From theory to practice - page 1136

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Martin Cheguevara:

here's the final version to make it easy to count

good luck to you!

Sincerely

Che.

Thanks, Che!

I'll see how the variance calculations change...

 
Martin Cheguevara:

here is the final version to make it easy to count

good luck to you!

Sincerely

Che.

Well, yes - as expected, taking into account the nonlinearity of time, the variance of the process becomes practically = const, i.e. in the nonlinear space-time continuum we have practically a stationary process. And this is true not only in the sliding window = 24 hours but in any other window as well!

Let's look at the behaviour of EURUSD on Friday 05.04.2019:

On the lower chart:

red and blue are the variance without regard to time non-linearity.

Orange and blue - dispersion with time non-linearities taken into account.

And this is the quasi-stationarity of the process obtained in the sliding window = 1 (one!) hour.


Question: How did you manage to transform the Local Time column? Are you a genius?

 

As for moving to a price image via distances (according to Pythagoras' theorem), i.e. a pure event graph with a linear horizontal scale, we get the following picture:

Here:

upper graph - just the EURUSD price

lower chart - sum of distances.

I do not yet know what conclusions can be drawn from this...

I have not looked into the Minkowski space as well.

All in all, interesting. From a practical point of view, of course, I am most interested in the behavior of the dispersion of the process, given the nonlinearity of time. This stationarity in the narrow sense, I have already included in my TS. And we will look at the results during April. If all goes well, I will run to the real world.

 
Макс:
You wrote it wrong. I should have written it in big blue letters. :)

Some Marx has appeared in the thread... That's crazy. Engels is just waiting for...

 
Alexander_K:

Question: How did you manage to convert the Local Time column? Are you a genius?

No, I'm not a genius...
I've just done programs not only in Java but also in Visual Basic in Excel... and I understand something... nothing special...
 
Alexander_K:

As for moving to a price image via distances (according to Pythagoras' theorem), i.e. a pure event graph with a linear horizontal scale, we get the following picture:

Here:

upper graph - just the EURUSD price

lower chart - sum of distances.

I do not yet know what conclusions can be drawn from this...

I have not looked into the Minkowski space as well.

All in all, interesting. From a practical point of view, of course, I am most interested in the behavior of the dispersion of the process, taking into account the nonlinearity of time. This stationarity in the narrow sense, I have already included in my TS. And we will look at the results during April. If all goes well, I will run to the real world.

the sum of what distances?

if from the coloured lines to the average or to the price, then the first screenshot is correct, but the second (in the next post) is not.
 
Alexander_K:

As for moving to a price image via distances (according to Pythagoras' theorem), i.e. a pure event graph with a linear horizontal scale, we get the following picture:

Here:

upper graph - just the EURUSD price

lower chart - sum of distances.

I do not yet know what conclusions can be drawn from this...

I have not looked into the Minkowski space as well.

All in all, interesting. From a practical point of view, of course, I am most interested in the behavior of the dispersion of the process, taking into account the nonlinearity of time. This stationarity in the narrow sense, I have already included in my TS. And we will look at the results during April. If everything goes well - go for real.

The interesting thing is that Renat has his way of achieving results, I have mine, and you have a third option:)
True, you do not have it yet:
1. determining the strength of directional price movement
2. The price chart is not divided into sectors based on characteristic movement signatures
3. You have no method for determining the degree of parity of the price movement at certain parts of the market.
4. Do not use the arithmetic mean in any form, do not take it as a basis for analysis.
Although who knows maybe you will solve this in your own way too =)
 
Martin Cheguevara:
The most interesting thing is that Renat has his way of achieving a result, I have mine, while you have the third option :)
The truth is that you don't have it yet:
1. determining the strength of the directional price movement
2. The price chart is not divided into sections by the characteristic movement signatures
3. You have no method for determining the degree of parity of the price movement at certain parts of the market.
4. Do not use the arithmetic mean in any form, do not take it as a basis for analysis.
Although who knows maybe you will solve this in your own way too =)

extremely agree.

 
Renat Akhtyamov:

The sum of what distances?

if to the average or to the price, then the first screenshot is correct and the second (in the next post) is not.

Well, distances S = +-sqrt((PRICEn-PRICEn-1))^2+(TIMEn-TIMEn-1)^2)) by Pythagoras' theorem, taking into account the sign. In this case, time already sits in the price.

The devil knows - it doesn't seem to see anything... But, it's an accumulative amount... Maybe when calculating on more than 1 day's data something more interesting will happen. I don't know.

 
Martin Cheguevara:
The interesting thing is that Renat has his way to achieve a result, I have mine, while you have the third option:)
The truth is that you don't have it yet:
1. determining the strength of the directional price movement
2. The price chart is not divided into sections by the characteristic movement signatures
3. You have no method for determining the degree of parity of the price movement at certain parts of the market.
4. Do not use the arithmetic mean in any form, do not take it as a basis for analysis.
Although who knows maybe you'll solve that in your own way too =)

I think you're one of the few in this thread who really knows how to work. Good luck to you!

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