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Feb
9
comment Get distribution for aggregate loss using Monte Carlo
You try to fit this $x_0$ by the method of moments (as I have seen in the other question). Maybe this estimte has too much variance. Try maximum-likeliohood instead. It should work too.
Feb
9
answered Compute moments of aggregate loss using Monte Carlo
Feb
9
comment Get distribution for aggregate loss using Monte Carlo
Yes you can average $L^3$ from the sample or you look here on page 8 for the formla of the skewness in the collective risk model. If you like my answer then don't forger to accept ;)
Feb
6
comment Black-Litterman: Why should the views be independent of each other?
Thanks for your nice examples-I really like the ideas behind them. I just still wonder why B and L themselves use diagonal in the papers. Usually whenever possible one works as general as it makes sense. Non-diagonal absolutely makes sense...
Feb
6
comment Get distribution for aggregate loss using Monte Carlo
See the EDIT and the link for the moment and the Gamma distribution.
Feb
6
revised Get distribution for aggregate loss using Monte Carlo
added 603 characters in body
Feb
6
answered Get distribution for aggregate loss using Monte Carlo
Jan
28
awarded  Popular Question
Jan
27
comment Black-Litterman: Why should the views be independent of each other?
Yes, Jay Walters writes this on top of page 13 and starting with page 14 he also states the specification $\Omega = P \Sigma P^T$. So he speaks about both choices ... looking at his survey paper diagonal and full matrices are possible. My question is, why does Litterman himself use a diagonal matrix?
Jan
27
asked Black-Litterman: Why should the views be independent of each other?
Jan
27
comment Is the CAPM beta equivalent to the coefficient estimate of an OLS regression?
What are these other methods? Do they rigorously fit into the framework of CAPM?
Jan
26
comment Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
Thanks for the link to the full publication - I have already read summaries of it ...
Jan
22
accepted Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
Jan
22
comment Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
Your edit is a good point!
Jan
21
comment Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
@Felix do you have a reference for this choice of $\Omega$ in a preprint or article that I can look at for free? Maye one of Meucci's papers? Thanks!
Jan
20
comment Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
Or where does $\tau$ enter? do we have 2 factors: $(1/c-1) \tau$? Then one would see things quite clearly in the correction term above ...
Jan
20
comment Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
But you have to agree that setting $1/c-1 = \tau$ leads to what I write above ... I will play with your $c$ factor - thanks for your answer.
Jan
20
asked Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior
Jan
20
revised How to price an option on a dividend-paying stock using the binomial model?
edited title
Jan
19
answered How to price an European call on zero-coupon from the yield curve?