Richard
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 Feb9 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. Feb9 answered Compute moments of aggregate loss using Monte Carlo Feb9 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 ;) Feb6 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... Feb6 comment Get distribution for aggregate loss using Monte Carlo See the EDIT and the link for the moment and the Gamma distribution. Feb6 revised Get distribution for aggregate loss using Monte Carlo added 603 characters in body Feb6 answered Get distribution for aggregate loss using Monte Carlo Jan28 awarded Popular Question Jan27 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? Jan27 asked Black-Litterman: Why should the views be independent of each other? Jan27 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? Jan26 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 ... Jan22 accepted Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior Jan22 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! Jan21 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! Jan20 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 ... Jan20 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. Jan20 asked Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior Jan20 revised How to price an option on a dividend-paying stock using the binomial model? edited title Jan19 answered How to price an European call on zero-coupon from the yield curve?