Fill The Gap: The Official Podcast of the CMT Association

Episode 12: John Bollinger, CMT, CFA

December 10, 2021 John Bollinger, CMT, CFA with Tyler Wood and Dave Lundgren, CMT, CFA Season 1 Episode 12
Episode 12: John Bollinger, CMT, CFA
Fill The Gap: The Official Podcast of the CMT Association
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Fill The Gap: The Official Podcast of the CMT Association
Episode 12: John Bollinger, CMT, CFA
Dec 10, 2021 Season 1 Episode 12
John Bollinger, CMT, CFA with Tyler Wood and Dave Lundgren, CMT, CFA

What are the first principles of the market?
Listeners this month will embark on a journey of original research. By examining the life and career of John Bollinger, CMT, CFA we will better understand how to identify the foundational elements of any market and begin the investigative process that leads to robust, durable investment processes.
Stripping away assumptions, and digging into how indicators are calculated, how data is structured and represented, and what actually drives price will aid traders and investors worldwide in developing their own process and edge.
Fill the Gap covers a lot of ground this month, including: 

  • Why volatility is an opportunity
  • Why delivering consistent returns is far more important than picking market tops and bottoms
  • How Bollinger Bands and companion indicators were developed and why
  • Why optimization misleads system developers toward continuously fragile investment strategies

John is a lifelong student of the markets who has observed how structural changes and the advent of new investment vehicles have changed trading for each new generation – from the launch of options to the early days of cryptocurrency trading. From this perspective, he emphasizes how important it is to go back to the original source material and the forgotten legends of the markets who had a more intimate relationship with their trading as all their computation, calculation, and charting was done by hand.
This final episode of Season One is a launchpad for further investigation into the markets, demonstrating how thinking like a scientist will help all investors identify tools that provide an edge to the First Principles of the Markets.
To better understand the concepts covered, and current market commentary, we recommend reviewing the supplemental resources accompanying this episode using this link:

Fill the Gap, hosted by David Lundgren, CMT, CFA and Tyler Wood, CMT brings veteran market analysts and money managers onto a monthly podcast.

For complete show notes of every episode, visit:

Give us a shout:
@dlundgren3333 or
@_TBone_Pickens or
@CMTAssociation or

CMT Association is the global credentialing authority committed to advancing the discipline of technical analysis in the financial services industry. We serve members in over 137 countries. Our mission is to elevate investors mastery and skill in mitigating market risk and maximizing return in capital markets through a rigorous credentialing process, professional ethics, and continuous education. CMT Association formed in the late 1960s with headquarters in lower Manhattan, NY and Mumbai, India.

Learn more at:

Show Notes Transcript

What are the first principles of the market?
Listeners this month will embark on a journey of original research. By examining the life and career of John Bollinger, CMT, CFA we will better understand how to identify the foundational elements of any market and begin the investigative process that leads to robust, durable investment processes.
Stripping away assumptions, and digging into how indicators are calculated, how data is structured and represented, and what actually drives price will aid traders and investors worldwide in developing their own process and edge.
Fill the Gap covers a lot of ground this month, including: 

  • Why volatility is an opportunity
  • Why delivering consistent returns is far more important than picking market tops and bottoms
  • How Bollinger Bands and companion indicators were developed and why
  • Why optimization misleads system developers toward continuously fragile investment strategies

John is a lifelong student of the markets who has observed how structural changes and the advent of new investment vehicles have changed trading for each new generation – from the launch of options to the early days of cryptocurrency trading. From this perspective, he emphasizes how important it is to go back to the original source material and the forgotten legends of the markets who had a more intimate relationship with their trading as all their computation, calculation, and charting was done by hand.
This final episode of Season One is a launchpad for further investigation into the markets, demonstrating how thinking like a scientist will help all investors identify tools that provide an edge to the First Principles of the Markets.
To better understand the concepts covered, and current market commentary, we recommend reviewing the supplemental resources accompanying this episode using this link:

Fill the Gap, hosted by David Lundgren, CMT, CFA and Tyler Wood, CMT brings veteran market analysts and money managers onto a monthly podcast.

For complete show notes of every episode, visit:

Give us a shout:
@dlundgren3333 or
@_TBone_Pickens or
@CMTAssociation or

CMT Association is the global credentialing authority committed to advancing the discipline of technical analysis in the financial services industry. We serve members in over 137 countries. Our mission is to elevate investors mastery and skill in mitigating market risk and maximizing return in capital markets through a rigorous credentialing process, professional ethics, and continuous education. CMT Association formed in the late 1960s with headquarters in lower Manhattan, NY and Mumbai, India.

Learn more at:

John Bollinger, CMT, CFA, is the president and founder of Bollinger Capital Management, Inc., an investment management company that provides technically-driven money management services and develops proprietary research for institutions and individuals. He is probably best known for his Bollinger Bands, which he developed in the early 1980s. Traders and investors worldwide use Bollinger Bands to assess expected price action in the financial markets, and the bands are featured on most financial charting software and websites. His book, Bollinger on Bollinger Bands, was published by McGraw-Hill in 2001 and has been translated into twelve languages.


John Bollinger book: Bollinger on Bollinger Bands

Garfield Drew book: New methods for profit in the stock market (1950)

Robert Rhea book: The Dow Theory

Richard Wyckoff books

Humphrey Neil books: Vermont Ruminator, The Art of Contrary Thinking, and Tape Reading and Market Tactics

H. M. Gartley book: Profits in the stock market

Richard Schabaker books: Edwards & McGee Technical Analysis and Stock Market Profits and Stock Market Theory And Practice

In 1951, Frank Vignola and his wife Maude V. Woods, publishing in San Francisco, used OBV for stock trading. More information in this presentation from George Schade Jr:

Excerpt from The tragic neglect of the old masters by James Alphier:

I still become physically queasy when I recall my shock and surprise as I read a short article written by James Dines some years ago. In it, he related how he had asked an assemblage of [CMT] Association members how many of them had read anything written by the “founding fathers” of technical analysis. Only a handful gave a positive response.

The same feeling returned almost four years ago when I became involved in a rather complex discussion with three [CMT] members. I referred to concepts originated by Garfield Drew and Paul Dysart and suddenly got blank looks. One person “thought” he “might have heard Drew’s name.” Fortunately, I retained enough tact not to state my real opinion: that not being familiar with these names was tantamount to, say, an economist not knowing who Marx and Keynes were.

And, finally, this same physical despondency recurred just a month ago when one of the largest investment book dealers specializing in out-of-print items closed its doors. I went down there and spent a great deal more than I probably should have, compelled by the thought that I wouldn’t have many more chances to buy some of these old, great works that I hadn’t already obtained.

To me, having read and experimented with everything I could that related to technical analysis for the past 30 years, the smug, placid neglect of the old works in our field — a neglect that sometimes crosses the border into scorn — is incomprehensible. The fact is that, with too few exceptions, these “old masters” almost page for page had more overall knowledge, far better “feel” and understanding of the data, superior mastery of basic concepts, and a far wider imagination than current technicians (including myself). Working without computers or even hand-held calculators, they somehow had insights that today have been lost, simplified to elementary gloss or just plain grossly distorted.


