the opposite Bollinger band, but we use 3 standard deviations for the entry and 1 standard deviation for the exit, just to keep the trailing stop a little bit tighter.”

In Unholy Grails the strategy is used on the Australian stockmarket but in this article we’re going to test it on the Nasdaq 100 instead to determine if the strategy has potential in other markets.

The trading rules.

Firstly, here are the test parameters:

Period: Daily charts Universe: Nasdaq 100, using historical constituents to eliminate survivorship bias, data from Premium Data Test period: From 1/1/2005 to 1/1/2015. This period was chosen because it has a mix of bull and bear markets, along with high and low volatility Starting equity: $100,000 Maximum number of simultaneous trades: 6 Position size: Each position will be 1/6th of $100,000 Compounding profits: No Commissions: $10 each way Leverage: 0%

Now for the entry and exit rules. In Nicks book, he uses 100 period Bollinger Bands so we’ll do the same. The upper Bollinger Band will be 3 deviations from the central line, the lower Bollinger Band will be 1 deviation below the central line.

Entry: Buy on the Open the day after a stock closes above the top Bollinger Band.

Exit: Exit on the Open the day after a stock closes below the lower Bollinger Band.

Here is an example of an entry (10/05/2007) and exit for AAPL:

Comparing the results of the basic Bollinger Band strategy to Buy & Hold:

The annual return of the basic strategy is almost 20% better than Buy & Hold with less than 1/2 the drawdown. The equity curve of the basic strategy shows a general rise in equity with a few periods of drawdown:

Adding a market filter.

A market filter is used to switch a strategy on or off based on broader market conditions. As this is a long only system we probably don’t want to enter trades in a bear market so we’ll only enter trades when the index is rising. With the S&P 500 the most frequently used index by financial professionals, we’re going to use that for the index filter.

In this test a bull market will be defined as the index closing above the 100 day simple moving average; when the index closes below the 100-day moving average it is a bear market and we won’t enter trades until prices closes back above the 100 day moving average. The 100 day moving average was chosen to match the Bollinger Band value, other moving average lengths may work better but will need to be tested. The results:

The index filter has improved the quality of the strategy, with a higher return, lower drawdown and higher win/loss ratio with fewer trades.

There are periods during the test where more trade entry signals are presented than we can take using a maximum of 6 positions, so we need to decide which stocks to choose when this happens.

Let’s try a basic ranking strategy in order to systematise the selection process.

When a number of stock entries occur on the same day we need to make a decision on which ones to take. We could choose them randomly but we would need to run monte carlo simulations to get a better indication of the possible variations using this method. I prefer to add a simple ranking system to the strategy so stock selection is completely systematic.

The ranking strategy I’m going to use here is based on what I think the strategies strength is. I expect the strategy will perform best either just after a bear market or a period of consolidation, entering at the start of a new bull market or breaking out of consolidation and riding it higher. In this case, we’re going to try ranking by Rate of Change over the last 90 days, so the stocks with the smallest Rate of Change will have a higher priority than those with a large Rate of Change. Logically it makes sense but what do the results tell us?

The ranking strategy produced a higher annual return, with lower drawdown, a lower number of trades and a higher win %. It may have not impacted too many trades so the addition of the ranking may not be statistically significant but it does provide a systematic method to choosing stocks when multiple opportunities present themselves.

The power of Compounding.

So far we’ve seen the basic strategy slightly outperforms Buy & Hold but with considerably lower drawdowns. The inclusion of an Index Filter and ranking by smallest ROC has improved the strategy although the results aren’t outstanding.

Let’s see how compounding profits impacts strategy results:

Update 27/4 – As requested by Rick, here is a histogram of distributions, with the majority of trades in the -25 to +70% range and a few trades with 100% and higher:

With compounded profits we now have a strategy that produces more than double the returns of Buy & Hold with only half the drawdown. The win rate of 73.33% and win/loss ratio of 3.33 are also good for a trend following system.

