An accident or an unrecognised pattern? - page 3
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The only difference is the levels of average volatility - it is unique for each currency pair.
Average volatility data can be found on specialised websites or you can calculate it yourself
There is no point in arguing with believers.
What has faith got to do with it ? Faith is a religion... And Traders operate with facts ! You can PROVE that the patterns "are there, not here at all, but much more complex"...
Or is this just another "binge" of the advanced Trader...?
Generate 100-500-1000-10000 random rows and test your TS on all of them - if the average results are better or comparable to the results on the price series, then the TS should be scrapped.
Only all rows should be comparable in length to price series.
You can even generate rows in Excel.
Dimitri. This is curious...
Looked at your topic "How to distinguish the FOREX chart from the PRNG?".
Perhaps, this is what I need now... I just need to figure out how to do it).
Please explain the essence and how it is implemented, what you defined as a condition.
Only all rows should be comparable in length to the price row.
Dimitri. This is curious...
Checked out your thread "How do you tell the difference between a FOREX chart and a PRNG?"
Maybe that's what I need now... I just need to figure out how to do it).
Please explain the essence and how it is implemented, what you defined as a condition.
Only all rows must be comparable in length to the price row.
You tested your system on a ten-year chart - how many points is that?
Here is the same length and take the rows
The only difference is the levels of average volatility - it is unique for each currency pair.
Average volatility data can be found on specialised websites or you can calculate it yourself
Yes, you're right, " the levels of average volatility - it's unique for every currency pair"... But this is a PERSONAL case... And the search for patterns starts with THEORY...
Yes, you are right, " average volatility levels - they are unique to each currency pair"... But this is a PERSONAL case... And the search for patterns starts with THEORY...
Ahtyjöklamn, that's clever.....
Ahtyjöklamn, that's clever.....
Yep, the future period test makes sense to me... I just have to wait until that future period arrives...
Life is so short and the worm is so long)))
When I was talking about properties of quotes, I didn't mean to try to predict the future.
to inherit some unique features of the instrument, such as spread, internal oscillation range or something else...
Actually, I don't understand these features and peculiarities very well, but I see by testing that EURUSD is qualitatively different from USDCHF.
For the same algorithm settings, I get characteristically different dispersion patterns for different symbols.
Frank
Yen .
What makes them different... from each other, which means they have some characteristic properties/peculiarities.
Curious to understand - which ones, how to identify them and how to apply them in modelling to synthetics without conflicting with what you said(Random Wandering).
If you don't take these features into account, then there is no point in testing on synthetic quotes, because with the same success,
the algorithm may be tested simply on another pair...
Has the topic of specific differences of quotes by symbols been discussed/studied anywhere?
It would be interesting to read...
About the average volatility has already been written. You can also say about the average intensity of ticks. Also - volatility and intensity of ticks change depending on the time of day - every instrument has a different one.
If you reduce different instruments to a "common denominator", it will appear that the same results for different instruments will correspond to different values of your algorithm's parameters.
Frank is a "good" example of "guessing" the future properties of quotes)) - There is a good thread somewhere here about the black swan
Here is an example of one of the black swans that flew to the Swiss franc on January 15, 2015:
In my opinion there is a whole range of regularities that I would identify somehow.
Let's assume that you have a history of the intensity of that factor (let's call it F1), which causes quite a natural price change. You need to filter the price history so that it, after filtering (we will call it C1), clearly correlated with the history of that factor. Then the price that will be filtered by C1 will give you a picture of its regular movement C1, associated with the action of F1.
Determine all other factors important for pricing (Ф2, ..., Фn) and find their corresponding filters (С2, ..., Сn), which will give a spectrum of regular price movements (Ц1, ..., Цn).
I'm trying to understand and somehow apply your proposed filter checking conditions, but I can't figure out how...
The problem is that I can't define the F1 condition. I don't understand how to determine a regular price change even from history.
Because my algorithm works on heads and tails principle and in fact the price doesn't play a role at all, there is only the result of outcomes - guessed/unguessed.
There are also sequences of events in history - guessed/not guessed, but this history is not considered in the algorithm, otherwise we may get to a false Monte Carlo output.
That's why we have nothing to rely on but the outcome.
And we should somehow understand that the result of guessing eagle/turtle is more than 50% random or logical...
But I will think how to apply your condition)