From theory to practice - page 603
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The only remaining question is whether the price is wavering or whether the channel is going after the price.
The channel is naturally price-competitive.
The channel goes for the price naturally.it's for Sat)
My option is the latter - I dare only speculate...
And is it correct that the gist of 600 pages of this tossing around the grail is as follows:
Is it right? Is the gist correct? Nothing is missing?
:-)
And in your drawing you have the Grail of pure gold.
I looked at the 100% quantiles of the distributions of the sums of increments and compared them to the quantiles of the price itself for the same historical plot:
Black - 100% quantile for the sum of the increments in the sliding window=8 hours
Purple - 100% quantile for the price in the same window.
Taki are two different processes generating different probability distributions.
If we use the dynamic 100% quantile for the sum of the increments, we get the following picture:
I don't rule out that if you work in a sliding window = 24 hours (on the advice of my friend Bas'a) and use a dynamic 99% quantile, you can get a picture similar to yours.
this is for the sub).
If the channel is based on price, why should the price follow the channel? The channel will naturally follow the price.
If price were to follow the channel data, it would be the other way around.
And is it true that the point of 600 pages of this grail-throwing is as follows:
You are looking for a magic mathematical formula for the SUP and RES lines running roughly as in the figure:
The price, hypnotized by the beauty of mathematics, has to rush between red and green.
The channel will naturally follow the price.If the channel is based on price, then why should the price follow the channel? Of course the channel will follow the price.
why would you do that? was there any intrigue in the topic ))))
Your confidence is based on:
- Personal experience of successful trading?
- Rigorous mathematical calculation?
- Opinion of others?
- The "I think so" principle?
Or is it a guess rather than a certainty?
On statistics.
))
There are three kinds of lies: lies, blatant lies and statistics. (с)
And you have the Grail of pure gold in your picture.
I looked at the 100% quantiles of the increment sum distributions and compared them to the quantiles of the price itself for the same historical plot:
Black - 100% quantile for the sum of the increments in the sliding window=8 hours
Purple - 100% quantile for the price in the same window.
Taki are two different processes generating different probability distributions.
If we use the dynamic 100% quantile for the sum of the increments, we get the following picture:
I don't exclude that if you work in sliding window = 24 hours (on the advice of my friend Bas'a) and use 99%-quantile, you can get a picture similar to yours
Grail project #100500.
1. Assumed assumptions (require proof or practical confirmation).
1.1 At any time a market profile is defined as some function of the collected history of the price at certain levels.
1.2. Humps of the market profile define boundaries of a channel of price fluctuations.
1.3 The time sequence of market profiles gives us a support-resistance channel.
1.4 It is assumed that the inside part of the channel is a potential pit for the price, and correspondingly, in case of small disturbances, the price tends to approach the average price (flat).
1.5 With significant perturbations, price will break out of the channel and slide along the outside of the channel (trend) to form a new channel structure.
1.6 Multiple channels can be constructed at any given time using different depth of history and method of gathering and transforming historical data.
1.7. Time, as an influencing factor on time intervals less than a day, can only be considered in terms of the arrival of significant perturbations (news).
Time quantization is related to the arrival of price ticks. As a consequence, it does not make sense to search for periodicity on small time intervals.
1.8. The practical depth of history for plotting of channel profiles is significant in time, so it's possible to use quantization on a minute scale for these constructions.
1.9. To specify the borders of a channel, it is necessary to use the tick history and some method to correct the decision concerning forecast of further price development.
In particular, it should be possible to determine the probability of the price being on the inner or outer slope of the channel at that moment.
1.10. Since strong disturbances break the channel trading model, the area of applicability of this model should not approach the areas of strong disturbances predicted.
etc.
All the 600500 pages cited here are an attempt to address only 1.9 and completely ignoring 1.10, which makes 1.9 meaningless at all.
On statistics.
Apparently this is some kind of secret statistic.
No such statistics are found in this thread.
What is printed here seems to give only hope, not certainty.