Tyler Wood  00:13

Welcome to Fill the Gap, the official podcast series of the CMT Association, hosted by David Lundgren and Tyler Wood. This monthly podcast will bring veteran market analysts and money managers into conversations that will explore the interviewees’ investment philosophy, their process and decision making tools. By learning more about their key mentors, early influences, and their long careers in financial services, Fill the Gap will highlight lessons our guests have learned over many decades and multiple market cycles. Join us in conversation with the men and women of Wall Street, who discovered, engineered, and refined the design of Technical Market Analysis. Fill the Gap is brought to you with support from Optuma, a professional charting and data analytics platform. Whether you are a professional analyst, Portfolio Manager or trader, Optuma provides advanced technical and quantitative software to help you discover financial opportunities. Candidates in the CMT Program gain free access to these powerful tools during the course of their study. Learn more at

Good afternoon, Dave Lundgren, welcome to Episode 12 of Fill the Gap. How are you today?


Dave Lundgren  01:57

I’m doing excellent Tyler, happy holiday season to you.


Tyler Wood  02:00

Happy Holiday season to you as well. And to all of our listeners. This does mark the end of Season One, our first year of doing this fantastic project. I just wanted to thank Mathew Verdouw, the team at Optuma for supporting this, taking a chance on us; we appreciate certainly all of the help from the CMT Association staff in producing each of these episodes, and to you all of our listeners for tuning in. Stay with us, asking great questions, sending in feedback suggestions for further guests. Remember, you can – you can always reach me at And then of course, we have to thank our illustrious guests from Bob Farrell, all the way to this month’s interview with John Bollinger Dave, for anybody who’s new to Fill the Gap. This seems like the right time for an advent calendar of podcasts, you know that the 12 days of Fill the Gap for you in December?


Dave Lundgren  02:50

Well, you’re the drummer and the musician, you may as well come up with the soundtrack for that idea.


Tyler Wood  02:54

That’s right, you know, well, while people are taking a break from the trading desk, you know, you could just pop on a little fill the gap in the background. Since I started at the association, I’ve heard that we exist to help advance the discipline of technical analysis, which is a really big mission statement, and really difficult to define how somebody would do. I feel like our guest this month, has really spent a lifetime articulating how somebody goes about coming up with original thought, solving a market problem with your own research, rather than just taking, you know the work that other people have done. So I know for you and for me first principles is really the the main concept of this month’s episode. Talk to us a little bit about what your takeaways were from John.


Dave Lundgren  03:39

Yeah, I mean, it’s that – it’s the the first principles concept. I think that not enough people think about that idea when they’re either developing systems or making decisions in the market. And just recognizing that with it with respect to markets in particular, or really any organism or system, there’s always first principles that relate to that, that organism and then it’s basically these concepts that are reduced down to the basic, the most basic elements of that structure, such that you can’t reduce them any further. And if you can, if you start there with your system development and build from there, and frankly, don’t deviate from those basic principles, then what you should what you end up with should be robust, it should work through time and overtime, different cycles, etc. So, Tyler, one of the concepts that you’ve heard me talk about in our presentations together and I really leaned heavily on this concept when I was teaching at Brandeis is that is the checklists of trend change. And and I refer to them as the inviolable rules of trend following and these are, these are trends in concepts that must happen in the market in order to in order for trend to actually change. And if and until these four items, these boxes can be checked. You don’t have to worry about trend changing. And these concepts are based on things that we teach in the CMT curriculum and, and yes, trend line breaks, moving average crosses the change in the direction of the moving average. These are base courses. principles that are sort of foundational to trend following and they have to happen. This you know, as for a stock to go from 20 to 80, there’s a lot of fundamental reasons for why that could happen. It could be expanding margins, accelerating growth, new product, new product announcements, something that the competition did, something that the government did, all these different things do management could drive a stock from 20, to 40. So it could be any reason, could be just simple valuation expansion. But technically, there are four things that must happen before a stock can go from 20 to 40. And that’s the power of this core sort of principle process or theory or thought process, if you will, what I really liked about our conversation with John is how we kind of rerouted everybody to that notion that start with a core, these principles, and then build from there and don’t deviate from them.


Tyler Wood  05:48

The need for a bedrock or a foundation to be built on which could extrapolate it can’t be overstated. And John is just such a unique individual. I want to encourage everybody who’s listening to this episode, not to miss you know, he just glossed over the fact that he built his own computer. When when there were no computers for sale. This is a person who, who really does investigate down to the smallest level, how the sausage is made, how things are built. And I think, you know, in kind of the closing of this interview, we were talking about just how popular technical tools are technical indicators, technical analysis concepts, but there is such a lack of awareness to really how those indicators are calculated, and what they’re telling you even how the data is being represented to you. I hope that our listeners find this conversation as fascinating as I did. I have to admit, I get a little sheepish around John voluntaries is kind of an idol. I get a little starstruck, but this was such a pleasure and such an honor. And looking forward to having John at future conferences for the CMT Association.


Dave Lundgren  06:50

Yeah, I’m sure that’ll happen. You know, just in reference to what you were just talking about how, back in the day when before there were computers, which for our listeners, by the way, when when Tyler says if he made his own computer before computers were for sale, I mean, I think you were talking in the early 80s, late 70s. Right, this was when he was actually assembly computer. So this is how smart this guy is. But also at around that time, there weren’t there were no such things as computers, it calculated indicators and things like that. So to the extent that you used indicators you had, you had to actually things as simple as moving averages, or whatever indicators, Welles Wilder developed a bunch of indicators in the 70s. All that had to be done by hand. And so it’s a blessing that we have all these chart, pack toolkits together that just press a button and you have stochastics. But and that’s definitely advantage from a scalability process. But what we lose is being intimately aware of what happens to the indicator under certain market conditions. And we know that because we calculate it by hand, you can actually know ahead of time, if the market does this tomorrow, this indicator will do X, if it does this tomorrow, it’ll do Y. And that’s a significant advantage. Not only do we not do that, but we don’t even we don’t even really know how indicators are calculated today, because it’s all done for us. So there’s a lot to be said for the lost art of indicator development and use.


Tyler Wood  08:04

Yeah, I’ve heard a lot of veteran technicians talk about the power of charting by hand and you get a feel for the market. I felt like John articulated so well what that power is of really understanding the tools that you’re using. And for anybody out there who has an interest in technical analysis. You’ve been hearing from these illustrious guests, by all means pick up a copy of the CMT Association curriculum, get registered for those exams, because that is that is the bedrock of all these ideas are built on start from the beginning. Don’t be afraid of a little education. And with that, Dave, let’s go get educated from John Bollinger, CMT CFA.


Dave Lundgren  08:45

Welcome to Fill the Gap, the official podcast of the CMT Association. This particular episode marks our one year anniversary from when Tyler and I launched fill the gap. So we’re especially proud to have as our guest this month, the one and only John Bollinger, if you’re thinking now that theme sounds really familiar. Well, it should but trading community has John Bollinger to thank for having developed in generously shared his iconic volatility based indicator the Bollinger Band, although John is most well known for Bollinger Bands, he’s actually developed an entire suite of related indicators, which we’ll talk about. John is the world’s first dual CMT and CFA charter holder, author of the book Bollinger on Bollinger Bands, past member of the CMT Association’s board of directors and as if that weren’t enough, he is the lead Portfolio Manager at Bollinger Capital Management. And of course, I remember John, from his years as the chief market analyst at financial news network, the predecessor to CNBC, which I really love following and watching John on that show. So without further delay, John Ballinger, welcome to the one year anniversary episode of fill the gap. David Tyler,


John Bollinger  09:53

Thank you very much for having me.


