Analysis and Trading based on Envelopes, Waves, Cycles

You wil notice just prior to taking this trade I was short under the center extension (yellow dot), normally I expected a test of the bottom where I was planning to go long...but it reversed and I got out with just a few dollars loss....I move my lines as the price progresses, or declines.....most of the time.

Listen, unless you have a super fast platform, from a very reputable honest broker, I would not be trading Bitcoin, they will slaughter a new trader who has to go through a dealing desk......my trades are in and out in a millisecond....I can limit losses and take profits instantly that way...so very close supervision of my trades needed, no bouncing around from currency to currency other instruments...no time for that..lol

note how I adjusted in just the last few minutes....and why...you need to keep the center ma dynamic all the time...

So I adjusted and look what happenned...look at the bounce and where it bounced from

ps...now we have a new center line, and upper channel established....for now...

Thank you for clarification ; )

Just wanted to confirm I do the same as you guys lol. The point of moving the lines is to be mindful of changes in direction and to also try to predict where it will cross other CMAs, am I right on that one?

As for BTC yes you're right, I actually only trade it on demo for training since the commissions are super high and as you said it can get very volatile.

It is easy to get analyses paralyses, I noticed all your posts. They are good posts but I think you would do well to hit the pause button, choose a currency (just one) that has an ADR of around 100 pips, choose this one method for a week, along with the larger time frames for the same currency, and just watch, watch and watch some more. Don't even take demo trades unless your doing it just for yourself...(not sharing).

Take your one hour, mark support and resistance, mark big round numbers and then when the 1 min reaches those levels you will see something very interesting....

You're right. I do feel that way too. Now that I've built some base, it's time for some peace and quiet and just observing the instrument. See the potentials, behavior etc..

Thanks Swede. Have a good one.

Now, just one half hour later...look once again at the 1 hour chart I posted...and then open your 1 min 5cma chart....see what I mean??

I hour later....now look at the 1 min and 1 hour chart...was that or was that not a great entry?

works pretty good for Bitcoin....

Yes i have, i read It thousand times but i don't understand this "smooth a rennant of a 12w componenti from 20w ma".....

Thank u for you help, green pips to all

DAX m1:

DAX 1 mn

History and Background Who First Came Up With Moving Averages?

Technical analysts have been using moving averages now for several decades. They are so ubiquitous in our work that most of us do not know where they came from.

Statisticians categorize Moving Averages as part of a family of tools for “Time Series Analysis”.

Development of the “moving average” dates back to 1901, although the name was applied to it later. From math historian Jeff Miller:
MOVING AVERAGE. This technique for smoothing data points was used for decades before this, or any general term, came into use. In 1909 G. U. Yule (Journal of the Royal Statistical Society, 72, 721-730) described the “instantaneous averages” R. H. Hooker calculated in 1901 as “moving-averages.” Yule did not adopt the term in his textbook, but it entered circulation through W. I. King’s Elements of Statistical Method (1912).

“Moving average” referring to a type of stochastic process is an abbreviation of H. Wold’s “process of moving average” (A Study in the Analysis of Stationary Time Series (1938)). Wold described how special cases of the process had been studied in the 1920s by Yule (in connection with the properties of the variate difference correlation method) and Slutsky [John Aldrich].

From StatSoft Inc. comes this description of Exponential Smoothing, which is one of several techniques for weighting past data differently:

“Exponential smoothing has become very popular as a forecasting method for a wide variety of time series data. Historically, the method was independently developed by [Robert Goodell] Brown and [Charles] Holt. Brown worked for the US Navy during World War II, where his assignment was to design a tracking system for fire-control information to compute the location of submarines. Later, he applied this technique to the forecasting of demand for spare parts (an inventory control problem). He described those ideas in his 1959 book on inventory control. Holt’s research was sponsored by the Office of Naval Research; independently, he developed exponential smoothing models for constant processes, processes with linear trends, and for seasonal data.”
Brown’s book, Smoothing, Forecasting and Prediction of Discrete Time Series, was republished in 2004.

Holt’s paper, “Forecasting Seasonals and Trends by Exponentially Weighted Moving Averages” was published in 1957 in O.N.R. Research Memorandum 52, Carnegie Institute of Technology. It does not exist online for free, but may be accessible by those with access to academic paper resources.
See also Forecasting With Exponential Smoothing, by Hyndman, Koehler, Ord, and Snyder.

