The Holy Grail of Trading, Advanced Volatility Theory

23 Oca 2019

You don't need my indicators to do what I'm doing here. Every indicator on my chart is a derivative of a Bollinger Band.
I've been trading forex and crypto for several years now and would like to share some of my findings. Let me ask an important question. Would you ever expect to have a trading edge using the same strategy, default setting indicators, and breakout patterns as everyone else? Especially when 95% of traders lose? I genuinely believe that the "golden standard" of understanding of trading fundamentals is flawed to the core. There is no "trading edge" for lagging indicators and chart lines even a child could draw. I'm not saying that you need to adhere to the information I'm providing, though hopefully the information I offer will make you think "Maybe, just maybe, there is a better way to do things." If not my way, I very much recommend Ichimoku as an effective leading indicator. I've already paid my dues (literally) by failing with the same standard of tools presented as effective.

What if the "golden standard" is only so because they're tools that make you predictable for people who know better? If you have the masses all trading the same information, that makes for predictable moves.

Predictable traders make for a predictable market. A predictable market makes for a profitable market. The only reason you've been given the "golden standard" is to provide liquidity for those with more buying power, resources, knowledge, experience and connections than you.

There's some widespread misconceptions about Bollinger Bands. It's common knowledge that BB represent the bellcurve surrounding price, also known as a distribution. Do remember there are more periods than just the default 20 that comes preloaded. The shorter the period, the faster the bellcurve will expand and compress.

The first standard deviation represents 68% of the data, the second standard deviation represents 95% of the data, the third 99.7%, and so on.

In this picture I have a 50 period 3rd stdev and a 500 period 3rd stdev BB loaded up on a chart. Both theoretically contain 99.7% of the data, so why does the shorter 50 period have more data outside the 3rd stdev than the 200 period? The 50 is more reactive and the width of its standard deviations expand and contract much faster to accommodate for new information. Every time a candle closes the bands will adapt to the new information. If price for instance continuously goes upward (or downward,) the distribution would need to expand to accommodate for the movement. After all, the 3rd stdev is supposed to account for virtually all of the data. Here's the problem though, the 3rd standard deviation will only account for 99.7% of the data if NO NEW INFORMATION IS ADDED. What's the point of measuring how much data is in a standard deviation if the boundaries are going to change with every candle close? That causes a problem, if we can't use a BB to accurately represent how much data is contained, why is the BB indicator even useful?

This is where the train of thought usually ends.

Let me present the question...

What if the the amount of data contained in a BB isn't the valuable piece of information, but whether or not the distribution is expanding or compressing?

It doesn't matter what percentile of data price is in since it's not accurately tradable information. All that matters is if the standard deviations are getting closer together or farther apart. (see below)

Expansion (the adding of mass) is news, the alignment of expectations for growth or decay.

Compression (the shedding of mass) is a lack of clear expectations of market participants.

It's important to note that all standard deviations for a period will expand and contract at the same time. Changing the standard deviation won't change if that period is expanding or contracting, that's what's beautiful about this.

So why the 1.25 stdev?


It's the pivot point for the expansion and compression of the ENTIRE distribution for that period.

As an empirical constant, if you are outside the 1.25 stdev every single stdev will expand for that period. The moment you return inside the 1.25 stdev all the stdevs will get closer together. Again, shorter periods will always be more reactive. Comparing short term and long term distributions on multiple periods will let you define the short and long term alignment of expectations of market participants.

Everyone seems particularly occupied with how fast price is moving, not stopping to consider the other variables that actually determine speed.

Force = Mass x Acceleration

The more mass you have the more force is required to continue pushing something, yes?

Force is volume, literal buying and selling pushes the price.

Mass is the variable no one was taught to talk about. Mass is how wide the bellcurve around price is, the size of the distribution relative to that period. The longer you have been in a state of trend (the expansion of a distribution,) the more mass that distribution is carrying. The more mass you have the more force you need to continue expansion.

So let's say you're pushing a snowball up a hill and the snowball gets too large for you to reasonably continue to push it without an unrealistic amount of force. The more you push the snowball the bigger it gets. You have two options. Add more force, or come back to the snowball later after the sun has come out and melted the snowball, shedding its mass. Obviously the snowball hasn't moved much since you left it there yesterday. Once mass is lower a breakout occurs! The snowball begins to roll again and mass is added to the distribution once more, since force was once again able to be higher than mass which caused the trend in the first place.


Here's a great example. As defined by the 50 distribution we see bouts of expansion and compression. Every time mass is larger than force, price returns inside the 1.25 standard deviation which allows mass to compress. When the expansion of the 50 distribution begins and the trend resumes, it's because force once again is larger than mass!

That's all a flag is really. The shorter period distributions have too much mass to realistically continue to be pushed. By going sideways (or back to the mean) it allows these distributions to shed their mass. Low mass means easy movement, less force is required to continue the move.

Which brings me to my favorite question. If flags are formations caused by an aspect of volatility, why look at derivative information instead of the force that's actually causing price to react that way?

Now what if I told you mass is a measurable, tradable metric?


The indicator on the bottom is Mark Whistler's Wave PM, it's an oscillator that shows how large a period's distributional width is. A reading above 0.9 represents critical mass. Guess what happens if a distribution has critical mass and starts compressing? It returns to the center of data. If a 200 period distribution has a mass reading above 0.9, and price returns inside the 1.25 standard deviation of the 200 period, price will return to the 200 MA.


This is where things get exciting.

This phenomenon happens on every timeframe, on every period. The period length doesn't even matter, as long as the mass reading is above 0.9 and the 1.25 standard deviation is crossed price will return to that relative mean with around 90% consistency.

So you may be thinking to yourself, would it be possible to measure the longest period of mass to find the longest possible pivot that will define trend and mean reversion? Why yes it is. I've had my developer create a 3D heat map representing 32 separate periods of mass. Red represents a mass level above 0.9. This allows you to define which periods are overexpanded, your longest overexpanded period, and volatility overhead (longer period distributions compressing that will define lateral trading as represented by their 1.25 stdev.)

Here's an example on the daily.


and the 1 minute.

Again, every timeframe, and every period.


This can be used for trading chop, finding retracement values, defining trend and ranged trading, finding the required relative force to overpower mass, and mean reversions. A whole lot more accurate than MACD, RSI, and Fibonacci if you ask me.

I hope this was an insightful peek into my adaptation of advanced volatility theory, utilize this information however you like and I hope it increases your profitability. If any of this info feels unwarranted, click below to look at my last 100 trades which are all timestamped with an interactive tradingview idea.