Dave Lundgren  09:55

It’s a real pleasure to have you here, as I said, an iconic member of the technical community so it’s So really excited, exciting to have you here. Looking forward to this conversation. Typically, what we’ll do before we jump into the meat of the conversation is just give you an opportunity to to inform our listeners as to your background, what got you into the business. And you know, what brought you to where you are today. So I’ll just spend a little bit of time on that. And then we’ll jump into indicators. And like.


John Bollinger  10:18

I started my professional life as a camera person in the film industry, grew up in New York, and that camera work took me to California, about that time, literally, about the time I arrived from California, my mother, who had a small advertising agency decided to retire and she was having some problems with her advanced financial advisors, aka they were taking advantage of her. So she called up she knew I was interested in stocks in the stock market, such like that and asked me if I would take over her portfolio, which I did. And, you know, I tried to do it the traditional way with brokerage house reports and fundamental research and such like that. And that just didn’t work for me. I was very fortunate at the time to meet a couple people who are interested in technical analysis. And I started diving into the discipline. And I found that it helped my results tremendously. So gradually, over a period of a few years, I went from trying to do the classic sort of feel your way through the markets to a more discipline technical approach. And my results started to improve. I’m happy to say that my mother when she finally passed, had more money than when she retired. So I have technical analysis to thank for that.


Dave Lundgren  11:34

What year was this? John? When did you kind of get started in transition and technical?


John Bollinger  11:38

I’m moved to California in 76. And I was involved in the market full time by 80. Yeah, so someplace in in 1980, I realized, or maybe it was 1981, I realized that I hadn’t taken a job in the film business for a year. So I probably wasn’t in the film business anymore.


Dave Lundgren  12:00

And so who were some of the technicians that you leaned on and learn from in the early years, you know.


John Bollinger  12:05

I did the things that people at the time would do, that is you go to brokerage offices, and you talk to people because there was no internet or anything like that. And finding like minded people is actually relatively hard. Some people did get together on Saturday mornings, William O’Neil publishes daily graphs, we get together in a little crowd outside the printing facility, get their art books, right open press, that was one way to meet like minded people. But the real thing was back in those days, almost all brokerage firms maintained a bullpen, the big open space in the brokerage firm stuffed with desks and photons or whatever quote machine that that brokerage house had, and they would give those desks to active traders, I was very fortunate to get one of those desks at AG Becker. And it was primarily the people around me that really got me going with, you know, the technical analysis, analysis literature, that give you one example, I wanted to read something about the Dow Theory and Robert Ray’s book is is the best source for that. But in those days, you know, it was very hard to find a copy of something like that. So there was a guy, you know, hung his hat out is called Needham book finders, then you’d call him up and tell him what book you wanted. And so just like that, and you know, like six or eight weeks later, you get a little postcard in the mail, saying, Your book is ready for you and how much it was, and so on and so forth. And you picked it up at a local antique dealer, where he would leave it for you. So that was actually one of the first one of the first books I read, I was very fortunate to read Martin printings book, the year it was published, that was very helpful. But what really worked for me was going back and reading the Old Masters. That was a fantastic range of knowledge. I had gone to apprentice to a trader, I kept his charts form in real time indicators by hand and stuff like that. And he had a nice library of technical analysis literature, many of the classics, and that worked really well for me, that was like, was like a garden, you could go and play it, you know, it was a process. And it was a much, much, much harder process than it is today, simply because we didn’t have the sort of communications that you have now, such


Dave Lundgren  14:23

as like this podcast. I mean, this is this is all about in trying to inform the investment community and things like this just simply didn’t exist. So back when you when you mentioned some of the old masters. What comes to mind for me, of course, would be Charles Dow and Jesse Livermore and things like that. Are there any others that you would cite that perhaps you think don’t get the proper attention they deserve today that people should reflect back on and learn from?


John Bollinger  14:45

I’m a real fan of Richard Wyckoff. I think that his writings both in magazine of Wall Street, which is still possible to find copies of and in the courses that he developed for the Stock Market Institute, he had tuberculosis. So he said, move to Phoenix, Phoenix, Arizona, and started the Stock Market Institute, which was a place where you go to learn technical analysis. And his first course which is rigid, which was published in 1933 is still one of the best ever technical resources. Yeah, I’m very fond of that. I love Garfield. Drew’s book, new methods for profit in the stock market. That was a sort of survey of what was going on. Then there. Actually, at the time, there were very few survey sorts of books. That’s the only one I can think of he covered, you know, what a lot of other people were doing. On the psychological side, Humphrey, Neil, that Fremont ruminator they call them was certainly a founder of contrary opinion, reading his work was really important for me, there are so many more hm Gartley is one. Richard Schabacker wrote a course that that that you could find


Dave Lundgren  15:55

his book – his book came out before Edwards and McGee, right. I mean, it was actually preceded the classic. Well, we consider to be the classic book on technicals.


John Bollinger  16:03

Well, yeah. And in many ways, Edwards and McGee is basically a rewrite update and an extension of the Schabacker work,


Dave Lundgren  16:11

right, right. Now, as you were, as you were doing your studying and learning about what the classics, how they, how they traded and, and some of their various educational products and whatnot. I would imagine there was nothing in there about volatility. So I’m curious what sparked your interest in volatility that to get you to eventually lead lead up to the Bollinger Band?


John Bollinger  16:30

Oh, I was an option trader.


Dave Lundgren  16:31

Were you trading options in your mother’s account?


John Bollinger  16:33

I did a little covered call writing for her. You know, I traded them for myself. You know, I needed some income, options trading seemed to be a good way to do that. So I was an option trader and I was very lucky. I had an early microcomputer. This is in the days before PCs. I had an early microcomputer that I assembled myself from boards, I ran the old CPM operating system and had it there was a spreadsheet called Super Calc, which was available for that operators. I remember that. Yeah. So one day, I copied the formula for volatility down a column of data in the spreadsheet, I saw that volatility was changing over time. And that was radical concept. Because at that time, we believe volatility was a fixed quantity, like the car is blue or the house is white or the you know, the day is long, something like that, for example, we thought IBM is beta, which is a another measure of volatility was 1.2. And that was it. And it may be if a company’s beta changed over time, it only changed over lifecycle is a company started out very small and was much more volatile. And then volatility would decrease as the company mature, you know, but it was in the era that this was, this idea was incorrect. There was a very famous paper that was published right about that time became famous it was it was largely ignored it at the time about the volatility of economic data, specifically the volatility of CPI, CPI and the price, price indexes. 30 years later, that paper earned a Nobel Prize. So you can see how important the change was. But it was in the air, you know that people understood that there was something that was was we didn’t understand. So when I copied that formula for volatility with standard deviation, because that’s what we used to calculate the volatility for options. When I saw it changing over time, I said, aha, this could solve a problem. Now, the problem had bugged me for a long time. And that was how to properly construct trading beds. So in those days, we took a moving average and shifted it up and down by some percentage to create percentage bands or fixed with trading bands. And that was fine that that that worked pretty well. But over a volatility cycle, you needed to adjust the width of those bands. And from stock to stock. You had different bandwidths. And the problem with that is, if you’re bullish, you set the bands presented bullish picture and if you were bearish, a bearish picture. So you’re letting your your motions into the, into the trading process, which is always a disaster, I looked at this thing for volatility, I said, Well, maybe I could use volatility to set the width to the band. So that way, you know, the market would drive the width of the bands. Once I had that idea. Bollinger bands came very, very quickly, there


Dave Lundgren  19:18

was the initial insight that the value was not just to display the volatility, but to actually indicate a signal when volatility was changing. And therein lies the opportunity, particularly from low volatility and high volatility. Well, both


John Bollinger  19:33

I’m not sure I understood your point very early on. I just wanted trading bands that defined price being higher low on a relative basis. So I can could could compare the price action rigorously to the action of indicators. But quite early on, I understood that, you know, there was volatility cycles and that they were very important and indeed, this entire category of ideas called volatile breakout systems started coming along in in in the middle 80s. Is that how you would characterize


Dave Lundgren  20:05

bollinger bands as being best utilized as a breakout system much like the donchian, breakout chat channel breakout system only volatility based?