It appears the strategy has some potential and warrants further investigation. Some areas of consideration could be:

The length of the Bollinger Bands, Different market filters, More adaptive trailing stops, Ranking based on other metrics, Suitability to other markets.

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Related Posts.

Hans van der Helm.

Thanks for the very interesting article “Blast Buy & Hold with this simple Bollinger Band strategy”. I’m using Amibroker as well. Is it possible to post (or send me) the code of this system?

Thanks in advance.

Hans van der Helm.

Hi Hans, I’ve just ed you the AFL code, hope it helps.

Andrew - Thanks for the write up. I am interested in the afl. Appreciate your work on this.

Thanks Derrick, I’ve ed you a copy of the AFL.

Thanks for the great information. Could you please the afl? Thanks.

This strategy is stocks only strategy?

Hi Casey, I’ve only tested it on stocks however it may work on futures/forex etc.

I can provide the AmiBroker code if you want to test it for yourself?

Nice article. Can you please send the AFL code?

Thanks Bob, I’ve just sent you the AFL code.

Thanks for that interview with Nick and the analysis of his Bollinger Band system.

Looking forward to the AFL code.

Cheers John, I’ve just sent you the AFL code.

Really enjoying the podcasts and the great information you provide. Could you please send through the AFL code.

Thanks Paul, glad you’re enjoying the podcast.

I’ve just ed you the AFL.

Good article, I really enjoyed it. Could I also have the AFL to play with?

Hi Rick, the AFL code is on its way.

Thanks a lot, got it!

Two things: (a) Could you post results from index start? Although there is a downtrend, the chose period has two uptrends.

(b) What was the contribution of AAPL and GOOG in the results? If you were to remove those companies from the index, what would be the result? I’m saying this because it is unlike;y to have similar companies in the near future. To what degree are your results influenced by a few outliers?

Great point about considering the outliers.

I checked the trade results and the trades with the highest returns weren’t actually AAPL or GOOG. In fact, the strategy didn’t take a trade in GOOG at all and AAPL was only the 3rd highest, here are the top 5:

If I remove all the AAPL trades, the Annual Return is 18.43% and DD is -23.60% so the returns are slightly lower but who’s to know what will happen in the future – AAPL may continue higher, another stock could take over, this strategy may fail miserably tomorrow, we just never know.

Thanks! Still I am concerned about outliers. I would be nice if you could add to the blog a histogram of returns per stock traded, maybe at least the top 30 ones. Then it will be clear if the performance was due to a few random outliers or due to the method. Apologies for the request but I do not have the data to do it, otherwise I would.

Hi Rick, I’ve added a chart showing the returns. The bulk of the trades are in the range of -25 to +70%, with a few +100% or higher. I hope that answers your questions.

Please keep in mind that this research is not a complete trading system, it is just a starting point. The purpose of the research was to determine if the strategy that Nick mentions in the podcast has potential in other markets. It appears it may but further investigation obviously has to be completed before taking it further.

If you can I highly recommend getting some data and running some of these tests yourself, I’m sure the strategy could be improved so I’d be interested to hear your results.

Great write up. It’s amazing what a a simple system with just a few tweaks can do. I’d appreciate a copy of the AFL code so I can see if I can make a few other tweaks that might help. Thanks.

Hey Gav, glad you enjoyed it.

Yes, I’ve found the simple systems are often the best, I look forward to hearing what you uncover in your testing.

The AFL is on its way.

Nice methodology! I’d love to get a look at the strategy’s code, please 🙂

Hi Ran, have just sent you the code.

Nice article, can u please mail me the code so i can test it on instruments i trade.

Cheers Mandeep, just sent you the code.

Hello Andrew, Thank you for the great Information and Podcasts. I also enjoyed the interview with Cesar Alvarez. I´m looking forward for more Podcasts with real Traders. Could you please send through the AFL code.

