Logistic Distribution

vasvet

New Member
Hi All,

If .the logistic distribution is defined as it corresponding quantile function:

1579038146500.png
How can I show that q is strictly increasing and compute logistic distribution function and it's density function?

How to compute VaR and ES of r.v. with logistic distribution?

Thank you for your help
 

Detective

Active Member
Did you mean to write F inverse = ln((alpha)/(1-alpha))? I.e. the logit probability function?

To prove g(x) is strictly increasing, show g’(x) > 0 for all x.

To get CDF you can find the inverse of the function you have, take derivative you get PDF.

VAR: By definition VAR is based on the quantile. https://en.m.wikipedia.org/wiki/Value_at_risk

See mathematical definition

ES: You’ll need to take an integral.

https://en.m.wikipedia.org/wiki/Expected_shortfall

See formal definition.
 

sapozan

New Member
Thank you @Detective . The function appears to be correct as it is presentes as a quantile function. Would ah inverse of an inverse just be an actual CDF ?
In this case F=ln((alpha)/(1-alpha))

Am I correct here ?
 

sapozan

New Member
Awesome thank you @Detective,

Is it possible to derive the actual distribution function from the above quantile function and not the other way round?

I am not too sure if the above formula is exactly correct so i will have to double check this.
 

Detective

Active Member
Awesome thank you @Detective,

Is it possible to derive the actual distribution function from the above quantile function and not the other way round?

I am not too sure if the above formula is exactly correct so i will have to double check this.

Not sure if I follow, you have a function,

y= f(x) = ln(x/(1-x)), with 0<x<1 and you want to find inverse?

The way I was taught was to replace “y” with “x” and then solve for y. Getting rid of LN will involve taking EXP.
 
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