John Bollinger  20:14

No, it’s a good use. But it’s only one of many uses. The basic idea of comparing price action to indicator action, I think is the most robust application for Bollinger Bands actually. But you know, we say that there are two states and it’s the squeeze where the band squeezed together very tightly or low volatility in the bulge. They’re, they’re very wider, or high volatility. And we say that trends are born in squeezes and they go to die in bulges. So very, very helpful in terms of market timing, such like that.


Dave Lundgren  20:47

Right? In. I’m just curious if the, I’m familiar with, I’m very familiar with, obviously, the Bollinger band, but I’ve never used it on weekly or monthly charts, does it work? Is it as useful on weekly monthly charts? Or does it really need to have that daily and intraday type signal,


John Bollinger  21:02

they work on virtually all timeframes, the limit is actually downward, not upward, the limit is getting into very, very short timeframes, it’s there’s not enough information in each time period to see the price formation mechanism at work, then Bollinger Bands are going to fail so far as stock like Google that might be you know, five second or 10 Second bands would be okay. But for some, you know, small cap stock that trades by appointment only, you might not be able to get down to even, you know, anything shorter than one day bars, you know, so it depends on the activity of the of the stock, or the commodity or the bond or whatever. It’s interesting, they have been employed in a wide variety of uses as a firm and in China that uses it in glass manufacture this aviation safety protocol and Euro land uses bollinger bands that have been adopted to all sorts of activity stuff. They’re actually very robust. And this gets to a point that, you know, I think we’ll talk about a little bit later, the reason that there’s so robust is they’re based on a first principle, they’re based on a core concept of the market, you actually going to have to destroy the markets to destroy the bets.


Dave Lundgren  22:13

Yeah, I definitely want to talk about that with you because that we briefly mentioned it in our prep conversation. And that’s something that I Tyler is familiar with a concept that I refer to as a checklist of trend change, and it’s based on base principles that must happen in order for trend to change from down to up and vice versa. So that’s definitely a concept I want to I want to touch on in kind of really get your thoughts on. But before we get into that, I want to maybe just finish up a little bit more on the, on the development of the Bollinger band, and then maybe some of the other ways we can use it when you started developing what got you to settle on the 20 day moving average versus something else? Because again, I would think that a 20 day moving average on a utility stock might be a little bit slow relative to a 20 day average on a biotech or something. But does that or is it the Bollinger band itself? The band is what is really the meat of what matters most?


John Bollinger  23:02

Well, two things, two answers to that. First of all, 20 is just the default, you just set to whatever your application is. Right. But


Dave Lundgren  23:08

I think the default is Was that what you what you determined to be the default, like when you think about Stochastics, it’s 14 days, because that’s what was wireless settled on, or nuts, not Welles Wilder, George Lane settled on when he when he developed the indicator,


John Bollinger  23:20

20 days was sort of what we used in those days, you use two simple timeframes, 1020 100, things like that, because we’re calculating things by hand. So here’s an example for you, if you want a 10 day moving average, you just sum 10 days worth of data and cancel the last digit and you have a 10 day moving average. And then each day, you just have to take, you know, the oldest day out and sub in the newest day. So you do have to understand that many things in technical analysis came from the idea that we were doing things by hand, you know, especially where there was a computational shortcut available. So those ideas became very, very popular. The real truth is, is that it’s I think that real ideas, it’s the number of trading days in a month, 21 Usually, as the number of trading days in a month, I think that’s I think that’s a really important version because I was primarily a daily trader, that is I use primarily daily charts. I think that’s a big piece of everything it came from, we had a trading system at the time that I learned was very useful. It took the Dow Jones Industrial Average, and you charted it with a 21 day moving average, why 21? Who knows is just the way it was done this way they told us to do it. So you did that. And you put a trading ban fixed with trading ban above it four and a half percent and one below it, four and a half percent. And then you kept two oscillators, a 20 day ad oscillator, which is to say you took each day you subtracted the number of issues declining from the number of issues advancing for the that day and you kept a 20 days some of those net numbers That was your D oscillator needed the same thing for up and down volume. So if you went up and tagged the upper band and one of those oscillators was negative, that was a cellular tag, the lower band and one of those oscillators was positive. That was a Beyeler. And that system worked well for many, many, many years. And it was, in fact, the system that I learned trading bands from and the system that I was trying to automate and creating bollinger bands.


Dave Lundgren  25:28

So you saying that that system today doesn’t work as well as it wants it?


John Bollinger  25:32

You know, I tested it about 10 years ago, and it worked. Oh, K. But he didn’t know is near what he had done in times past. And I think that that’s because of the changing of the sorts of things that were listed on the New York Stock Exchange. So remember, we talked a little bit about first principles. So this is a change in a first principle, back in the day, when you know, this work was originally done, basically, the only thing that was listed on the New York Stock Exchange was operating companies, right? There just wasn’t much more today, I think that there’s at least an equal number of other things listed on the exchange, whether they’re a exchange traded funds, closed end funds, preferred issues, inverse funds, you name it. There’s all kinds of stuff listed there. And I think that that’s what broke the efficacy of that particular approach,


Dave Lundgren  26:23

interesting in your role in Bollinger cap Capital Management, where you have the opportunity to change the parameter backtested, as you see fit, if you can discuss reports and fundamental research and such like that, to find something else, so if you just accepted that that’s close enough.


John Bollinger  26:40

Yeah, of course, I have. I mean, I’ve looked at everything you can think up. But in fact, for stocks and most things, financial 20 periods seems to work really well. I’ve seen some applications that that use very short term versions, Bollinger Bands, 10 periods, or so. And I’ve seen some use very, very long periods. I think it’s something mathematical to 20. It’s a decent sample size, it’s not, you know, great sample size, but at least it’s a good sample size. And so what I tend to recommend people if they weren’t, if they feel that their application needs to use really short term, Bollinger Bands, I suggest that they change the timeframe in the bars rather than pressing down because I think the calculation starts to fall apart. Now, that makes a lot of sense. And the same going up, you know, if you’re tempted to go much beyond 50, period, Bollinger Bands, you know, why not switch to to weekly data on and use the this the default parameters and see how that works for you. Interesting. So there’s, there’s a ton of things to test. And, you know, I’ve tested a lot of things, but the original choices seem pretty vibrant, still,


Dave Lundgren  27:47

what is you’re just just sort of off the cuff, or maybe a little divergent here. But what what is your, your view or your take on back testing and optimization? And that kind of things? Where do you see value in it? Do you see people getting in trouble with it?