Thanks Juergen, I’ve just sent you the AFL code.

Keep an eye out for the next few episodes, we have some awesome traders coming – Kevin Davey, Gary Stone, Rob Hanna, Howard Bandy and more.

Simple works best and that’s what this system is. I like many of the concepts used in this system.

Some of my concerns or ideas for improvement are:

1) The high winning percentage. I would expect this to come down over time and be closer to 50%.

2) A sample size of 60 isn’t really enough to draw too many wide ranging conclusions.

3) Also having a max of 6 open trades is a bit on the risky side for me. It really doesn’t provide enough protection against specific risk.

4) Dividing capital equally among the 6 open positions could be improved to something along the lines of fixed fractional or volatility adjusted position sizing to help control risk better.

Love the website and podcasts. Keep up the great work!

Could you send me the AFL code?

All valid concerns which need to be investigated further, I’ve sent you the code.

Keep in mind that Nick Radge uses this strategy on the ASX and it produces better results than the results in this test, which tells me the strategy is robust. If you want more details I highly recommend you check out his book Unholy Grails.

Hi Andrew. Loving the podcasts! I’d like to hear some more about your own background and trading style in a future podcast.

Can you please send me the AFL. I’m a huge fan of Nick’s work.

Hey Ashley, glad you’re enjoying the podcast.

You can read a little about my background and trading in the About page on the website or in podcast episode 000 available in iTunes but it’s a good idea to include it in a future podcast episode so I’ll do that too.

I’ve just ed you a copy of the AFL code.

Good Work. Please send the AFL code.

Hey Emil, have just ed you the AFL.

Hi Andrew, your doing an excellent job with the podcasts and I’m really enjoying them, keep up the great work and when you have a chance could you please send me the AFL code.

Thanks Glenn, glad you’re enjoying the podcasts, I just ed you the AFL code.

I’d like the AFL code too please. Just getting started with AFL and need all the good sample code I can read.

I’m especially interested in your thoughts on the 100 day moving average as a long-term bull-bear indicator… do you have any other long-term bull-bear-sideways indicators that you use, or have references to others using?

Hi Paul, I’ve just sent you a copy of the AFL code.

If you’re just getting started in AmiBroker, I recommend you take a look at the AmiBroker book by Howard Bandy here, it’s a free download for personal use.

If you’re more interested in a course, check out the AmiBroker course by Cesar Alvarez here. Cesar has offered to open his AmiBroker Backtesting 101 course to Better System Trader podcast listeners. The course will teach you how to program strategies from beginning to end and even provides you with a strategy that averages 20%+ returns per year. The offer is only valid until May 20th and numbers are limited so get in quick.

As for ways to determine bullish/bearish conditions, I’ve found simple methods are the most effective, like moving averages, volatility indicators etc. Keep an eye out for the podcast interviews we release on May 18th and May 25th where we discuss more about this.

Nice article, I’d like to see the Amibroker code too. Thanks.

Thanks Barry, I’ve just ed you the code.

Very impressive results for such a basic system. Certainly not over-optimized.

I’m interested. Could you please send me the AFL code.

Hi Peter, have just sent you the AFL code.

I know I’m a pain but I insist that you remove from the list the top 4-5 stocks.

How does CAR change?

Hi Rick, if I remove all GILD, BIDU, AAPL and EXPE trades the CAR has reduced as expected, down to +15.57% with -23.60% drawdown. It still beats Buy & Hold of +9.88% CAR with -52.81% drawdown but there is obviously more scope for improvement.

I encourage you to use this strategy as a starting point only, it is by no means a complete strategy and I’m sure there are many ways it can be refined.

Thanks. I( agree. Good work!

JanWillem den Boer.

Could yo sent met the AFL Code.

Thanks JanWillem, just sent you the code.

Hi Jan, your spam filter is blocking the so I cant send to you, can you fix or me andrewbettersystemtrader with another address and I’ll resend.

janwillem den boer.

