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13h
reviewed Approve suggested edit on What are the dynamics of the reverse of this FX process?
Nov
14
answered CVaR reformulation correct?
Oct
7
comment Determine $E[W_p W_q W_r]$
For a normal distributed rv $X ~ N(\mu,\sigma)$, $E[(X-\mu)^3] = \mu^3+3\mu\sigma^2$ (just search for moment normal). In our case, $\mu=0$ and $\sigma = p$. Alternatively, you can calculate it by hand (several times integration by parts) or via the moment-generating function.
Oct
6
answered Determine $E[W_p W_q W_r]$
Oct
1
comment quadratic programming portfolio optimisation
Hm, thats why I wasn't sure this is the right explanation because $x$ should be $x = [0.8,0,0.5,0,-0.3,0]$ in this case (splitting $x$ up in a positive and a negative part). Now, $x(1:3)+x(4:6)$ is the original portfolio and $x(1:3) - x(4:6)$ its component-wise absolute value.
Oct
1
comment quadratic programming portfolio optimisation
Its not linear because $|-x|\neq-|x|$ which would hold for a linear function.
Oct
1
answered quadratic programming portfolio optimisation
Oct
1
comment quadratic programming portfolio optimisation
Please provide some more information about the constraints the example employs. There are techniques to reformulate optimization problems that simplify those but I doubt thats the problem here. Does your example use a different solver than matlab? Have you tried solving the example your way and compared the solutions? Further more: If you look at F and multiply with vectors $(x,-x)^T$ and $(x,-x)$ from both sides, you will miss the factor $1/2$. Probably the author moved into the $c$ but without any more information its really hard to say...
Sep
10
answered How do Return.portfolio and Return.rebalancing work in Performance Analytics in R?
Jul
28
revised Non-Negativity of up-factor and down-factor in Binomial No-Arbitrage Pricing Model
added 686 characters in body
Jul
28
answered Non-Negativity of up-factor and down-factor in Binomial No-Arbitrage Pricing Model
Jul
25
awarded  Yearling
Jul
23
comment reference question about portfolio optimization
Although I voted to close this question: You are recommending the Pfaff book. I havent read it yet, is it good? Just a small comment though: #4 is also weritten by Bernd Sherer and those are commercial software packages. #3 Is basically a cookbook for the corresponding R package and treats rather advanced optimization problems (compared to classical MVO).
Jul
21
answered Risk Parity portfolio construction
Jul
17
revised Handling Missing values in stocks returns when estimating the co variance matrix
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Jul
17
comment Handling Missing values in stocks returns when estimating the co variance matrix
@user3481555 Well if you delete the stock you simply reduce your investment universe. My intuition says that this induces at least some bias because the stocks with shorter history had a reason to enter the index later on. On the other hand, If you throw away the all the data where at least one stock has a missing value you might run into dimension problems (if you estimate a covariance matrix for hundrets of assets you want to search for "dimension reduction" or "shrinkage" or "robust" in quant.SEs search function). I will see if I can come up with the paper I mentioned...
Jul
17
answered Handling Missing values in stocks returns when estimating the co variance matrix
Jul
16
revised ETFs have lower tracking error than Futures?
added tags
Jul
16
suggested suggested edit on ETFs have lower tracking error than Futures?
Jul
2
awarded  Curious