John Bollinger  28:00

I think back testing is important. It’s a way to validate your ideas. But the idea has to come first, the idea preferably has to be derived from first principles of brands and more and more concepts of the market. So you develop an idea and test it. And if it doesn’t work, I throw it away, it’s really easy to come up with a lot of ideas. I think that what happens when you start doing optimizations, if you find some combination of the variables that are involved in whatever approach that is that work, unless it’s a really robust set. So say that the number is 32. You test this, whatever system it is, in the variable that the core variable inside it is you test it, you find 32 works really, really well. Well, if 20 820-930-3132 3456 all work roughly as well, then you’ve got a robust idea. And so I have no problem with the idea that you found that result from an optimization. But if 31 doesn’t work, as well as 32, then I think you’ve got a real problem. It’s Yeah, so like,


Dave Lundgren  29:10

if you have if you’ve, if you find your back tests, and you discover that 1314 1516, and 17 all work very well. But 25 works the best, you’d be more inclined to use 16 or 17. Because it’s a cluster of what works well,


John Bollinger  29:24

I pick up I pick the number from the middle of that cluster. Exactly


Dave Lundgren  29:28

right. And you would ignore the fact that 25 actually works the best because it’s just sort of like a satellite observation that runs the risk of just being almost random. Correct. We


John Bollinger  29:37

have very powerful software these days, you know, and we can go in there and search and find stuff. I think you ought to really run it the other way. I think you ought to come up with ideas and then test the ideas. This idea of, you know, beating the market until it confesses, well, you know, it will confess it will give you answers, but I don’t think those answers are going to serve you for Well, one exam Apple that I personally find very troubling. And I know that people have success with this. But so this is a personal feeling is this walk forward sort of analysis where you’re newly re optimizing, you know, to define the optimal set, I just think that that’s fraught with potential for disaster, I understand that it works. I understand a lot of people use it, that’s very, very popular technique and such like that, but it’s just not for me, I need something which I personally feel is very robust. Because I’m a disciplined trader, I’m going to go out there and execute it, period. If it looks like a terrible trade, I’m going to go out there and execute it anyway, because I’m gonna follow my sisters. And the only way I can do that is if I believe that the system is really robust, because then I have a core belief that I can rely on. That makes a lot of sense. But I understand the other side of the equation to really well, too, I understand all this data mining and all that I understand that you can find important results that way such like that. It’s just not for me. Yeah,


Dave Lundgren  31:05

this is this is really fascinating that you’re saying this, because I’m sure Tyler is picking up on it as well. But there are just a number of people that have highlighted the idea of, of in order to get to investment success, you have to make sure that you’re sticking with concepts and principles that resonate with you. So don’t try to be somebody else, you have to figure out what works for you. Obviously, what you’re doing has to work. But there’s a lot of things that work in order to execute it over time, you have to make sure that that process fits your personal profile.


John Bollinger  31:32

So in 1982, I was I was apprenticing I apprentice for a year to a guy for free. I kept his charts and I kept all his indicators and such like that, as he correctly identified the birth of the bull market in 1982. I mean, we we had on that day or the day the bull market was born, right? Literally, champagne, we had champagne for lunch. I mean, you know, he went, he got it, he knew it. Right. And, you know, he had systems and approaches to support that. But the one thing that he told me that was really influential in my life, that was a one off event. And it was a glorious, fabulous moment to be there and all that. But he said to me, pick a system, any system and use it. Alright. And I still think that that’s the best financial advice you can give somebody who’s setting off and I looked at him and said, How about buying the new highs list? He said, Fine, do it. Yeah. How about we had an oscillator named after John Galt he was a real libertarian sword he and ran fan, I said, How about zero crossing to the Gulf oscillate, he said, Fine, just do it.


Dave Lundgren  32:42

That’s a really important contribution to the conversation that should be obviously what you’re doing has to have an edge, you can’t just continue to do something that doesn’t have an edge just because it feels good to you, you will lose money, but provided that you have found something that has an edge, and you have multiple things that have an edge, make sure you stick with the one that that resonates with you because it doesn’t work all the time. And in in those moments when it’s not working. That’s when you have to really bear down and stick with what you know, and kind of see the system through. Right. Exactly. Yeah,


Tyler Wood  33:08

I’m fascinated by this idea of following your system obeying the rules. And being disciplined as an investor, I think we’ve, we’ve had a lot of guests who have talked about sticking to your rules, even when perhaps the the market regime isn’t favoring that. But I’ve also heard even in this conversation, just now you mentioned going back and testing the 20 period for bollinger bands just 10 years ago, so 30 years after you invented the concept, you’re you’re still going back to test and to check. And we’ve also talked about how the market is constantly evolving. And my question for you, John, is, what’s the process you use to understand all the changes at play? And how do you know when you need to go back and test or perhaps even make some tweaks or changes to your system to keep up with changing times?


John Bollinger  33:57

Well, there’s statistical ways of doing that. You can compare the statistical distribution of your results over time. And if that starts to change, then you know that it’s time for some introspection, but I don’t think you have to go there. Actually, I think it’s pretty evident. I’ll give you an example. So the Bollinger Bands contain approximately 89 to 90% of the data. So that’s a statistical statistical anomaly. They should contain about 95% of the data, but stocks, things financial follow no known distribution. So the result of that is that the bands contain a smaller sample of the data than they, they in quotes. Sure, because they do the job that they do. And so that’s what they should do. So I go, you know, every 10 years or so, I pick, you know, a list of 10 or 15 or 20 non correlated financial assets. I You know, in the old days, it used to be things like the T bond, the Deutsche Mark, gold oil, IBM, the Dow, the s&p, the NASDAQ, whatever I mean, you know, a list of 10 financial items that seemed to be reasonably independent from one another, and you just run the test and see how much data they contained. That’s proved to be remarkably stable over time. The interesting bit is that one thing has changed. There used to be a large difference in containment between very short term Bollinger Bands, say 10 period, bollinger bands and longer period, Bollinger Bands, a 50. Period volunteer event, that difference has diminished dramatically. There’s almost no difference these days. And I don’t really have good answers to why that has happened. It’s been stable in its current configuration for many years. But at some point, you know, something changed about the way that the timeframes in which things were traded is all I can say whether, you know, more short term trading entered the market, more arbitrage entered the market, index arbitrage was was a big thing. So when I came into the market, we had no stock index futures, we had no ETFs, we had no index funds, we had no options on on anything other than individual stocks. And we had only calls on most of the list and puts were just coming in. So we’ve had a huge number, a huge amount of change in the market. So over my career, it could be any number of things. Do you see


Tyler Wood  36:38

some similarities or differences between the change that we’re seeing with advent of cryptocurrencies and Spacs? I mean, there are market structural changes happening, you know, even as we’re recording this interview, do they feel the same as the changes that have happened prior?


John Bollinger  36:53

So I started trading Kryptos, four years ago. And it was it was a paradox. Because the technical tools worked. So well, it was ridiculous, right? Yeah. Hey, that worked. Yeah, exactly. And it worked. And it worked really well. But you know, now we have futures on Kryptos. And we have ETFs on Kryptos. And, and we have all kinds of noise and arbitrage that has been introduced into the system. And this stuff just doesn’t work as well as it did, once Bulletyme still works very well, perhaps better than almost anything else. But it’s lost a good deal of its edge. So you can see just in that four year period, that the microcosm as the adoption of crypto, you know, went up the grade, more and more people came in derivatives were brought in, and so on, so forth. That integrated TA and I think there’s a real simple reason for that. Because ta at its heart gets its hands on the supply demand relationship, it’s a first principle of what’s going on. And when you start introducing outside forces that affect the supply and demand TA, you know, has a harder time catching on to that relationship. Another way of saying it is, the old technicians would always talk about accumulation and distribution in different phases of the market. So all this arbitrage she wouldn’t have started really, really started with index arbitrage. With the birth of stock index futures, people realized that the futures would trade at a premium, and you can buy the basket of stocks, and sell the expensive futures. And when the futures went to a discount, you could you could buy the cheap futures and short the basket of stocks as risk free in quotes, sort of arbitrage. That’s where it started in. And you know, now we have you know, pairs trading got really popular as the software was got strong enough to define the really good pairs to trade pairs trade where you, you buy one stock, and you sell it non correlated stock against it, trying to capture a spread between the two of them. So that’s just a couple examples of the sorts of arbitrage and non supply demand related events that have entered the marketplace ethic introduced a lot of noise and made the job for technicians harder, has made it impossible. It’s really important to make that point. But it is harder to be a technician today than it was when I first came into the


Dave Lundgren  39:17

market. John, you You’ve mentioned a few times the phrase first principles, I wonder if we can spend a little bit of time on that. And maybe talk about, first of all, how you would define a first principle and then maybe some examples of what you think are core first principles that people should be having in their minds is setting out to think about markets, back testing, things like that.


