network profile
| bio | website | |
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| location | ||
| age | ||
| visits | member for | 7 months |
| seen | May 14 at 6:49 | |
| stats | profile views | 59 |
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May 14 |
accepted | characterization of coherent risk measures |
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May 13 |
asked | characterization of coherent risk measures |
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May 4 |
accepted | reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) |
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Apr 29 |
comment |
reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) I'm struggling with the details. If you would provide these small technicalities for point one and also for point 2 I accept your answer an you will get the bounty. |
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Apr 29 |
comment |
reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) Sorry I am still unsure about these two points. I try to figure out 1) by myself. But for point two: I do not understand your last comment. I still stuck on uniformity. |
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Apr 27 |
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reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) About the second question: I've never heard about locally uniformly strict convex functions. All I know is a uniform convex space. I searched the web without succes. Could you please give me a reference. I know that $V(\frac{a+b}{2})\le \frac{1}{2}V(a)+\frac{1}{2}V(b)-\epsilon$. But, why does it hold with the $\lim\sup$ in front? Again, I'm very thankful for your help/patience! |
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Apr 27 |
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reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) About the first question: What is your definition of bounded in probability? I use the following: a family of r.v. $\mathcal{F}$ is bounded in probability if and only if $\lim_{r\to \infty}\sup_{f\in\mathcal{F}}P(|f|>r)=0$. But what exactly do you mean by "add in a term for free"? |
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Apr 26 |
asked | reasonable asymptotic elasticity in utility maximization (paper by Kramkov / Schachermayer) |
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Apr 23 |
accepted | Utility maximisation |
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Apr 23 |
comment |
Utility maximisation @quasi I think I need only the inclusion, that I not have. Since for a given $V(z,\theta)$ I need to split it up, right? For your decomposition: Why is it true that $x+\frac{x}{x+y}(\theta\bullet S)\ge 0$? |
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Apr 23 |
asked | Utility maximisation |
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Apr 12 |
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Hedging duality how can I migrate a question? Btw...thank a lot for your patience. I think we have a different approach in the proof of $X$ being a supermartingale, i.e. different definition for fork-convex. Note, in my notes we never call it "fork-convex". |
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Apr 11 |
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Hedging duality The reason why I asked about Fork-convexity, is the following question, posted on MSE. In the prove that $X_t$ is supermartingale, they claim this. Maybe you want to answer this too ;) math.stackexchange.com/questions/355702/… |
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Apr 11 |
accepted | Hedging duality |
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Apr 11 |
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Hedging duality Btw...I searched the web about a proof of the fork-convexity of $\mathbb{P}$ without success. Do you have a reference, link, pdf etc? |
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Apr 11 |
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Hedging duality Well I agree that $X$ is $Q^*$ martingale and hence everything works. But I don't understand what you mean with $X$ and $X^{Q^*}$ are equal? But this is not needed. All you need is, (at least I guess), is: you have a supermatingel with $E[X_0]=E[X_T]$ hence it is a martingale. |
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Apr 11 |
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Hedging duality Thanks for your answer. I know the result that $X_t$ is a supermartingale for every $Q\in\mathbb{P}$. The poof is not straightforward, not at all. At least the one I know. This just as a personal side remark :) I have one question: 1. Why are the two processes $X$ and $H$ are equal? |
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Apr 10 |
revised |
Hedging duality edited body |
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Apr 10 |
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Hedging duality @Freddy No, not at all :) |
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Apr 10 |
asked | Hedging duality |