To our knowledge, P. N. (Pete) Haurlan was the first to use exponential smoothing for tracking stock prices. Haurlan was an actual rocket scientist who worked for JPL in the early 1960s, and thus he had access to a computer. He did not call them “exponential moving averages (EMAs)”, or the mathematically fashionable “exponentially weighted moving averages (EWMAs)”. Instead he called them “Trend Values”, and referred to them by their smoothing constants. Thus, what today is commonly called a 19-day EMA, he called a “10% Trend”. Since his terminology was the original for such use in stock price tracking, that is why we continue to use that terminology in our work.

Haurlan had employed EMAs in designing the tracking systems for rockets, which might for example need to intercept a moving object like a satellite, a planet, etc. If the path to the target was off, then some sort of input would need to be applied to the steering mechanism, but they did not want to overdo or underdo that input and either become unstable or fail to turn. Thus, the right sort of smoothing of data inputs was helpful. Haurlan called this “Proportional Control”, meaning that the steering mechanism would not try to adjust out all of the tracking error all at once.

EMAs were easier to code into early analog circuitry than other types of filters because they only need two pieces of variable data: the current input value (e.g. price, position, angle, etc.), and the prior EMA value. The smoothing constant would be hard-wired into the circuitry, so the “memory” would only have to keep track of those two variables. A simple moving average, on the other hand, requires keeping track of all values within the lookback period. So a 50-SMA would mean keeping track of 50 data points, then averaging them. It ties up a lot more processing power.
See more about EMAs versus Simple Moving Averages (SMAs) at Exponential Versus Simple.

Haurlan founded the Trade Levels newsletter in the 1960s, leaving JPL for that more lucrative work. His newsletter was a sponsor of the Charting The Market TV show on KWHY-TV in Los Angeles, the first-ever TA television show, hosted by Gene Morgan. The work of Haurlan and Morgan were a big part of the inspiration behind Sherman and Marian McClellan’s development of the McClellan Oscillator and Summation Index, which involve exponential smoothing of Advance-Decline data.

You can read a 1968 booklet called Measuring Trend Values published by Haurlan starting on page 8 of MTA Award Handout, which we prepared for attendees at the 2004 MTA conference where Sherman and Marian were awarded the MTA’s Lifetime Achievement Award. Haurlan does not list the origin of that mathematical technique, but notes that it had been in use in aerospace engineering for many years.

About Technical Analysis and "Recalibration"

a paper from Peter Haurlan

BITCOIN 1 mn

MA's Chart

This is a good line of inquiry because it made me think, and I think a lot of people jumped over this in the text (like I did on first read). I read this part in the book several times and I think the answer must be inferred from other concepts presented in the text previously.

So to start off, how did Hurst estimate that the full span average had a 12 period remnant or cycle? I attach Hurst's original picture with numbers overlaid in red counting off the 12 period cycle. As we know, a cycle moves over the course of a sine wave from a starting point and ending with that starting point plus or minus trend. The trend is the slope of the straight line from the starting point to the ending point. So starting and ending on the same straight line would indicate the length of the cycle as parisboy has shown us many times and the 12 count is shown clearly in the picture.

Next, how did Hurst smooth a 12 period cycle from his full span average? He stated previously that when you apply a moving average of a particular length, it suppresses the cycle of that length. So obviously you apply a 12 period moving average to the full span average to smooth it out. Then the smooth line can easily be extended.

As proof that a 12 period cycle can be smoothed out with a 12 period moving average, I created a simple 12 period cycle in R (white line) using points 1,2,3,4,5,6,6,5,4,3,2,1 repeated over and over and then smoothed it with a 12 period moving average (red line) shown in the picture below. As you can see, the red line is perfectly flat indicating that a 12 period moving average does in fact smooth out a 12 period cycle.

This is the sort of analysis one can do if trades take weeks at a time as was the case for Hurst. If you are doing this on intraday charts, it would need to be automatically done or simply estimated as Tillman does by using a longer period moving average (double the length of the full span) to confirm where the focal point occurs.

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Opened Short position

Excellent ! Thank you very much FXEZ

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