The market is a controlled dynamic system. - page 116

 
avtomat:
No. I gave you the formula.
I couldn't find it. It doesn't matter, it's wrong anyway. True 25% efficiency :) not 130
 
avtomat:

It is not clear how you envisage this.

The superexponent s(-t;n=1) is exactly the same as the ordinary exp(-t):

 
yosuf:

The superexponent s(-t;n=1) is exactly the same as the ordinary exp(-t):


As I understand it, this is some function from Excel. Which one is it? I am interested in the formula itself.
 
TheXpert:
I haven't found it. Anyway, it's wrong anyway. True 25% efficiency :) not 130


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Applies to each tractor individually, and to the tractor team as a whole.


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I was talking about right/wrong - I was talking about that too:


Efficiency can be defined in many different ways, depending on the objectives. But the primary one is the 'goal'. As a goal, a target function, one can consider growth of balance, or growth of equity, or growth of cache, or one can consider growth rate of balance \equity \ cache .... etc. etc. --- i.e. set some maximisable functional. On the contrary, it is possible to consider time to reach a given level of balance \ eviti \ cache as a target function, or to focus on drawdown ..... etc. etc. --- i.e. set some minimisable functional. Depending on this choice of target functional, the efficiency will be determined. ( # )


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What is the correct way to do it?

 
avtomat:
As I understand it, this is some kind of function from Excel. Which one is it? I'm interested in the formula itself.
s (t;n) = AND (t;n) = 1-HAMMARASP(t;n;1;1)
 
avtomat:


.

Applies to each tractor individually, and to the tractor team as a whole.


.


I was talking about right/wrong - I was talking about that too:


Efficiency can be defined in many different ways, depending on the objectives. But the primary one is the 'goal'. As a goal, a target function, one can consider growth of balance, or growth of equity, or growth of cache, or one can consider growth rate of balance \equity \ cache .... etc. etc. --- i.e. set some maximisable functional. On the contrary, it is possible to consider time to reach a given level of balance \ eviti \ cache as a target function, or focus on drawdown ..... etc. etc. --- i.e. set some minimisable functional. Depending on this choice of target functional, the efficiency will be determined. ( # )


.




What do you think is the right way to do it?

In the most general sense, efficiency is the ratio between the result and the inputs or resources that caused that result. Since the main result is the profit generated, it can be taken as an option:

Efficiency = profit / (initial deposit + replenishments)*100% = [funds / (initial deposit + replenishments) - 1]*100%

 

I open up an Excel reference and I see:

yosuf:
s (t;n) = AND (t;n) = 1-HAMMARASP(t;n;1;1)


I can't figure out how you arrived at this.

I do remember, though.

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Explain.

 
yosuf:

In the most general sense, efficiency is the ratio between the result and the inputs or resources that caused that result. Since the main result is the profit made, it can be taken as an option:

Efficiency = profit / (initial deposit + replenishment)*100%



This is what is reflected in the formula above
 
yosuf:


1 - And - Superexponent, the progenitor of the set of exponents, turning into "our" exponent e = 2.7181..... only at n = 1;

Consequently, I am forced to admit the possibility of the existence of the set of exponents, which will encounter a categorical denial from mathematicians brought up on the immutability of the number e = 2.7181...



So from the gamma distribution you infer a multiplicity of exponents???

Recall that

 
avtomat:

I open up an Excel reference and I see:


I can't figure out how you arrived at this.

But I do remember that...

Explain.

What you remember is written in Exel language as follows:

H (t,t,n) = GAMMARASP(t/t;n;1;0) is the density function of the Gamma distribution or the density function of the Erlang distribution;

P (t,t,n) = GAMMARASP(t/t;n+1;1;1) is the integral function of Gamma distribution or the integral function of Erlang distribution;

AND (t,t,n) = GAMMARASP(t/t;n;1;1) is an integral function of Gamma distribution or an integral function of Erlang distribution;

B (t,t,n) =1 - GAMMARASP(t/t;n;1;1) is what I call "integral superexponential function" or "two-parameter integral exponential distribution function .........", which has not been in circulation so far; It converts to the well-known exponential distribution when n = 1.

In the superexponential example above, for simplicity, the case t = 1 is given.