John Bollinger  39:34

First Principles are the core operative principles of any market. Right? It basically the first principle of the market is supply and demand. Right? It’s it’s what ultimately drives price when there’s more demand than supply prices go up and it’s more supply that demand prices go down the forces to change that those supply and demand relationships we call accumulation and distribution. These are very old technical concepts. You know, they were, they were talked about 150 years ago and remain relevant and dynamic today. So those sorts of things are first principles of the market, the growth cycle of a company is a first principle of market volatility is a first principle of the market, there are tons of them, it just depends on what market it is that you’re looking at, in many markets, for example, this is a great example. So when I came into this business, we had an a risk free quotes, again, arbitrage in the futures market, it was called the crack spread you you would buy a crude oil future and you would sell short heating oil future and a, let’s say, gasoline future in a long time since this worked, right, you know, and then you did it in relatively fixed ratio, because if you took a barrel of oil, and gave it to a refiner, that the barrel of oil, you know, would come out and gallons of gasoline and gallons of diesel and gallons and heating oil and some sludge, right? That maybe some some some jet fuel, kerosene and mid midweight distillate their futures contracts at the time. And it was a risk free in quotes spread, then along came something called a catalytic cracker, which was a bit of refining technology that used catalytic metals, specifically platinum, I believe. And it allowed refiners to dial in whatever list of products that they wanted, if they needed more benzene and less diesel, then they could do that. And so the crack spread went out the window, the refining was no longer a fixed process, it was now a variable process. So that’s an idea of a first principle of the market was was the mechanics of the, of the refining process. And something came along and changed the mechanics of the, of the refining process. And it changed that, that that first principle,


Dave Lundgren  41:59

your description of first principles has me a little bit unnerved because I guess the way I always always thought about them is that there weren’t a lot of them. And you had to know what they were in order to survive, you had to know that these things must exist, that they do exist, and you need to be aware of them. And you said that they were you? I think you said there were tons of them. So what is there to say about the idea? There are many principles, but if you don’t know them isn’t isn’t that a risk in your process?


John Bollinger  42:27

What I mean, when I said tons of them is because there are tons of things. I see tons of relationships, like stocks, you know, like listed stocks, there are relatively few gotcha No, but you know, in different areas and, and such. So I agree with you that there are relatively few first principles, but I still think that there’s plenty of opportunity for analysts to go out there and explore those first principles and find great ideas, you know, this idea that you can go out there and do data mining, and discover relationships and such like that, that’s entirely true. But you can end up with a different sort of knowledge than you do by, you know, creating theories about how the market operates, and then going out testing them, you’re more likely to come across a robust approach by, you know, trying to stick to first principles, exactly. But that doesn’t mean you can’t, you know, with data mining and such like that, that doesn’t mean you can’t find something valuable. People do it all the time. It’s absolutely true.


Dave Lundgren  43:24

Yeah, it’s just not it may not be durable, because it’s not based on a first principle,


John Bollinger  43:28

I think almost by definition, it’s not going to be durable, unless, of course, you stumble across a first principles concept, right? But a whole data mining thing is you know, the most they use neural nets, and you can’t trace the path of the neural net, you can understand what the relationships are, so that you can’t verify you know, whether you stumbled across something that really is really important, because you can’t distinguish between that and every other result that the neural net gave you.


Tyler Wood  43:58

So sticking with that example, was it the crack arbitrage that stopped working? That then forced you to go investigate what was happening at the refineries? Or did you understand what was happening with the catalytic crack process that then led you to believe the arbitrage would go away, which came first?


John Bollinger  44:15

Found out I found out about the cat crackers much, much later. I had a client here at Ballinger capital management that was running a retirement portfolio for he was a refinery operator out of out of Texas, Texas, he called himself an old oil boiler. Refining is right as boiling oil and several different pieces to come off. And he was the one explaining the variable nature of these cat crackers and such like that to me. So I understood this only long after that.


Tyler Wood  44:45

So it’s not a process of trying to understand a you know, driverless cars or extended life batteries or every new piece of technology that comes out in our economy, but rather to pay attention when things stop working.


John Bollinger  44:58

And also you can run into other way, you know, you can use stock prices to tell you where to look at for fundamental factors and such. I think that that’s actually really important. My favorite example of this is the chart of Enron, you know, it looks like a mountain, it goes straight up, and it comes crashing straight back down. And if you go back and look at the news clips at the time, the first problem that Enron acknowledged was after was down 80% technical analysis and the markets, which technical analysis is really just a close look at markets, right. So technical analysis, and the markets told you that something was wrong with Enron, long, long, long before the first actual news story came out.


Tyler Wood  45:42

Very well said it was down to 80%, just before it lost another 80%. Right. Yeah, you can always


Dave Lundgren  45:47

lose 100%, from where you are. Yeah. John, in New York Ballinger Capital Management, is your toolkit entirely based on the Bollinger band suite of indicators? Or do you use other indicators as well, in addition,


John Bollinger  46:01

absolutely use other indicators as well. Back in the 80s, I coined this term rational analysis, and I had a little little story I said, suppose you you’re an auto mechanic, and you work in garages, against the back wall of the garage, there were four toolboxes and one was painted red one was painted green, one was playing blue, and one was painted white, you know, the, the stall that you were working in the floor was painted white. So you were only supposed to use the tools from the white toolbox. But yet you knew that in the red toolbox was actually the tool that you needed to fix this problem right now. So once you in fact, obey the rule and not use it? Or would you, you know, kind of go over to the guy that had the red toolbox and says, Look, you know, I really need a tool box. Can I borrow that? Of course, I seek out the right. So I think that’s a really important idea. You know, I developed some tools, which I’ve shared pretty widely. But, you know, we use other tools here as well. A big portion of our operations is based on the concept of relative strength, for example, which isn’t particularly a Bollinger band concept, but Bollinger Bands can be used to enhance it. So that’s a way of looking at


Dave Lundgren  47:06

  1. How would you use Bollinger bands to enhance relative strength? That’s interesting.


John Bollinger  47:10

Strong stocks. Don’t go straight up. Right. Last time I checked it. They’re really strong. Yeah, they are. From time to time, but usually they have pullbacks and that is low. Yeah. So he he do price analysis within the concept of relative strength, relative strength gives you a universe of stocks that you want. And then you can use Bollinger bands to pick and choose your entry and exit points


Dave Lundgren  47:34

for timing. Yeah. Interesting. Right. Yeah,


John Bollinger  47:37

I actually wanted one of the things we always talked about, I sat for the CFA and at four, or five and six, so I was a CFA by the time 1990 meeting in Scottsdale of the of the what was then called the Market Technicians Association gave the first test for the see for CMT test. So I became the first dual credential holder by default, because I was the only CFA that sat for that test.


Dave Lundgren  48:03

I knew we were honored to have you on the podcast, we actually have the first CFA CMT dual charter holder on the podcast, that hey,


John Bollinger  48:10

yeah, yeah, 200 buckets of us, you know, yeah, I’m one of them, which I’m really pleased to see, I think it’s really useful to marry these disciplines. You know, anytime I meet a hardcore fundamentalist, and you know, I say, Fine, do your fundamental analysis. But you know, try these tools to see see if they can’t help improve your results, give you an example of out of out of our practice here. Three years ago, my daughter joined the firm. And she came with a very strong interest in social entrepreneurship. And she said, Well, you know, one things I’d really like to do while I’m here is build an ESG fund. And I said, Well, that’s fine. I don’t particularly know that much about it, but you know a lot about it. So let’s combine our disciplines and, and let’s produce a fund that generates better than market performance, because up till then almost all of this social investing came with a performance penalty, almost all done by subtractive. Investing. So you took the s&p 500, you kicked out the you kick out big oil, and you kicked out tobacco, and you kicked out firearms, and you kicked out casinos, and but all those companies contributed to the returns of the s&p 500. So you’re left with this, you know, residual piece of the s&p 500. And typically what would happen is that piece would underperform over a market cycle. So I just didn’t want to do that. So we married, you know, some technical analysis approaches with an ESG approach. And we even went and modified the traditional ESG approach because I really hated the idea of subtractive investing, you know, beating all the things out because what do you have that what you have left doesn’t have any cohesiveness? So we went and did, we did two things that were really important. We did additive, we went out and identified We’d like to be clear. daughter went like this, she went out and identified companies that were making positive impacts on governance, positive impacts on the environment, positive impacts on society and stuff like that it she assembled list of almost 300 companies. And from that we created two indexes, our impact 100 And our impact 200. And then, you know, I developed to go with this, a technical approach approach to running portfolios built on those. So we broke the rules in two ways. We didn’t do subtractive negative screening, we did positive screening, we chose the companies that we wanted to have an index, and then we apply technical analysis to make sure that we generated positive returns from that list.


Dave Lundgren  50:49

Right. And now, these certainly managed accounts, are there, is there an ETF that goes with this?


John Bollinger  50:53

They are at the moment, there’s no ETF, they are individually managed accounts here, and then on the access platform, RIAs can access the program through them. Interesting. That’s that’s sort of a classic story about marriage of the two disciplines. So concept, which I really believe that,


Dave Lundgren  51:11

you know, and I think that’s, that’s a key takeaway, for those that are thinking about augmenting their fundamental process with technicals is just as you said, it’s an additive tool, in the sense that it makes you make sure that you’re staying on the right side of those stocks in the benchmark that are outperforming


John Bollinger  51:26

investment managers, you know, they’ve had technicians in in their shops forever. They just, you know, if you wanted to find when you walk down the hall, and there would be a sign on the door, it said, quantitative analysis, and invariably, there’d be a technician in there, right. So, you know, just to talk about our subject matter for a moment, in the beginning, we had, what we classify was known as technical analysis. And then the other sort of investment discipline was fundamental analysis. And I always proposed that if you sort of overlap those if you chose the best fundamental tools, and the best technical tools that you’d have this rational analysis piece would do really well. But you know, over the past 20 years, actually, it’s a little longer now, there have been two major grabs of technical analysis knowledge. The first one was by the quantitative community, they went through the technical analysis, body of knowledge, and they just looted and they really renamed all of these parts and pieces with quantitative names, and raise the fees dramatically and did really, really well. And then the same process was repeated again, on the behavioral side, they came in and created this thing called behavioral finance and created acne academically respectable as the concept and created an entire discipline, again, called behavioral finance, and again, raise the fees and did really well. But it’s really important to understand if you have any sense of history, and this is in China, where we were periodically rewrite history, at least, I hope it isn’t. If you have any sense of history, you know, that the real progenitor of behavioral finance was a market technician by the name of Humphrey Neil, and you know that the real progenitor of quantitative analysis was market technician by the name of Colonel Ayers, both people who practice bat all the way back in the 30s. You know, despite the fact that they’ve been these two big land grabs of the technical analysis territory, I think that if, you know, thinking people go back and examine the history, they’ll understand that there’s things to take from the fundamental world, there’s things to take from behavioral finance this thing, two things to take from the quantitative world, there’s things to take from the cook from the technical world. And there shouldn’t be any argument about this, you know, this isn’t one or the other. These aren’t binary choices, there’s this good material. In all these things. The constant a fantastic job of quantifying much of what had been technical analysis and to behavioral finance folks have done a fantastic job of uncovering all sorts of market anomalies based on on investor behavior. So we should all be working together and in my view of the modern investment firm, right, people from all these different disciplines pulling the oars together to produce a superior result for the client, no arguing, you know, the with what’s the bottom line of what we’re doing here. The bottom line of what we’re doing here is delivering superior results for clients for investment clients for their particular needs, and risks. Profile


Dave Lundgren  54:26

analogy I’ve always used when you think about the Army, Navy, Air Force, Marines, they’re always sort of at their, at each other’s throats in terms of who’s the best part of the service, but when it comes to wartime, they’re all on the same team. And I’ve always felt like trying to beat the benchmark is a bit of a war and a bit of a battle. So we’re all better off rather than fighting each other just saying, look, let’s put together these these various elements that all work independently, but particularly work really well together. You just fight this battle together as opposed to doing battle with each other.


John Bollinger  54:54

I love that analogy to different service branches of the service. How do you incorporate


Tyler Wood  54:59

Fundamental discipline into your own process. Do you use that to narrow the universe of security as we touched on it in the ESG aspect, but even before beginning a socially responsible investing strategy, did you use fundamental factors in your work at Ballinger capital?


John Bollinger  55:15

I think that’s probably the best example of that is the analysis of growth, company growth, whether it’s the sales, whether it’s fear, earnings, whether it’s, I think, growth factors in companies, I’m clearly a growth investor, you know, it’s just my my discipline, the value thing just doesn’t work for me every time every time I go, as, as Dave said, before, every time I go try to do a value play, I find out that, you know, it is in fact going to be cheaper.


Dave Lundgren  55:48

We, as a firm, I should say, are primarily growth oriented investors. So I think an analysis of growth factors is the single fundamental idea here, that’s the most important


Tyler Wood  55:58

now well said. And for the technical analysis community for all of the CMT charterholders and candidates who are going to be listening to this. For me, the the most consistent refrain that I’ve heard you deliver at CMT conferences and through this interview is just the inspiration for more intellectual curiosity to not be afraid of ideas that challenge what you currently think, you know, but I wanted to ask you, where would you steer people in terms of going back to the old masters? Where’s the right place to start for people who don’t have a real strong background in technical analysis?


