meta user
network profile
| bio | website | |
|---|---|---|
| location | Oslo, Norway | |
| age | ||
| visits | member for | 1 year, 6 months |
| seen | May 7 at 7:03 | |
| stats | profile views | 28 |
|
Mar 5 |
comment |
Quantitative Analysis Games on Investing? Does this mentioned game above come in a non-finish version? The documentation looks fun, but when I try to navigate around I get to finish pages. |
|
Feb 20 |
comment |
How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? As I have not found any good litterature on linear combination of lognormals and this question round neither gave any good results, I assume it is because there is no currently known closed solution of the problem stated. A hope for the question was to find something like a "better approximation" to the problem. I guess the best solution is to either reduce number of simulations or accept the (unknown) deviation. Thanks for help, guys. |
|
Feb 14 |
awarded | Nice Question |
|
Feb 8 |
comment |
How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? Setting a fixed seed will reduce the "mc-noise" but the two methods will still differ as we simulate prices as lognormal, but use that the arithmetic return is normal in the parametric case. Your second approach is smart but i have already hiven it a try. As the portfolio changes over time too, it didnt come out very well in my "sample tests"... |
|
Feb 8 |
comment |
How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? True, but hen you have the multivariate case. Do you know how linear combination of lognormal distributed rv's looks like? The litterature Ive seen looks messy. Unfortunately.. |
|
Feb 8 |
comment |
How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? Yep, think the method goes under that name too. The problem is not to get a better model in that way, rather it is to find a closed form solution that mimic the geometric part of the stock model. |
|
Feb 7 |
awarded | Editor |
|
Feb 7 |
revised |
How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? added 2 characters in body |
|
Feb 7 |
comment |
What weights should be used when adjusting a correlation matrix to be positive definite? Well. Thinking within the model, one would believe that some correlation pairs are more trustworthy than other (e.g. high liquidity implies good data implies a better correlation coefficient). Thinking outside a model, looking at how much the correlation have changed in history could also be a parameter that determine the weight of a pair (high variability in time implies lower weight). Not sure if its worth an own question. Rather it is a part of the overall, although the quesiton above consist of technical and a economical considerations. |
|
Feb 7 |
comment |
What weights should be used when adjusting a correlation matrix to be positive definite? Yes, I agree, but I have received some pretty nasty results while weighting. Also, how should one evaluate correlation pairs? |
|
Feb 7 |
asked | How to minimize the difference between a parametric VaR and a MC-VaR with lognormal assumption? |
|
Feb 6 |
awarded | Supporter |
|
Feb 6 |
comment |
Calculating log returns using R hadnt noticed the "diff" function yet. A handy one, indeed. |
|
Feb 6 |
awarded | Teacher |
|
Feb 6 |
answered | Calculating log returns using R |
|
Nov 8 |
comment |
What weights should be used when adjusting a correlation matrix to be positive definite? Thanks. Well, so far I have not found any solution and are currently running unweighted approximations. I find this about alright, but as I am approximating correlations from some stocks that are somewhat illiquid it would be satisfying knowing that these will be altered more than the main stocks in our portfolios.. |
|
Oct 26 |
awarded | Student |
|
Oct 26 |
asked | What weights should be used when adjusting a correlation matrix to be positive definite? |
