Similarity Thoughts: Unterschied zwischen den Versionen

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= Similarity =
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Dear Peter,
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I hope your are fine. I wrote this page to summarize my thoughts about the theories and things you have presented. I have to admit that your way of thinking and approaching the fx world is pretty unique. However, I was never able to make it work. The reason is that there seems to be always (not just in your approaches presented) a trade-off between the probability of winning and the potential losses, i.e. the higher my winning probability becomes, the higher are the potential losses, too.
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So, my question is not really directly related to your strategies (I know that you won't talk about it although I think I came closest to understand your thoughts in the similarity field) but is more on how you manage the risk and your money while trading these ideas. Thus, if you are not interested in how I perceived your theory, you can directly go to the end of this page and continue reading there.
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May god bless you for your help and kindness!
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D
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== General idea ==
 
== General idea ==
  
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The Greek letter λ can then be interpreted as a parameter (i.e. indicator setting) that determines the relative frequency of similarity. Following Eurusdd's statements, λ should be chosen in a way that the two processes are similar most of the time (almost surely), i.e. > 90 % similarity (e.g. P = 0.97).
 
The Greek letter λ can then be interpreted as a parameter (i.e. indicator setting) that determines the relative frequency of similarity. Following Eurusdd's statements, λ should be chosen in a way that the two processes are similar most of the time (almost surely), i.e. > 90 % similarity (e.g. P = 0.97).
  
I interpret it this way: If two processes are hardly dissimilar then one could assume that a similar state follows a dissimilar state most of the time. Thus, the stochastic processes are somewhat predictable (at least if further properties are true, e.g. that a trend will most likely continue instead of reverse).
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I interpret it this way: If two processes are hardly dissimilar then one could assume that a similar state follows a dissimilar state most of the time. Thus, the stochastic processes are somewhat predictable (at least if further properties are true, e.g. that a trend will most likely continue instead of reverse). Let's see how it does apply to the presented similarity setups discussed in the course of the similarity thread:

Version vom 27. April 2019, 11:07 Uhr

Dear Peter,

I hope your are fine. I wrote this page to summarize my thoughts about the theories and things you have presented. I have to admit that your way of thinking and approaching the fx world is pretty unique. However, I was never able to make it work. The reason is that there seems to be always (not just in your approaches presented) a trade-off between the probability of winning and the potential losses, i.e. the higher my winning probability becomes, the higher are the potential losses, too.

So, my question is not really directly related to your strategies (I know that you won't talk about it although I think I came closest to understand your thoughts in the similarity field) but is more on how you manage the risk and your money while trading these ideas. Thus, if you are not interested in how I perceived your theory, you can directly go to the end of this page and continue reading there.

May god bless you for your help and kindness! D


General idea

Eurusdd added supposedly later on a formal description of the similarity idea to the 1st post in the similarity thread:

Fehler beim Erstellen des Vorschaubildes: Die Miniaturansicht konnte nicht am vorgesehenen Ort gespeichert werden

This doesn't seem to be something special. It states that there are two stochastic processes that should be isomorphic (bijective?) most of the time. This imo could be either

  • the price itself and an indicator that resembles the prices, or
  • two indicators that show similar readings most of the time.

The Greek letter λ can then be interpreted as a parameter (i.e. indicator setting) that determines the relative frequency of similarity. Following Eurusdd's statements, λ should be chosen in a way that the two processes are similar most of the time (almost surely), i.e. > 90 % similarity (e.g. P = 0.97).

I interpret it this way: If two processes are hardly dissimilar then one could assume that a similar state follows a dissimilar state most of the time. Thus, the stochastic processes are somewhat predictable (at least if further properties are true, e.g. that a trend will most likely continue instead of reverse). Let's see how it does apply to the presented similarity setups discussed in the course of the similarity thread: