Reputation
1,003
Top tag
Next privilege 1,250 Rep.
Create tag synonyms
Badges
7 18
Impact
~55k people reached

Jul
1
comment good R package for vectorized option pricing
I updated my question to make it more clear
Jul
1
comment good R package for vectorized option pricing
thank you for your answer, but lapply is actually looping in R, which is slow (at least too slow for me). I am looking for a package that has a compiled loop, ie that provides a native vectorized function.
Jul
1
comment good R package for vectorized option pricing
@Richard getting the price for a bunch of options with one call, or getting the delta for a bunch of options with one call
May
5
comment What is the main reasons to use Miltersen & Schartz (1998) model for commodity futures options
Note that it is a very widely cited paper, not a crazy model coming from nowhere
Apr
3
comment What are some different methods for calculating hedge ratios for multiple leg spreads?
Do you mean "hedge ratio"?
Apr
3
comment Why is delta-hedging of ATM options near expiry difficult to do?
Why is this closed? There is a scientific explanation to this question, as the delta of ATM options close to expiry becomes binary.
Apr
3
comment What are some different methods for calculating hedge ratios for multiple leg spreads?
which "ratios" do you mean?
Aug
14
comment portfolio optimisation with VaR (or CVaR) constraints
Thank you very much, this is very insightful
Aug
14
comment portfolio optimisation with VaR (or CVaR) constraints
it seems that even though CVXOPT is open source, it only contains interfaces to the solvers in MOSEK, which is not open source.
Aug
14
comment portfolio optimisation with VaR (or CVaR) constraints
Thanks for your input, makes sense. What about $r_{ij}$ ? The return of asset $i$ in simulation $j$ ? Do you really have to simulate them or can you take simply the past ones? i would like to avoid modelling the returns, as it could create errors (bad tail correlation estimation etc.) Now if you need 10,000 of them I understand you have to simulate. But is it not dangerous?
Aug
14
comment portfolio optimisation with VaR (or CVaR) constraints
If I am not wrong these $m$ are the Monte Carlo simulations that @David Nehme is mentioning in his answer. I guess $m$ has to be high enough. 1000? 2000? Do you have an idea?
Aug
13
comment portfolio optimisation with VaR (or CVaR) constraints
The second link seems very interesting, thanks. I have read carefully the paper. however, I truggle to understand how they replace the expectancy that is in formula (9) page 8, with a sum over $j$. What are these $r_{ij}$ and what is $m$? Apart from that, the solution is quite elegant... Can be solved with a very standard optimizer.
Aug
13
comment portfolio optimisation with VaR (or CVaR) constraints
+Alexey, do you have this ebook "Portfolio Optimization with R/Rmetrics"? On the google preview at page 333 it seems that I read that quadratic constraints are treated in the other ebook "Advanced Portfolio Optimization with R/Rmetrics" If you have the book, can you confirm if there are such examples? books.google.com.sg/…
Aug
13
comment How to normalize different instruments by volatility?
not sure what your discussion on quants really brings to Freewind's question. Sounds like a useless digression.
Aug
10
comment portfolio optimisation with VaR (or CVaR) constraints
indeed. I need quadratic constraints. The objective function is linear but the VaR constraint is definitely quadratic. Will have a look at your link. Thanks
Aug
10
comment portfolio optimisation with VaR (or CVaR) constraints
@BobJansen I have several VaR constraints on several groups of assets in my portfolio. I cannot manually adjust every day the expected returns of all my assets to ensure the VaR constraints. Ideally I would have to model the constraint in the optimization problem.
Apr
18
comment Why is the first principal component a proxy for the market portfolio, and what other proxies exist?
Thank you for enhancing your answer, I appreciate reading it a lot.
Apr
18
comment Why is the first principal component a proxy for the market portfolio, and what other proxies exist?
When you say "Why is this the market factor? If you examine the weights (factor loadings) of the first eigenvector in a histogram you will find they are generally all of the same sign whereas this is not the case for any of the subsequent eigenvectors", I am not convinced by this argument. I agree that the among all PCA components, the first one is the most representative of the market, but maybe there is another set of weights that is better than this one.
Feb
10
comment How to compute performance attribution between daily rebalanced strategies?
interesting idea
Feb
10
comment Why is the first principal component a proxy for the market portfolio, and what other proxies exist?
I still think it is very accurate to say that "PCA is maximizing the variance". PCA weights can be found by formulating the problem as a max of the variance under constaint