a) Kurtosis, K = M4 / s^4
or
b) Excess, Ex = K − 3
where,
M4 = fourth central moment
s^4 = standard deviation to the fourth power
thx in adv
Best regards,
Koval
Here is a full explanation
- www.investopedia.com
Thanks, I know what Kurtosis is and what it comes with.
I'm just not sure what the function in MQL5 actually returns, does it return Kurtosis or maybe Excess?
Do you know the answer?
I need this to determine the type of data distribution (e.g. Platykurtic)
Best regards
Koval
Did you refer to the documentation? ... https://www.mql5.com/en/search#!keyword=MathKurtosis&module=mql5_module_documentation
oh, thanks a lot Fernando.
here https://www.mql5.com/en/docs/standardlibrary/mathematics/stat/array_stat/mathkurtosis
is a link to https://www.r-tutor.com/elementary-statistics/numerical-measures/kurtosis
I looks, like function returning Excess of Kurtosis (not Kurtosis) :)
Best regards,
Koval
- www.mql5.com
oh, thanks a lot Fernando.
here https://www.mql5.com/en/docs/standardlibrary/mathematics/stat/array_stat/mathkurtosis
is a link to https://www.r-tutor.com/elementary-statistics/numerical-measures/kurtosis
I looks, like function returning Excess of Kurtosis (not Kurtosis) :)
Best regards,
Koval
It seems you overlooked some of the details in the documentation, on the very MQL5 document link you provided.
It states and I quote ...
"Disclaimer
Calculation of the kurtosis is performed using the excess kurtosis around the normal distribution (excess kurtosis=kurtosis-3), i.e. the excess kurtosis of a normal distribution is zero.
It is positive if the peak of the distribution around the expected value is sharp, and negative if the peak is flat."
As usual, you are invaluable Fernando.
Thank you for being so understanding and willing to help.
Now I'm 100% clear, and in the future I have to read the documentation more carefully.
Thank you,
Koval
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a) Kurtosis, K = M4 / s^4
or
b) Excess, Ex = K − 3
where,
M4 = fourth central moment
s^4 = standard deviation to the fourth power
thx in adv
Best regards,
Koval