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Dec
9
comment Book recommendation on robust optimization
I am afraid for a bachelor in economics, the Ben Tal / Nemirovski book will be far too technical.
Dec
4
comment How to extrapolate VaR?
as @Richard pointed out, the scaling rule depends on the distribution. Value at Risk is a distribution quantile. The Quantile of a Normal Distribution with $\mu = 0$ scales with $\sqrt{T}$, in general it does not!
Dec
2
comment How do I artificially generate intraday ticks data from a given input (Open,High,Low,Close,Volume) using Brownian Bridge method?
@jaamor You could do that, but those times will not be independent I suppose. I think the result wouldnt look too good. I would take the high and low value and use it as a dispersion measure to improve my intraday volatility estimator and then create BB paths from it. They will, in general, not reach the high and low values but the question is: Does it make sense to enforce this?
Dec
2
comment Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
Hope it helps. Lets try to find a day - check your inbox in a few hours!
Dec
2
comment Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
@Richard I tried to clarify my answer a little and added an additional point.
Dec
2
revised Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
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Dec
1
comment Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
@Richard Hallo, I have to check the details about the risk parity portfolio agai and will catch up on that tomorrow.
Dec
1
revised Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
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Dec
1
answered Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?
Nov
24
reviewed Approve 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
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Jul
28
answered Non-Negativity of up-factor and down-factor in Binomial No-Arbitrage Pricing Model