I have sent you my gmail address by seperate mail.

Hi Andrew, thanks for the podcast. Really appreciate your effort. Could you help with the code. Also wondering have you tried a long/short variation.

Hey Vivek, glad you like the podcast.

I haven’t tried a long/short variation, please let us know how you go if you test it yourself.

Have just sent you the AFL.

I’m learning Amibroker and find it helpful working through other peoples code and understanding how the logic has been coded. Would love a copy of your AFL code for this system.

Just sent you the code.

Nice article. Can you please send the AFL code?

Hi Miro, have sent you the code.

Many thanks for this interesting article. Would it be possible to have a copy of the Amibroker code?

Have a good one!

Hi Stephane, glad you liked it, have just sent you the AFL code.

Could you please send me the afl code. I am interested in further studies.

I’ve just sent you the code.

Is it possible to get the AFL code?

Hi Nir, click the blue ‘Download the FREE Bollinger Band code for AmiBroker’ button at the bottom of the article to download the code.

Thanks for the strategy. I have seen so many promising strategies that trade only LONG. I am yet to see a strategy trading profitable both LONG and SHORT. This would be a one up for your site if you could get an expert to write up an article on such a strategy. Regards.

Hi Perry, thanks for the comment.

Check the blog next week, Rob Hanna provides a simple trading idea that does exactly that!

I’m really enjoying your podcasts and blog. May I please have a copy of, the AFL for this post.

Hey Growbuck, click the Blue download button just above the comments section to download the AFL code.

Great post, i’m learning the amibroker to develop the trading strategy. Lucky to see your website. May i get the afl code for deep studying? Thanks.

Hi, click the blue download button on the page to get the AFL code.

May I please have a copy of, the AFL for this post.

Hey Phil, click the blue Download button just above the comments to get a copy of the code.

Just found your podcast and this was the first one I listened to – GREAT stuff. Thank you!

Thanks Simon, glad you enjoyed it.

thanks for this great post. I would like to use the code to learn how to program an efficient strategy. Please send me the AFL code.

Hi Philipp, click the blue Download button just above the comments to get a copy of the code.

Dear Mr Andrew Swanscott.

Can you please send me the AFL code for this as I am using Amibroker and would like to back test the same.

Hey Ashok, click the blue download button to get the AFL code.

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[…] Blast Buy & Hold with this simple Bollinger Band strategy [Better System Trader] In Episode 4 of the Better System Trader podcast, Nick Radge discusses some trading ideas hes used to create profitable systems. He mentions a Bollinger Band idea which is also published in his book Unholy Grails. Nick says: the strategy that we did test and showed very promising results was an entry using a Bollinger band and an exit using the opposite Bollinger band, but we use 3 standard […]

[…] Källa: Blast Buy & Hold with this simple Bollinger Band strategy – Better System Trader […]

Trading stocks, options, futures and forex involves significant risk of loss and is not suitable for everyone. Past performance is not necessarily indicative of future results.

DigitalCommonsLiberty University.

Senior Honors Theses.

Bollinger Bands and Stop-Loss Orders: An Econometric Analysis.

The use of Bollinger Band trading strategies has become increasingly popular since Bollinger Bands were conceived in the 1980s, yet little documentation exists measuring Bollinger Band trading strategy performances in market conditions post January 1, 2000. This study examines the efficacy of a representative sample of Bollinger Band trading strategies against a standard buy-and-hold strategy spanning each sector, and relative beta in market conditions post January 1, 2000. Among these strategies was John Bollinger’s recommended volatility breakout trading system.

Twenty-eight strategies were tested on 245 securities for a total of 6,860 backtests. Not one Bollinger Band Strategy consistently outperformed a standard buy-and-hold strategy. Additionally, the volatility breakout system failed significantly in every circumstance when compared to a standard buy-and-hold strategy.