| bio | website | researchgate.net/profile/… |
|---|---|---|
| location | Vienna | |
| age | 31 | |
| visits | member for | 11 months |
| seen | May 14 at 7:53 | |
| stats | profile views | 128 |
Risk Manager at Raiffeisen Capital Management
External Lecturer at Vienna University of Technology
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Feb 1 |
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What to do with linear regression or regression splines outside of the training range? @John I have the feeling that some questions are relevant and interesting for QSE as well as StatsSE - I am thinking of regression and similar topics. However these problems are probably treated differently here and there. So I am/was interested in some more views here. I hope that some more comments come in. Coming back: I think in quantitative finance a regression model in some kind is often applied and then my question can easily arise. |
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Jan 31 |
asked | What to do with linear regression or regression splines outside of the training range? |
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Jan 31 |
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Pricing in HJM framework My point above was that in case one wants to do real curve modelling (shape and volas) one has to use something advanced - advanced short rate models or HJM. For example for the generalized Hull White model one could calibrate it to traded Swaptions with the terms and maturities matching the terms that you want to model in the volatilities. Reading the paper Nr.2 will hopefully give you some more insight - it is the best thing I've ever seen on HJM. Nr. 3 offers a nice application step by step. |
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Jan 31 |
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Pricing in HJM framework @hulik but you will not be able to have all curve shapes with Vasicek, Ho Lee or CIR - you need the Hull White model to get the curve right and you need the generalized Hull White model if you want to model time dependent volatilities -> then we are already close to HJM conerning complexity. |
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Jan 31 |
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Pricing in HJM framework @SRKX thanks for pointing this out - I think you hit the point +1 from my side ;) |
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Jan 30 |
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Pricing in HJM framework deleted 21 characters in body |
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Jan 30 |
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Predict Quadratic Trend in Time Series code formatting |
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Jan 30 |
awarded | Informed |
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Jan 30 |
answered | Predict Quadratic Trend in Time Series |
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Jan 30 |
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Predict Quadratic Trend in Time Series And I can't really read the formula in lm. Shouldn't it just be lm(sales~year+I(year^2)) equivalent to lm(sales~year+year.sq) ? |
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Jan 30 |
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Predict Quadratic Trend in Time Series Should it be $1985:2003$ instead of $1985:1986$? And I can't really read the formula in lm. |
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Jan 30 |
answered | Pricing in HJM framework |
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Jan 29 |
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Liquidity in a market risk model based on historical simulation Thanks, nice idea - clear and doable. |
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Jan 29 |
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Threshold calculation for buying a mean-reverting asset ... I mean "hear" ;) |
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Jan 29 |
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Copula models and the distribution of the sum of random variables without Monte Carlo Believing that the people of "Corr Validated" could have additional ideas I have posted the question there too. |
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Jan 29 |
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Copula models and the distribution of the sum of random variables without Monte Carlo Does anybody have an idea which is more copula based? Do copulas and sums don't go together well? I mean - the answer by Julian Wergieluk shows that this is not true in general - but using copulas we do not gain any insight to the sum? No (Fourier/moment/ ...) transform trick? |
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Jan 28 |
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Threshold calculation for buying a mean-reverting asset But most importantly - let us here what @Alon needs. Are you with us, Alon? |
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Jan 28 |
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Threshold calculation for buying a mean-reverting asset The OU-process has $3$ parameters - what can be different if I speak of theoretical results concerning stopping times and theresuch? OU process is OU process no matter the context - at least if I speak of stopping times - of course the parameters will be different and all "caveats" too. |
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Jan 28 |
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Threshold calculation for buying a mean-reverting asset thanks for improving the answer. |
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Jan 28 |
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Liquidity in a market risk model based on historical simulation Thank you for your comments, @Freddy. Am I right that these apply for the stock market mainly? Do you have any ideas about the bond market? Furthermore - how can I capture this in a quantitative manner? I assume the big vendors of factor based models have some liquidity factor - but what can I do in pure historical simulation? Thanks. |