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A downer can't find a pattern on a sine wave either.
A smart person will not find a pattern on a forex chart.
You must be one of the 1/1000 smartest people on the planet to find patterns on the Forex market.)
I would have certainly looked for it if he had generously shared his profits.
but apparently he's not ready to do it.
I can't say anything about the profit of Mr. Gunn, but I have great respect for his different methods of market analysis, he develops his intuition in a professional way. the market does not give out 100 percent of information, and intuition as a tool works in an environment with limited data, for example, an object is slowly moved around the corner and when you reach 50 percent - yep, a pump for a bicycle, provided that the subject has an image of the object in the glossary (brain), and in its absence, even at 100 percent no associative links arise. I'm thinking of re-reading James Hedgerick.
Stops are one-off losses. And I'm talking about statistics, not one-offs.
Take any system at random, run a 10 year test, calculate the average trade and compare it to the spread.
In most cases, the drain will be about the rate of spread per trade. If you set the spread as close to zero as possible (one 5-digit point), the drain turns into a chatter around zero.
That's absolutely right)
I found a good definition in my head, but didn't know how to express it.
A sequence is random if its algorithmic complexity is close to its sequence length.
Now the question is, how to calculate the algorithmic complexity of a sequence?
I finally found a good definition, which was on my mind, but I didn't know how to express it.
A sequence is random if its algorithmic complexity is close to its sequence length.
The question now is how to calculate the algorithmic complexity of a sequence?
It's also calledKolmogorov's randomness. The main problem is that it is not an absolute concept, but a relative one. It defines randomness relative to a fixed "computing device", and the same sequence can be perceived quite differently. For example, a sequence of digits of Pi may seem random to someone who does not know about this number.
Shiryaev's lecture on randomness:
This is also calledKolmogorov Randomness. The main problem is that it is not an absolute concept, but a relative one. It defines randomness relative to a fixed "computing device" and the same sequence can be perceived quite differently. For example, a sequence of digits of Pi may seem random to someone who does not know about this number.
Shiryaev's lecture on randomness:
Thanks, I'll have a look
This is also calledKolmogorov Randomness. The main problem is that it is not an absolute concept, but a relative one. It defines randomness relative to a fixed "computing device" and the same sequence can be perceived quite differently. For example, a sequence of digits of Pi may seem random to someone who does not know about this number.
Shiryaev's lecture on randomness:
A great lecture!))))