John Bollinger  56:30

Well, first of all, I think that every budding technical analysis should get a tattoo that says question everything. Well said, yeah, the more you do that, I mean, I questioned volatility. And that’s how, you know, the results. Above is Bollinger Bands high, I questioned that fundamental belief, we thought that volatility was, you know, a fixed factor. And I questioned that idea and added that Campbell contraband. So I think that that’s really important. You know, there’s one book that I really like, it’s from circa 1950, or so it was written by Garfield Drew, it’s called new methods for profit in the stock market. And it’s a survey book, he went out and surveyed what other people were doing, it’s actually a very rare thing. In technical analysis of the period, of course, it became much more popular later in the 70s. And it’s like the Market Wizards types type format, or no, no, no, he actually talks about methods and such like that, and how to and what people were doing. Interesting, the focus wasn’t on the people, the focus was on the methods and stuff like that. Oh, you know, I think market wizard Wizards is, is a good one, Wilkinson did one for Bloomberg press, maybe 20 years ago, went out and did that anyway, there are a bunch of them now. But for in the 50s, for 30s 40s, and 50s, into the 60s, this the only one I know of. So I think that’s a really great one, because it’s just a whole bunch of trail heads in it that you can, you can go and explore everything from different methods of charting, we have a method of charting called today called Echo volume. Well, actually, that’s a very, very old method of charting. And, you know, Drew talks about Edwin Quinn, who developed that method of charting, so there’s a ton of old ideas in there. And you know, you just go pick a couple of pick a couple of those ideas and just go explore them. And you, you’ll find, you know, you’ll find your your depth of knowledge expanding as you I think it’s it’s really important, very


Tyler Wood  58:38

well said, the last question that I have for you today, having spoken to so many great contributors to our community, since I started at the then Market Technicians Association, I’ve heard a lot of people talk about that period in time where institutional fund management didn’t believe the technical analysis had anything of value to offer. And I think we’re sitting in a world right now where everyone on the planet has a trading account, or just about and talk to my friends at TradingView, who have, you know, 14 million monthly active users, and they have access to every kind of chart type hundreds of indicators, if not 1000s, what do you think is more dangerous people having access to all these tools and lacking the, you know, the curiosity to find out how they work or actually know what’s behind them, versus people ignoring the toolkit?


John Bollinger  59:28

So a little bit of a digression in the old days, we calculated indicators by hand so we really got to understand the indicators we understood what you know, Mark types of market action would cause the indicator to behave in a certain way. And so that gave us a certain intimacy with the work that I think is is lost today. So if anything, I think that people really need to study their tools a bit more closely. They really need to understand how they work and and what market factors might affect them. What market factors could be lead to an unexpected or unintended result. So I think that’s really, really important. Take the 10 day moving average, as a little example, there’s what we have a takeout value each day, there’s a window of 10 periods, and the next day it advances and the oldest Day falls out of the calculation, the newest date comes in into the calculation. Well, if they’re all this day was a large gap day, then the front end of the calculation is going to change today, regardless of whether price changes today or not. So something as simple as that understanding the mechanics of simple moving average can help you avoid problems, but they can also help you anticipate a signal for so let’s again, use this ultra simplistic idea of a 10 day moving average, say you’re running a crossover system. And if price crosses above it, you’re going to buy Christ, because blood, well, if you look at the takeout value, and you you know, you can understand how much the average is going to change and in what direction tomorrow. So it’s, it’s like having a little peek at tomorrow’s newspaper, it’s it’s a little little ideas like that, if you really get intimately familiar with the tools that you’re using, you’ll find that they have, you know, properties, and they may offer you things that you weren’t aware that they were offering you. Again, I think the big foible of today’s is over getting overly complicated, too many indicators, too many things to me, because it’s also easy to assemble and throw together now. And it’s such that so you know, along with first principles, I would stress simplicity, all of our approaches here are remarkably simple, you know, very few rules, very few variables. So we really can’t understand what’s going on, you get, you know, six or 810 indicators together all operating at the same time. And it gets really hard to understand that synthesis of that information. I think that keep it simple. The old, the old KISS principle is really, really important in this work.


Dave Lundgren  1:02:07

So this has been a truly informative discussion, John, it’s been, you know, tend to be able to sit with somebody who is at the forefront of the technical community having contributed so much as you have over the years and decades, frankly, it’s been for sure Tyler in my my great privilege to have you on the podcast, is there anything you want to leave the technical community with before we wrap up,


John Bollinger  1:02:31

you know, it just, you know, first principles, keep it simple, be disciplined, you know, these these are, I think the keys to long term success. And I think that’s really important. Everybody, you know, there’s a lot of focus on short term trading and such like that, and that’s fun. You know, it’s it’s all dandy, but what we’re really about, or at least we hear are really about is producing long term positive results for for our clients, they focus on these primary factors of our business, I think is really important. And most of all, read the classics. Yes, read the original source material, not pre digested, you know, stuff, but go back and, and read the classics. Right.


Tyler Wood  1:03:14

That’s important takeaways, John, and just before we started this interview, we were discussing Bollinger Bands COMM The many, many ways that you give back to the community, including weekly chart packs and a number of resources, where where’s the best place for our listeners to stay in touch with you where where should we send them?


John Bollinger  1:03:33

Well, Bollinger Bands calm is my homepage primary just got a lot of educational material there. And that could be helpful. There’s some tutorial material and at the bottom of that page each week, I produce a market timing chart pack that’s available for free so they can download that over the weekends and see what’s going on stock markets. We have a Bollinger Bands Analytics site. It’s full on Japan’s dot eu s and you know, full range of screening and charting and bollinger band tools and, and a bunch of other related tools, including the various Bollinger band methods and but really nice screening and can be very, very helpful. Our money management arm has a website as well Ballinger Cap Com.


Tyler Wood  1:04:14

Fantastic, John until we get to see you again in person really wishing you and the family the best. Really appreciate your time this afternoon with Dave and I and be well and we’ll see you soon.


John Bollinger  1:04:24

I couldn’t be more pleased that I could spend time with you guys today. Thank you very much for having me on. And I do hope to see you in the flesh soon. Soon.


Dave Lundgren  1:04:32

That’s for sure. Yeah. Thank you so much, John. Happy holidays. Tyler, you know, as a member of the board of the CMT Association, of course, I’m very well aware of all the firehose of information in ideas that are being generated and, and things that are happening within the association for our listeners, why don’t you give us a quick overview of what’s taking place and what they can look forward to in the coming months. Thanks, Dave.


Tyler Wood  1:04:57

First, I want to congratulate all of our CMT candidates who are just now concluding their December exams. As a reminder results will be available up to eight weeks after the conclusion of this December exam administration. For new candidates to the CMT program, you can register for the June exams beginning on December 20. To get a jumpstart on their journey towards attaining the CMT credential. And for all of our current candidates, you will certainly be able to register at the earliest discounted pricing even after you receive your results. Dave. The other item I’d like to highlight, which we’ve talked about before, is that in an effort to advance our mission, the CMT Association has established an academic partner program that helps promote technical analysis education, colleges and universities worldwide. That program is available to academic institutions that provide accredited graduate or undergraduate finance degrees and includes courses focused on technical analysis, there are no fees associated with becoming an academic partner of the CMT Association. Joining the program indicates that those institutions maintain the highest standards of academic rigor and professional practice. And it signals their commitment to students career readiness, and applied learning. The CMT association is very proud of all 44 partners as these institutions of higher learning ensure their students are prepared for careers in financial services with a complete curriculum that covers technical analysis. And to that end, we will be launching an investment competition in the spring semester for these students and faculty to continue their practicum education. For more information about the academic partner program, and this upcoming investment competition, please contact Academy at CMT And with that, Dave, I want to wish you and your family a very happy holiday season to all of our listeners. Stay safe, be well, and we’ll see you in 2022. For Season Two of fill the gap fill the gap is brought to you with support from optima. In addition to candidate study of the official CMT curriculum, Optima provides a full video course on all of the material that candidates need to know for each level of the CMT exams. Each course is broken up into modules, ranging from 15 to 45 minutes, depending on the complexity and length of the topics being covered. Learn more at